Cancer cells impede T cell early activation and drive immune evasion by transferring Tmem176b

Cancer cells impede T cell early activation and drive immune evasion by transferring Tmem176b | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Cancer cells impede T cell early activation and drive immune evasion by transferring Tmem176b Nengming Xiao, Xianjjun Gao, Fang Liu, Abin You, Yangqi Jin, Fengxia Luo, and 24 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6199894/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Despite its remarkable clinical success in human cancer treatment, immune checkpoint blockade is effective only in a minority of patients. One major obstacle is tumor-driven impairment of T cell priming and early activation, however, the underlying mechanism remains elusive. Here we identify TMEM176B-positive exosomes specifically secreted by cancer cells in plasma of cancer patients rather than healthy donors, high levels of which correlate with worse prognosis and unfavorable outcomes of anti-PD1 therapy. A small-scale CRISPR-Cas9 screen discovers Tmem176b on tumor-derived exosomes as a negative regulator of T cell early activation. Genetic ablation of Tmem176b in mouse cancer cells substantially suppresses tumour growth in a CD8 + T cell-dependent manner. Mechanistically, tumour-derived exosomal Tmem176b attenuates proximal T cell receptor signaling in CD8 + T cells by recruiting tyrosine phosphatase Shp1 to immunological synapse. Blocking TMEM176B, either using neutralizing antibody or using competitive peptide to disrupt Tmem176b-Shp1 interaction, remarkably restrains tumour progression in models of mouse and human cancers, and synergizes with anti-PD1/PD-L1 therapy. Our findings not only uncover tumor-derived Tmem176b as a promising target for cancer immunotherapy, but also provide a potential non-invasive diagnostic tool to detect early cancer and predict clinical response to anti-PD1 therapy. Biological sciences/Immunology/Immune evasion Health sciences/Oncology/Cancer/Cancer microenvironment Health sciences/Oncology/Cancer/Cancer therapy/Cancer immunotherapy Health sciences/Oncology/Cancer/Tumour immunology Biological sciences/Immunology/Adaptive immunity/Cellular immunity/Lymphocyte activation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Although immune checkpoint blockade (ICB) has achieved unprecedented tumor regression and long-term survival benefit in patients with advanced melanoma and other cancers, such immunotherapies fail to control neoplasia in a large proportion of patients 1 . Within tumor microenvironment (TME), CD8 + cytotoxic T lymphocytes (CTLs) play a crucial role in the eradication of tumor cells 2 . The priming, activation, recruitment of T cells to the TME are necessary for a potent antitumor immune response. To combat immune elimination, cancer cells often curtail T cell activities for immune evasion. Inhibitory molecules expressed on cancer cells or antigen-presenting cells (APCs) interact with T cells to induce T cell dysfunction. ICB such as anti-PD1/PD-L1 (Programmed cell death 1/ Programmed death ligand 1) antibody therapy disrupt these inhibitory receptor-ligand interactions to reinvigorate tumor-specific T cells 1 . The success of this therapy occur most often in patients with ‘hot’ (‘immune-inflamed)’ tumors with abundant T cell responses, and a large subsets of patients do not respond to ICB therapy or develop acquired resistance, especially in ‘cold’ (‘immune-desert’/‘immune-excluded’) tumors, characterized by the absence or exclusion of T cells in the tumor parenchyma 3 . Besides T cell dysfunction, resistance to ICB therapy can result from the key tumor characteristics that impair the priming, activation, recruitment of T cells to the TME, thereby reducing T cell infiltration and activity 4-6 . MHC-Ⅰ loss by mutations in MHC-Ⅰ(including human leukocyte antigen class Ⅰ (HLA - Ⅰ ) and B2M ) have been found in several human cancers, and is a common mechanism of both primary and acquired resistance to ICB therapy 7-10 . In addition to DNA mutations, MHC-Ⅰ loss can occur through epigenetic silencing 11 , protein degradation in lysosomes 12-15 . Defect in IFN-γ signaling in tumors also results in inability to upregulate MHC-Ⅰ and PD-L1 and confers resistance to anti-PD1 therapy 7,16 . The oncogenic pathways within cancer cells can also promote immune evasion and resistance to ICB therapy by excluding T cells from tumors. For example, loss of PTEN in cancer cells increases the expression of immunosuppressive cytokines, resulting in decreased T cell infiltration 17 , which can be reversed by inactivation of PI3Kβ 18 . Overactivation of β-catenin or prostaglandin E2 (PGE2) production driven by oncogenic signaling in tumors, prevent T cell infiltration by suppressing the recruitment and function of type 1 conventional dendritic cells (cDC1s) 19-24 . It is well-known that PD-L1 expressed on cancer cells or APCs interacts with PD1 on activated CD8 + T cells to conteract an ongoing antitumor immune response by diminishing both T cell receptor (TCR) and costimulatory signaling, while ITPRIPL1 expressed on tumors refractory to anti-PD1 therapy binds to CD3ε on activated T cells to attenuate TCR signaling 25 . However, it remains unclear whether and how cancer cells impede the priming and early activation of naive CD8 + T cells by attenuating TCR signaling. Although hundreds of new agents overcoming tumor-intrinsic resistance in combination with anti-PD1/PD-L1 therapies are being tested in thousands of clinical trials globally, few combinations have proven to be clinical success 26,27 . Therefore, new therapeutic strategies to enhance the efficacy of ICB therapy are of paramount importance. Extracellular vesicles (EVs) are classified into two subsets, exosomes and ectosomes (also known as microvesicles), based on the biogenesis 28 . Cancer cells generally release more EVs than non-tumorigenic cells into the TME and circulation 29,30 , to promote tumor-intrinsic resistance to ICB therapy 31-35 . In addition, EVs exhibit multiple properties that may confer superior performance in cancer diagnosis and prognosis relative to other types of liquid biopsy biomarkers due to their relative abundance, stability, and array of cargoes (including proteins, lipids, nucleic acids and metabolites) 36 . Although many efforts have been made to define tumor-derived EV biomarkers that distinguish cancer patients from healthy individuals 37,38 , reliable EV biomarkers that can detect early cancer, predict therapeutic response to ICB therapy, also be targeted to enhance the efficacy of immunotherapy, are still lacking. To identify such tumor-derived exosomal markers, we performed proteomic profiling of exosomes from human and murine cancer cell lines and non-tumorigenic cell lines, and identified the transmembrane protein Tmem176b, one related member of the tetraspan MS4A (membrane-spanning 4-domain, subfamily A) family 39 , specifically enriched on cancer-cell-derived exosomes. TMEM176B-positive circulating exosomes were detected in peripheral blood of various types of cancer patients, distinguishing healthy subjects from cancer patients with early- and late-stage cancer. High levels of TMEM176B-positive circulating exosomes were associated with worse prognosis and unfavorable outcomes of anti-PD1 therapy, suggesting that they may serve as a potential non-invasive diagnostic tool to detect early cancer and predict clinical response to anti-PD1 therapy. We have also demonstrated that Tmem176b on tumor-derived exosomes (TDEs) promotes immune evasion and tumor progression via direct inhibition of T cell early activation. Blocking Tmem176b remarkably restrained tumor growth, providing a potential strategy to overcome tumor-intrinsic resistance to cancer immunotherapy. Results TMEM176B is specific marker of cancer-cell-derived exosomes To identify specific markers that distinguish cancer-cell-derived exosomes from normal exosomes, we purified small EVs from both human and mouse cancer cells (A549 human lung carcinoma cells, SW480 human colorectal adenocarcinoma cells, HeLa human cervical adenocarcinoma cells, B16F10 mouse melanoma cells, MC38 mouse colorectal adenocarcinoma cells), and non-tumorigenic cells (MCF-10A human mammary gland epithelial cells and BEAS-2B human bronchial epithelial cells) by sequential ultracentrifugation. These EVs were characterized as exosomes in terms of morphology and size range via transmission electron microscopy (TEM) and Nanosight nanoparticle tracking analysis (NTA) (Extended Data Fig. 1 a-b). Immunoblot confirmed the expression of conventional exosomal markers TSG101, Alix and CD63 in exosomes from all sources (Extended Data Fig. 1 c). Proteins of these exosomes were evaluated by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) (Fig. 1 a). 5223, 6000, 5464, 4552, 4453, 716, and 3485 proteins were identified in exosomes from A549, SW480, HeLa, BEAS-2B, MCF-10A, B16F10 and MC38 cells, respectively, all of which included conventional exosomal markers TSG101, Alix, Flotillins, CD9 and CD81 (Supplementary Table 1). Bioinformatic analyses revealed 294 proteins specifically present in exosomes from all three human cancer cell lines but not in those from non-tumorigenic cell lines (Fig. 1 b). Only 4 of these 294 proteins were also detected in exosomes from both B16F10 and MC38 murine cancer cell lines (Fig. 1 c). Among these 4 proteins, TMEM176B belongs to the distantly related members of the tetraspan MS4A (membrane-spanning 4-domian, subfamily A) family 39 . We next performed ultrasensitive Nano-Flow Cytometry (NanoFCM) analysis to detect Tmem176b on individual exosomes 40 , using monoclonal antibody (6E8) against the large loop between the third and fourth transmembrane domains of Tmem176b. NanoFCM revealed that a small proportion of exosomes secreted by murine and human malignant cancer cells (B16F10, MC38, SW480, A549 and HeLa) carried Tmem176b (or TMEM176B) protein (Extended Data Fig. 1 d-g), whereas ectosomes released by cancer cells did not contain Tmem176b protein (Extended Data Fig. 1 h). Genetic ablation of Tmem176b (or TMEM176B) in cancer cells completely eliminated its cellular and exosomal expression (Extended Data Fig. 1 i-j). By contrast, murine and human non-tumorigenic cells (NIH3T3 mouse fibroblast, BEAS-2B and MCF-10A), innate immune cells (cDC2 and macrophages) and mesenchyma stem cells (MSCs) that highly expressed Tmem176b, did not secrete or secrete extremely low frequencies of Tmem176b (or TMEM176B)-positive exosomes (Extended Data Fig. 1 d-g, 1 k-j). Together, these results show the presence of Tmem176b speficically on exosomes released from malignant cancer cells. Exosomes are generated mostly via the endosomal sorting complex required for transport (ESCRT), albeit it can also occur independent of ESCRT 28 . Immunofluorescence staining revealed that most of Tmem176b proteins co-localized with endosomal markers Rab5 and Rab7, as well as Hrs, one component of ESCRT-0, in B16F10 melanoma cells, similar to a previous report (Extended Data Fig. 2 a) 41 . Intracellular flow cytometric staining with monoclonal antibody (6E8) against the large loop of Tmem176b detected high levels of Tmem176b protein in scramble B16F10 and MC38 cells but not in all strains of Tmem176b -deficient cancer cells, whereas cell surface staining scarcely detected Tmem176b protein in both scramble and Tmem176b -deficient cancer cells, confirming that Tmem176b protein mainly localized in the cytoplasm (Extended Data Fig. 1 i). Consistently, immunoprecipitation of Flag-tagged Tmem176b in B16F10 cells followed by mass spectrometry (IP-MS) identified a large number of proteins involved in intracellular protein transport and vesicle transport, including Hrs, as Tmem176b-binding partners (Extended Data Fig. 2 b-c and Supplementary Table 2). Genetic deletion of Hrs or Rab27a, which mediates cargo sorting and exosome release respectively, blocked Tmem176b secretion via exosomes (Extended Data Fig. 2 d). TMEM176B + circulating exosomes are a non-invasive cancer biomarker To investigate the secretion of exosomal Tmem176b from transplanted tumors in vivo , we collected blood from B16F10- or MC38-bearing mice to purify exosomes and subsequently examined Tmem176b on exosomes by NanoFCM. NanoFCM identified Tmem176b on a small proportion (about 6%) of circulating exosomes from tumor-bearing mice but not those from naive mice (Extended Data Fig. 2 e-f). To examine the protein levels of TMEM176B on circulating exosomes in cancer patients, we collected blood from various types of cancer patients, including colon adenocarcinoma (COAD), stomach adenocarcinoma (STAD), oesophageal carcinoma (ESCA), lung adenocarcinoma (LUAD), and breast invasive carcinoma (BRCA), for exosomes purification and subsequent detection of exosomal TMEM176B by NanoFCM and Sandwich ELISA (Fig. 1 a). A small portion of TMEM176B + exosomes were detected in the plasma from almost all patients with these types of cancers but not from healthy donors, by NanoFCM (Fig. 1 d-e). 78.5% of COAD patients (95 out of 121), 90.9% of STAD patients (100 out of 110), 90.4% of ESCA patients (66 out of 73), 94.4% of LUAD patients (102 out of 108), 92.3% of BRCA patients (36 out of 39), showed significantly higher percentages of TMEM176B + circulating exosomes than healthy donors. Likewise, the protein levels of TMEM176B on the circulating exosomes were significantly higher in these cancer patients than in healthy donors, as revealed by ELISA (Extended Data Fig. 2 g-h). TMEM176B + circulating exosomes were already present in the plasma of patients with early stages (Ⅰ) of tumors and their frequencies were comparable with those in the plasma of patients with late stages (Ⅳ) of tumors (Fig. 1 f). Moreover, the frequencies of TMEM176B + circulating exosomes were substantially reduced in cancer patients after surgical resection of cancerous tissues (Fig. 1 g), indicating that these TMEM176B + circulating exosomes mainly arose from cancerous tissues. To determine the prognostic relevance of TMEM176B + circulating exosomes in cancers, patients bearing LUAD, STAD, COAD or ESCA with complete follow-up information were dichotomized into high- versus low- groups on the basis of a median split of frequencies of TMEM176B + circulating exosomes. Apparently, LUAD patients with a high frequency of TMEM176B + circulating exosomes had significantly shorter overall survival than those with a low frequency of TMEM176B + circulating exosomes (Fig. 1 h). This correlation was not significant in other types of cancer patients probably due to the limited numbers of patients with complete follow-up information (Fig. 1 h). Furthermore, the pre-treatment level of TMEM176B + circulating exosomes was significantly higher in blood of patients who had weaker response to the anti-PD1 treatment (Fig. 1 i). Thus, these data consolidate that circulating exosomal TMEM176B can serve as a non-invasive biomarker for detection of multiple types of early cancers, like GPC1 for pancreatic cancer 38 , and for prediction of reponse to anti-PD1 therapy. TDEs facilitate tumor progression via immunosuppressive TME Although TDEs play an immunogenic role by transferring a number of immunostimulatory factors including tumor antigens 42 , TDEs have also been shown to promote immunosuppressive TME 34 , 35 . To examine the overall role of TDEs in tumor progression, we deleted Rab27a , that is required for the secretion of exosomes 43 , in B16F10 melanoma cells, using CRISPR-Cas9-mediated mutagenesis. When Rab27a -deficient cells were subcutaneously injected into syngeneic immunocompetent C57BL/6J mice, their abilities to form tumors were significantly attenuated, compared to B16F10 cells transduced with scramble single guide RNA (Scramble sgRNA), consistent with previous report (Extended Data Fig. 3 a) 32 . Meanwhile, deletion of Rab27a in B16F10 cells dramatically extended the survival of tumor-bearing mice (Extended Data Fig. 3 b). As Rab27a controls both exosomes secretion and secretory vesicle exocytosis, it could promote tumor progression through both exosome-dependent and -independent mechanisms 44 . To directly evaluate the effect of TDEs in tumor growth, we then subcutaneously injected B16F10 or MC38 cells together with extra purified syngeneic TDEs into C57BL/6J mice. In both tumor models, co-inoculation of syngeneic TDEs significantly accelerated tumor growth and shortened host survival (Extended Data Fig. 3 c-f). Together, these results suggest that the overall effect of TDEs is to strongly promote tumor growth. To examine the effect of TDEs on the tumor immune microenvironment (TIME), we performed single-cell RNA-sequencing (scRNA-seq) analysis of intratumoral CD45 + immune cells from B16F10 tumors of C57BL/6J mice co-inoculated with or without extra purified B16F10-derived exosomes, using 10× Genomics platform. Unsupervised clustering led to identification of 15 unique cell populations, including αβ T cells, γδ T cells, natural killer T cells (NKT), B cells, macrophages, monocytes, neutrophils, dendritic cells (DC),, natural killer cells (NK), and innate lymphoid cells (ILC) (Extended Data Fig. 3 g-h and Supplementary Table 3). Co-inoculation of syngeneic TDEs strongly expanded B cells with higher activity score for immune inhibitory signature genes as well as immunosuppressive subpopulations within macrophages (Extended Data Fig. 3 i-m) 45 , 46 . By contrast, some immune-stimulatory cell populations, including ILC1, ILC3, CD8 + T cells and CD4 + T cells, decreased in B16F10 tumors co-inoculated with syngeneic TDEs (Extended Data Fig. 3 g-h). Within CD8 + T cells, scRNA-seq analysis revealed reduction in the abundance of intermediately exhausted, exhausted effector, innate-like and interferon-stimulated CD8 + T cells, with a concomitant increase in naive/central memory-like and memory-like CD8 + T cell subsets 47 – 50 , in B16F10 tumors co-inoculated with syngeneic TDEs (Extended Data Fig. 4 a-b). Correspondingly, co-inoculation of syngeneic TDEs resulted in lower activity scores for gene signatures related to early activation, exhaustion and effector/cytokine signaling of intratumoral CD8 + T cells (Extended Data Fig. 4 c and Supplementary Table 3). These results suggested that TDEs had a global impact on most of immune cells in the TME, consistent with previous reports. However, the pro-tumoral effect of TDEs, was completely dependent on CD8 + T cells, as it was still observed in Igh-j −/− Igk −/− (B cell deficient, BCD) mice (Extended Data Fig. 4 d), but not in other immunodeficient mice including Rag1 −/− (lacking mature T and B cells) and CD8a −/− (lacking CD8 + T cells) (Extended Data Fig. 4 e-h). Taken together, these results suggest that TDEs suppress CD8 + T cell function directly and indirectly through other immune cells in the TME. We next further analyzed tumor-infiltrating T cells using flow cytometry. In line with the results of scRNA-seq analysis, co-inoculation of extra syngeneic TDEs resulted in a remarkable decrease in total CD8 + T cells, CD44 + CD62L − effector and PD1 + Tim3 + terminally exhausted CD8 + T subsets in both B16F10 and MC38 tumor models (Extended Data Fig. 5 a-d). Accordingly, the production of effector cytokines in CD8 + T cells, including IFN-γ, TNF-α and Granzyme B, was also dramatically impaired in both types of tumors co-inoculated with syngeneic TDEs (Extended Data Fig. 5 e-h). Interestingly, the frequencies of both CD4 + T cells and CD8 + T cells were significantly lower in the tumor-draining lymph nodes (TdLN) of MC38-bearing mice with co-inoculation of syngeneic TDEs than in the counterparts without co-inoculation of TDEs (Extended Data Fig. 5 i-j). Therefore, these data demonstrate that TDEs suppress CD8 + T cell activity in both TME and TdLN. Tmem176b on TDEs directly suppressed T cell early activation Given that the early activation of intratumoral CD8 + T cells was inhibited by co-inoculation of syngeneic TDEs (Extended Data Fig. 5 c), we next investigated whether TDEs directly obstructs T cell early activation, as the failure in the priming and activation of T cells is one of the major mechanisms of tumor-intrinsic resistance to ICB therapy 4 . To address this, we treated naive T cells with or without B16F10-derived exosomes before or 24 hours after in-vitro stimulation with anti-CD3 and anti-CD28 antibodies (Extended Data Fig. 6 a). Treatment of TDEs before stimulation significantly inhibited proliferation and early activation of CD8 + T cells in a dose-dependent manner, as demonstrated by the decreased proportion of cells containing diluted carboxyfluorescein diacetate succinimidyl ester (CFSE), the decreased cell numbers (Extended Data Fig. 6 b-c), and the reduced expression of T cell activation markers (CD25, CD69, CD71, CD44) (Extended Data Fig. 6 d). In contrast, TDEs treatment after stimulation scarcely affected CD8 + T cell proliferation (Extended Data Fig. 6 b-c). Likewise, treatment of TDEs before but not after stimulation caused a significant but milder reduction in early activation and proliferation of CD4 + T cells (Extended Data Fig. 6 e-g). Thus, these findings suggest that TDEs directly suppress early activation and proliferation of CD8 + T cells. In order to identify the key molecules that mediate suppression of T cell activation by TDEs, we selected dozens of candidate genes including Tmem176b that encode proteins more than two-fold enriched in B16F10-derived exosomes (Supplementary Table 1), which were identified in aforementioned proteomic profiling of TDEs by mass spectrometry, to construct sgRNA-expressing lentiviral vectors (Supplementary Table 4). B16F10 cells were individually infected with lentiviruses containing sgRNA to generate candidate gene knockout B16F10 cell lines. we then performed a small-scale CRISPR-Cas9 arrayed screen using an in-vitro T cell activation system, in which naïve CD8 + T cells were treated with or without B16F10-derived exosomes in the presence of anti-CD3 and anti-CD28 antibodies. We measured protein levels of early activation markers (CD25, CD69, CD71 and PD1) of T cells by flow cytometry as functional readouts. Pretreatment of exosomes from wild-type (WT) or scramble sgRNA-transduced B16F10 cells significantly inhibited early activation of CD8 + T cells, while vehicle treatment or pretreatment of exosomes from non-malignant fibroblast NIH3T3 cells did not suppress the early activation (Extended Data Fig. 6 h). The suppression of T cell activation by exosomes from B16F10 cells was unleashed by two independent sgRNAs for Tmem176b (Extended Data Fig. 6 h). By contrast, exosomes from B16F10 cells transduced with sgRNA for Cd274 (encoding PD-L1) still maintained the capability to suppress T cell activation (Extended Data Fig. 6 h), suggesting that this suppression was not mediated by the PD1/PD-L1 checkpoint, as naïve CD8 + T cells do not express PD1. Thus, Tmem176b appear to be a key mediator of suppression of T cell early activation by TDEs . Genetic ablation of Tmem176b in cancer cells inhibits tumor growth To assess the effects of Tmem176b on tumor growth, we generated monoclonal mouse malignant cancer cell lines (B16F10 and MC38) lacking Tmem176b by CRISPR-Cas9 technology, using three different sgRNAs (Extended Data Fig. 1 i). On the one hand, deletion of Tmem176b did not significantly affect the in-vitro growth rate and the exosome secretion of cancer cells (Extended Data Fig. 7a-b). On the other hand, neither the nanoscale and morphology, nor the protein composition of exosomes including the exosome markers and protein cargoes directly involved in immune signaling, was altered by Tmem176b deficiency (Extended Data Fig. 7c-f and Supplementary Table 5). After inoculation into syngeneic C57BL/6J hosts, all the strains of Tmem176b -deficient B16F10 cells exhibited much slower tumor growth and all the strains of Tmem176b -deficient MC38 cells hardly formed tumors, compared to the corresponding scramble cancer cells; Meanwhile, deletion of Tmem176b in both B16F10 and MC38 cells largely extended the survival of tumor-bearing mice (Fig. 2 a-d). In pulmonary metastasis model of intravenous injection of B16F10 cells, which seed the lung with tumors, deletion of Tmem176b in B16F10 cells greatly reduced the numbers of lung metastases (Fig. 2 e-f). Furthermore, reintroducing Tmem176b into Tmem176b -deficient B16F10 and MC38 cells completely restored the tumor progression, thereby excluding the possibility that CRISPR-Cas9-mediated off-target mutagenesis might be responsible for the delayed tumor growth (Fig. 2 g-j). Consistent with the previous study 41 , when B16F10 cells were inoculated into germline Tmem176b −/− mice, dendritic cell-specific Tmem176b -deficient and Tmem176a/b -deficient mice ( Tmem176b fl/fl CD11c-Cre, Tmem176a/b fl/fl CD11c-Cre, called Tmem176b-dcKO, Tmem176a/b-dcKO here, respectively) on pure C57BL/6J background, the growth of tumors was comparable to that in WT mice (Fig. 2 k-l and Extended Data Fig. 7g). Therefore, tumor-derived Tmem176b, rather than host Tmem176b facilitates tumor progression. Tumor-derived exosomal Tmem176b facilitates tumor growth To examine whether the pro-tumoral effect of Tmem176b was mediated by TDEs, when Tmem176b -deficient B16F10 or MC38 cells were inoculated into C57BL/6J mice, extra syngeneic TDEs were supplemented, either by co-inoculation with cancer cells, or by independent intravenous (tail vein) injection. Exogenous introduction of exosomes from WT rather than Tmem176b -deficient cancer cells by both approaches, accelerated growth of Tmem176b -deficient tumors in both tumor models (Fig. 2 m-o). Exosomes from tumor at one site can potentially influence tumor growth at distant sites, by the travel of their own or immune cells educated at the same sites, throughout the body 32 . We next asked whether exosomal Tmem176b secreted by WT cancer cells promote growth of the cancer cells at a distant site, or whether immune cells activated by Tmem176b -deficient cancer cells suppress growth of the cancer cells at a distant site. To this end, WT MC38 cells were co-injected in the right flank of each C57BL/6J mouse with Scramble, or Tmem176b -deficient, or Rab27a -deficient MC38 cells in the left flank (Fig. 2 p). Remarkably, WT MC38 cells on the right flank that were co-injected with Scramble cells in the left flank grew much faster than WT cells injected alone in the right flank. In contrast, co-injection of Tmem176b -deficient or Rab27a -deficient MC38 cells in the left flank significantly delayed the growth of WT MC38 cell in the right flank (Fig. 2 q). Taken together, these findings strongly supported the notion that Tmem176b acts on TDEs to accelerate the growth of tumors at both local and distant sites. Tmem176b ablation in tumors remodels the TME TDEs that are released into TME and body fluids can be taken up by recipient cells through fusion with the plasma membrane, or through endocytosis 51 . To visualize the transfer of Tmem176b from tumor cells to the recipient cells, we injected B16F10 or MC38 cells that stably express Tmem176b-GFP fusion protein into C57BL/6J mice. Flow cytometry analysis of tumor-infiltrating immune cells showed that Tmem176b accumulated in all types of immune cells tested, including T cells, B cells and conventional dendritic cells (cDCs), with the highest frequency and density in cDCs (Extended Data Fig. 8a-b). The transfer of Tmem176b was completely dependent on Rab27a, as it was eliminated when Rab27a was deleted in tumor cells (Extended Data Fig. 8c-d). Although cDCs have strong capacity to uptake TDEs, the absence of Tmem176b on TDEs did not enhance cross-presentation in type 1 cDCs (cDC1s) (Extended Data Fig. 8e). To determine the involvement of the immune system, we inoculated Tmem176b -deficient or Scramble B16F10 and MC38 cancer cells into Rag1 −/ − (no mature T and B cells), Tcrb −/− Tcrd −/− (T cell deficient, TCD), or CD8a −/− (no CD8 + T cells) mice. Our results demonstrated that Tmem176b deficiency had no effect on tumor growth in these immunodeficient mice (Fig. 3 a-d), suggesting that the increased growth control of Tmem176b -deficient tumors was mainly mediated by CD8 + T cells. We next sought to investigate the cellular consequence of Tmem176b deficiency on TIME. To this end, we profiled intratumoral CD45 + immune cells from mice bearing scramble or Tmem176b -deficient B16F10 tumors, using scRNA-seq. Unsupervised clustering analysis revealed few pronounced variations in most of cell populations (Fig. 3 e-g and Supplementary Table 3). The proportions of CD8 + T cells and non-MDSC neutrophils were greatly increased (Fig. 3 e-g and Extended Data Fig. 8f-g) 52 , 53 , with a concomitant increase in all subsets of CD8 + T cells (Fig. 3 h-i), whereas ILC1, ILC3 and monocytes were mildly decreased in Tmem176b -deficient tumors relative to scramble tumors (Fig. 3 e-g). The increased infiltration of CD8 + T cells in Tmem176b -deficient MC38 tumors was also observed by immunofluorescence staining (Fig. 3 j-k). Therefore, unlike the global effects of TDEs on TIME, the most affected population by Tmem176b ablation is CD8 + T cells. Furthermore, the loss of increased growth control of Tmem176b -deficient tumors in Rag1 −/ − mice was restored by adoptive transfer of antigen-specific P14 CD8 + T cells (Fig. 3 l), confirming that the increased growth control of Tmem176b -deficient tumors was due to the enhanced antitumor CD8 + T cell immunity. Tmem176b deficiency in tumors enhances antitumor CD8 + T cell immunity We next performed flow cytometry to validate the difference of intratumoral T cells in scramble and Tmem176b -deficient tumors. In accord with the results of scRNA-seq analysis, flow cytometry analysis also demonstrated a marked increase in CD8 + T cells, CD44 + CD62L − effector and PD1 + Tim3 + terminally exhausted CD8 + T subsets, and a mild increase in those of CD4 + T cells in Tmem176b -deficient B16F10 and MC38 tumors relative to scramble tumors (Fig. 4 a-b and Extended Data Fig. 9a-b). Correspondingly, both the percentages and numbers of IFN-γ- and TNF-α-producing CD8 + T cells were dramatically increased in Tmem176b -deficient tumors, while the production of such cytokines in CD4 + T cells was slightly enhanced (Fig. 4 c-d and Extended Data Fig. 9c-d). Furthermore, the frequencies of both CD4 + T cells and CD8 + T cells were significantly higher in the TdLN of mice bearing Tmem176b -deficient MC38 tumors than in counterparts of scramble MC38 tumors (Extended Data Fig. 9e-f). Not only the increased numbers and activities of effector CD8 + T cells in Tmem176b -deficient tumors (Fig. 4 e-f and Extended Data Fig. 9g-l), but also the higher frequencies of T cells in the corresponding TdLN (Extended Data Fig. 9m-n), were repressed by re-expression of Tmem176b in Tmem176b -deficient cancer cells, thereby further confirming the on-target effect of CRISPR-Cas9-mediated Tmem176b gene deletion on the antitumor T cell immunity. We next asked whether exogenously introduced exosomal Tmem176b could suppress the antitumor T cell immunity. Co-inoculation of syngeneic exosomes from WT rather than Tmem176b -deficient cancer cells reduced CD8 + T cells, CD44 + CD62L − effector and PD1 + Tim3 + terminally exhausted CD8 + T subsets, and their cytokine-producing capacities in Tmem176b -deficient B16F10 and MC38 tumors (Fig. 4 g-h and Extended Data Fig. 10a-f). Correspondingly, the higher frequencies of T cells in the TdLN of mice bearing Tmem176b -deficient MC38 tumors were also suppressed by co-inoculation of syngeneic exosomes from WT rather than Tmem176b -deficient MC38 cells (Extended Data Fig. 10g-h). These results further confirmed that TDEs are functioning through Tmem176b to suppress antitumor T cell response and thus facilitate tumor growth. Tumor-derived exosomal Tmem176b attenuates proximal TCR signaling Consistent with the finding that TDEs are functioning through Tmem176b to suppress antitumor T cell response (Fig. 4 ), we identified tumor-derived exosomal Tmem176b as a negative regulator of T cell early activation in the aforementioned small-scale CRISPR-Cas9 arrayed in-vitro T cell activation screen (Extended Data Fig. 10h). The inhibitory role of tumor-derived exosomal Tmem176b on T cell early activation was further confirmed using exosomes purified from monoclonal Tmem176b knockout (T8KO) murine cancer cells (B16F10 and MC38) (Fig. 5 a-b). More importantly, this function of Tmem176b is conserved between mouse and human, because treatment of exosomes from human cancer cells (HeLa and SW480) substantially inhibited early activation of human primary T cells while treatment of exosomes from monoclonal TMEM176B knockout (T176B-KO) human cancer cells failed (Fig. 5 c-d). We next sought to test whether tumor-derived exosomal Tmem176b could affect TCR signaling, which is responsible for T cell activation and proliferation. To this end, we treated naive T cells with or without exosomes from Tmem176b -deficient (T8KO) or Tmem176b -overexpressed (T-OE) B16F10 cells, followed by stimulation with anti-CD3 antibodies. Notably, after stimulation with TCR, phosphorylation of proximal TCR signaling components (including PLC-γ1, SLP76, LAT) was markedly compromised in response to treatment of exosomes from Tmem176b -overexpressed B16F10 cells (Fig. 5 e). By contrast, treatment of exosomes from Tmem176b -deficient cells failed to attenuate these proximal TCR signaling events (Fig. 5 e). Therefore, these results suggested that tumor-derived exosomal Tmem176b inhibits T cell early activation by attenuating proximal TCR signaling. To delineate the molecular mechanism by which tumor-derived exosomal Tmem176b attenuates TCR signaling and suppresses early T cell activation, we used a proteomics approach to identify binding partners of Tmem176b in mouse T cell lymphoma EL4 cells before and after TCR stimulation. Mass spectrometry of immunocomplexes purified by affinity chromatography of Flag-tagged Tmem176b stably expressed in EL4 cells, identified 357 and 346 proteins associated with Tmem176b before or after TCR stimulation respectively, including proteins involved in the regulation of T cell activation and TCR signaling, in addition to proteins involved in vesicle transport (Fig. 5 f and Supplementary Table 6). Among these, LAT and non-receptor protein tyrosine phosphatase Shp1 were the most noteworthy, because LAT is the core of TCR signalsome to transduce antigenic signaling and Shp1 is thought to have a predominantly, if not exclusively, inhibitory role in TCR signaling 54 . Co-immunoprecipitation assay confirmed the interaction between Flag-tagged Tmem176b and endogenous Shp1 or LAT in EL4 cells (Fig. 5 g-h). Deletion mapping of Tmem176b showed that the absence of the C-terminus (amino acids 218–263) and, in particular, of amino acids 218–227, completely abolished the binding to Shp1 (Fig. 5 i-j). In contrast, deletion of N-terminus of Tmem176b, which contains an ITIM motif, did not reduce the binding to Shp1 (Fig. 5 i-j). Deletion of either side of the large loop of Tmem176b showed almost complete loss of binding to LAT (Fig. 5 k). To demonstrate the functional importance of the Shp1 binding region of Tmem176b, we reintroduced WT or mutant Tmem176b (with a deletion of amino acids 218–227, called TΔ218–227) into Tmem176b -deficient B16F10 cells. In tumor growth experiments, reintroduction of WT Tmem176b (T-OE) restored tumor growth rate of Tmem176b -deficient cells to the levels of scramble tumor cells, while that of mutant Tmem176b (TΔ218-227-OE) had no effect (Fig. 5 l). To understand how tumor-derived exosomal Tmem176b attenuates proximal TCR signaling by recruiting Shp1, we next sought to examine its subcellular localization in CD8 + T cells by immunofluorescence staining. When naïve CD8 + T cells were incubated with Tmem176b-GFP-carrying B16F10 exosomes labeled with a self-quenched probe, octadecyl rhodamine B chloride (R18), fluorescence was triggered and colocalized with Tmem176b, suggesting that B16F10 exosomes fused with plasma membranes of naïve CD8 + T cells and that exosomal Tmem176b was delivered to T cell plasma membranes (Fig. 5 m). After stimulation with cognate peptide-pulsed B cells, tumor-derived exosomal Tmem176b accumulated at the immunological synapse of CD8 + T cells (Fig. 5 n). Moreover, pretreatment of naïve CD8 + T cell with Tmem176b-carrying TDEs led to more recruitment of Shp1 to the immunological synapse of CD8 + T cells after conjugation with peptide-pulsed B cells. By contrast, in T cell-B cell conjugates without TDEs pretreatment, Shp1 was more diffusely spread out of the immunological synapse (Fig. 5 n-o). We then investigated whether inhibition of antitumor T cell immunity by tumor-derived Tmem176b was mediated by Shp1. To address this, we inoculated Scramble or Tmem176b -deficient B16F10 or MC38 cells subcutaneously into WT or T cell-specific Shp1 conditional knockout mice ( Ptpn6 fl/fl dLck-Cre, called Shp1-tKO here). In both tumor models, Tmem176b -deficient tumors grew much slower than Scramble tumors in WT mice. Ablation of Shp1 in T cells markedly restrained the growth of Scramble tumors, but deletion of Tmem176b in tumor cells did not further improve tumor control in Shp1-tKO mice, suggesting Shp1 was required for inhibition of T cell activity by Tmem176b (Fig. 5 p-q). Together, these data demonstrated that tumor-derived exosomal Tmem176b attenuates TCR signaling by recruiting Shp1 to the immunological synapse of T cells via LAT and thus suppresses antitumor T cell immunity. Tmem176b blockade restrains tumor growth Given that the region of amino acids 218–227 in C terminus of Tmem176b was responsible for the interaction between Tmem176b and Shp1 (Fig. 5 i-j), we generated a cell-permeable competitive peptide by fusing cell-penetrating peptide with amino acids 218–232 of Tmem176b (called CPP-Pep hereinafter). Addition of CPP-Pep to the cell culture significantly disrupted the interaction between Tmem176b and Shp1 in EL4 cells (Extended Data Fig. 11a). After treating EL4 cells with the CPP-Pep, immunofluorescence staining showed that the CPP-Pep co-localized with Shp1 in the cytoplasm of EL4 cells (Extended Data Fig. 11b). To examine the effect of CPP-Pep on the inhibition of T cell early activation by TDEs, we treated naïve CD8 + T cells with B16F10 exosomes plus CPP-Pep or Scramble peptide (Cpp-Scr), in the presence of anti-CD3 and anti-CD28 antibodies. CPP-Pep addition significantly enhanced early activation of CD8 + T cells, suggesting that the inhibitory effect of TDEs on T cells was relieved (Extended Data Fig. 11c). We next sought to evaluate the therapeutic effect of CPP-Pep on tumor growth in immunocompetent mice. We administrated B16F10 tumor-bearing C57BL/6J mice with CPP-Pep via twice intraperitoneal injection after tumor size reaching about 200 mm 3 . Consistent with the observed growth retardation of Tmem176b -deficient B16F10 tumors, CPP-Pep administration resulted in significant tumor rejection and host survival extension compared with Scramble and vehicle treatment (Fig. 6 a-b). Similar results were obtained in MC38 tumor models, in which triple intraperitoneal injection of CPP-Pep strongly delayed tumor growth and prolonged animal survival (Fig. 6 c-d). We then tested the efficacy of CPP-Pep in lung metastasis models. CPP-Pep administration at day 3 post injection, substantially reduced the numbers of lung metastases, compared to Scramble and vehicle treatment (Extended Data Fig. 11d-e). As tumor-derived exosomal Tmem176b recruited Shp1 in CD8 + T cells though its C-terminus (Fig. 5 i-j), we speculated that the large loop of Tmem176b could be exposed in the extracellular space of CD8 + T cells when Tmem176b-carrying TDEs fuse with CD8 + T cells. We screened high-affinity neutralizing antibodies against the large loop of murine Tmem176b or human TMEM176B using in vitro T cell activation system, since the large loop of Tmem176b is responsible for its binding to LAT (Fig. 5 k). Like CPP-Pep treatment, addition of monoclonal antibody (6E8) against Tmem176b to CD8 + T cell culture abrogated B16F10-derived exosomes-induced attenuation of CD8 + T cell activation (Extended Data Fig. 11c). Similarly, addition of monoclonal antibody against human TMEM176B (2F2) also abolished the suppression of human T cell activation by exosomes from human cancer cells (HeLa and SW480) (Extended Data Fig. 11f). Triple intraperitoneal administration of anti-Tmem176b (6E8) antibody into B16F10-bearing C57BL/6J mice markedly inhibited tumor growth and extended host survival (Fig. 6 e-f). Moreover, we observed analogous tumor rejection and animal survival extension in MC38-bearing mice after 6E8 treatment (Fig. 6 g-h). Furthermore, 6E8 treatment had no effect on the growth of Tmem176b -deficient B16F10 tumors (Extended Data Fig. 11g), indicating that tumor-derived Tmem176b, instead of host Tmem176b, is the real target of 6E8. Given the normal tumor growth in Tmem176b −/− and dendritic cell-specific Tmem176b -deficient mice, these data further confirmed that tumor-drived Tmem176b, rather than host Tmem176b, facilitates tumor progression. We then further evaluate the antitumor effects of Tmem176b blockade in Hepa1-6 orthotopic mouse model, in which mouse hepatocellular carcinoma Hepa1-6 cells were orthotopically implanted in the livers of C57BL/6J mice. Triple intraperitoneal administration of either CPP-Pep or 6E8 significantly inhibited tumor growth as tumor volumes were dramatically reduced, compared with vehicle treatment or CPP-Scr treatment (Extended Data Fig. 11h-i). Collectively, these findings demonstrate that Tmem176b blockade is therapeutically effective in tumor rejection in both heterotopic and orthotopic transplanted tumor models. Synergy with anti-PD1/PD-L1 therapy PD1 is expressed after T cell activation and acts as a brake for the function of activated T cells 55 . Our study demonstrated that tumor-derived exosomal Tmem176b is a negative regulator in proximal TCR signaling and T cell early activation. PD1 + Tim3 + terminally exhausted CD8 + T cells were significantly increased in Tmem176b -deficient tumors compared with Scramble tumors (Fig. 4 a-b, g and Extended Data Fig. 10a,c-d). This prompted us to test whether Tmem176b blockade may have a synergistic effect with anti-PD1 therapy. B16F10 melanoma is a low immunogenic tumor model that poorly responds to anti-PD1/PD-L1 therapy. Administration of anti-PD1 antibody into B16F10-bearing C57BL/6J mice only slightly reduced tumor growth with lower efficacy than that of CPP-Pep administration. However, administration of CPP-Pep in combination with treatment with anti-PD1 exhibited stronger capability to inhibit tumor growth and to extend host survival than either single treatment did, suggesting that CPP-Pep has a synergistic antitumor effect with anti-PD1 therapy (Fig. 6 i-j). MC38 is a highly immunogenic colon carcinoma model. Notably, treating MC38-bearing C57BL/6J mice with anti-PD1 antibody substantially delay tumor growth, although its efficacy is lower than CPP-Pep treatment. Combination of PD1 blockade with CPP-Pep treatment had an additive effect, resulting in more rapid tumor rejection and longer survival extension in MC38 bearing mice than either treatment alone (Fig. 6 k-l). We next examined whether the observed synergy between Tmem176b competitive peptide (CPP-Pep) and anti-PD1 antibody treatment could be recapitulated by using Tmem176b neutralizing antibody 6E8. Similar to CPP-Pep treatment, 6E8 administration alone was already more efficient in tumor growth control than anti-PD1 therapy, in both B16F10 and MC38 tumor models (Fig. 6 m-p). Furthermore, the efficacies of single treatments were enhanced significantly when combined 6E8 treatment with anti-PD1 antibody, with much longer extension of host survival (Fig. 6 m-p). We then applied monoclonal antibody against human TMEM176B (2F2) to humanized mice models. Immunodeficient NCG mice were transplanted with human hematopoietic stem cells (HSCs) to generate huHSC-NCG mice, followed by inoculation with A375 human melanoma cells. We then administrated these A375-bearing huHSC-NCG mice with anti-TMEM176B (2F2) antibody or anti-PD-L1 antibody (atezolizumab) alone, or their combination, via intraperitoneal injection after tumor size reaching about 200 mm 3 (Fig. 6 q). Anti-TMEM176B treatment showed remarkable tumor growth inhibition and host survival extension, with significant superiority over anti-PD-L1 antibody treatment, whereas the combination treatment had a large synergistic effect, with a higher level of tumor rejection and host survival extension than either single treatment (Fig. 6 r-s). Taken together, these data suggest TMEM176B blockade could be a promising strategy to boost the therapeutic efficacy of ICB therapy in human cancer treatment. Discussion TDEs have been not only implicated in immunosuppression and tumor progression, but also considered as multiparameter biomarker platforms of liquid biopsy for cancer diagnosis and prognosis. However, a reliable target on TDEs that can be used for both liquid biopsy and immunotherapy is still lacking. In this study, we identified TMEM176B + circulating exosomes in the plasma from various types of patients with early- and late-stage cancer but not from healthy subjects, whose levels negatively correlated with patient survival and clinical outcomes of anti-PD1 therapy. We have also demonstrated that Tmem176b on TDEs suppressed T cell early activation and thus promoted tumor progression, which provides a promising target to overcome tumor-intrinsic resistance to immunotherapy (Extended Data Fig. 12). Early cancer diagnosis is critical for improving patient survival and reducing mortality rates. However, routine imaging tests would be prohibitively expensive and have low sensitivity and specificity, and the utility of tissue biopsies is limited by the requirement that the tumor should be surgically accessible 36,56 . To address these challenges, researchers have developed liquid biopsy platforms including circulating tumor cells (CTC), cell-free tumor DNA (ctDNA) and EVs. Unlike CTC and ctDNA that are typically associated with later or even more advanced disease stage, EVs are actively released by growing cells and contain cargoes closely reflecting the cells of origin associated with health or very early stages of disease 57 . EVs, especially exosomes, may confer superior diagnostic and prognostic performance relative to other liquid biopsies, because the abundance and composition of circulating exosomes are usually altered in individuals with cancer. Cancer cells secrete more exosomes than their nonmalignant conterparts 29,36,58 , which are further enhanced by various tumor microenvironment characteristics such as hypoxia 59-61 . A recent study demonstrated that phosphorylation of Hrs by oncogenic signaling leads to selective loading of cargo proteins including PD-L1 to exosomes in cancer cells 30 . As Tmem176b was also found to interact with Hrs, highly phosphorylated Hrs in cancer cells might also help sort Tmem176b to exosomes. Consistently, TMEM176B + circulating exosomes were specifically detected in the plasma of patients with early- and late-stage cancer but not in that of healthy subjects. Furthermore, the levels of TMEM176B + circulating exosomes inversely correlated with cancer patient survival. Thus, our results suggested that TMEM176B + circulating exosomes may serve as a potential non-invasive diagnostic and screening tool to detect early cancer. As the expression of any single biomarker can be variable across individuals, combined panels of biomarkers can better reflect a disease’s multiple biological processes in the setting of cancer. For example, a five-marker panel (including LMP1, LMP2A, PD-L1, EGFR and EpCAM) of analysis on plasma EVs by NanoFCM significantly surpassed the traditional assay in discriminating nasopharyngeal carcinoma (NPC) from both healthy donors and nasopharyngitis (NPG) patients 62 . As such, combination of the pan-cancer biomarker TMEM176B and any cancer-type-specific markers may help more accurately differentiate cancer patients from healthy donors in clinical practice. Tmem176b has been originally identified as an immune regulatory cation channel in immature dendritic cells 63,64 . A previous study revealed that Tmem176b inhibited inflammasome activation by controlling cytosolic Ca 2+ in dendritic cells, and tumor growth was suppressed in Tmem176b -deficient mice, originally generated in 129 background and backcrossed onto C57BL/6 background for 10 times, due to enhanced antitumor CD8 + T cell immunity 65 . However, the role of host Tmem176b in antitumor immunity remains controversial. Two other groups failed to observe the enhanced antitumor capacity in Tmem176b - or Tmem176a/b -deficient mice in pure C57BL/6 background generated by CRISPR-Cas9 technology 41,66 . We also did not observe enhanced tumor control in either germline Tmem176b- deficient or DC-specific Tmem176b - or Tmem176ba/b- deficient mice in pure C57BL/6 background. Therefore, this discrepancy need further investigation. In patients with solid tumors, ICB nonresponders often exhibit a ‘immunologically cold’ or ‘immune-desert’ phenotype, characterized by the absence or exclusion of T cells in the tumor parenchyma 3 . Extensive endeavors are underway to turn ‘cold’ tumors into ‘hot’ tumors to achieve better response to immunotherapy 6 . Targeting tumor-intrinsic resistance has emerged as an attractive strategy to increase the response rate and efficacy of ICB therapy for cancers. Prevention of MHC-Ⅰdegradation in tumor, by inhibition of PCSK9 or autophagy, or deletion of SUSD6/TMEM127/WWP2 inhibitory axis, enhances intratumoral infiltration of CD8 + T cells, thereby sensitizing tumor to immune checkpoint blockade 13-15 . Genetic ablation or pharmaceutical inhibition of TBK1 or Ptpn2 in tumor enhances the response of tumor to effector cytokines, and thus increases efficacy of immunotherapy 67-69 . Although TDEs have been shown to modulate many types of immune cells including T cells, whether TDEs directly impede the priming, early activation and proliferation of T cells remains unclear. We presented evidence that tumor-derived exosomal Tmem176b suppressed T cell early activation by recruiting Shp1 to TCR proximal signalosome. Genetic ablation of Tmem176b increased intratumoral infiltration by both effector and exhausted CD8 + T cells, thereby providing a compelling rationale for the combination of anti-PD1 antibody and Tmem176b blockade. Tmem176b normally localizes on the membrane of intracellular vesicular compartments such as endosome and Golgi, but not on the plasma membrane 41,70 , and is secreted via exosoms only in cancer cells. Similar to our findings, other group has reported that host Tmem176b does not promote tumor growth 41 . It is reasonable to speculate that therapeutic administration of monoclonal antibody against TMEM176B could have very low toxicity. In summary, our study has demonstrated that tumor-derived exosomal Tmem176b suppresses T cell early activation and facilitates tumor progression. Blocking Tmem176b exhibits potent antitumor efficacy as well as synergistic effects with immune checkpoint blockade, providing a convincing strategy for cancer immunotherapy. The selectively enrichment of TMEM176B on circulating exosomes in peripheral blood of various types of cancer patients opens a new avenue for non-invasive cancer diagnosis and prognosis, with promising clinical application. Methods Key Resources Tables REAGENT or RESOURCE SOURCE IDENTIFIER Antibodies Clone# Biotin anti-mouse CD28 37.51 BioLegend 102104, RRID:AB_312868 Biotin anti-mouse CD3 145-2C11 BioLegend 100304, RRID:AB_312669 Biotin anti-mouse CD4 GK1.5 BioLegend 100404, RRID:AB_312689 Biotin anti-mouse CD5 53-7.3 BioLegend 100604, RRID:AB_312732 Biotin anti-mouse CD8 53-6.7 BioLegend 100704, RRID:AB_312742 Biotin anti-mouse CD9 MZ3 BioLegend 124804, RRID:AB_2076036 Biotin anti-mouse CD11b M1/70 BioLegend 101204, RRID:AB_312787 Biotin anti-mouse CD11c N418 BioLegend 117304, RRID:AB_313772 Biotin anti-mouse CD25 PC61 BioLegend 102004, RRID:AB_312852 Biotin anti-mouse CD43 1B11 BioLegend 121204, RRID:AB_493384 Biotin anti-mouse CD44 IM7 BioLegend 103004, RRID:AB_312955 Biotin anti-mouse CD45R/B220 RA3-6B2 BioLegend 103204, RRID:AB_312988 Biotin anti-mouse CD93 VIMD2 BioLegend 336104, RRID:AB_2076050 Biotin anti-mouse Ly-6G/Ly-6C RB6-8C5 BioLegend 108404, RRID:AB_313368 Biotin anti-mouse CD105 MJ7/18 BioLegend 120404, RRID:AB_961062 Biotin anti-mouse F4/80 BM8 BioLegend 123106, RRID:AB_893499 Biotin anti-mouse TCRg/d GL3 BioLegend 118103, RRID:AB_313827 Biotin anti-mouse NK-1.1 PK136 BioLegend 108704, RRID: AB_313390 Biotin anti-mouse TER-119 TER-119 BioLegend 116204, RRID:AB_313704 LEAF™ Purified anti-mouse CD3e 145-2C11 BioLegend 100359, RRID:AB_2800555 LEAF™ Purified anti-mouse CD28 37.51 BioLegend 102121, RRID:AB_11147170 Anti-Mouse CD279 (PD-1) RMP1-14 Leinco technologies P372, RRID:AB_2749820 Purified anti-mouse CD16/32 93 BioLegend 101302, RRID:AB_312800 Anti-mouse CD3, Alexa Fluor647 145-2C11 BioLegend 100209, RRID:AB_389323 Anti-mouse CD3e, PE-Cyanine7 145-2C11 ebioscience 25-0031-82, RRID:AB_469572 Anti-mouse TCR β chain, BV785 H57-597 Biolegend 109249, RRID:AB_2810347 Anti-mouse CD4, FITC RM4-4 ebioscience 11-0043-85, RRID:AB_464901 Anti-mouse CD4 , PerCP-Cy5.5 RM4-5 ebioscience 45-0042-82, RRID:AB_1107001 Anti-mouse CD4, eFluor450 RM4-5 ebioscience 48-0042-82, RRID:AB_1272194 Anti-mouse CD4, APC-eFluor780 RM4-5 eBioscience 47-0042-82, RRID:AB_1272183 Anti-mouse CD8a, APC-eFluor780 53-6.7 ebioscience 47-0081-82, RRID:AB_1272185 Anti-mouse CD8, Percp/cy5.5 53-6.7 BD Bioscience 551162, RRID:AB_394081 Anti-mouse CD8, Alexa Fluor647 53-6.7 Biolegend 100724, RRID:AB_389326 Anti-mouse CD19, APC-eFluor780 eBio1D3 eBioscience 47-0193-82, RRID:AB_10853189 Anti-mouse CD19, PE-Cy7 eBio1D3 eBioscience 25-0193-82, RRID:AB_657663 Anti-mouse CD19, PE eBio1D3 eBioscience 12-0193-81, RRID:AB_657661 Anti-mouse CD19, FITC eBio1D3 eBioscience 11-0193-85, RRID:AB_657668 Anti-mouse CD25, APC PC61.5 eBioscience 17-0251-82, RRID:AB_469366 Anti-mouse CD25, PE PC61.5 eBioscience 12-0251-83, RRID:AB_465608 Anti-mouse CD44, PE-Cy7 IM7 BD Bioscience 560569, RRID:AB_1727484 Anti-mouse CD69, PE H1.2F3 BD Bioscience 561932, RRID:AB_394726 Anti-mouse CD44, BV650 IM7 BD Bioscience 740455, RRID:AB_2740182 Continued REAGENT or RESOURCE SOURCE IDENTIFIER Anti-mouse CD62L, APC MEL-14 eBioscience 17-0621-83, RRID:AB_469411 Anti-mouse CD62L, PE/Cy7 MEL-14 BioLegend 104418, RRID:AB_313102 Anti-mouse CD71, APC R17217 eBioscience 17-0711-82, RRID:AB_1834355 Anti-mouse B220, BV510 RA3-6B2 BD Bioscience 563103, RRID:AB_2738007 Anti-mouse B220, BV650 RA3-6B2 BD Bioscience 563893, RRID:AB_2738471 Anti-mouse B220, PerCP/Cy5.5 RA3-6B2 BioLegend 103236, RRID:AB_893354 Anti-human/mouse B220 APC RA3-6B2 eBioscience 17-0452-83, RRID:AB_469396 Anti-human/mouse B220 eFluor450 RA3-6B2 eBioscience 48-0452-82, RRID:AB_1548761 Anti-mouse ICOS, PE 7E.17G9 eBioscience 12-9942-82, RRID:AB_466274 Anti-mouse CD279 (PD-1), PE 29F.1A12 BioLegend 135206, RRID:AB_1877231 Anti-mouse CD279 (PD-1), FITC 29F.1A12 BioLegend 135214, RRID:AB_10680238 Anti-mouse Tim-3, BV 421 RMT3-23 BioLegend 119723, RRID:AB_2616908 Anti-mouse IFN-γ, APC XMG1.2 BioLegend 505810, RRID:AB_315403 Anti-mouse TNF alpha, PE TN3-19.12 eBioscience 12-7423-41, RRID:AB_11149178 Anti-mouse Granzyme B, eFluor450 NGZB eBioscience 48-8898-82, RRID:AB_11149362 Anti-mouse FOXP3, PE FJK-16S eBioscience 15-5773-82, RRID:AB_468806 Anti-GFP, Alexa Fluor488 FM264G BioLegend 338008, RRID: AB_2563287 Fixable Viability Dye, eFluor506 ebioscience 65-0866-18 Biotin anti-human CD11b ICRF44 Biolegend 301304, RRID:AB_314156 Biotin anti-human CD16 3G8 Biolegend 302004, RRID:AB_314204 Biotin anti-human CD19 H1B19 Biolegend 302204, RRID:AB_314233 Biotin anti-human CD41a HIP8 Biolegend 303734, RRID:AB_2687174 Biotin anti-human CD56 MEM-188 Biolegend 304620, RRID:AB_528851 Biotin anti-human CD235a HIR2 Biolegend 306618, RRID:AB_2565773 Biotin anti-human CD36 5-271 Biolegend 336218, RRID:AB_2565771 Biotin anti-human CD45RO antibody UCHL1 Biolegend 304220, RRID:AB_893359 Ultra-LEAF™ Purified anti-human CD28 Antibody CD28.2 Biolegend 302934, RRID:AB_11148949 Ultra-LEAF™ Purified anti-human CD3 Antibody OKT3 Biolegend 317326, RRID:AB_11150592 Anti-human CD69, FITC FN50 Biolegend 310904, RRID:AB_314838 Anti-human CD3, PE/Cy7 UCH71 Biolegend 300420, RRID:AB_439780 Anti-human CD25, APC M-A251 Biolegend 356110, RRID:AB_2561976 Anti-human CD71, PE CY1G4 Biolegend 334106, RRID:AB_2271603 Anti-human CD45RA, FITC HI100 Biolegend 304105, RRID:AB_314410 Alix Rabbit mAb ABclonal A2215, RRID:AB_2764230 Beta Actin Monoclonal antibody proteintech 66009-1-Ig, RRID:AB_2687938 CD63 Rabbit pAb ABclonal A5271, RRID:AB_2766092 CD63 Monoclonal Antibody 3D4D1 Proteintech 67605-1-Ig, RRID:AB_2882811 LAMP1 Rabbit pAb ABclonal A2582, RRID:AB_2770145 HGS (Hrs) Rabbit mAb ABclonal A1790, RRID:AB_2763831 Continued REAGENT or RESOURCE SOURCE IDENTIFIER Goat anti-Rabbit IgG (H+L) Highly Cross-Adsorbed Secondary Antibody, Alexa Fluor™488 Invitrogen A-11034, RRID:AB_2576217 FLAG® M2 mouse monoclonal Sigma F1804 LAT Polyclonal antibody Proteintech 11326-1-AP, RRID:AB_10695624 LCK Rabbit pAb ABclonal A2177, RRID:AB_2764195 Phospho-LAT (Tyr220) Antibody CST 3584T Phospho-PLCγ1 (Tyr783) Antibody CST 2821T Phospho-SHP1-Y564 Rabbit pAb ABclonal AP0787, RRID:AB_2771481 Phospho-SLP-76 (Ser376) (E3G9U) XP® Rabbit mAb CST 76384T Phospho-Zap-70 (Tyr493)/Syk (Tyr526) Antibody CST 2704T Phospho-ZAP70 (Y493) Antibody RD MAB7694-SP p-LAT(Tyr220) (E3S5L) Rabbit mAb CST 20172S pLCK(Y505) Rabbit pAb ABclonal AP0285, RRID:AB_2771264 PLCγ-1 Rabbit mAb ABclonal A8899, RRID:AB_2863625 RAB27A Rabbit pAb ABclonal A1934, RRID:AB_2862644 Rab5 (C8B1) Rabbit mAb CST 3547T RAB7 Rabbit pAb ABclonal A12784, RRID:AB_2759627 SHP1 Rabbit pAb ABclonal A19111, RRID:AB_2862604 T Cell Signaling Antibody Sampler Kit CST 14541T TMEM176B Rabbit pAb ABclonal A16118, RRID:AB_2763562 Anti-mouse Tmem176b 6E8 ABclonal This paper Anti-human TMEM176b 2F2 ABclonal This paper Anti-mouse PD1 RMP1-14 Leinco technologies P362, RRID:AB_2749820 Anti-Human PD-L1 Atezolizumab BioXCell SIM0009, RRID:AB_2894730 TSG101 Rabbit mAb ABclonal A2216, RRID:AB_2764231 HRP Goat Anti-Mouse IgG (H+L) ABclonal AS003, RRID:AB_2769851 HRP Goat Anti-Rabbit IgG (H+L) ABclonal AS014, RRID:AB_2769854 Anti-mouse IgG (H+L), F(ab')2Fragment (Alexa Fluor®488 Conjugate) CST 4408S Anti-rabbit IgG (H+L), F(ab')2 Fragment (Alexa Fluor®594 Conjugate) CST 8889S Goat anti-Rabbit IgG (H+L) Highly Cross-Adsorbed Secondary Antibody, Alexa Fluor™ 555 Invitrogen A-21429, RRID:AB_2535850 Streptavidin 4A biotech FXP024-010 REAGENT or RESOURCE SOURCE IDENTIFIER Chemicals and recombinant proteins Foxp3 / Transcription Factor Fixation / Permeabilization Concentrate and Diluent eBioscience 00-5523-00 BD Cytofix/Cytoperm™ Fixation /Permeabilization Solution Kit BD Bioscience 554714 CellTrace™ CFSE Cell Proliferation Kit Invitrogen C34554 ECL select GE healthcare RPN2235 Percoll GE Healthcare 17-0891-01 DNase I Roche 10104159001 Collagenase D Roche 11088882001 phorbol 12-Myristate 13-Acetate Sigma-Aldrich P1585-1MG Ionomycin YEASEN 50401ES03 GolgiPlug BD Biosciences 555029 CellTrace™ CFSE Invitrogen C34554 Pierce™ BCA Protein Assay Kits Thermo Scientific A55864 Fluo-4, AM Invitrogen F14201 ANTI-FLAG® M2 Affinity Gel, purified immunoglobulin Sigma-Aldrich A2220 Biosci™ Human Lymphocyte Separation Medium I (Ficoll) DAKEWEI 7111011 SignalUpTM Super Sensitive ELISA Assay Kit with Fluorescent HRP Substrate Beyotime P0205 Antifade Mounting Medium with DAPI Beyotime P0131 Streptavidin-POD Kit Solarbio SP0041 DAB Substrate kit,20× Solarbio DA1010 Neutral balsam Solarbio G8590 DMEM Yuanpei L110KJ RPMI-1640 Yuanpei L210KJ MEM NEAA Gibco 11140050 Sodium pyruvate Gibco 11360070 HEPES Gibco 15630080 Penicillin and Streptomycin Gibco 15140122 Recombinant Human FLT3LG Novoprotein CA82 Recombinant Mouse IFN gamma Novoprotein CM40 Recombinant human IFN gamma Novoprotein C014 Experimental models: Cell lines REAGENT or RESOURCE SOURCE IDENTIFIER B16F10 (mouse melanoma) ATCC CRL-6475, RRID:CVCL_0159 MC38 (mouse colon adenocarcinoma) Dr. John Teijaro (The Scripps Research Institute) RRID:CVCL_B288 B16GP33 Dr. Ananda Goldrath (University of California, San Diego) N/A Hepa1-6 (mouse hepatoma) ATCC CRL-1830, RRID:CVCL_0327 NIH3T3 (murine embryonic fibroblast) ATCC CRL-1658, RRID:CVCL_0594 HeLa (human cervical carcinoma) ATCC CCL-2, RRID:CVCL_0030 EL4 (mouse T lymphoma) ATCC TIB-39, RRID:CVCL_0255 SW480 (human colorectal adenocarcinoma) ATCC CCL-228, RRID:CVCL_0546 293T (human kidney epithelial-like cells) ATCC CRL-3216, RRID:CVCL_0063 A549 (human Non-small cell lung cancer cells) ATCC CCL-185, RRID:CVCL_0023 A375 (human melanoma) ATCC CRL-1619, RRID:CVCL_0132 BEAS-2B (human normal lung epithelial cells) ATCC CRL-3588, RRID:CVCL_0168 MCF-10A (human normal mammary epithelial cells) ATCC CRL-10317, RRID:CVCL_0598 Experimental models: Mouse C57BL/6J Jackson Laboratory 000664, RRID:IMSR_JAX:000664 Rag1 -/- Jackson Laboratory 002216, RRID:IMSR_JAX:002216 Tcrb -/- Tcrd -/- Jackson Laboratory 002122, RRID:IMSR_JAX:002122 Igh-j -/- Igk -/- Jackson Laboratory 002438&011074 CD8a -/- Jackson Laboratory 002665, RRID:IMSR_JAX:002665 dLck -Cre Jackson Laboratory 012837, RRID:IMSR_JAX:012837 CD11c -Cre Jackson Laboratory 008068, RRID:IMSR_JAX:008068 EIIA-cre Jackson Laboratory 003724, RRID:IMSR_JAX:003724 P14 Jackson Laboratory 004694, RRID:IMSR_JAX:004694 OT-I Jackson Laboratory 003831, RRID:IMSR_JAX:003831 Ptpn6 fl/fl Zhongjun Dong (Tsinghua University) 008336, RRID:IMSR_JAX:008336 Tmem176b fl/fl Cyagen S-CKO-12834 Tmem176a/b fl/fl Cyagen AIBM0240 Recombinant DNA pMD2.G Addgene 12259 psPAX2 Addgene 12260 LentiCRISPRv2-mTmem176b-sgRNA2-mCherry This paper N/A LentiCRISPRv2-mTmem176b-sgRNA3-mCherry This paper N/A LentiCRISPRv2-mTmem176b-sgRNA8-mCherry This paper N/A Continued REAGENT or RESOURCE SOURCE IDENTIFIER LentiCRISPRv2-hTMEM176B-sgRNA3-mCherry This paper N/A LentiCRISPRv2-m Rab27a -sgRNA1-mCherry This paper N/A LentiCRISPRv2-m Rab27a -sgRNA2-mCherry This paper N/A LentiCRISPRv2-m Rab27a -sgRNA3-mCherry This paper N/A plv-Tmem176b-3×Flag-IRES-eGFP This paper N/A plv-eGFP-Tmem176b This paper N/A plv-eBFP-Shp1 This paper N/A Human sample preparation Colorectal cancer tissues and adjacent normal tissues from patients, and peripheral blood from cancer patients and healthy donors, were collected by the First Affiliated Hospital of Xiamen University (Xiamen, China) with written informed consent from either subjects or their legal authorized representatives prior to sample collection. Tumor specimens were used for protein and RNA transcript detection, and peripheral blood samples from cancer patients or healthy donors were used for exosome isolation. Human peripheral blood mononuclear cells (PBMCs) were harvested from peripheral blood of health donors, by density gradient centrifugation with Ficoll (DAKEWE, 7111011). The use of all tissue and blood samples in this study were all approved by the Ethics Committees at the First Affiliated Hospital of Xiamen University (Xiamen, China). Animals C57BL/6J (B6) (#000664), Rag1 -/- (#002216), Tcrb -/- Tcrd -/- (TCD, #002122), Igh-j -/- Igk -/- (BCD, #002438⭂), CD8a -/- (#002665), dLck-Cre (#012837), CD11c-Cre (#008068), EIIA-cre (#003724), P14 (#004694) and OT-I (#003831) TCR transgenic mice were originally from the Jackson Laboratory. Ptpn6 fl/fl mice (Jax #008336) were kindly provided by Dr. Zhongjun Dong at Tsinghua University. Tmem176b fl/fl (S-CKO-12834) and Tmem176a/b fl/fl (AIBM0240) mice were generated in C57BL/6J background using CRISPR-Cas9 technology, by Cyagen. Tmem176b -/- mice were generated by crossing Tmem176b fl/fl to EIIA-cre (#003724) mice. HuHSC-NCG(NOD/ShiLtJGpt- Prkdc em26Cd52 Il2rg em26Cd22 /Gpt)(CH) mice (#T037620) were purchased from GemPharmatech (Nanjing, China). All mice (gender matched) were littermates and were 8-12 weeks old, unless otherwise indicated in the text. The mice were housed in specific pathogen-free facilities of Xiamen University Laboratory Animal Center with a light-dark cycle of 12 h, at a temperature about 22 ℃, humidity of 40-70%, and were fed with standard mouse chew diet. All animal experiments were performed in accordance with protocols approved by the Institutional Animal Care and Use Committee of Xiamen University. Cell lines The B16F10 (mouse melanoma), EL4 (mouse T lymphoma), NIH3T3 (mouse embryonic fibroblast), HeLa ( human cervical carcinoma ), SW480 (human colorectal adenocarcinoma), A549 (human lung carcinoma cells), MCF-10A (human mammary gland epithelia cells), 293T (human kidney epithelial-like cell) were originally from American Type Culture Collection (ATCC). BEAS-2B human bronchial epithelial cells were from Servicebio (Wuhan, China). MC38 (mouse colon adenocarcinoma) cell line was kindly provided by Dr. John Teijaro at The Scripps Research Institute. B16GP33 cell line was kindly provided by Dr. Ananda Goldrath at University of California, San Diego. A375 (human melanoma) cell line was a gift from Dr. Yan Li at Nanjing University. B16F10 cells were infected with lentivirus encoding Tmem176b-Flag to generate Tmem176b-Flag-expressing B16F10 cells. Tumor cell lines were cultured in DMEM (Yuanpei, L110KJ) supplemented with 10% Fetal Bovine Serum (FBS), 1% MEM NEAA (Gibco, 11140050), 100 U/mL penicillin and 100 μg/mL streptomycin (Gibco, 15140122). EL4 cell line were cultured in RPMI-1640 Medium (Yuanpei, L210KJ) supplemented with 10% FBS, 1 mM sodium pyruvate (Gibco, 11360070), 10 mM HEPES (Gibco, 15630080), 50 μM β-mercaptoethanol, 100 U/ml penicillin and 100 μg/ml streptomycin (Gibco, 15140122). All cells were cultured at 37 ℃ in a humidified atmosphere containing 5% CO 2 . Unless otherwise denoted, knockout cell lines were cultured in the same condition of the corresponding parental cells. Lentiviral transduction LentiCRISPRv2-mCherry was used for construction of candidate gene knockout cell lines, and plv-Tmem176b-3×Flag-IRES-eGFP, plv-eGFP-Tmem176b, plv-eBFP-Shp1 were used to establish stable gene-overexpression cell lines. 293T cells were seeded at 1×10 6 cells per well of 6-well dish before transfection. Cells were transfected with 200 μl Opti-MEM mixed with 2 μg lentiviral plasmids, lentiviral packing plasmids including 0.5 μg pMD2.G (Addgene, 12259) and 1.5 μg psPAX2 (Addgene, 12260), and 8 μl polyethylenimine (PEI) (1 mg/mL). The mixture was incubated 15 min at room temperature and then dropwise added to cells. After 6-8 h, the culture medium was replaced with pre-warmed fresh DMEM complete medium. Viral supernatant was collected at 48 h and 72 h post-transfection. Cell debris was removed by centrifugation with 1,000 g for 3 min. The aliquot of virus stock was stored at -80 ℃. 2×10 5 adherent cells (B16F10 or MC38) were cultured in 2 ml DMEM complete medium in 6-well plate to 40-50% confluency and were then changed to 1 ml fresh medium before infection. For suspension cells (EL4), 2×10 5 cells were resuspended with 100 μl RPMI-1640 complete medium in 24-well plate. 1 ml or 400 μl of virus supernatant containing 10 μg/ml polybrene was added into each well of 6-well or 24-well plates, respectively. Cells were centrifuged at 2,500 rpm for 30 min at 37 ℃ in a pre-warmed centrifuge. After being incubated at 37 ℃ for 12 h, cells were being cultured in fresh complete media until cell sorting. Cells then were resuspended in sorting buffer (PBS supplemented with 1 mM EDTA, 25 mM HEPES, and 1% FBS) and then sorted with a BD Aria III sorter. CRISPR-Cas9-mediated gene knockout Knockout cell lines were generated with lentivirus-mediated CRISPR-Cas9 technology. Single guide RNA (sgRNA) sequences were designed using CrisprGold systems  (https://crisprgold.mdc-berlin.de/index.php) and the sequences of sgRNA oligonucleotides are listed in Table S3 . Scrambled sgRNA served as a non-target control. Double-stranded oligonucleotides encoding the sgRNA sequences were cloned into the LentiCRISPRv2-mCherry, which co-express Cas9 and sgRNA in the same vector. To generate the gene knockout cancer cell lines, target cells (B16F10, MC38, HeLa or SW480) were infected with sgRNA-encoding CRISPR-Lentivirus. The positively infected cells were sorted by flow cytometry based on mCherry fluorescence and were seeded into 96-well plates for single-cell expansion. The expression of target proteins in infected cells was examined by western blot (for other candidates) or flow cytometry (for Tmem176b) to validate the knockout. Successful genomic editing was verified by sequencing of PCR products of the targeted region. Mouse tumor models For subcutaneous tumor models, 2×10 5 B16F10 or 1×10 6 MC38 cells were resuspended in 100 μl of phosphate-buffered saline solution (PBS) and were subcutaneously ( s.c. ) inoculated into the right flank of each C57BL/6J or immune-deficient mouse, and tumor size was measured every other day using a caliper. Tumor volume was calculated as length×(width 2 )/2. Survival was monitored each day. For survival curve analysis, mice with tumor size reaching 2,000 mm 3 were euthanized with carbon dioxide and were defined as humane endpoints. To analyze the tumor-infiltrating immune cells, tumors were harvested at day 14 (for B16F10) or day 18 (for MC38). In tumor models with supplementation of syngeneic exosomes, 20 μg of syngeneic exosomes were mixed with 2×10 5 B16F10 or 1×10 6 MC38 cells in 100 μl of PBS, and were subcutaneously ( s.c ) inoculated into the right flank of each C57BL/6J or immune-deficient mouse, and tumor size was measured every other day using a caliper. Otherwise, 100 μg of syngeneic exosomes were intravenously ( i.v. ) injected every 3 days for 3 times into the tumor-bearing mice 3 days after subcutaneous inoculation of B16F10 cells. For metastatic melanoma studies, 1× 10 6 of B16F10-Scr or Tmem176b -deficient cells were injected i.v. into the tail vein of each C57BL/6J mouse. Mice were euthanized at day 14 after tumor inoculation and surface metastatic nodules in the lung were counted under a dissecting microscope. To test the antitumor function of Tmem176b competitive peptide, chimeric Tmem176b or scramble peptides (cell-penetrating peptide fused with amino acids 218-232 of Tmem176b (RXRRBRRXRRBRXB-ASLGLSLRSMYGRSS) or scramble peptide (RXRRBRRXRRBRXB-MLSGSRYSGLSARLS), called CPP-Pep or CPP-Scr hereinafter) 71 (10 mg/kg) were injected i.v. into B16F10 or MC38 tumor-bearing mice after tumor volume reaching 200 mm 3 , every 3 days for 3 times. The same dosage was used to in B16F10 lung metastasis tumor models at day 3 after tumor inoculation. To test the therapeutic efficacy of Tmem176b-neutralizing antibody, anti-Tmem176b (Abclonal, Clone# 6E8), anti-PD1 (Leinco technologies, Clone# RMP1-14) or Rabbit isotype antibody (200 μg/mouse) were injected i.p. into B16F10 or MC38 tumor-bearing mice after tumors volume reaching 200 mm 3 , every 3 days for 3 times. For the therapeutic efficacy of combination of CPP-Pep with anti-PD1 therapy, CPP-Pep or CPP-Scr ( i.v injection, 10 mg/kg), or CPP-Pep ( i.v injection, 10 mg/kg) plus anti-PD1 antibody ( i.p. injection, 200 μg/mouse) were injected into tumor-bearing mice when the tumor volume reaching 200 mm 3 , every 3 days for 3 times . For the therapeutic efficacy of combination of anti-Tmem176b with anti-PD1 therapy, 6E8 or isotype antibody, or 6E8 plus anti-PD1 antibody (200 μg each antibody per mouse) were injected i.p. into B16F10 or MC38 tumor-bearing mice after tumor volume reaching 200 mm 3 , every 3 days for 3 times. To establish orthotopic hepatocellular carcinoma (HCC) mouse models, subcutaneous tumors were peeled from Hepa1-6 tumor-bearing mice. Tumor tissues were cut into about 1 mm 3 /piece, three tumor pieces were implanted in the liver of each recipient C57BL/6J mouse under anesthesia, and tumor size were monitored by the magnetic resonance images (MRI). Tumor-bearing mice were randomized into treatment groups based on MRI. The mice were treated 3 weeks after inoculation, with CPP-Pep or CPP-Scr (10 mg/kg) via intravenous ( i.v. ) injection, or with anti-Tmem176b (Abclonal, Clone# 6E8) or isotype antibody (200 μg/mouse) via intraperitoneal ( i.p. ) injection, every 3 days for 3 times. Tumor-bearing mice were euthanized at 6 weeks after inoculation and tumor size was measured using a caliper. A375 tumor model in humanized mice HuHSC-NCG mice were constructed by transplanting human hematopoietic stem cells (10 5 CD34 + Hu-HSC per mouse) into irradiated and myeloablated severe immunodeficient NCG (NOD/ShiLtJGpt- Prkdc em26Cd52 Il2rg em26Cd22 /Gpt)(CH) mice (4 week old). 18 weeks after hu-HSC reconstitution, a total of 10 6 A375 human melanoma cells were implanted into the right dorsal flanks of huHSC-NCG mice. When the tumor volumes were over 200 mm 3 , the A375-bearing-huHSC-NCG mice were treated with anti-human TMEM176B (Abclonal, Clone# 2F2), or anti-human PD-L1 (BioXCell, Clone# Atezolizumab), or isotype antibody, or anti-human TMEM176B plus anti-human PD-L1 (100 μg each antibody per mouse) via intraperitoneal ( i.p. ) injection, every 3 days for 5 times. Exosome isolation, characterization, and quantification Exosomes were isolated from conditioned medium using a protocol as previously described 72 . Briefly, cancer cells (B16F10, MC38, HeLa, SW480) or non-malignant NIH3T3 cells were cultured in DMEM medium containing 10% exosome-depleted FBS, 100 U/ml penicillin and 100 μg/ml streptomycin for 24-48 h to 80% confluence. Culture supernatants was collected and centrifugated at 500 g for 15 min to remove cell debris, and then centrifugated at 10,000 g for 30 min, followed by filtration with 0.22 μm filter. Exosome were pelleted by ultracentrifugation (Beckman Optima L-100 XP, Beckman Coulter) at 100,000 g for 70 min, washed with PBS using the same ultracentrifugation conditions, and resuspended in PBS. For human plasma exosome isolation, plasma from cancer patients or health volunteers were sequentially centrifuged at 3,000 g , and 10,000 g for 30 min twice to remove cell debris, followed by filtration with 0.22 μm filter, and exosomes were pelleted by ultracentrifugation (Beckman Optima L-100 XP, Beckman Coulter) at 100,000 g for 70 min, and washed with PBS using the same ultracentrifugation conditions, and resuspended in PBS. Exosomes were quantified as protein measurement using BCA protein assay kit (Thermo Scientific, A55864). Transmission electron microscopy (Hitachi, HT-7800), nanoparticle tracking analysis (Nanosight NS300, Malvern) and Nano-Flow cytometry (Flow NanoAnalyzer, NanoFCM, Fujian, China) were performed to characterize the isolated exosomes. For quantitative mass spectrometry, centrifugated exosomes were lysed in 1% sodium deoxycholate and quantified using BCA protein assay kit. Isolation of tissue leukocytes for flow cytometry For the isolation of leukocytes from spleen and draining lymph nodes, tissues were dissected from mice, and were minced with dissection scissors, and were mashed and filtered. Red blood cells were removed by ACK (Ammonium-Chloride-Potassium) lysis buffer. For the isolation of leukocytes from tumor tissues, tumors were dissected from mice, and were minced with dissection scissors, then were digested in RPMI 1640 containing 20 μg/ml of DNase I (Roche, 10104159001) and 200 μg/ml of Collagenase D (Roche, 11088882001) at 37 ℃ with 220 rpm shaking for 1 h. After digestion, the tissues were then ground, filtered, collected by centrifugation at 500 g for 5 min. Supernatant was aspirated and the mononuclear immune cells were isolated by centrifugation on a 40 to 72% Percoll gradient. Red blood cells were removed by ACK lysis buffer. Single cell suspensions were then washed, filtered and then collected by centrifugation. Cell enrichment and purification The purification (>95% purity) of naive polyclonal CD4 + or CD8 + T cells from B6 mice or naive CD8 + T cells from OT-Ⅰ mice were performed by negative selection using Beaverbeads TM Streptavidin (Cat#22307; Beaver). Briefly, single cell suspensions were incubated with different cocktails of biotin-conjugated antibodies (BioLegend) in Cell Staining Buffer (2 % FBS, 2 mM EDTA in PBS) at 4 ℃ for 15 min, and then washed with Cell Staining Buffer. After washing, cells were resuspended in Staning Buffer and incubated with Beaverbeads TM Streptavidin on rotator at 4 ℃ for 10 min. Then cells were separated by placing the labeled cells in tube on DynaMag™-2 Magnet (Cat# 12321D; Invitrogen) for 5 min. Flow cytometry and cell sorting For blocking of Fc receptors, single cell suspensions were incubated with purified anti-CD16/32 for 15 min on ice prior to immunostaining. For surface staining, cells stained with fluorochrome-conjugated antibodies and live/dead Fixable Viability Dye (eBioscience, 65-0866-18) in flow cytometry buffer (PBS containing 0.5% BSA) for 30 min at 4 ℃. For intracellular cytokine staining, cells were incubated in media containing 50 ng/ml of phorbol 12-Myristate 13-Acetate (PMA, Sigma-Aldrich, P1585-1MG) and 1 μg/ml of Ionomycin (YEASEN, 50401ES03), and 1 μg/ml of GolgiPlug (BD Biosciences, 555029) at 37 ℃ for 4 h. After restimulation, cells were spun down and blocked by anti-CD16/32, and stained with antibodies against cell surface markers and live/dead Fixable Viability Dye (eBioscience, 65-0866-18). After washing with 1×BD Perm/Wash buffer, cells were fixed and permeabilized with BD Cytofix/Cytoperm solution (BD Biosciences, 51-2090KZ) for 30 min, and then stained with antibodies against indicated cytokines in 1×BD Perm/Wash buffer. For carboxyfluorescein diacetate succinimidyl ester (CFSE) dilution assay, cells were labeled with 0.5 μM of CFSE (Invitrogen, C34554) in PBS at 37 ℃ for 15 min. Then, the cells were washed with PBS to remove the excess dye before culture. All flow cytometry data were acquired on LSRFortessa (BD), NovoCyte or Quanteon (ACEA) flow cytometry analyzer and were analyzed using FlowJo V10.10.0 software (BD Biosciences). For cell sorting, single-cell suspensions were stained with fluorochrome-conjugated antibodies in sorting buffer (1 mM EDTA, 25 mM HEPES, 1% FBS in PBS) and then sorted with BD FACSAria Ⅲ and FACSAria Fusion cell sorter. Nano-Flow Cytometry For detection of the proportions of Tmem176b + exosomes harvested from cancer cell culture supernatant or peripheral blood from cancer patients, 50 μg of purified exosomes were stained with 1 μg/ml of Alexa Fluor 647-labled antibodies against Tmem176b (Abclonal, clone# 6E8) and incubated at 4℃ in the dark for 1 h. Isotype control antibody was used to test for unspecific binding. Then exosomes were washed with 12 ml of 0.22 µm-filtered PBS and collected by ultracentrifugation (Beckman Optima L-100 XP, Beckman Coulter) at 100,000 g for 1 h to remove unbinding antibodies. Supernatant was aspirated and exosomes in pellet were resuspended in 50 µl of 0.22 µm-filtered PBS and subjected to Nano-flow cytometry on Flow NanoAnalyzer (NanoFCM, Fujian, China) 40,62 , and data analysis was performed using FlowJo V10.10.0 software. Murine T Cell Stimulation Assay Primary T cells were cultured in RPMI-1640 medium supplemented with 10% FBS, glutamine (1 mM), HEPES (10 mM), sodium pyruvate (1 mM), β-mercaptoethanol (50 μM), penicillin (100 U/ml) and streptomycin (100 μg/ml). To examine TCR signaling, purified naïve CD8 + T cells were rested on ice in FBS-depleted medium for 60 min, then incubated with biotin-conjugated anti-CD3 (Clone# 145-2C11) and anti-CD28 (Clone# 37.51) antibodies (3 μg each antibody/10 7 cells) plus 5 μg of exosomes on ice for 30 min. Then the cells were crosslinked by streptavidin (3 μg/10 7 cells, FXP024-010, 4A biotech) in shaking heat block at 400 rpm, at 37 ℃ for indicated time. After being stimulated, reactions were immediately stopped by ice-cold PBS and cells were collected by centrifugation at 500 g for 5 min. Finally, cells were lysed with 1×SDS loading buffer diluted by NP-40 lysis buffer (20 mM tris-HCl (pH 7.5), 150 mM NaCl, 1% NP-40, 5 mM EDTA (pH 8.0), 5 mM Na 4 P 2 O 7 , 1 mM Na 3 VO 4 , 5 mM NaF, and protease inhibitor cocktail). For in vitro T cell activation assays, purified naïve CD4 + or CD8 + T cells were activated by plate-bound anti-CD3 (1 μg/ml) and anti-CD28 (1 μg/ml) in the absence or presence of B16F10 or MC38-derived exosomes in T cell culture medium. After being stimulated for indicated time, the cells were collected and analyzed by flow cytometry. Human T Cell Stimulation Assay Human PBMCs were isolated from peripheral blood of healthy donor, and human primary naïve T cells were also purified (>95% purity) by negative selection using Beaverbeads TM Streptavidin. T cells were cultured in X-VIVO TM 15 medium (Lonza, 04-418Q) supplemented with 5% FBS and recombinant human IL-2 (100 U/ml). Naïve T cells were activated by plate-bound anti-CD3 (Clone# OKT3) (3 μg/ml) and α-CD28 (Clone# CD28.2) (3 μg/ml) antibodies in the absence or presence of exosomes derived from the indicated WT or TMEM176B -deficeint human cancer cells. After being stimulated for indicated time, the cells were collected and analyzed by flow cytometry. DC generation and antigen cross-presentation assays Bone marrow (BM) cells were harvest B6 mice by flushing out tibias and femurs with RPMI-1640 medium. Red blood cells were lysed by ACK buffer and BM cells were cultured in 24-well plates at 1×10 6 cells/ml in complete RPMI-1640 medium containing 10% FBS, 100 ng/ml Flt3L (Novoprotein, CA82), 1% NEAA (Gibco, 11140050), 1 mM sodium pyruvate (Gibco, cat. 11360070), 2 mM GlutaMAX (Gibco, 35050061), 100 U/ml Penicillin and 100 μg/ml Streptomycin (Gibco, 15140122) and 50 μM β-mercaptoethanol for 9-11 days without disturbance. The medium was refreshed on day 5. cDC1s were sorted as L/D - B220 - MHCⅡ + CD11c + CD24 + SIRP-α - from Flt3L-cultured BM cells and were pre-treated with 5 μg of exosomes derived from Scramble or Tmem176b -deficient B16F10 or MC38 cells for 6 h. Unbound exosomes were removed by washing with RPMI-1640 medium, and Flt3L-cDC1s were cocultured with 2.5×10 4 CFSE-labelled naïve OT-Ⅰ CD8 + T cells, in the presence of HKLM-OVA for 3 days. OT-Ⅰ CD8 + T cells were then analyzed by flow cytometry for CFSE dilution. Immunoprecipitation and Mass spectrometry B16F10 and EL4 cell lines were lentivirally transduced with plv-Tmem176b-3×Flag-IRES-eGFP to overexpress Tmem176b fusion protein with Flag-tag at C-terminus. 1×10 7 cells were collected and centrifuged at 300 g for 5 min. After aspiration of supernatant, the cells were lysed with 1 ml NP-40 lysis buffer for 30 min in the ice, followed by ultrasonication. The cell lysates were incubated with 10 μl Anti-Flag M2 beads (Sigma-Aldrich, A2220) overnight on a rotator at 4 ℃. After washing with lysis buffer 5-6 times, the protein complexes were competitively eluted with Flag peptides in shaking heat block at 1,200 rpm at 25 ℃ for 30 min. The immunoprecipitation samples were stored in -80℃ for following assays, such as western blot and mass spectrometry. To identify Tmem176b-interacting proteins, the immunoprecipitation samples were subjected to SDS-PAGE. After staining with Coomassie Brilliant Blue, excised gel segments were subjected to in-gel trypsin digestion and dried. Samples were analyzed on a nanoElute (Bruker) coupled to a timsTOF Pro (Bruker) equipped with a CaptiveSpray source. Peptides were dissolved in 10 μl formic acid (0.1%) and were loaded onto a homemade C18 column (35cm×75μm i.d., 1.9μm 100Å). Samples were then eluted with linear gradients of 3%–35% acetonitrile in 0.1% formic acid for 60 min at a flow rate of 300 μl/min. Mass spectrum data were acquired with a timsTOF Pro mass spectrometer (Bruker) operated in PASEF mode and were analyzed by Peaks Studio X software against uniprot database. For the proteomic profiling of exosomes, the exosomes and cells were lysed with 1% sodium deoxycholate in 0.1 M Tris-HCl (pH8.5), and 100 μg sample were subjected to acquire protein quantitative mass spectrum. Liquid chromatography was performed with an ultra-high-pressure nano flow chromatography system (Elute UHPLC, Bruker Daltonics). Peptides were digested in 5 μl 0.1% formic acid and were loaded onto a homemade made C18 column (35 cm × 75 μm, ID 1.9 μm 100Å). Samples were then eluted with linear gradients of 3-35% acetonitrile in 0.1% formic acid for 60 min at a flow rate of 0.3 μl/min. LC was coupled online to a hybrid TIMS quadrupole time-of-flight mass spectrometer (Bruker timsTOF Pro) by a CaptiveSpray nanoelectrospray ion source. For data-independent acquisition, we used a 25m/z precursor isolation width to cover 400−1200 mz. diaPASEF (.d) files were searched using DIA-NN (V.1.8.1) against the mouse UniProt Reference Proteome database. The following parameters of dia-nn software were set: 1, “FASTA digest for library-free search” and “Deep learning-based spectra and RTs prediction” were used: 2, Protease, “Trypsin/P”; Missed cleavage, “2”; N-termM excision, “checked”; c carbamido methylation, “checked”; M-oxidation, “checked”. 3, The maximum mass accuracy tolerances were set to 10 ppm for both MS1 and MS2 spectra. 4, Protein inference in DIA-NN was the protein name (from fasta). 5, Quantification mode was set to“Robust LC (high accuracy)”. 6, All other settings were left default. Western Blot Analysis Cells were lysed using NP-40 cell lysis buffer followed by addition of SDS loading buffer, or were directly lysed by 1×SDS loading buffer diluted with NP-40 cell lysis buffer. Cell lysates were denatured by being boiled for 10 min. samples were separated by SDS-polyacrylamide gel electrophoresis, followed by electrotransfer to polyvinylidene difluoride (PVDF) membranes (Merck Millipore). The membranes were blocked with TBS containing 5% nonfat milk in and 0.1% Tween20 (TBST). After washing with TBST, membranes were incubated with appropriate primary antibodies at 4 ℃ overnight, followed by horseradish peroxidase-conjugated second antibody (AS003 or AS014; ABclonal) and development with an enhanced chemiluminescence detection reagent (RPN2235; GE healthcare). Images were acquired with Amersham Imager 600 (GE Healthcare). ELISA assay For detection of TMEM176B on exosomes harvested from patients’ plasma or cell culture supernatant, 96-well ELISA plates were coated with 1 μg/ml of antibody against CD63 (Proteintech, 67605-1-Ig) (50 μl/well) overnight at 4 ℃. Next day, free binding sites were blocked with 200 μl blocking buffer (PBS containing 0.5% BSA) for 1 h at room temperature. Then 5 μg of exosomes were added to each well. After incubation for 10 h at 4 ℃, 0.5 μg/ml of rabbit monoclonal antibody against TMEM176B (6E8) diluted in PBS containing 0.5% BSA was added and incubated overnight at 4 ℃. After washing with PBS, 100 μl of horseradish peroxidase-conjugated secondary antibody against rabbit (ABclonal, AS014) diluted in PBS containing 0.5% BSA was added into each well and incubated for 1 h at room temperature. After each step, the wells were washed by PBS three times. Plates were developed with SignalUp Super Sensitive ELISA Kit (Beyotime, P0205) and read within 30 min at 570/600 nm at Tecan Infinite E pelx. Recombinant TMEM176B protein was used to make a standard curve, and the result of standard curve demonstrated that the established ELISA exhibited a reliable linear detection range from 0.0078 to 1 μg/ml. Immunofluorescence The adherent cells were seeded in advance on glass coverslips in 24-well plate, and suspension cells can be used immediately. Cells were fixed with 4% paraformaldehyde and permeabilized with 0.1% Triton X-100 for 30 min, and then blocked with PBS containing 0.1% Tween-20 and 5% BSA for 30 min at room temperature. Cells were then incubated with primary antibodies overnight at 4℃, followed by staining with fluorochrome-conjugated secondary antibodies for 1 h at room temperature. After washing with PBS, the stained slides were mounted with mounting medium containing DAPI (Beyotime, P0131). Confocal microscopy images were acquired with a Zeiss LSM 780 confocal microscope, and images were processed and analyzed using ZEN 2.0 software. Purified B cells were activated with 1 μM of CpG DNA in RPMI-1640 complete medium for 48 h, and then pulsed with LCMV GP33 peptide for 1 h at 37 ℃. 40 μg of exosomes carrying with Tmem176b-GFP fusion protein, were added into 3×10 6 naïve P14 CD8 + T and incubated for 24 h at 37 ℃. After washing with PBS, exosome-pretreated naïve CD8 + T cells were mixed with equal amount of GP33-pulsed B cells, and incubated for 10 min at 37 ℃ in tubes to allow conjugate formation. Hereafter, the pellet was carefully resuspended and were plated on a poly-L-lysine-coated coverslip by spin at 2,000 rpm for 2 min. Then cells were fixed and permeabilized with precooled methanol for 10 min, washed 3 times with PBS, and blocked in PBS containing 1% BSA for 1 h at room temperature. Cells were incubated with primary antibody against Shp1 (Abclonal, A19111, 1:200) overnight at 4 ℃, washed 4–5 times, followed by staining with Alexa Fluor™ 555-labelled Goat anti-Rabbit IgG (Invitrogen, A21429) for 1 h at room temperature. Cells were washed with PBS, and stained with Alexa Fluor ® 647-labelled antibody against CD8 (Clone# 53-6.7, Biolegend, 100724) at 4 ℃ for 2h. After three washings with PBS, cells were stained with DAPI in mounting medium (Beyotime, P0131) for 15 min at room temperature. Confocal microscopy images were acquired with a Zeiss LSM 780 confocal microscope, and images were processed and analyzed using ZEN 2.0 software. The Shp1 enrichment in the immune synapse was determined by using the equation: Shp1 enrichment (%)= Intensity synapse /Intensity T cell ×100. To examine the presence of tumor-infiltrating CD8 + T cells, tumors with suitable size were harvested and embedded in optimal cutting temperature compound (O.C.T., SAKURA, 4583). Sections of 15 μm were cut and mounted on coated slides, and the sections were fixed with BD Cytoperm/Cytofix (BD Bioscience, Cat#: 554722) solution (diluted with PBS at 1:2) for 30 min at room temperature, then washed twice for 10 min each with PBS. Nonspecific unions were blocked with PBS containing 1% normal mouse serum, 1% bovine serum albumin, and 0.3% Triton X-100 for 60 min at room temperature. Tissue sections were sequentially incubated with Alexa Fluor ® 647 anti-mouse CD8α (Clone# 53-6.7, Biolegend, Cat#100724) overnight at 4℃ and Hoechst 33342 (Thermo Fischer Scientific, Cat# H21492) for 10 min. After washing with PBS, the sections were mounted with Fluormount G (Southern Biotech, Cat#: 0100-01) and images were acquired on a Leica TCS SP8 confocal microscope. Images were analyzed with Imaris software (Bitplane). Immunohistochemistry To validate the expression discrepancy of TMEM176B in human cancer clinical specimens, a tissue microarray containing 82 paired human colon cancer tissues (Superbiotek, Cat No. COC1601) were sequentially stained with an anti-TMEM176B antibody (Abclonal, Clone# 2F2), biotin-conjugated goat-anti-rabbit IgG antibody and Streptavidin-POD (Solarbio, SP0041) for 30 min at room temperature. Tissue microarray were then incubated with diaminobenzidine (Solarbio, DA1010) for 10 min, and were counterstained with haematoxylin and mounted with Neutral balsam (Solarbio, G8590). The slides were examined with a microscope (Leica, DM4B), digitally imaged using Zeiss AxioScan7 and analyzed using ImageJ software. Single-cell RNA-seq analysis B16F10 melanoma tumors were harvested from tumor-bearing mice as denoted and single-cell suspensions were prepared as described above. Viable CD45 + tumor-infiltrating immune cells were sorted with BD Aria sorter, and then cells were counted and separated into droplet emulsions using the automated Chromium Controller (10×Genomics). Libraries were constructed using the Single Cell 3′ Library prepare protocol (10×Genomics). The transcriptome profiles of individual cells were sequenced through combinatorial Probe-Anchor Synthesis (cPAS) on an DNBseq platform (MGI, China), and 100 bp paired end reads was generated. Sample demultiplexing, barcode processing, alignment, filtering, unique molecular identifier counting and aggregation of sequencing runs were performed using the Cell Ranger analysis pipeline (v6.1.2). Raw unfiltered matrix was performed in R (v4.3.0) using the Seurat package (v4.3.0). Cell quality control was conducted based on the detected number of genes and the proportion of mitochondrial reads, following these specific steps: ⅰ) Filtering out cells with fewer than 200 identified genes or more than 90% of the maximum gene count. ⅱ) Sorting cells in descending order based on the proportion of mitochondrial reads and filtering out the top 6% (B16F10 tumors co-inoculated with exosomes or PBS) or 10% (Scramble or Tmem176b -deficient B16F10 tumors) of cells individually for each set of samples. Doublets were identified and removed using doublet detection R package DobuletFinder (v2.0.3), while cell cycle analysis was performed using the Seurat package's CellCycleScoring function. After scaling using the SCTransform function, the highly variable genes were identified using the Find Variable Features function. Subsequently, principal component analysis (PCA) was performed on the dataset using the top 2000 variable genes. To further reduce dimensionality and cluster the data, the UMAP (Uniform Manifold Approximation and Projection) method from the Seurat package was utilized to visualize the top 30 (B16F10 tumors co-inoculated with exosomes or PBS) or 40 (Scrambles or Tmem176b -deficient B16F10 tumor) principal components of each dataset. The UMAP analysis was performed with n.neighbors value of 50 and a learning rate of 100 for both sets of data. We employed the Harmony algorithm, which was directly obtained from the R package harmony (v1.2.0), for data integration and batch effect correction. This algorithm allowed us to effectively align and harmonize different batches of single-cell RNA sequencing data, mitigating batch-specific variation and enhancing the comparability and reliability of our analyses. The "Find Clusters" functionality was utilized to perform clustering analysis. Unsupervised clustering employing a shared nearest neighbor modularity optimization-based algorithm with a resolution parameter of 0.8 (B16F10 tumors co-inoculated with exosomes or PBS) or 0.5 (Scramble or Tmem176b -deficient B16F10 tumors) resulted in the identification of 19 or 14 distinct clusters, respectively. To classify immune cell populations, differential expression analysis using the Wilcoxon rank-sum test was conducted to assess differential gene expression between each cluster and all other cells. The top differentially expressed genes for each cluster were cross-referenced with canonical markers representing various immune cell populations, allowing the generation of identifiable transcriptional marker sets for each of the 16 (B16F10 tumors co-inoculated with exosomes or PBS) or 11 (Scramble or Tmem176b -deficient B16F10 tumors) clusters in the two datasets, respectively. Dimplots were generated summarizing the features of 16 or 11 immune cell clusters. All visualizations were created using the ggplot2 (v3.4.4) R package. Gene signatures scoring The gene signatures utilized in this study were derived from the gene signature database summarized in Table S3. For CD8 + T cells, gene signatures of ‘early activation’, ‘effector/cytokine’ and ‘Exhaustion’ were described in previous publications 47,73 . For B cells, gene signature of ‘Exhaustion’ was curated by previous studies 46,74 . To assess the activity of each gene set, we employed the R package AUCell (v1.22.0). Initially, for each cell, we computed gene expression rankings using the AUCell_buildRankings function with default parameters based on the expression matrix. For each gene set and cell, area-under-the-curve (AUC) values were calculated using the AUCell_calcAUC function, utilizing the gene expression rankings. The AUC values represent the proportion of genes within the top-ranking genes of each cell that are defined as part of the corresponding gene set. Furthermore, for visualization purposes, we utilized the plot_density function from the Nebulosa (v1.10.0) R package to generate faceted plots. In addition, we employed the "ssGSEA" method from the R package GSVA (v1.48.3) to calculate the scores/activities of the gene signatures. To examine the differences in gene feature score activities, we conducted Wilcoxon rank-sum tests. The results were visualized using violin plots to help data representation and visualization. Survival analysis The metadata of ESCA (esophageal carcinoma), GBM (glioblastoma multiforme), HNSC (head and neck squamous cell carcinoma), KIRC (kidney renal clear cell carcinoma), KIRP (kidney renal papillary cell carcinoma), STAD (stomach adenocarcinoma), SKCM (skin cutaneous melanoma) were obtained from the TCGA database at the National Cancer Institute (https://gdc.cancer.gov). Patients were stratified into two groups based on the median expression level of the TMEM176B gene signature. Kaplan-Meier survival analysis was performed to estimate overall survival, and a log-rank test was employed to compare the differences in survival between the two patient groups. Statistical analysis All statistical analyses were performed using GraphPad Prism (v.8.2.1) or R software (v4.3.0). Unpaired two-sided student t-test was used to calculate significance, unless stated otherwise. Tumor growth were assessed by two-way ANOVA. Survival comparison was performed using log-rank (Mantel-Cox) test. scRNA-seq analysis was used two-sided Wilcoxon rank-sum test. Significance was assumed to be reached at P < 0.05. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. ns, not significant. Declarations Data availability ScRNA-seq datasets that support the findings of this study have been deposited in the Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi) with accession number GSE254953 with a secure token ‘mzorcikevjwnbgt’. All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Acknowledgements We thank Xiufeng Sun, Lixin Hong, Xiaohong Ma, Qingfeng Liu, Lei Huang, Luming Yao, Changchuan Xie, Yaying Wu, Zheni Xu at the Core Facility of Biomedical Sciences, Xiamen University and Suqin Wu at the Xiamen University Laboratory Animal Center for technical assistance. We thank Dr. Zhongjun Dong at Tsinghua University for kindly providing Ptpn6 fl/fl mice. This study was supported by the National Natural Science Foundation of China (31570883, 31770955, 31970851 to N.X., 82303111 to A.Y., 32070877 to W.-H.L., 81971557 to K.M., 32394003 to H.H.), the Fundamental Research Funds for the Central Universities of China-Xiamen University (20720150065 to N.X.), Xiamen Municipal Bureau of Science and Technology (3502Z20204003 to F.Y.), the National Key R&D Program of China (2020YFA0803500 to K.M., 2023YFC2306400 to H.H.) and and Major Project of Guangzhou National Laboratory (GZNL2024A02004 to H.H). Author contributions X.G. and F.L. designed and executed the experiments, analyzed the data and prepared manuscript; A.Y., N.D., N.Y., C.N., F.Y. provided clinical samples and performed related experiments; Q.Z. analyzed high-throughput sequencing data under supervision of Q.L.; Y.J., F.X.L., Z.L., J.X., Q.Z., R.H., Y.Y.W., J.L., S.Z., Y.W., F.M., S.P.L. performed the experiments; S.Q.L. and X.C. helped in Immunofluorescence experiments; Y.C., Q.Y., Y.H., H.H., K.M. and W.-H.L. provided materials and study advices; F.Y. supervised and supported the project; N.X. conceived the study, designed the experiments, analyzed the data and wrote the manuscript with input from all authors. Competing interests N.X., X.G., F.L. and Y.H. are inventors on pending patent applications filed by Xiamen University that cover the use of TMEM176B competitive peptides and anti-TMEM176B antibodies in cancer immunotherapy and cancer diagnosis. The other authors declare no competing interests. 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N.X., X.G., F.L. and Y.H. are inventors on pending patent applications filed by Xiamen University that cover the use of TMEM176B competitive peptides and anti-TMEM176B antibodies in cancer immunotherapy and cancer diagnosis. The other authors declare no competing interests. Supplementary Files SupplementaryTablesV2.zip Supplementary Tables 1-6 GraphicalAbstract.docx Tmem176bimmuneevasionNatureCancersupplementalFigures20250311.pdf Extended Data Fig. 1. TMEM176B is specifically secreted via exosomes by cancer cells. a, b, Representative transmission electron microscopy (TEM) images (a), nanoparticle tracking analysis (NTA) (b), of exosomes purified from SW480 (top) or B16F10 (middle) or MC38 (bottom) cancer cells. c, Immunoblot analysis of whole cell lysate (WCL) and purified exosomes (EXO) from SW480 (top) or B16F10 (middle) or MC38 (bottom) cancer cells, probed with antibodies against exosome marker Alix, Tsg101 and CD63. All lanes were loaded with the same amount of total protein. d-f, Representative Nano-Flow Cytometry (NanoFCM) plot (d, g) and the percentages (e, g) of Tmem176b + or TMEM176B + exosomes among total exosomes released from NIH3T3, B16F10, MC38 cells (d, g; n=3), and from BEAS-2B, MCF-10A, SW480, A549, Hela cells (g, f; n=4), after staining with monoclonal anti-Tmem176b (6E8) antibody. h, The percentages of Tmem176b + EVs among total exosomes and ectosomes released from Tmem176b-OE B16F10 tumor cells after staining with monoclonal anti-Tmem176b (6E8) antibody. i, Representative flow cytometry of Scramble or Tmem176b -deficient B16F10 and MC38 cells after intracellular staining (left) or surface staining (right) with anti-Tmem176b antibody (6E8). j, The percentages of Tmem176b + or TMEM176B + exosomes among total exosomes released from Scramble or Tmem176b -deficient B16F10, MC38 cells (top), and from Scramble or TMEM176B -deficient SW480, A549(bottom), analyzed by NanoFCM (n=3). k, Representative flow cytometry of macrophages, cDC2 and MSC after intracellular staining (left) or surface staining (right) with anti-Tmem176b antibody (6E8). l, The percentages of Tmem176b + exosomes among total exosomes released from B16F10, macrophages, cDC2 and MSC, analyzed by NanoFCM (n=2). Data are representative of three independent experiments. Data are represented as mean ± s.d. Statistical analysis was performed using two-tailed unpaired Student’s t -test (e-g, h, j, l). Extended Data Fig. 2. Malignant cancer cells sort TMEM176B into exosomes and secrete into the circulation. a, Representative immunofluorescence images of localization of Tmem176b (Green) and indicated organelle markers (Red): Rab5, Rab7, Hrs and Lamp1, in B16F10 cells stably expressing Tmem176b-GFP. DAPI was used for nuclear staining (blue). b, Gene Ontology (GO) analysis of Tmem176b-interacting proteins in Tmem176b-Flag-expressing B16F10 cells, identified by IP-MS. c, Immunoblot analysis of lysates of B16F10 cells transduced with Tmem176b -Flag or empty vector, assessed by immunoprecipitation with anti-Flag antibody. d, The percentages of Tmem176b + exosomes among total exosomes released from Scramble, Hrs -deficient or Rab27a -deficient B16F10 (n=2). e, f, Representative NanoFCM plot (e) and the percentages (f) of Tmem176b + exosomes among total circulating exosomes in plasma of B6 mice inoculated s.c. with or without B16F10 or MC38 cells (n=5). g, h, Schematic (g) of ELISA to detect the amount (h) of TMEM176B protein on circulating exosomes in plasma samples from healthy donors (n=23) and patients with COAD (n=32), STAD (n=45), ESCA (n=35), LUAD (n=41), BRCA (n=34), LIHC (n=9), or THYM (n=5). Data are representative of two (h) or three (a, c-f) independent experiments. Data are represented as mean ± s.d. Statistical analysis was performed using two-tailed unpaired Student’s t -test (d, f, h). Extended Data Fig. 3. TDEs promote tumor progression via immunosuppressive TME. a, b, Tumor growth (a) and survival curves (b) of immunocompetent B6 mice injected s.c. with Scramble or Rab27a-deficient B16F10 melanoma cells (n=8). c-f Tumor growth (c, e) and survival curves (d, f) of B6 mice injected s.c. with B16F10 (c, d) or MC38 (e, f) cells plus the corresponding syngeneic exosomes or PBS (n=8). g, h, scRNA-seq analysis of intratumoral CD45 + cells from B6 mice injected s.c. with B16F10 cells plus syngeneic exosomes (n=6773) or PBS (n=6507). UMAP representation of all CD45 + cells with 16 unqiue immune populations (g) and the percentages of immune populations within CD45 + cells in tumors (h). i, UMAP representation of B cell subpopulations in tumor as in g. j, k, Violin plots (j) and UMAP (k) showing activity scores of exhaustion gene signatures in B cell subpopulations in tumor as in g. l, m, UMAP representation of macrophage subpopulations (l) and the percentages (m) of macrophage subpopulations within CD45 + cells in tumors as in g. Data are representative of three (a-f) independent experiments. Tumor growth data are presented as mean ± s.e.m. Statistical analysis was performed using two-way analysis of variance (ANOVA) (a, c, e) or log-rank (Mantel-Cox) test (b, d, f), or two-sided Wilcoxon rank-sum test (j). Extended Data Fig. 4. The pro-tumoral effect of TDEs is mainly dependent on CD8 + T cells. a, b, scRNA-seq analysis of intratumoral CD45 + cells from B6 mice injected s.c. with B16F10 cells plus syngeneic exosomes (n=6773) or PBS (n=6507). UMAP representation of CD8 + T cells (a) and the percentages (b) of subsets of CD8 + T cells within CD45 + cells. c, Violin plots showing activity scores of early activation, exhaustion and effector/cytokine signatures in intratumoral CD8 + T cells in tumor as in a. d-f, Tumor growth in BCD mice (PBS, n=7; EXO, n=6) (d), Rag1 -/- mice (PBS, n=7; EXO, n=10) (e), or CD8 -/- mice (n=8) (f) injected s.c. with B16F10 tumor cells plus syngeneic exosomes or PBS. g, h, Tumor growth in Rag1 -/- mice (n=5) (g) or CD8 -/- mice (n=8) (h) injected s.c. with MC38 cells plus syngeneic exosomes or PBS (PBS, n=7; EXO, n=8). Data are representative of three (d-h) independent experiments. Tumor growth data are presented as mean ± s.e.m. Statistical analysis was performed using two-sided Wilcoxon rank-sum test (c) or two-way ANOVA (d-h). Extended Data Fig. 5. TDEs suppress antitumor T cell immunity. a-d, Representative flow cytometry (a, c), frequencies and numbers (b, d) of intratumoral CD4 + and CD8 + T cells, effector (CD44 + CD62L - ) CD4 + or CD8 + T cells, and exhausted (PD1 + Tim3 + ) CD8 + T cells from B6 mice injected s.c. with B16F10 (a, b; PBS, n=7; EXO, n=8) or MC38 (c, d; PBS, n=10; EXO, n=9) cells plus the corresponding syngeneic exosomes or PBS. e, f, Representative flow cytometry (e), frequencies and numbers (f) of intratumoral IFN-γ + , IFN-γ + TNF-α + , or Granzyme B + CD8 + T cells and IFN-γ + or TNF-α + CD4 + T cells from B6 mice as in a (n=6). g, h, Representative flow cytometry (g), frequencies and numbers (h) of intratumoral TNF-α + or IFN-γ + TNF-α + CD4 + , and IFN-γ + or IFN-γ + TNF-α + CD8 + T cells from B6 mice as in c (n=8). i, j, Representative flow cytometry (i) and frequencies (j) of CD4 + and CD8 + T cells in tumor draining lymph nodes (TdLN) from mice as in c (PBS, n=9; EXO, n=10). Data are representative of three independent experiments. Data are presented as mean ± s.d. Statistical analysis was performed using two-tailed unpaired Student’s t -test (b, d, f, h, j). Extended Data Fig. 6. TDEs inhibit early activation and proliferation of T cells through Tmem176b. a-c, Proliferation of naive CD8 + T cells treated with B16F10-derived exosomes before (top row) or after (bottom row) stimulation with anti-CD3 and anti-CD28 antibodies. Schematic of in vitro T cell activation (a), representative flow cytometry plot of CFSE dilution (b; n=4), the percentages of CFSE low CD8 + T cells (c, left; n=4) and the absolute numbers of total CD8 + T cells (c, right; n=3). d, The percentages of CD25 + , CD69 + , CD71 + or CD44 + CD62L - cells among CD8 + T cells stimulated with anti-CD3 and anti-CD28 antibodies plus B16F10-derived exosomes or PBS for indicated time (n=3). e, f, Representative flow cytometry (e) and the percentages (f) of CFSE low cells among CD4 + T cells treated with B16F10-derived exosomes before (top row) or after (bottom row) anti-CD3 and anti-CD28 stimulation (n=4). g, The percentages of CD25 + , CD69 + , CD71 + , or ICOS + cells among CD4 + T cells stimulated with anti-CD3 and anti-CD28 antibodies plus B16F10-derived exosomes or PBS for indicated time (n=3). h, The frequencies of CD25 + , CD69 + , CD71 + , or PD1 + among CD8 + T cells stimulated with anti-CD3 and anti-CD28 antibodies plus PBS, NIH3T3- or B16F10-derived exosomes, or exosomes from B16F10 cells transduced with indicated sgRNA (n=4). Data are representative of two (h) or three (b-g) independent experiments. Data are presented as mean ± s.d. Statistical analysis was performed using two-tailed unpaired Student’s t -test (c, d, f, g). Extended Data Fig. 7. Ablation of Tmem176b in cancer cells does not significantly affect cancer cell proliferation, the secretion and immune cargoes of exosomes. a, Proliferation rate of Scramble or Tmem176b -deficient B16F10 (left) and MC38 (right) cells cultured for indicated time. b, Quantification of exosomes secreted by Scramble or Tmem176b -deficient MC38 cells. c, d, Representative TEM images (c) and NTA (d) of purified exosomes from Scramble or Tmem176b -deficient B16F10 (Top row) or MC38 (Bottom row) cells. e, Immunoblot analysis of WCL and purified exosomes (EXO) from Scramble or Tmem176b -deficient B16F10 or MC38 cells, probed with antibodies against exosome markers Alix, Tsg101, CD63, CD9 or CD81. All lanes were loaded with the same amount of total protein. f, GO analysis of the differentially expressed proteins in exosomes from Tmem176b -deficient B16F10 cells relative to those from Scramble B16F10 cells. g, Growth of B16F10 tumors in WT and Tmem176a/b fl/fl CD11c-Cre (c) (WT, n=6; Tmem176a/b fl/fl CD11c-Cre, n=10). Data are representative of two (b, d) or three (a, c, e, g) independent experiments. Data are presented as mean ± s.d. Statistical analysis was performed using two-tailed unpaired Student’s t -test (b) and two-way ANOVA (g). Extended Data Fig. 8. The impact of tumor-derived exosomal Tmem176b on immune cells in the TME. a, b, Representative flow cytometry (a) and frequencies (b) of GFP + cells among indicated immune cell populations in tumors from B6 mice injected s.c. with MC38 cells stably expressing Tmem176b-GFP or Tmem176b alone (n=4). c, d, Representative flow cytometry (c) and frequencies (d) of GFP + cells among indicated immune cell populations in tumors from B6 mice injected s.c. with Tmem176b-GFP -expressing Scramble or Rab27a -deficient B16F10 cells (n=3). e, Flt3L-cDC1 were pre-treated with indicated exosomes and then cultured for 3 days with CFSE-labeled OT-Ⅰ T cells and HKLM-OVA, and assayed for OT-Ⅰ proliferation and activation (CFSE low CD44 + ) (n=5). f, g, UMAP representation (f) and the percentages (g) of the Neutrophil subpopulations within CD45 + cells in tumors from B6 mice injected s.c. with Scramble or Tmem176b -deficient B16F10 cells. Data are representative of two (a-d) or three (e) independent experiments. Data are presented as mean ± s.d. Statistical analysis was performed using two-tailed unpaired Student’s t -test (b, d, e). Extended Data Fig. 9. Tmem176b Ablation in tumors ameliorates antitumor T cell immunity. a, b, Representative flow cytometry (a), frequencies and numbers (b) of intratumoral CD4 + and CD8 + T cells (top row), effector (CD44 + CD62L - ) CD4 + or CD8 + T cells (bottom row) of B6 mice injected s.c. with Scramble or Tmem176b -deficient MC38 cells (n=6). c, d, Representative flow cytometry (c) frequencies and numbers (d) of intratumoral IFN-γ + or TNF-α + CD8 + , and IFN-γ + or TNF-α + CD4 + T cells in tumors from mice as in a (MC38-Scr, n=8; MC38-T8KO, n=6). e, f, Representative flow cytometry (e) and frequencies (f) of CD4 + and CD8 + T cells in TdLN from mice as in a (n=6). g, Representative flow cytometry of intratumoral CD4 + and CD8 + T cells, effector (CD44 + CD62L - ) CD4 + or CD8 + T cells of B6 mice inoculated s.c. with Scramble (B16-Scr) or Tmem176b -deficient B16F10 cells (B16-T8KO), or Tmem176b -deficient B16F10 cells transduced with Tmem176b (B16-T8KO (T-OE)) (B16-Scr, n = 6; B16-T8KO, n=7; B16-T8KO (T-OE), n=7). h, Representative flow cytometry of intratumoral IFN-γ + or IFN-γ + TNF-α + CD8 + T cells in tumors from mice as in g (B16-Scr, n = 5; B16-T8KO, n=7; B16-T8KO (T-OE), n=7). i, j, Representative flow cytometry (i) and frequencies (j) of intratumoral CD4 + and CD8 + T cells, and effector (CD44 + CD62L - ) CD4 + or CD8 + T cells of B6 mice inoculated s.c. with Scramble (MC38-Scr) or Tmem176b -deficient (MC38-T8KO) cells, or Tmem176b -deficient MC38 cells transduced with Tmem176b (MC38-T8KO (T-OE)) (n=6). k, l, Representative flow cytometry (k) and frequencies (l) of IFN-γ + or IFN-γ + TNF-α + CD8 + T cells in tumors from mice as in i (MC38-Scr, n = 6; MC38-T8KO, n=5; MC38-T8KO(T-OE), n=5). m, n, Representative flow cytometry (m) and frequencies (n) of CD4 + and CD8 + T cells in TdLN from mice as in i (MC38-Scr, n = 7; MC38-T8KO, n=6; MC38-T8KO(T-OE), n=7). Data are representative of three independent experiments. Data are represented as mean ± s.d. Statistical analysis was performed using two-tailed unpaired Student’s t -test (b, d, f, j, l, n). Extended Data Fig. 10. Tumor-derived exosomal Tmem176b represses antitumor T cell immunity. a, Representative flow cytometry of intratumoral CD4 + and CD8 + T cells, effector (CD44 + CD62L - ) CD4 + or CD8 + T cells, and exhausted (PD1 + Tim3 + ) CD8 + T cells in B6 mice inoculated s.c. with Tmem176b -deficient B16F10 cells plus PBS or syngeneic exosomes from indicated genotypes of B16F10 cells (PBS, n = 6; EXO WT , n=7; EXO T8KO , n=6). b, Representative flow cytometry of intratumoral IFN-γ + or IFN-γ + TNF-α + CD8 + T cells in tumors from mice as in a (PBS, n = 7; EXO WT , n=7; EXO T8KO , n=6). c-d, Representative flow cytometry (c) and frequencies (d) intratumoral CD4 + and CD8 + T cells, effector (CD44 + CD62L - ) CD4 + or CD8 + T cells, and exhausted (PD1 + Tim3 + ) CD8 + T cells in B6 mice inoculated s.c. with Tmem176b -deficient MC38 cells plus PBS or syngeneic exosomes from indicated genotypes (PBS, n = 7; EXO WT , n=7; EXO T8KO , n=7). e, f, Representative flow cytometry (e) and frequencies (f) of intratumoral TNF-α + or IFN-γ + TNF-α + CD4 + T cells, and IFNγ + or IFN-γ + TNF-α + CD8 + T cells in tumors from mice as in c (PBS, n = 7; EXO WT , n=6; EXO T8KO , n=6). g, h, Representative flow cytometry (g) and frequencies (h) of CD4 + and CD8 + T cells in TdLN from mice as in c (PBS, n = 7; EXO WT , n=6; EXO T8KO , n=6). Data are representative of three independent experiments. Data are represented as mean ± s.d. Statistical analysis was performed using two-tailed unpaired Student’s t -test (d, f, h). Extended Data Fig. 11. The therapeutic effects of Tmem176b blockade in various tumor models. a, Immunoblot analysis of lysates of Tmem176b-Flag-expressing EL4 cells treated with PBS or indicated chimeric peptides, assessed by immunoprecipitation with anti-Flag antibody. b, Representative immunofluorescence images of localizations of BFP-Shp1 fusion protein and FITC-labelled CPP-Pep in EL4 cells. c, The percentages of CD25 + , CD69 + or PD1 + cells among CD8 + T cells stimulated with anti-CD3 and anti-CD28 antibodies in the presence of PBS or B16F10-derived exosomes, or B16F10-derived exosomes plus indicated peptides or antibodies (n=5). d, e, Representative image (d) and quantification of the numbers (e) of lung surface metastases from B6 mice injected i.v . with B16F10 cells, followed by treatments with indicated peptides (PBS, n=8; CPP-Scr, n=6; CPP-Pep, n=9). f, The percentages of CD25 + , CD69 + or CD71 + cells among human PBMC CD8 + T cells stimulated with anti-CD3 and anti-CD28 stimulation plus PBS, or exosomes from SW480 (top row) or HeLa (bottom row) cells together with or without anti-TMEM176B (2F2) antibody (n=4). g, Growth of Tmem176b -deficient B16F10 tumors in B6 mice treated with anti-Tmem176b antibody (6E8) or isotype antibody (n=5). Red arrows indicate the time points of treatment. h, i, Representative image (h) and tumor volumes (i) of livers from B6 mice orthotopically implanted with Hepa1-6 cells, followed by treatment with PBS, CPP-Scr, CPP-Pep or 6E8 (n=5). Data are representative of two (d, e, h-i) or three (a-c, f-g) independent experiments. Tumor growth data are presented as mean ± s.e.m. and all other data are presented as mean ± s.d. Statistical analysis was performed using two-tailed unpaired Student’s t -test (c, e, f, i), or two-way ANOVA (g). Extended Data Fig. 12. Proposed model for the role of Tmem176b in tumor-driven immune evasion and its applications in cancer diagnosis and immunotherapy. Tmem176b is secreted via exosomes by cancer cells but not by non-malignant cells. TMEM176B (or Tmem176b)-positive circulating exosomes are specifically present in peripheral blood of tumor-bearing mice and various types of cancer patients, distinguishing healthy subjects from cancer patients with early- and late-stage cancer. High levels of TMEM176B-positive circulating exosomes with worse prognosis and unfavorable outcomes of anti-PD1 therapy, suggesting that they can serves as a potential non-invasive diagnostic and prognostic tool for cancer diagnosis and prognosis. Tmem176b on TDEs inhibits T cell early activation, and its ablation in mouse cancer cells substantially reduces tumor growth in a CD8 + T cell-dependent manner. Mechanistically, tumor-derived exosomal Tmem176b is delivered to CD8 + T cells and attenuates proximal TCR signaling by recruiting protein tyrosine phosphatase Shp1. Blocking Tmem176b, either using neutralizing antibody or using competitive peptide to disrupt interaction between Tmem176b and Shp1, remarkably restrains tumor growth in models of mouse and human cancers, and synergizes with anti-PD1/PD-L1 therapy. Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6199894","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":430229773,"identity":"72fa348d-d3bc-41f0-876b-1e79b01a20ef","order_by":0,"name":"Nengming 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University","correspondingAuthor":false,"prefix":"","firstName":"Nan","middleName":"","lastName":"Ding","suffix":""},{"id":430229797,"identity":"51cef5c0-0648-4f78-be35-da7d0319e9a6","order_by":19,"name":"Nan Ye","email":"","orcid":"","institution":"The First Affiliated Hospital of Xiamen University","correspondingAuthor":false,"prefix":"","firstName":"Nan","middleName":"","lastName":"Ye","suffix":""},{"id":430229798,"identity":"32ecfd88-8300-4d91-b7f8-822993a7a962","order_by":20,"name":"Xin Chen","email":"","orcid":"https://orcid.org/0000-0002-2477-6087","institution":"Xiamen University","correspondingAuthor":false,"prefix":"","firstName":"Xin","middleName":"","lastName":"Chen","suffix":""},{"id":430229799,"identity":"57dccbd6-56d3-4ce9-963f-4a008bfaea3b","order_by":21,"name":"Yixin Chen","email":"","orcid":"https://orcid.org/0000-0002-9591-634X","institution":"School of Life Sciences, Xiamen University","correspondingAuthor":false,"prefix":"","firstName":"Yixin","middleName":"","lastName":"Chen","suffix":""},{"id":430229800,"identity":"45a6d086-0bca-44a4-a342-97ee0bed5ed2","order_by":22,"name":"Qingkai Yang","email":"","orcid":"https://orcid.org/0000-0001-6628-5393","institution":"Dalian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Qingkai","middleName":"","lastName":"Yang","suffix":""},{"id":430229801,"identity":"5ad8b549-0bd2-40d4-8f37-d8ef4fe17715","order_by":23,"name":"Qiyuan Li","email":"","orcid":"https://orcid.org/0000-0002-8934-8948","institution":"National Institute for Data Science in Health and Medicine, School of Medicine, Xiamen University, Xiamen 361102, China","correspondingAuthor":false,"prefix":"","firstName":"Qiyuan","middleName":"","lastName":"Li","suffix":""},{"id":430229802,"identity":"2a14f821-2d7b-49a6-bc07-f3c170fa0e7e","order_by":24,"name":"Yazhen Hong","email":"","orcid":"","institution":"Xiamen University","correspondingAuthor":false,"prefix":"","firstName":"Yazhen","middleName":"","lastName":"Hong","suffix":""},{"id":430229803,"identity":"9f07bb2c-7d9a-4930-b369-b82b2630d950","order_by":25,"name":"Hongling Huang","email":"","orcid":"","institution":"Xiamen University","correspondingAuthor":false,"prefix":"","firstName":"Hongling","middleName":"","lastName":"Huang","suffix":""},{"id":430229804,"identity":"d96e3347-4af1-43fe-87b3-02f55b78d070","order_by":26,"name":"Kairui Mao","email":"","orcid":"","institution":"Xiamen University","correspondingAuthor":false,"prefix":"","firstName":"Kairui","middleName":"","lastName":"Mao","suffix":""},{"id":430229805,"identity":"30cd4376-e23d-4496-90b1-074463549adf","order_by":27,"name":"Wen-Hsien Liu","email":"","orcid":"https://orcid.org/0000-0003-2500-3892","institution":"School of Life Sciences, Xiamen University","correspondingAuthor":false,"prefix":"","firstName":"Wen-Hsien","middleName":"","lastName":"Liu","suffix":""},{"id":430229806,"identity":"9202435a-f317-4bc6-897b-ac4f91eb3e04","order_by":28,"name":"Chao Ni","email":"","orcid":"","institution":"Second Affiliated Hospital, Zhejiang University","correspondingAuthor":false,"prefix":"","firstName":"Chao","middleName":"","lastName":"Ni","suffix":""},{"id":430229807,"identity":"e348c49d-2623-4687-a2ea-e36ec14db690","order_by":29,"name":"Feng Ye","email":"","orcid":"https://orcid.org/0000-0002-9159-7767","institution":"the First Affiliated Hospital of Xiamen University","correspondingAuthor":false,"prefix":"","firstName":"Feng","middleName":"","lastName":"Ye","suffix":""}],"badges":[],"createdAt":"2025-03-11 03:40:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6199894/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6199894/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86135802,"identity":"f1ec9a0b-bbec-47bb-acb4-e3190f138fda","added_by":"auto","created_at":"2025-07-07 07:45:42","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2344665,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIdentification of TMEM176B\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e+\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e circulating exosomes as a non-invasive biomarker for cancer patients.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e, Schematic diagram of mass spectrometry or nano-flow cytometry (NanoFCM) analysis of exosomes from cancer cell culture media and from the sera of healthy donors and cancer patients. \u003cstrong\u003eb\u003c/strong\u003e, Venn diagram of proteins of exosomes from SW480 (red), A549 (blue), Hela (green), MCF-10A (brown) and BEAS-2B (yellow) cells. 294 proteins were exclusively detected in human cancer-cell-derived exosomes (n=2 protein samples). \u003cstrong\u003ec\u003c/strong\u003e, Venn diagram of proteins of exosomes from B16F10, MC38 cells (n=3 protein samples) and 294 common proteins from human cancer-cell-derived exosomes as in \u003cstrong\u003eb\u003c/strong\u003e. \u003cstrong\u003ed, e,\u003c/strong\u003e Representative NanoFCM plot (\u003cstrong\u003ed\u003c/strong\u003e) and the percentages (\u003cstrong\u003ee\u003c/strong\u003e) of TMEM176B\u003csup\u003e+\u003c/sup\u003e exosomes among total circulating exosomes in sera from healthy donors (n=32) and multiple types of cancer patients (COAD, n=121; STAD, n=110; ESCA, n=73; LUAD, n=108; BRCA, n=39). \u003cstrong\u003ef\u003c/strong\u003e, The percentages of TMEM176B\u003csup\u003e+\u003c/sup\u003e exosomes among total circulating exosomes in sera from patients with different stage of cancer. COAD (stage Ⅰ: n=19, Ⅱ: n=35, Ⅲ: n=32, Ⅳ: n=23), STAD (stage Ⅰ: n=29, Ⅱ: n=15, Ⅲ: n=21, Ⅳ: n=22), ESCA (stage Ⅰ: n=9, Ⅱ: n=10, Ⅲ: n=22, Ⅳ: n=21), LUAD (stage Ⅰ: n=21, Ⅱ: n=13, Ⅲ: n=27, Ⅳ: n=20) and BRCA (stage Ⅰ: n=2, Ⅱ: n=10, Ⅲ: n=13, Ⅳ: n=11) ) or healthy donors (n=32). \u003cstrong\u003eg\u003c/strong\u003e, The percentages of TMEM176B\u003csup\u003e+\u003c/sup\u003e exosomes in sera from patients with STAD (n=18), LUAD (n=12), COAD (n=10) or ESCA (n=15) before and 7 days after resection (pre-resection and post-resection). \u003cstrong\u003eh\u003c/strong\u003e, Kaplan–Meier curves (log-rank test) displaying overall survival of patients with high (≥median) (green) or low (＜median) (blue) percentages of TMEM176B\u003csup\u003e+\u003c/sup\u003e circulating exosomes. LUAD (n=47), STAD (n=43), ESCA (n=34) or COAD (n=36). \u003cstrong\u003ei\u003c/strong\u003e, the percentages of TMEM176B\u003csup\u003e+\u003c/sup\u003e exosomes among total circulating exosomes in sera from cancer patients with complete response to PD-1 antibody treatment (CR, n=9) and with partial response to PD-1 antibody treatment (PR, n=15). Data are representative of two (\u003cstrong\u003ed-i\u003c/strong\u003e) independent experiments. Data are presented as mean ± s.d. Statistical analysis was performed using two-tailed unpaired Student’s\u003cem\u003e t\u003c/em\u003e-test (\u003cstrong\u003ee, f, i\u003c/strong\u003e), two-tailed paired Student’s t test (\u003cstrong\u003eg\u003c/strong\u003e), or log-rank (Mantel-Cox) test (\u003cstrong\u003eh\u003c/strong\u003e).\u003c/p\u003e","description":"","filename":"Tmem176bimmuneevasionNatureCancermainFigures202503111.png","url":"https://assets-eu.researchsquare.com/files/rs-6199894/v1/5e6df0c3b51da3e334cdd5cb.png"},{"id":86135803,"identity":"1a6d7073-d826-438c-ac5e-b10965179e58","added_by":"auto","created_at":"2025-07-07 07:45:42","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2976321,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTmem176b depletion attenuates tumor growth in a TDE-dependent manner.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea-d, \u003c/strong\u003eTumor growth (\u003cstrong\u003ea, c\u003c/strong\u003e) and survival curves (\u003cstrong\u003eb, d\u003c/strong\u003e) of C57BL/6J (B6) mice injected subcutaneously (s.c.) with Scramble, or \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 (\u003cstrong\u003ea, b\u003c/strong\u003e) (indicated as B16-Scr, B16-T2KO or B16-T3KO or B16-T8KO; n = 5) or MC38 cells (\u003cstrong\u003ec, d\u003c/strong\u003e) (indicated as MC38-Scr, n = 7; MC38-T3KO, n=6; MC38-T8KO, n=6). \u003cstrong\u003ee, f,\u003c/strong\u003e Representative photograph (\u003cstrong\u003ee\u003c/strong\u003e) and quantification of the total numbers (\u003cstrong\u003ef\u003c/strong\u003e) of lung surface metastases from B6 mice injected intravenously (\u003cem\u003ei.v.\u003c/em\u003e) with Scramble or \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 cells (n=5). \u003cstrong\u003eg-j,\u003c/strong\u003e Tumor growth (\u003cstrong\u003eg, i\u003c/strong\u003e) and survival curves (\u003cstrong\u003eh, j\u003c/strong\u003e) of B6 mice injected s.c. with Scramble, or \u003cem\u003eTmem176b\u003c/em\u003e-deficient, or \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 (\u003cstrong\u003eg, h\u003c/strong\u003e) or MC38 (\u003cstrong\u003ei, j\u003c/strong\u003e) cells transduced with \u003cem\u003eTmem176b\u003c/em\u003e (indicated as T-OE) (B16-Scr, n =6; B16-T8KO, n=5; B16-T8KO(T-OE), n=6; MC38-Scr, n =8; MC38-T8KO, n=8; MC38-T8KO(T-OE), n=9). \u003cstrong\u003ek, l, \u003c/strong\u003eGrowth of B16F10 tumors in WT and \u003cem\u003eTmem176b \u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e\u003csup\u003e \u003c/sup\u003eCD11c-Cre mice (K) (WT, n=9; \u003cem\u003eTmem176b \u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e\u003csup\u003e \u003c/sup\u003eCD11c-Cre, n=10) or \u003cem\u003eTmem176b\u003c/em\u003e\u003csup\u003e-/-\u003c/sup\u003e mice (\u003cstrong\u003el\u003c/strong\u003e) (WT, n=6; \u003cem\u003eTmem176b\u003c/em\u003e\u003csup\u003e-/-\u003c/sup\u003e, n=6). \u003cstrong\u003em, n,\u003c/strong\u003e Tumor growth in B6 mice inoculated s.c. with \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 cells plus PBS or syngeneic exosomes from indicated genotypes of B16F10 cells via co-inoculation (\u003cstrong\u003em\u003c/strong\u003e) (PBS, n=8; EXO\u003csup\u003eWT\u003c/sup\u003e, n=7; EXO\u003csup\u003eT8KO\u003c/sup\u003e, n=8; EXO\u003csup\u003eT-OE\u003c/sup\u003e, n=8) or intravenous (\u003cem\u003ei.v.\u003c/em\u003e) injection (\u003cstrong\u003en\u003c/strong\u003e) (PBS, n=9; EXO\u003csup\u003eWT\u003c/sup\u003e, n=10; EXO\u003csup\u003eT8KO\u003c/sup\u003e, n=10). \u003cstrong\u003eo\u003c/strong\u003e, Tumor growth in B6 mice inoculated s.c. with \u003cem\u003eTmem176b\u003c/em\u003e-deficient MC38 cells together with PBS or syngeneic exosomes from indicated genotypes of MC38 cells (PBS, n=7; EXO\u003csup\u003eWT\u003c/sup\u003e, n=7; EXO\u003csup\u003eT8KO\u003c/sup\u003e, n=8). \u003cstrong\u003ep, q, \u003c/strong\u003eSchematic of B6 mice co-injected with WT MC38 cells in the right flank and with PBS, Scramble, \u003cem\u003eTmem176b\u003c/em\u003e-deficient or \u003cem\u003eRab27a\u003c/em\u003e-deficient MC38 cells in the left flank (\u003cstrong\u003ep\u003c/strong\u003e). Growth of WT MC38 tumors in the right flank of B6 mice was shown in \u003cstrong\u003ep\u003c/strong\u003e (\u003cstrong\u003eq\u003c/strong\u003e; n=5). Data are representative of two (\u003cstrong\u003ee, f,\u003c/strong\u003e p-\u003cstrong\u003eq\u003c/strong\u003e) or three (\u003cstrong\u003ea-d, g-o\u003c/strong\u003e) independent experiments. Tumor growth data are presented as mean ± s.e.m. Statistical analysis was performed using two-tailed unpaired Student’s \u003cem\u003et\u003c/em\u003e-test (\u003cstrong\u003ef\u003c/strong\u003e), or two-way analysis of variance (ANOVA) (\u003cstrong\u003ea, c, g, i, k-o\u003c/strong\u003e, \u003cstrong\u003eq\u003c/strong\u003e), or log-rank (Mantel-Cox) test (\u003cstrong\u003eb, d, h,\u003c/strong\u003e \u003cstrong\u003ej\u003c/strong\u003e).\u003c/p\u003e","description":"","filename":"Tmem176bimmuneevasionNatureCancermainFigures202503112.png","url":"https://assets-eu.researchsquare.com/files/rs-6199894/v1/6850bfdb2415ba17d6cc55a3.png"},{"id":86135810,"identity":"dcf1ce8a-4a6c-4f9e-9854-39469fd51dc7","added_by":"auto","created_at":"2025-07-07 07:45:42","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":5978660,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTmem176b ablation in tumors remodels immunosuppressive TME.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea, b,\u003c/strong\u003e Growth of Scramble or \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 tumors\u003cem\u003e \u003c/em\u003ein B6 or TCD mice (\u003cstrong\u003ea\u003c/strong\u003e; n=9), or \u003cem\u003eCD8\u003c/em\u003e\u003csup\u003e-/-\u003c/sup\u003e mice (\u003cstrong\u003eb\u003c/strong\u003e; n = 10). \u003cstrong\u003ec, d,\u003c/strong\u003e Growth of Scramble or \u003cem\u003eTmem176b\u003c/em\u003e-deficient MC38 tumors in\u003cem\u003e Rag1\u003c/em\u003e\u003csup\u003e\u003cem\u003e-/-\u003c/em\u003e\u003c/sup\u003e mice (\u003cstrong\u003ec\u003c/strong\u003e; n=6) or \u003cem\u003eCD8\u003c/em\u003e\u003csup\u003e\u003cem\u003e-/-\u003c/em\u003e\u003c/sup\u003e mice (\u003cstrong\u003ed\u003c/strong\u003e; n=8). \u003cstrong\u003ec, d,\u003c/strong\u003e Growth of Scramble or \u003cem\u003eTmem176b\u003c/em\u003e-deficient MC38 tumors in\u003cem\u003e Rag1\u003c/em\u003e\u003csup\u003e\u003cem\u003e-/-\u003c/em\u003e\u003c/sup\u003e mice (\u003cstrong\u003ec\u003c/strong\u003e; n=6) or \u003cem\u003eCD8\u003c/em\u003e\u003csup\u003e\u003cem\u003e-/-\u003c/em\u003e\u003c/sup\u003e mice (\u003cstrong\u003ed\u003c/strong\u003e; n=8). \u003cstrong\u003ee-i, \u003c/strong\u003escRNA-seq analysis of intratumoral CD45\u003csup\u003e+\u003c/sup\u003e cells from B6 mice injected s.c. with Scramble or \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 cells. Uniform manifold approximation and projection (UMAP) representation of all CD45\u003csup\u003e+\u003c/sup\u003e cells showing 12 unqiue immune populations (\u003cstrong\u003ee\u003c/strong\u003e) and showing CD45\u003csup\u003e+ \u003c/sup\u003eCD8\u003csup\u003e+\u003c/sup\u003e T cells (\u003cstrong\u003ef\u003c/strong\u003e). The percentages of indicated immune populations within CD45\u003csup\u003e+\u003c/sup\u003e cells (\u003cstrong\u003eg\u003c/strong\u003e) from Scramble (\u003cem\u003en\u003c/em\u003e = 8263 cells) or \u003cem\u003eTmem176b\u003c/em\u003e-deficient (\u003cem\u003en\u003c/em\u003e = 8651 cells) B16F10 tumors. UMAP representation of CD8\u003csup\u003e+\u003c/sup\u003e T cells (\u003cstrong\u003eh\u003c/strong\u003e) and the percentages (\u003cstrong\u003ei\u003c/strong\u003e) of CD8\u003csup\u003e+\u003c/sup\u003e T cell subsets within CD45\u003csup\u003e+\u003c/sup\u003e cells in tumors. \u003cstrong\u003ej, k,\u003c/strong\u003e Representative immunofluorescent staining (\u003cstrong\u003ej\u003c/strong\u003e) and quantification (\u003cstrong\u003ek\u003c/strong\u003e) of CD8\u003csup\u003e+ \u003c/sup\u003eT cell in Scramble or \u003cem\u003eTmem176b\u003c/em\u003e-deficient MC38 tumors from B6 mice. \u003cstrong\u003el\u003c/strong\u003e, Growth of Scramble or \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16GP33 tumors in \u003cem\u003eRag1\u003c/em\u003e\u003csup\u003e\u003cem\u003e-/-\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e \u003c/em\u003emice received adoptive transfer of P14 CD8\u003csup\u003e+\u003c/sup\u003e T cells or medium (n =8). Data are representative of three (\u003cstrong\u003ea-d\u003c/strong\u003e, \u003cstrong\u003ej-l\u003c/strong\u003e) independent experiments. Tumor growth data are presented as mean ± s.e.m. and all other data are presented as mean ± s.d. Statistical analysis was performed using two-tailed unpaired Student’s\u003cem\u003e t\u003c/em\u003e-test (\u003cstrong\u003ek\u003c/strong\u003e), or two-way ANOVA (\u003cstrong\u003ea-d, l\u003c/strong\u003e).\u003c/p\u003e","description":"","filename":"Tmem176bimmuneevasionNatureCancermainFigures202503113.png","url":"https://assets-eu.researchsquare.com/files/rs-6199894/v1/8bd6bd1d3650e65b8ec5c810.png"},{"id":86136637,"identity":"9c99851b-18de-447c-bbc5-8c701e10aa44","added_by":"auto","created_at":"2025-07-07 07:54:12","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1209298,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTmem176b deficiency in tumors enhances antitumor T cell immunity in a TDE-dependent manner.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea, b,\u003c/strong\u003e Representative flow cytometry (\u003cstrong\u003ea\u003c/strong\u003e), frequencies and numbers (\u003cstrong\u003eb\u003c/strong\u003e) of intratumoral CD4\u003csup\u003e+\u003c/sup\u003e and CD8\u003csup\u003e+ \u003c/sup\u003eT cells (top row), effector (CD44\u003csup\u003e+\u003c/sup\u003eCD62L\u003csup\u003e-\u003c/sup\u003e) CD4\u003csup\u003e+ \u003c/sup\u003eor CD8\u003csup\u003e+ \u003c/sup\u003eT cells (middle row), and terminally exhausted (PD1\u003csup\u003e+\u003c/sup\u003eTim3\u003csup\u003e+\u003c/sup\u003e) CD8\u003csup\u003e+ \u003c/sup\u003eT cells (bottom row) of B6 mice injected s.c. with Scramble or \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 cells (Scr, n=6; B16-T3KO, n=6; B16-T8KO, n=5). \u003cstrong\u003ec, d, \u003c/strong\u003eRepresentative flow cytometry (\u003cstrong\u003ec\u003c/strong\u003e), frequencies and numbers (\u003cstrong\u003ed\u003c/strong\u003e) of intratumoral IFN-γ\u003csup\u003e+\u003c/sup\u003e or TNF-α\u003csup\u003e+ \u003c/sup\u003eCD4\u003csup\u003e+ \u003c/sup\u003eT cells, and IFN-γ\u003csup\u003e+\u003c/sup\u003e or TNF-α\u003csup\u003e+ \u003c/sup\u003eCD8\u003csup\u003e+\u003c/sup\u003e, in tumors from mice as in \u003cstrong\u003ea\u003c/strong\u003e (n=6). \u003cstrong\u003ee,\u003c/strong\u003e Frequencies and numbers of intratumoral CD4\u003csup\u003e+\u003c/sup\u003e and CD8\u003csup\u003e+\u003c/sup\u003e T cells, and effector (CD44\u003csup\u003e+\u003c/sup\u003eCD62L\u003csup\u003e-\u003c/sup\u003e) CD4\u003csup\u003e+ \u003c/sup\u003eor CD8\u003csup\u003e+ \u003c/sup\u003eT cells of B6 mice inoculated s.c. with Scramble or \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 cells (B16-T8KO), or \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 cells transduced with \u003cem\u003eTmem176b\u003c/em\u003e (B16-T8KO (T-OE)) (B16-Scr, n = 6; B16-T8KO, n=7; B16-T8KO (T-OE), n=7). \u003cstrong\u003ef,\u003c/strong\u003e Frequencies and numbers of intratumoral IFN-γ\u003csup\u003e+ \u003c/sup\u003eor IFN-γ\u003csup\u003e+\u003c/sup\u003eTNF-α\u003csup\u003e+ \u003c/sup\u003eCD8\u003csup\u003e+\u003c/sup\u003e T cells in tumors from mice as in E (B16-Scr, n = 5; B16-T8KO, n=7; B16-T8KO (T-OE), n=7). \u003cstrong\u003eg\u003c/strong\u003e, Frequencies and numbers of intratumoral CD4\u003csup\u003e+\u003c/sup\u003e and CD8\u003csup\u003e+\u003c/sup\u003e T cells, effector (CD44\u003csup\u003e+\u003c/sup\u003eCD62L\u003csup\u003e-\u003c/sup\u003e) CD4\u003csup\u003e+ \u003c/sup\u003eor CD8\u003csup\u003e+ \u003c/sup\u003eT cells, and exhausted (PD1\u003csup\u003e+\u003c/sup\u003eTim3\u003csup\u003e+\u003c/sup\u003e) CD8\u003csup\u003e+ \u003c/sup\u003eT cells in B6 mice inoculated s.c. with \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 cells plus PBS or syngeneic exosomes from indicated genotypes of B16F10 cells (PBS, n = 6; EXO\u003csup\u003eWT\u003c/sup\u003e, n=7; EXO\u003csup\u003eT8KO\u003c/sup\u003e, n=6). \u003cstrong\u003eh,\u003c/strong\u003e Frequencies and numbers of intratumoral IFN-γ\u003csup\u003e+ \u003c/sup\u003eor IFN-γ\u003csup\u003e+\u003c/sup\u003eTNF-α\u003csup\u003e+ \u003c/sup\u003eCD8\u003csup\u003e+\u003c/sup\u003e T cells in tumors from mice as in \u003cstrong\u003eg\u003c/strong\u003e (PBS, n = 7; EXO\u003csup\u003eWT\u003c/sup\u003e, n=7; EXO\u003csup\u003eT8KO\u003c/sup\u003e, n=6). Data are representative of three independent experiments. Data are represented as mean ± s.d. Statistical analysis was performed using two-tailed unpaired Student’s\u003cem\u003e t\u003c/em\u003e-test (\u003cstrong\u003eb, d,\u003c/strong\u003e \u003cstrong\u003ee-h\u003c/strong\u003e).\u003c/p\u003e","description":"","filename":"Tmem176bimmuneevasionNatureCancermainFigures202503114.png","url":"https://assets-eu.researchsquare.com/files/rs-6199894/v1/982ac6700f807d479ae67361.png"},{"id":86135811,"identity":"b774fd41-22c6-4dc1-b4bb-b3a9a1ea0c41","added_by":"auto","created_at":"2025-07-07 07:45:42","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":4493972,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTumor-derived exosomal Tmem176b attenuates TCR signaling by recruiting Shp1.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea, b,\u003c/strong\u003e The percentages of CD25\u003csup\u003e+\u003c/sup\u003e, CD69\u003csup\u003e+\u003c/sup\u003e, CD71\u003csup\u003e+\u003c/sup\u003e or PD1\u003csup\u003e+\u003c/sup\u003e cells among CD8\u003csup\u003e+ \u003c/sup\u003eT cells or the absolute numbers of CD8\u003csup\u003e+ \u003c/sup\u003eT cells stimulated with anti-CD3 and anti-CD28 antibodies plus PBS or exosomes from indicated genotypes of B16F10 (\u003cstrong\u003ea\u003c/strong\u003e;\u003cstrong\u003e \u003c/strong\u003en=4) or MC38 (\u003cstrong\u003eb\u003c/strong\u003e; n=5). \u003cstrong\u003ec, d,\u003c/strong\u003e The percentages of CD25\u003csup\u003e+\u003c/sup\u003e, CD69\u003csup\u003e+\u003c/sup\u003e or CD71\u003csup\u003e+\u003c/sup\u003e cells among CD8\u003csup\u003e+ \u003c/sup\u003eT cells purified from human peripheral blood mononuclear cells (PBMC), stimulated with anti-CD3 and anti-CD28 antibodies plus PBS, or exosomes from indicated genotypes of SW480 cells (\u003cstrong\u003ec\u003c/strong\u003e; n=4) or HeLa cells (\u003cstrong\u003ed\u003c/strong\u003e; n=5). \u003cstrong\u003ee,\u003c/strong\u003e Immunoblot analysis of lysates of naive CD8\u003csup\u003e+\u003c/sup\u003e T cells pretreated with the indicated exosomes followed by stimulation with anti-CD3 and anti-CD28 antibodies for indicated time. \u003cstrong\u003ef,\u003c/strong\u003e KEGG pathway analysis of Tmem176b-binding proteins identified by IP-MS of Flag-tagged Tmem176b in EL4 cells before (left) or after (right) stimulation with anti-CD3 and anti-CD28. \u003cstrong\u003eg-h, \u003c/strong\u003eImmunoblot analysis of lysates of EL4 cells transduced with \u003cem\u003eTmem176b-Flag\u003c/em\u003e or empty vector, assessed by immunoprecipitation with anti-Flag and blot with anti-Shp1 (\u003cstrong\u003eg\u003c/strong\u003e) or anti-LAT (\u003cstrong\u003eh\u003c/strong\u003e) antibody. \u003cstrong\u003ei,\u003c/strong\u003e Schematic diagram shows the construction of Tmem176b mutants.\u003cstrong\u003e j-k,\u003c/strong\u003e Immunoblot analysis of lysates of EL4 cells transduced with \u003cem\u003eTmem176b-Flag\u003c/em\u003e or its mutants, assessed by immunoprecipitation with anti-Flag antibody and blot with anti-Shp1 (\u003cstrong\u003ej\u003c/strong\u003e) or anti-LAT (\u003cstrong\u003ek\u003c/strong\u003e) antibody. \u003cstrong\u003el, \u003c/strong\u003eGrowth of tumors in B6 mice injected s.c. with Scramble, \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 cells transduced with WT \u003cem\u003eTmem176b\u003c/em\u003e or its mutant (△218-227) (n =6). \u003cstrong\u003em, \u003c/strong\u003eRepresentative immunofluorescence images of membrane fusion of naïve CD8\u003csup\u003e+\u003c/sup\u003e T cells treated with and without R18-labeled exosomes from B16F10 cells transduced with \u003cem\u003eTmem176b-GFP\u003c/em\u003e. Scale bar, 10 μm. \u003cstrong\u003en-o,\u003c/strong\u003e Representative immunofluorescence images (\u003cstrong\u003en\u003c/strong\u003e) and quantification (\u003cstrong\u003eo\u003c/strong\u003e) of the enrichment of Tmem176b-GFP and Shp1 at naive P14 CD8\u003csup\u003e+ \u003c/sup\u003eT cells pretreated with (bottom row) or without (top row) exosomes from Tmem176b-GFP-expressing B16F10 cells, followed by conjugation with GP33-pulsed LPS-activated B cells. Scale bar, 5 μm. \u003cstrong\u003ep-q,\u003c/strong\u003e Tumor growth in WT and \u003cem\u003eShp1-\u003c/em\u003etKO mice inoculated s.c. with Scramble or \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 (\u003cstrong\u003ep\u003c/strong\u003e; n=7) or MC38 (\u003cstrong\u003eq\u003c/strong\u003e; n=5) cancer cells. Data are representative of two (\u003cstrong\u003ep-q\u003c/strong\u003e) or three (\u003cstrong\u003ea-e\u003c/strong\u003e, \u003cstrong\u003eg-o\u003c/strong\u003e) independent experiments. Tumor growth data are presented as mean ± s.e.m. and all other data are presented as mean ± s.d. Statistical analysis was performed using two-tailed unpaired Student’s\u003cem\u003e t\u003c/em\u003e-test (\u003cstrong\u003ea-d\u003c/strong\u003e) or two-way ANOVA (\u003cstrong\u003el, o, p\u003c/strong\u003e).\u003c/p\u003e","description":"","filename":"Tmem176bimmuneevasionNatureCancermainFigures202503115.png","url":"https://assets-eu.researchsquare.com/files/rs-6199894/v1/c32f4db041ac6882e32c87a2.png"},{"id":86135814,"identity":"d2a04548-710a-4053-a1f8-2991cb296acb","added_by":"auto","created_at":"2025-07-07 07:45:42","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":974994,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTmem176b blockade inhibits established tumor growth and exhibits synergistic effects with anti-PD1/PD-L1.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea-d,\u003c/strong\u003e Tumor growth (\u003cstrong\u003ea\u003c/strong\u003e, \u003cstrong\u003ec\u003c/strong\u003e) and survival curves (\u003cstrong\u003eb\u003c/strong\u003e, \u003cstrong\u003ed\u003c/strong\u003e) of B6 mice injected s.c. with B16F10 (\u003cstrong\u003ea\u003c/strong\u003e, \u003cstrong\u003eb\u003c/strong\u003e) or MC38 (\u003cstrong\u003ec\u003c/strong\u003e, \u003cstrong\u003ed\u003c/strong\u003e) cells, followed by treatment with cell-permeable competitive peptide (cell-penetrating peptide fused with amino acids 218-232 of Tmem176b, called CPP-Pep here) or scramble peptide (CPP-Scr) (n=6). \u003cstrong\u003ee-h\u003c/strong\u003e, Tumor growth (\u003cstrong\u003ee\u003c/strong\u003e, \u003cstrong\u003eg\u003c/strong\u003e) and survival curves (\u003cstrong\u003ef\u003c/strong\u003e, \u003cstrong\u003eh\u003c/strong\u003e) of B6 mice injected s.c. with B16F10 (\u003cstrong\u003ee\u003c/strong\u003e, \u003cstrong\u003ef\u003c/strong\u003e) or MC38 (\u003cstrong\u003eg\u003c/strong\u003e, \u003cstrong\u003eh\u003c/strong\u003e) cells, followed by treatment with monoclonal anti-Tmem176b antibody (6E8) or isotype antibody (n=6). \u003cstrong\u003ei-l,\u003c/strong\u003e Tumor growth (\u003cstrong\u003ei, k\u003c/strong\u003e) and survival curves (\u003cstrong\u003ej, l\u003c/strong\u003e) of B6 mice injected s.c. with B16F10 (\u003cstrong\u003ei, j\u003c/strong\u003e) or MC38 (\u003cstrong\u003ek, l\u003c/strong\u003e) cells, followed by treatment with CPP-Scr, CPP-Pep, anti-PD1 antibody, or CPP-Pep plus anti-PD1 (n=6). \u003cstrong\u003em-p,\u003c/strong\u003e Tumor growth (\u003cstrong\u003em, o\u003c/strong\u003e) and survival curves (\u003cstrong\u003en, p\u003c/strong\u003e) of B6 mice injected s.c. with B16F10 (\u003cstrong\u003em, n\u003c/strong\u003e) or MC38 (\u003cstrong\u003eo, p\u003c/strong\u003e) cells, followed by treatment with isotype, anti-PD1, 6E8, or 6E8 plus anti-PD1 (n=6). \u003cstrong\u003eq-s, \u003c/strong\u003eStrategy (\u003cstrong\u003eq\u003c/strong\u003e), tumor growth (\u003cstrong\u003er\u003c/strong\u003e) and survival curves (\u003cstrong\u003es\u003c/strong\u003e) of huHSC-NCG mice injected s.c. with A375 human melanoma cells, followed by treatment with monoclonal anti-TMEM176B antibody (n=6), isotype antibody (n=6), anti-PD-L1 antibody, or anti-TMEM176B plus anti-PD-L1 antibody (n=5). Red arrows indicate the time points of treatment. Data are representative of three independent experiments. Data are presented as mean ± s.e.m. Statistical analysis was performed using two-way ANOVA (\u003cstrong\u003ea, c, e, f, i, k, m, o, r\u003c/strong\u003e), or log-rank (Mantel-Cox) test (\u003cstrong\u003eb, d, f, h, j, l, n, p, s\u003c/strong\u003e).\u003c/p\u003e","description":"","filename":"Tmem176bimmuneevasionNatureCancermainFigures202503116.png","url":"https://assets-eu.researchsquare.com/files/rs-6199894/v1/bf9b739ec732d5458741d8ea.png"},{"id":86139643,"identity":"4e904c14-c8ee-4414-917f-569c6ebb8a34","added_by":"auto","created_at":"2025-07-07 08:18:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":20666483,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6199894/v1/98efa39d-299f-4d5d-9cf5-97943b4f796e.pdf"},{"id":86135804,"identity":"a05051e0-505d-42af-8cc4-80c1a44c0236","added_by":"auto","created_at":"2025-07-07 07:45:42","extension":"zip","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":3798387,"visible":true,"origin":"","legend":"Supplementary Tables 1-6","description":"","filename":"SupplementaryTablesV2.zip","url":"https://assets-eu.researchsquare.com/files/rs-6199894/v1/9676c7291a78954c2326fe82.zip"},{"id":86138927,"identity":"717b3436-f1d6-449a-9cf7-3b077aba914b","added_by":"auto","created_at":"2025-07-07 08:10:12","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":4716248,"visible":true,"origin":"","legend":"","description":"","filename":"GraphicalAbstract.docx","url":"https://assets-eu.researchsquare.com/files/rs-6199894/v1/b27643eb1caf41f2658722a3.docx"},{"id":86135813,"identity":"38b5e62f-ee76-47a4-be91-5b8a01e1a6f7","added_by":"auto","created_at":"2025-07-07 07:45:42","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":10338037,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExtended Data Fig. 1. TMEM176B is specifically secreted via exosomes by cancer cells.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea, b, \u003c/strong\u003eRepresentative transmission electron microscopy (TEM) images (\u003cstrong\u003ea\u003c/strong\u003e), nanoparticle tracking analysis (NTA) (\u003cstrong\u003eb\u003c/strong\u003e), of exosomes purified from SW480 (top) or B16F10 (middle) or MC38 (bottom) cancer cells.\u003cstrong\u003e c,\u003c/strong\u003e Immunoblot analysis of whole cell lysate (WCL) and purified exosomes (EXO) from SW480 (top) or B16F10 (middle) or MC38 (bottom) cancer cells, probed with antibodies against exosome marker Alix, Tsg101 and CD63. All lanes were loaded with the same amount of total protein. \u003cstrong\u003ed-f,\u003c/strong\u003e Representative Nano-Flow Cytometry (NanoFCM) plot (\u003cstrong\u003ed, g\u003c/strong\u003e) and the percentages (\u003cstrong\u003ee, g\u003c/strong\u003e) of Tmem176b\u003csup\u003e+\u003c/sup\u003e or TMEM176B\u003csup\u003e+\u003c/sup\u003e exosomes among total exosomes released from NIH3T3, B16F10, MC38 cells (\u003cstrong\u003ed, g\u003c/strong\u003e; n=3), and from BEAS-2B, MCF-10A, SW480, A549, Hela cells (\u003cstrong\u003eg, f\u003c/strong\u003e; n=4), after staining with monoclonal anti-Tmem176b (6E8) antibody. \u003cstrong\u003eh,\u003c/strong\u003e The percentages of Tmem176b\u003csup\u003e+\u003c/sup\u003e EVs among total exosomes and ectosomes released from Tmem176b-OE B16F10 tumor cells after staining with monoclonal anti-Tmem176b (6E8) antibody. \u003cstrong\u003ei,\u003c/strong\u003e Representative flow cytometry of Scramble or \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 and MC38 cells after intracellular staining (left) or surface staining (right) with anti-Tmem176b antibody (6E8). \u003cstrong\u003ej,\u003c/strong\u003e The percentages of Tmem176b\u003csup\u003e+\u003c/sup\u003e or TMEM176B\u003csup\u003e+\u003c/sup\u003e exosomes among total exosomes released from Scramble or \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10, MC38 cells (top), and from Scramble or\u003cem\u003e TMEM176B\u003c/em\u003e-deficient SW480, A549(bottom), analyzed by NanoFCM (n=3). \u003cstrong\u003ek, \u003c/strong\u003eRepresentative flow cytometry of macrophages, cDC2 and MSC after intracellular staining (left) or surface staining (right) with anti-Tmem176b antibody (6E8). \u003cstrong\u003el,\u003c/strong\u003e The percentages of Tmem176b\u003csup\u003e+\u003c/sup\u003e exosomes among total exosomes released from B16F10, macrophages, cDC2 and MSC, analyzed by NanoFCM (n=2). Data are representative of three independent experiments. Data are represented as mean ± s.d. Statistical analysis was performed using two-tailed unpaired Student’s\u003cem\u003e t\u003c/em\u003e-test (\u003cstrong\u003ee-g, h, j, l\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExtended Data Fig. 2. Malignant cancer cells sort TMEM176B into exosomes and secrete into the circulation.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea, \u003c/strong\u003eRepresentative immunofluorescence images of localization of Tmem176b (Green) and indicated organelle markers (Red): Rab5, Rab7, Hrs and Lamp1, in B16F10 cells stably expressing Tmem176b-GFP. DAPI was used for nuclear staining (blue). \u003cstrong\u003eb,\u003c/strong\u003e Gene Ontology (GO) analysis of Tmem176b-interacting proteins in Tmem176b-Flag-expressing B16F10 cells, identified by IP-MS. \u003cstrong\u003ec, \u003c/strong\u003eImmunoblot analysis of lysates of B16F10 cells transduced with \u003cem\u003eTmem176b\u003c/em\u003e-Flag or empty vector, assessed by immunoprecipitation with anti-Flag antibody. \u003cstrong\u003ed,\u003c/strong\u003e The percentages of Tmem176b\u003csup\u003e+\u003c/sup\u003e exosomes among total exosomes released from Scramble, \u003cem\u003eHrs\u003c/em\u003e-deficient or \u003cem\u003eRab27a\u003c/em\u003e-deficient B16F10 (n=2). \u003cstrong\u003ee, f,\u003c/strong\u003e Representative NanoFCM plot (\u003cstrong\u003ee\u003c/strong\u003e) and the percentages (\u003cstrong\u003ef\u003c/strong\u003e) of Tmem176b\u003csup\u003e+\u003c/sup\u003e exosomes among total circulating exosomes in plasma of B6 mice inoculated s.c. with or without B16F10 or MC38 cells (n=5). \u003cstrong\u003eg, h,\u003c/strong\u003e Schematic (\u003cstrong\u003eg\u003c/strong\u003e) of ELISA to detect the amount (\u003cstrong\u003eh\u003c/strong\u003e) of TMEM176B protein on circulating exosomes in plasma samples from healthy donors (n=23) and patients with COAD (n=32), STAD (n=45), ESCA (n=35), LUAD (n=41), BRCA (n=34), LIHC (n=9), or THYM (n=5). Data are representative of two (\u003cstrong\u003eh\u003c/strong\u003e) or three (\u003cstrong\u003ea, c-f\u003c/strong\u003e) independent experiments. Data are represented as mean ± s.d. Statistical analysis was performed using two-tailed unpaired Student’s\u003cem\u003e t\u003c/em\u003e-test (\u003cstrong\u003ed, f, h\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExtended Data Fig. 3. TDEs promote tumor progression via immunosuppressive TME.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea, b,\u003c/strong\u003e Tumor growth (\u003cstrong\u003ea\u003c/strong\u003e) and survival curves (\u003cstrong\u003eb\u003c/strong\u003e) of immunocompetent B6 mice injected s.c. with Scramble or Rab27a-deficient B16F10 melanoma cells (n=8). \u003cstrong\u003ec-f\u003c/strong\u003e Tumor growth (\u003cstrong\u003ec, e\u003c/strong\u003e) and survival curves (\u003cstrong\u003ed, f\u003c/strong\u003e) of B6 mice injected s.c. with B16F10 (\u003cstrong\u003ec, d\u003c/strong\u003e) or MC38 (\u003cstrong\u003ee, f\u003c/strong\u003e) cells plus the corresponding syngeneic exosomes or PBS (n=8). \u003cstrong\u003eg, h,\u003c/strong\u003e scRNA-seq analysis of intratumoral CD45\u003csup\u003e+\u003c/sup\u003e cells from B6 mice injected s.c. with B16F10 cells plus syngeneic exosomes (n=6773) or PBS (n=6507). UMAP representation of all CD45\u003csup\u003e+\u003c/sup\u003e cells with 16 unqiue immune populations (\u003cstrong\u003eg\u003c/strong\u003e) and the percentages of immune populations within CD45\u003csup\u003e+\u003c/sup\u003e cells in tumors (\u003cstrong\u003eh\u003c/strong\u003e). \u003cstrong\u003ei,\u003c/strong\u003e UMAP representation of B cell subpopulations in tumor as in \u003cstrong\u003eg\u003c/strong\u003e. \u003cstrong\u003ej, k,\u003c/strong\u003e Violin plots (\u003cstrong\u003ej\u003c/strong\u003e) and UMAP (\u003cstrong\u003ek\u003c/strong\u003e) showing activity scores of exhaustion gene signatures in B cell subpopulations in tumor as in \u003cstrong\u003eg\u003c/strong\u003e. \u003cstrong\u003el, m,\u003c/strong\u003e UMAP representation of macrophage subpopulations (\u003cstrong\u003el\u003c/strong\u003e) and the percentages (\u003cstrong\u003em\u003c/strong\u003e) of macrophage subpopulations within CD45\u003csup\u003e+\u003c/sup\u003e cells in tumors as in \u003cstrong\u003eg\u003c/strong\u003e. Data are representative of three (\u003cstrong\u003ea-f\u003c/strong\u003e) independent experiments. Tumor growth data are presented as mean ± s.e.m. Statistical analysis was performed using two-way analysis of variance (ANOVA) (\u003cstrong\u003ea, c, e\u003c/strong\u003e) or log-rank (Mantel-Cox) test (\u003cstrong\u003eb, d, f\u003c/strong\u003e), or two-sided Wilcoxon rank-sum test (\u003cstrong\u003ej\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExtended Data Fig. 4. The pro-tumoral effect of TDEs is mainly dependent on CD8\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e+\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e T cells.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea, b,\u003c/strong\u003e scRNA-seq analysis of intratumoral CD45\u003csup\u003e+\u003c/sup\u003e cells from B6 mice injected s.c. with B16F10 cells plus syngeneic exosomes (n=6773) or PBS (n=6507). UMAP representation of CD8\u003csup\u003e+\u003c/sup\u003e T cells (\u003cstrong\u003ea\u003c/strong\u003e) and the percentages (\u003cstrong\u003eb\u003c/strong\u003e) of subsets of CD8\u003csup\u003e+\u003c/sup\u003e T cells within CD45\u003csup\u003e+\u003c/sup\u003e cells. \u003cstrong\u003ec, \u003c/strong\u003eViolin plots showing activity scores of early activation, exhaustion and effector/cytokine signatures in intratumoral CD8\u003csup\u003e+ \u003c/sup\u003eT cells in tumor as in \u003cstrong\u003ea\u003c/strong\u003e. \u003cstrong\u003ed-f, \u003c/strong\u003eTumor growth in BCD mice (PBS, n=7; EXO, n=6) (\u003cstrong\u003ed\u003c/strong\u003e), \u003cem\u003eRag1\u003c/em\u003e\u003csup\u003e\u003cem\u003e-/-\u003c/em\u003e\u003c/sup\u003e mice (PBS, n=7; EXO, n=10) (\u003cstrong\u003ee\u003c/strong\u003e), or \u003cem\u003eCD8\u003c/em\u003e\u003csup\u003e\u003cem\u003e-/-\u003c/em\u003e\u003c/sup\u003e mice (n=8) (\u003cstrong\u003ef\u003c/strong\u003e) injected s.c. with B16F10 tumor cells plus syngeneic exosomes or PBS. \u003cstrong\u003eg, h,\u003c/strong\u003e Tumor growth in \u003cem\u003eRag1\u003c/em\u003e\u003csup\u003e\u003cem\u003e-/-\u003c/em\u003e\u003c/sup\u003e mice (n=5) (\u003cstrong\u003eg\u003c/strong\u003e) or \u003cem\u003eCD8\u003c/em\u003e\u003csup\u003e\u003cem\u003e-/-\u003c/em\u003e\u003c/sup\u003e mice (n=8) (\u003cstrong\u003eh\u003c/strong\u003e) injected s.c. with MC38 cells plus syngeneic exosomes or PBS (PBS, n=7; EXO, n=8). Data are representative of three (\u003cstrong\u003ed-h\u003c/strong\u003e) independent experiments. Tumor growth data are presented as mean ± s.e.m. Statistical analysis was performed using two-sided Wilcoxon rank-sum test (\u003cstrong\u003ec\u003c/strong\u003e) or two-way ANOVA (\u003cstrong\u003ed-h\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExtended Data Fig. 5. TDEs suppress antitumor T cell immunity.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea-d,\u003c/strong\u003e Representative flow cytometry (\u003cstrong\u003ea, c\u003c/strong\u003e), frequencies and numbers (\u003cstrong\u003eb, d\u003c/strong\u003e) of intratumoral CD4\u003csup\u003e+\u003c/sup\u003e and CD8\u003csup\u003e+\u003c/sup\u003e T cells, effector (CD44\u003csup\u003e+\u003c/sup\u003eCD62L\u003csup\u003e-\u003c/sup\u003e) CD4\u003csup\u003e+\u003c/sup\u003e or CD8\u003csup\u003e+\u003c/sup\u003e T cells, and exhausted (PD1\u003csup\u003e+\u003c/sup\u003eTim3\u003csup\u003e+\u003c/sup\u003e) CD8\u003csup\u003e+ \u003c/sup\u003eT cells from B6 mice injected s.c. with B16F10 (\u003cstrong\u003ea, b\u003c/strong\u003e; PBS, n=7; EXO, n=8) or MC38 (\u003cstrong\u003ec, d\u003c/strong\u003e; PBS, n=10; EXO, n=9) cells plus the corresponding syngeneic exosomes or PBS. \u003cstrong\u003ee, f,\u003c/strong\u003e Representative flow cytometry (\u003cstrong\u003ee\u003c/strong\u003e), frequencies and numbers (\u003cstrong\u003ef\u003c/strong\u003e) of intratumoral IFN-γ\u003csup\u003e+\u003c/sup\u003e, IFN-γ\u003csup\u003e+\u003c/sup\u003eTNF-α\u003csup\u003e+\u003c/sup\u003e, or Granzyme B\u003csup\u003e+ \u003c/sup\u003eCD8\u003csup\u003e+\u003c/sup\u003e T cells and IFN-γ\u003csup\u003e+ \u003c/sup\u003eor TNF-α\u003csup\u003e+ \u003c/sup\u003eCD4\u003csup\u003e+\u003c/sup\u003e T cells from B6 mice as in \u003cstrong\u003ea\u003c/strong\u003e (n=6). \u003cstrong\u003eg, h,\u003c/strong\u003e Representative flow cytometry (\u003cstrong\u003eg\u003c/strong\u003e), frequencies and numbers (\u003cstrong\u003eh\u003c/strong\u003e) of intratumoral TNF-α\u003csup\u003e+\u003c/sup\u003e or IFN-γ\u003csup\u003e+\u003c/sup\u003eTNF-α\u003csup\u003e+\u003c/sup\u003e CD4\u003csup\u003e+\u003c/sup\u003e, and IFN-γ\u003csup\u003e+ \u003c/sup\u003eor IFN-γ\u003csup\u003e+\u003c/sup\u003eTNF-α\u003csup\u003e+ \u003c/sup\u003eCD8\u003csup\u003e+\u003c/sup\u003e T cells from B6 mice as in \u003cstrong\u003ec\u003c/strong\u003e (n=8). \u003cstrong\u003ei, j,\u003c/strong\u003e Representative flow cytometry (\u003cstrong\u003ei\u003c/strong\u003e) and frequencies (\u003cstrong\u003ej\u003c/strong\u003e) of CD4\u003csup\u003e+\u003c/sup\u003e and CD8\u003csup\u003e+\u003c/sup\u003e T cells in tumor draining lymph nodes (TdLN) from mice as in \u003cstrong\u003ec\u003c/strong\u003e (PBS, n=9; EXO, n=10). Data are representative of three independent experiments. Data are presented as mean ± s.d. Statistical analysis was performed using two-tailed unpaired Student’s\u003cem\u003e t\u003c/em\u003e-test (\u003cstrong\u003eb, d, f, h, j\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExtended Data Fig. 6. TDEs inhibit early activation and proliferation of T cells through Tmem176b.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea-c,\u003c/strong\u003e Proliferation of naive CD8\u003csup\u003e+\u003c/sup\u003e T cells treated with B16F10-derived exosomes before (top row) or after (bottom row) stimulation with anti-CD3 and anti-CD28 antibodies. Schematic of \u003cem\u003ein vitro\u003c/em\u003e T cell activation (\u003cstrong\u003ea\u003c/strong\u003e), representative flow cytometry plot of CFSE dilution (\u003cstrong\u003eb\u003c/strong\u003e; n=4), the percentages of CFSE\u003csup\u003elow \u003c/sup\u003eCD8\u003csup\u003e+ \u003c/sup\u003eT cells (\u003cstrong\u003ec\u003c/strong\u003e, left; n=4) and the absolute numbers of total CD8\u003csup\u003e+\u003c/sup\u003e T cells (\u003cstrong\u003ec\u003c/strong\u003e, right; n=3). \u003cstrong\u003ed,\u003c/strong\u003e The percentages of CD25\u003csup\u003e+\u003c/sup\u003e, CD69\u003csup\u003e+\u003c/sup\u003e, CD71\u003csup\u003e+\u003c/sup\u003e or CD44\u003csup\u003e+\u003c/sup\u003eCD62L\u003csup\u003e-\u003c/sup\u003e cells among CD8\u003csup\u003e+ \u003c/sup\u003eT cells stimulated with anti-CD3 and anti-CD28 antibodies plus B16F10-derived exosomes or PBS for indicated time (n=3). \u003cstrong\u003ee, f,\u003c/strong\u003e Representative flow cytometry (\u003cstrong\u003ee\u003c/strong\u003e) and the percentages (\u003cstrong\u003ef\u003c/strong\u003e) of CFSE\u003csup\u003elow\u003c/sup\u003e cells among CD4\u003csup\u003e+ \u003c/sup\u003eT cells treated with B16F10-derived exosomes before (top row) or after (bottom row) anti-CD3 and anti-CD28 stimulation (n=4). \u003cstrong\u003eg,\u003c/strong\u003e The percentages of CD25\u003csup\u003e+\u003c/sup\u003e, CD69\u003csup\u003e+\u003c/sup\u003e, CD71\u003csup\u003e+\u003c/sup\u003e, or ICOS\u003csup\u003e+\u003c/sup\u003e cells among CD4\u003csup\u003e+ \u003c/sup\u003eT cells stimulated with anti-CD3 and anti-CD28 antibodies plus B16F10-derived exosomes or PBS for indicated time (n=3). \u003cstrong\u003eh,\u003c/strong\u003e The frequencies of CD25\u003csup\u003e+\u003c/sup\u003e, CD69\u003csup\u003e+\u003c/sup\u003e, CD71\u003csup\u003e+\u003c/sup\u003e, or PD1\u003csup\u003e+\u003c/sup\u003e among CD8\u003csup\u003e+ \u003c/sup\u003eT cells stimulated with anti-CD3 and anti-CD28 antibodies plus PBS, NIH3T3- or B16F10-derived exosomes, or exosomes from B16F10 cells transduced with indicated sgRNA (n=4). Data are representative of two (\u003cstrong\u003eh\u003c/strong\u003e) or three (\u003cstrong\u003eb-g\u003c/strong\u003e) independent experiments. Data are presented as mean ± s.d. Statistical analysis was performed using two-tailed unpaired Student’s\u003cem\u003e t\u003c/em\u003e-test (\u003cstrong\u003ec, d, f, g\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExtended Data Fig. 7. Ablation of\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eTmem176b in cancer cells does not significantly affect cancer cell proliferation, the secretion and immune cargoes of exosomes.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea,\u003c/strong\u003e Proliferation rate of Scramble or \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 (left) and MC38 (right) cells cultured for indicated time. \u003cstrong\u003eb,\u003c/strong\u003e Quantification of exosomes secreted by Scramble or \u003cem\u003eTmem176b\u003c/em\u003e-deficient MC38 cells. \u003cstrong\u003ec, d,\u003c/strong\u003e Representative TEM images (\u003cstrong\u003ec\u003c/strong\u003e) and NTA (\u003cstrong\u003ed\u003c/strong\u003e) of purified exosomes from Scramble or \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 (Top row) or MC38 (Bottom row) cells. \u003cstrong\u003ee,\u003c/strong\u003e Immunoblot analysis of WCL and purified exosomes (EXO) from Scramble or \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 or MC38 cells, probed with antibodies against exosome markers Alix, Tsg101, CD63, CD9 or CD81. All lanes were loaded with the same amount of total protein. \u003cstrong\u003ef,\u003c/strong\u003e GO analysis of the differentially expressed proteins in exosomes from \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 cells relative to those from Scramble B16F10 cells. \u003cstrong\u003eg, \u003c/strong\u003eGrowth of B16F10 tumors in WT and \u003cem\u003eTmem176a/b \u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e\u003csup\u003e \u003c/sup\u003eCD11c-Cre (c) (WT, n=6; \u003cem\u003eTmem176a/b \u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e\u003csup\u003e \u003c/sup\u003eCD11c-Cre, n=10). Data are representative of two (\u003cstrong\u003eb\u003c/strong\u003e, \u003cstrong\u003ed\u003c/strong\u003e) or three (\u003cstrong\u003ea, c, e, g\u003c/strong\u003e) independent experiments. Data are presented as mean ± s.d. Statistical analysis was performed using two-tailed unpaired Student’s\u003cem\u003e t\u003c/em\u003e-test (\u003cstrong\u003eb\u003c/strong\u003e) and two-way ANOVA (\u003cstrong\u003eg\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExtended Data Fig. 8. The impact of tumor-derived exosomal Tmem176b on immune cells in the TME.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea, b,\u003c/strong\u003e Representative flow cytometry (\u003cstrong\u003ea\u003c/strong\u003e) and frequencies (\u003cstrong\u003eb\u003c/strong\u003e) of GFP\u003csup\u003e+ \u003c/sup\u003ecells among indicated immune cell populations in tumors from B6 mice injected s.c. with MC38 cells stably expressing Tmem176b-GFP or Tmem176b alone (n=4). \u003cstrong\u003ec, d,\u003c/strong\u003e Representative flow cytometry (\u003cstrong\u003ec\u003c/strong\u003e) and frequencies (\u003cstrong\u003ed\u003c/strong\u003e) of GFP\u003csup\u003e+\u003c/sup\u003e cells among indicated immune cell populations in tumors from B6 mice injected s.c. with Tmem176b-GFP -expressing Scramble or \u003cem\u003eRab27a\u003c/em\u003e-deficient B16F10 cells (n=3). \u003cstrong\u003ee,\u003c/strong\u003e Flt3L-cDC1 were pre-treated with indicated exosomes and then cultured for 3 days with CFSE-labeled OT-Ⅰ T cells and HKLM-OVA, and assayed for OT-Ⅰ proliferation and activation (CFSE\u003csup\u003elow\u003c/sup\u003eCD44\u003csup\u003e+\u003c/sup\u003e)\u003cem\u003e \u003c/em\u003e(n=5). \u003cstrong\u003ef, g,\u003c/strong\u003e UMAP representation (\u003cstrong\u003ef\u003c/strong\u003e) and the percentages (\u003cstrong\u003eg\u003c/strong\u003e) of the Neutrophil subpopulations within CD45\u003csup\u003e+\u003c/sup\u003e cells in tumors from B6 mice injected s.c. with Scramble or \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 cells. Data are representative of two (\u003cstrong\u003ea-d\u003c/strong\u003e) or three (\u003cstrong\u003ee\u003c/strong\u003e) independent experiments. Data are presented as mean ± s.d. Statistical analysis was performed using two-tailed unpaired Student’s \u003cem\u003et\u003c/em\u003e-test (\u003cstrong\u003eb, d, e\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExtended Data Fig. 9. Tmem176b Ablation in tumors ameliorates antitumor T cell immunity.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea, b,\u003c/strong\u003e Representative flow cytometry (\u003cstrong\u003ea\u003c/strong\u003e), frequencies and numbers (\u003cstrong\u003eb\u003c/strong\u003e) of intratumoral CD4\u003csup\u003e+\u003c/sup\u003e and CD8\u003csup\u003e+\u003c/sup\u003e T cells (top row), effector (CD44\u003csup\u003e+\u003c/sup\u003eCD62L\u003csup\u003e-\u003c/sup\u003e) CD4\u003csup\u003e+ \u003c/sup\u003eor CD8\u003csup\u003e+ \u003c/sup\u003eT cells (bottom row) of B6 mice injected s.c. with Scramble or \u003cem\u003eTmem176b\u003c/em\u003e-deficient MC38 cells (n=6). \u003cstrong\u003ec, d,\u003c/strong\u003e Representative flow cytometry (\u003cstrong\u003ec\u003c/strong\u003e) frequencies and numbers (\u003cstrong\u003ed\u003c/strong\u003e) of intratumoral IFN-γ\u003csup\u003e+\u003c/sup\u003e or TNF-α\u003csup\u003e+\u003c/sup\u003e CD8\u003csup\u003e+\u003c/sup\u003e, and IFN-γ\u003csup\u003e+\u003c/sup\u003e or TNF-α\u003csup\u003e+ \u003c/sup\u003eCD4\u003csup\u003e+\u003c/sup\u003e T cells in tumors from mice as in \u003cstrong\u003ea\u003c/strong\u003e (MC38-Scr, n=8; MC38-T8KO, n=6). \u003cstrong\u003ee, f,\u003c/strong\u003e Representative flow cytometry (\u003cstrong\u003ee\u003c/strong\u003e) and frequencies (\u003cstrong\u003ef\u003c/strong\u003e) of CD4\u003csup\u003e+\u003c/sup\u003e and CD8\u003csup\u003e+\u003c/sup\u003e T cells in TdLN from mice as in \u003cstrong\u003ea\u003c/strong\u003e (n=6). \u003cstrong\u003eg,\u003c/strong\u003e Representative flow cytometry of intratumoral CD4\u003csup\u003e+\u003c/sup\u003e and CD8\u003csup\u003e+\u003c/sup\u003e T cells, effector (CD44\u003csup\u003e+\u003c/sup\u003eCD62L\u003csup\u003e-\u003c/sup\u003e) CD4\u003csup\u003e+ \u003c/sup\u003eor CD8\u003csup\u003e+ \u003c/sup\u003eT cells of B6 mice inoculated s.c. with Scramble (B16-Scr) or \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 cells (B16-T8KO), or \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 cells transduced with \u003cem\u003eTmem176b\u003c/em\u003e (B16-T8KO (T-OE)) (B16-Scr, n = 6; B16-T8KO, n=7; B16-T8KO (T-OE), n=7). \u003cstrong\u003eh,\u003c/strong\u003e Representative flow cytometry of intratumoral IFN-γ\u003csup\u003e+ \u003c/sup\u003eor IFN-γ\u003csup\u003e+\u003c/sup\u003eTNF-α\u003csup\u003e+\u003c/sup\u003e CD8\u003csup\u003e+\u003c/sup\u003e T cells in tumors from mice as in \u003cstrong\u003eg\u003c/strong\u003e (B16-Scr, n = 5; B16-T8KO, n=7; B16-T8KO (T-OE), n=7). \u003cstrong\u003ei, j,\u003c/strong\u003e Representative flow cytometry (\u003cstrong\u003ei\u003c/strong\u003e) and frequencies (\u003cstrong\u003ej\u003c/strong\u003e) of intratumoral CD4\u003csup\u003e+\u003c/sup\u003e and CD8\u003csup\u003e+\u003c/sup\u003e T cells, and effector (CD44\u003csup\u003e+\u003c/sup\u003eCD62L\u003csup\u003e-\u003c/sup\u003e) CD4\u003csup\u003e+ \u003c/sup\u003eor CD8\u003csup\u003e+ \u003c/sup\u003eT cells of B6 mice inoculated s.c. with Scramble (MC38-Scr) or \u003cem\u003eTmem176b\u003c/em\u003e-deficient (MC38-T8KO) cells, or \u003cem\u003eTmem176b\u003c/em\u003e-deficient MC38 cells transduced with \u003cem\u003eTmem176b\u003c/em\u003e (MC38-T8KO (T-OE)) (n=6). \u003cstrong\u003ek, l,\u003c/strong\u003e Representative flow cytometry (\u003cstrong\u003ek\u003c/strong\u003e) and frequencies (\u003cstrong\u003el\u003c/strong\u003e) of IFN-γ\u003csup\u003e+ \u003c/sup\u003eor IFN-γ\u003csup\u003e+\u003c/sup\u003eTNF-α\u003csup\u003e+\u003c/sup\u003e CD8\u003csup\u003e+\u003c/sup\u003e T cells in tumors from mice as in \u003cstrong\u003ei\u003c/strong\u003e (MC38-Scr, n = 6; MC38-T8KO, n=5; MC38-T8KO(T-OE), n=5). \u003cstrong\u003em, n,\u003c/strong\u003e Representative flow cytometry (\u003cstrong\u003em\u003c/strong\u003e) and frequencies (\u003cstrong\u003en\u003c/strong\u003e) of CD4\u003csup\u003e+\u003c/sup\u003e and CD8\u003csup\u003e+\u003c/sup\u003e T cells in TdLN from mice as in \u003cstrong\u003ei\u003c/strong\u003e (MC38-Scr, n = 7; MC38-T8KO, n=6; MC38-T8KO(T-OE), n=7). Data are representative of three independent experiments. Data are represented as mean ± s.d. Statistical analysis was performed using two-tailed unpaired Student’s\u003cem\u003e t\u003c/em\u003e-test (\u003cstrong\u003eb, d, f, j, l, n)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExtended Data Fig. 10. Tumor-derived exosomal Tmem176b represses antitumor T cell immunity.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea, \u003c/strong\u003eRepresentative flow cytometry of intratumoral CD4\u003csup\u003e+\u003c/sup\u003e and CD8\u003csup\u003e+\u003c/sup\u003e T cells, effector (CD44\u003csup\u003e+\u003c/sup\u003eCD62L\u003csup\u003e-\u003c/sup\u003e) CD4\u003csup\u003e+ \u003c/sup\u003eor CD8\u003csup\u003e+ \u003c/sup\u003eT cells, and exhausted (PD1\u003csup\u003e+\u003c/sup\u003eTim3\u003csup\u003e+\u003c/sup\u003e) CD8\u003csup\u003e+ \u003c/sup\u003eT cells in B6 mice inoculated s.c. with \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 cells plus PBS or syngeneic exosomes from indicated genotypes of B16F10 cells (PBS, n = 6; EXO\u003csup\u003eWT\u003c/sup\u003e, n=7; EXO\u003csup\u003eT8KO\u003c/sup\u003e, n=6). \u003cstrong\u003eb,\u003c/strong\u003e Representative flow cytometry of intratumoral IFN-γ\u003csup\u003e+\u003c/sup\u003e or IFN-γ\u003csup\u003e+\u003c/sup\u003eTNF-α\u003csup\u003e+\u003c/sup\u003e CD8\u003csup\u003e+\u003c/sup\u003e T cells in tumors from mice as in \u003cstrong\u003ea\u003c/strong\u003e (PBS, n = 7; EXO\u003csup\u003eWT\u003c/sup\u003e, n=7; EXO\u003csup\u003eT8KO\u003c/sup\u003e, n=6). \u003cstrong\u003ec-d,\u003c/strong\u003e Representative flow cytometry (\u003cstrong\u003ec\u003c/strong\u003e) and frequencies (\u003cstrong\u003ed\u003c/strong\u003e) intratumoral CD4\u003csup\u003e+\u003c/sup\u003e and CD8\u003csup\u003e+\u003c/sup\u003e T cells, effector (CD44\u003csup\u003e+\u003c/sup\u003eCD62L\u003csup\u003e-\u003c/sup\u003e) CD4\u003csup\u003e+ \u003c/sup\u003eor CD8\u003csup\u003e+ \u003c/sup\u003eT cells, and exhausted (PD1\u003csup\u003e+\u003c/sup\u003eTim3\u003csup\u003e+\u003c/sup\u003e) CD8\u003csup\u003e+ \u003c/sup\u003eT cells in B6 mice inoculated s.c. with \u003cem\u003eTmem176b\u003c/em\u003e-deficient MC38 cells plus PBS or syngeneic exosomes from indicated genotypes (PBS, n = 7; EXO\u003csup\u003eWT\u003c/sup\u003e, n=7; EXO\u003csup\u003eT8KO\u003c/sup\u003e, n=7). \u003cstrong\u003ee, f,\u003c/strong\u003e Representative flow cytometry (\u003cstrong\u003ee\u003c/strong\u003e) and frequencies (\u003cstrong\u003ef\u003c/strong\u003e) of intratumoral TNF-α\u003csup\u003e+\u003c/sup\u003e or IFN-γ\u003csup\u003e+\u003c/sup\u003eTNF-α\u003csup\u003e+\u003c/sup\u003e CD4\u003csup\u003e+ \u003c/sup\u003eT cells, and IFNγ\u003csup\u003e+\u003c/sup\u003e or IFN-γ\u003csup\u003e+\u003c/sup\u003eTNF-α\u003csup\u003e+\u003c/sup\u003e CD8\u003csup\u003e+\u003c/sup\u003e T cells in tumors from mice as in \u003cstrong\u003ec\u003c/strong\u003e (PBS, n = 7; EXO\u003csup\u003eWT\u003c/sup\u003e, n=6; EXO\u003csup\u003eT8KO\u003c/sup\u003e, n=6). \u003cstrong\u003eg, h,\u003c/strong\u003e Representative flow cytometry (\u003cstrong\u003eg\u003c/strong\u003e) and frequencies (\u003cstrong\u003eh\u003c/strong\u003e) of CD4\u003csup\u003e+\u003c/sup\u003e and CD8\u003csup\u003e+\u003c/sup\u003e T cells in TdLN from mice as in \u003cstrong\u003ec\u003c/strong\u003e (PBS, n = 7; EXO\u003csup\u003eWT\u003c/sup\u003e, n=6; EXO\u003csup\u003eT8KO\u003c/sup\u003e, n=6). Data are representative of three independent experiments. Data are represented as mean ± s.d. Statistical analysis was performed using two-tailed unpaired Student’s\u003cem\u003e t\u003c/em\u003e-test (\u003cstrong\u003ed, f, h\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExtended Data Fig. 11. The therapeutic effects of Tmem176b blockade in various tumor models.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea,\u003c/strong\u003e Immunoblot analysis of lysates of Tmem176b-Flag-expressing EL4 cells treated with PBS or indicated chimeric peptides, assessed by immunoprecipitation with anti-Flag antibody. \u003cstrong\u003eb,\u003c/strong\u003e Representative immunofluorescence images of localizations of BFP-Shp1 fusion protein and FITC-labelled CPP-Pep in EL4 cells. \u003cstrong\u003ec,\u003c/strong\u003e The percentages of CD25\u003csup\u003e+\u003c/sup\u003e, CD69\u003csup\u003e+\u003c/sup\u003e or PD1\u003csup\u003e+\u003c/sup\u003e cells among CD8\u003csup\u003e+ \u003c/sup\u003eT cells stimulated with anti-CD3 and anti-CD28 antibodies in the presence of PBS or B16F10-derived exosomes, or B16F10-derived exosomes plus indicated peptides or antibodies (n=5). \u003cstrong\u003ed, e,\u003c/strong\u003e Representative image (\u003cstrong\u003ed\u003c/strong\u003e) and quantification of the numbers (\u003cstrong\u003ee\u003c/strong\u003e) of lung surface metastases from B6 mice injected \u003cem\u003ei.v\u003c/em\u003e. with B16F10 cells, followed by treatments with indicated peptides (PBS, n=8; CPP-Scr, n=6; CPP-Pep, n=9). \u003cstrong\u003ef, \u003c/strong\u003eThe percentages of CD25\u003csup\u003e+\u003c/sup\u003e, CD69\u003csup\u003e+\u003c/sup\u003e or CD71\u003csup\u003e+\u003c/sup\u003e cells among human PBMC CD8\u003csup\u003e+ \u003c/sup\u003eT cells stimulated with anti-CD3 and anti-CD28 stimulation plus PBS, or exosomes from SW480 (top row) or HeLa (bottom row) cells together with or without anti-TMEM176B (2F2) antibody (n=4). \u003cstrong\u003eg,\u003c/strong\u003e Growth of \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 tumors in B6 mice treated with anti-Tmem176b antibody (6E8) or isotype antibody (n=5). Red arrows indicate the time points of treatment. \u003cstrong\u003eh, i,\u003c/strong\u003e Representative image (\u003cstrong\u003eh\u003c/strong\u003e) and tumor volumes (\u003cstrong\u003ei\u003c/strong\u003e) of livers from B6 mice orthotopically implanted with Hepa1-6 cells, followed by treatment with PBS, CPP-Scr, CPP-Pep or 6E8 (n=5). Data are representative of two (\u003cstrong\u003ed, e, h-i\u003c/strong\u003e) or three (\u003cstrong\u003ea-c, f-g\u003c/strong\u003e) independent experiments. Tumor growth data are presented as mean ± s.e.m. and all other data are presented as mean ± s.d. Statistical analysis was performed using two-tailed unpaired Student’s\u003cem\u003e t\u003c/em\u003e-test (\u003cstrong\u003ec, e, f, i\u003c/strong\u003e), or two-way ANOVA (\u003cstrong\u003eg\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExtended Data Fig. 12. Proposed model for the role of Tmem176b in tumor-driven immune evasion and its applications in cancer diagnosis and immunotherapy.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTmem176b is secreted via exosomes by cancer cells but not by non-malignant cells. TMEM176B (or Tmem176b)-positive circulating exosomes are specifically present in peripheral blood of tumor-bearing mice and various types of cancer patients, distinguishing healthy subjects from cancer patients with early- and late-stage cancer. High levels of TMEM176B-positive circulating exosomes with worse prognosis and unfavorable outcomes of anti-PD1 therapy, suggesting that they can serves as a potential non-invasive diagnostic and prognostic tool for cancer diagnosis and prognosis. Tmem176b on TDEs inhibits T cell early activation, and its ablation in mouse cancer cells substantially reduces tumor growth in a CD8\u003csup\u003e+\u003c/sup\u003e T cell-dependent manner. Mechanistically, tumor-derived exosomal Tmem176b is delivered to CD8\u003csup\u003e+\u003c/sup\u003e T cells and attenuates proximal TCR signaling by recruiting protein tyrosine phosphatase Shp1. Blocking Tmem176b, either using neutralizing antibody or using competitive peptide to disrupt interaction between Tmem176b and Shp1, remarkably restrains tumor growth in models of mouse and human cancers, and synergizes with anti-PD1/PD-L1 therapy.\u003c/p\u003e","description":"","filename":"Tmem176bimmuneevasionNatureCancersupplementalFigures20250311.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6199894/v1/4cf7dbe49499909bf383c673.pdf"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e there is potential Competing Interest.\nN.X., X.G., F.L. and Y.H. are inventors on pending patent applications filed by Xiamen University that cover the use of TMEM176B competitive peptides and anti-TMEM176B antibodies in cancer immunotherapy and cancer diagnosis. The other authors declare no competing interests.","formattedTitle":"Cancer cells impede T cell early activation and drive immune evasion by transferring Tmem176b","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAlthough immune checkpoint blockade (ICB) has achieved unprecedented tumor regression and long-term survival benefit in patients with advanced melanoma and other cancers, such immunotherapies fail to control neoplasia in a large proportion of patients\u003csup\u003e1\u003c/sup\u003e. Within tumor microenvironment (TME), CD8\u003csup\u003e+\u003c/sup\u003e cytotoxic T lymphocytes (CTLs) play a crucial role in the eradication of tumor cells\u003csup\u003e2\u003c/sup\u003e. The priming, activation, recruitment of T cells to the TME are necessary for a potent antitumor immune response. To combat immune elimination, cancer cells often curtail T cell activities for immune evasion. Inhibitory molecules expressed on cancer cells or antigen-presenting cells (APCs) interact with T cells to induce T cell dysfunction. ICB such as anti-PD1/PD-L1 (Programmed cell death 1/ Programmed death ligand 1) antibody therapy disrupt these inhibitory receptor-ligand interactions to reinvigorate tumor-specific T cells\u003csup\u003e1\u003c/sup\u003e. The success of this therapy occur most often in patients with \u0026lsquo;hot\u0026rsquo; (\u0026lsquo;immune-inflamed)\u0026rsquo; tumors with abundant T cell responses, and a large subsets of patients do not respond to ICB therapy or develop acquired resistance, especially in \u0026lsquo;cold\u0026rsquo; (\u0026lsquo;immune-desert\u0026rsquo;/\u0026lsquo;immune-excluded\u0026rsquo;) tumors,\u0026nbsp;characterized by the absence or exclusion of T cells in the tumor parenchyma\u003csup\u003e3\u003c/sup\u003e. Besides T cell dysfunction, resistance to ICB therapy can result from the key tumor characteristics that impair the priming, activation, recruitment of T cells to the TME, thereby reducing T cell infiltration and activity\u003csup\u003e4-6\u003c/sup\u003e. MHC-Ⅰ\u0026nbsp;loss by\u0026nbsp;mutations in MHC-Ⅰ(including \u003cem\u003ehuman leukocyte antigen class\u003c/em\u003e\u003cem\u003eⅠ\u003c/em\u003e\u003cem\u003e\u0026nbsp;(HLA\u003c/em\u003e-\u003cem\u003eⅠ\u003c/em\u003e\u003cem\u003e)\u003c/em\u003e and \u003cem\u003eB2M\u003c/em\u003e) have been found in several human cancers, and is a common mechanism of both primary and acquired resistance to ICB therapy\u003csup\u003e7-10\u003c/sup\u003e. In addition to DNA mutations,\u0026nbsp;MHC-Ⅰ\u0026nbsp;loss can occur through epigenetic silencing\u003csup\u003e11\u003c/sup\u003e, protein degradation in lysosomes\u003csup\u003e12-15\u003c/sup\u003e. Defect in\u0026nbsp;IFN-\u0026gamma; signaling in tumors also results in inability to upregulate MHC-Ⅰ\u0026nbsp;and PD-L1 and confers resistance to anti-PD1 therapy\u003csup\u003e7,16\u003c/sup\u003e. The oncogenic pathways within cancer cells can also promote immune evasion and resistance to ICB therapy by excluding T cells from tumors. For example, loss of PTEN in cancer cells increases the expression of immunosuppressive cytokines, resulting in decreased T cell infiltration\u003csup\u003e17\u003c/sup\u003e, which can be reversed by inactivation of PI3K\u0026beta;\u003csup\u003e18\u003c/sup\u003e. Overactivation of\u0026nbsp;\u0026beta;-catenin or\u0026nbsp;prostaglandin E2 (PGE2) production driven by oncogenic signaling in tumors, prevent T cell infiltration by suppressing the recruitment and function of type 1 conventional dendritic cells (cDC1s)\u003csup\u003e19-24\u003c/sup\u003e. It is well-known that PD-L1 expressed on cancer cells or APCs interacts with PD1 on activated CD8\u003csup\u003e+\u0026nbsp;\u003c/sup\u003eT cells to conteract an ongoing antitumor immune response by diminishing both T cell receptor (TCR) and costimulatory signaling, while ITPRIPL1 expressed on tumors refractory to anti-PD1 therapy binds to CD3\u0026epsilon; on\u0026nbsp;activated\u0026nbsp;T cells to attenuate TCR signaling\u003csup\u003e25\u003c/sup\u003e. However, it remains unclear whether and how cancer cells impede the priming and early activation of naive\u0026nbsp;CD8\u003csup\u003e+\u003c/sup\u003e T cells by attenuating TCR signaling. Although hundreds of new agents overcoming tumor-intrinsic resistance in combination with anti-PD1/PD-L1 therapies are being tested in thousands of clinical trials globally, few combinations have proven to be clinical success\u003csup\u003e26,27\u003c/sup\u003e. Therefore, new therapeutic strategies\u0026nbsp;to enhance the efficacy of ICB therapy are of paramount importance.\u003c/p\u003e\n\u003cp\u003eExtracellular vesicles (EVs) are classified into two subsets, exosomes and ectosomes (also known as microvesicles), based on the biogenesis\u003csup\u003e28\u003c/sup\u003e. Cancer cells generally release more EVs than non-tumorigenic cells into the TME and circulation\u003csup\u003e29,30\u003c/sup\u003e, to promote tumor-intrinsic resistance to ICB therapy\u003csup\u003e31-35\u003c/sup\u003e. In addition, EVs exhibit multiple properties that may confer superior performance in cancer diagnosis and prognosis relative to other types of liquid biopsy biomarkers due to their relative abundance, stability, and array of cargoes (including proteins, lipids, nucleic acids and metabolites)\u003csup\u003e36\u003c/sup\u003e. Although many efforts have been made to define tumor-derived EV biomarkers that distinguish cancer patients from healthy individuals\u003csup\u003e37,38\u003c/sup\u003e, reliable EV biomarkers that can detect early cancer, predict therapeutic response to ICB therapy, also be targeted to enhance the efficacy of immunotherapy, are still lacking.\u003c/p\u003e\n\u003cp\u003eTo identify such tumor-derived exosomal markers, we performed proteomic profiling of exosomes from human and murine cancer cell lines and non-tumorigenic cell lines, and identified the transmembrane protein Tmem176b, one related member of the tetraspan MS4A (membrane-spanning 4-domain, subfamily A) family\u003csup\u003e39\u003c/sup\u003e, specifically enriched on cancer-cell-derived exosomes. TMEM176B-positive circulating exosomes were detected in peripheral blood of various types of cancer patients, distinguishing healthy subjects from cancer patients with early- and late-stage cancer. High levels of TMEM176B-positive circulating exosomes were associated with worse prognosis and unfavorable outcomes of anti-PD1 therapy, suggesting that they may serve as a potential non-invasive diagnostic tool to detect early cancer and predict clinical response to anti-PD1 therapy. We have also demonstrated that Tmem176b on tumor-derived exosomes (TDEs) promotes immune evasion and tumor progression via direct inhibition of T cell early activation. Blocking Tmem176b remarkably restrained tumor growth, providing a potential strategy to overcome tumor-intrinsic resistance to cancer immunotherapy.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eTMEM176B is specific marker of cancer-cell-derived exosomes\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo identify specific markers that distinguish cancer-cell-derived exosomes from normal exosomes, we purified small EVs from both human and mouse cancer cells (A549 human lung carcinoma cells, SW480 human colorectal adenocarcinoma cells, HeLa human cervical adenocarcinoma cells, B16F10 mouse melanoma cells, MC38 mouse colorectal adenocarcinoma cells), and non-tumorigenic cells (MCF-10A human mammary gland epithelial cells and BEAS-2B human bronchial epithelial cells) by sequential ultracentrifugation. These EVs were characterized as exosomes in terms of morphology and size range via transmission electron microscopy (TEM) and Nanosight nanoparticle tracking analysis (NTA) (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea-b). Immunoblot confirmed the expression of conventional exosomal markers TSG101, Alix and CD63 in exosomes from all sources (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). Proteins of these exosomes were evaluated by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). 5223, 6000, 5464, 4552, 4453, 716, and 3485 proteins were identified in exosomes from A549, SW480, HeLa, BEAS-2B, MCF-10A, B16F10 and MC38 cells, respectively, all of which included conventional exosomal markers TSG101, Alix, Flotillins, CD9 and CD81 (Supplementary Table\u0026nbsp;1). Bioinformatic analyses revealed 294 proteins specifically present in exosomes from all three human cancer cell lines but not in those from non-tumorigenic cell lines (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). Only 4 of these 294 proteins were also detected in exosomes from both B16F10 and MC38 murine cancer cell lines (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). Among these 4 proteins, TMEM176B belongs to the distantly related members of the tetraspan MS4A (membrane-spanning 4-domian, subfamily A) family\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. We next performed ultrasensitive Nano-Flow Cytometry (NanoFCM) analysis to detect Tmem176b on individual exosomes\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e, using monoclonal antibody (6E8) against the large loop between the third and fourth transmembrane domains of Tmem176b. NanoFCM revealed that a small proportion of exosomes secreted by murine and human malignant cancer cells (B16F10, MC38, SW480, A549 and HeLa) carried Tmem176b (or TMEM176B) protein (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed-g), whereas ectosomes released by cancer cells did not contain Tmem176b protein (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eh). Genetic ablation of Tmem176b (or TMEM176B) in cancer cells completely eliminated its cellular and exosomal expression (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ei-j). By contrast, murine and human non-tumorigenic cells (NIH3T3 mouse fibroblast, BEAS-2B and MCF-10A), innate immune cells (cDC2 and macrophages) and mesenchyma stem cells (MSCs) that highly expressed Tmem176b, did not secrete or secrete extremely low frequencies of Tmem176b (or TMEM176B)-positive exosomes (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed-g, \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ek-j). Together, these results show the presence of Tmem176b speficically on exosomes released from malignant cancer cells.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eExosomes are generated mostly via the endosomal sorting complex required for transport (ESCRT), albeit it can also occur independent of ESCRT\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Immunofluorescence staining revealed that most of Tmem176b proteins co-localized with endosomal markers Rab5 and Rab7, as well as Hrs, one component of ESCRT-0, in B16F10 melanoma cells, similar to a previous report (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea)\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. Intracellular flow cytometric staining with monoclonal antibody (6E8) against the large loop of Tmem176b detected high levels of Tmem176b protein in scramble B16F10 and MC38 cells but not in all strains of \u003cem\u003eTmem176b\u003c/em\u003e-deficient cancer cells, whereas cell surface staining scarcely detected Tmem176b protein in both scramble and \u003cem\u003eTmem176b\u003c/em\u003e-deficient cancer cells, confirming that Tmem176b protein mainly localized in the cytoplasm (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ei). Consistently, immunoprecipitation of Flag-tagged Tmem176b in B16F10 cells followed by mass spectrometry (IP-MS) identified a large number of proteins involved in intracellular protein transport and vesicle transport, including Hrs, as Tmem176b-binding partners (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb-c and Supplementary Table\u0026nbsp;2). Genetic deletion of Hrs or Rab27a, which mediates cargo sorting and exosome release respectively, blocked Tmem176b secretion via exosomes (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eTMEM176B\u003c/b\u003e\u003csup\u003e\u003cb\u003e+\u003c/b\u003e\u003c/sup\u003e \u003cb\u003ecirculating exosomes are a non-invasive cancer biomarker\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo investigate the secretion of exosomal Tmem176b from transplanted tumors \u003cem\u003ein vivo\u003c/em\u003e, we collected blood from B16F10- or MC38-bearing mice to purify exosomes and subsequently examined Tmem176b on exosomes by NanoFCM. NanoFCM identified Tmem176b on a small proportion (about 6%) of circulating exosomes from tumor-bearing mice but not those from naive mice (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee-f).\u003c/p\u003e\u003cp\u003eTo examine the protein levels of TMEM176B on circulating exosomes in cancer patients, we collected blood from various types of cancer patients, including colon adenocarcinoma (COAD), stomach adenocarcinoma (STAD), oesophageal carcinoma (ESCA), lung adenocarcinoma (LUAD), and breast invasive carcinoma (BRCA), for exosomes purification and subsequent detection of exosomal TMEM176B by NanoFCM and Sandwich ELISA (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). A small portion of TMEM176B\u003csup\u003e+\u003c/sup\u003e exosomes were detected in the plasma from almost all patients with these types of cancers but not from healthy donors, by NanoFCM (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed-e). 78.5% of COAD patients (95 out of 121), 90.9% of STAD patients (100 out of 110), 90.4% of ESCA patients (66 out of 73), 94.4% of LUAD patients (102 out of 108), 92.3% of BRCA patients (36 out of 39), showed significantly higher percentages of TMEM176B\u003csup\u003e+\u003c/sup\u003e circulating exosomes than healthy donors. Likewise, the protein levels of TMEM176B on the circulating exosomes were significantly higher in these cancer patients than in healthy donors, as revealed by ELISA (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eg-h). TMEM176B\u003csup\u003e+\u003c/sup\u003e circulating exosomes were already present in the plasma of patients with early stages (Ⅰ) of tumors and their frequencies were comparable with those in the plasma of patients with late stages (Ⅳ) of tumors (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ef). Moreover, the frequencies of TMEM176B\u003csup\u003e+\u003c/sup\u003e circulating exosomes were substantially reduced in cancer patients after surgical resection of cancerous tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eg), indicating that these TMEM176B\u003csup\u003e+\u003c/sup\u003e circulating exosomes mainly arose from cancerous tissues. To determine the prognostic relevance of TMEM176B\u003csup\u003e+\u003c/sup\u003e circulating exosomes in cancers, patients bearing LUAD, STAD, COAD or ESCA with complete follow-up information were dichotomized into high- versus low- groups on the basis of a median split of frequencies of TMEM176B\u003csup\u003e+\u003c/sup\u003e circulating exosomes. Apparently, LUAD patients with a high frequency of TMEM176B\u003csup\u003e+\u003c/sup\u003e circulating exosomes had significantly shorter overall survival than those with a low frequency of TMEM176B\u003csup\u003e+\u003c/sup\u003e circulating exosomes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eh). This correlation was not significant in other types of cancer patients probably due to the limited numbers of patients with complete follow-up information (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eh). Furthermore, the pre-treatment level of TMEM176B\u003csup\u003e+\u003c/sup\u003e circulating exosomes was significantly higher in blood of patients who had weaker response to the anti-PD1 treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ei). Thus, these data consolidate that circulating exosomal TMEM176B can serve as a non-invasive biomarker for detection of multiple types of early cancers, like GPC1 for pancreatic cancer\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e, and for prediction of reponse to anti-PD1 therapy.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTDEs facilitate tumor progression via immunosuppressive TME\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAlthough TDEs play an immunogenic role by transferring a number of immunostimulatory factors including tumor antigens\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e, TDEs have also been shown to promote immunosuppressive TME\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. To examine the overall role of TDEs in tumor progression, we deleted \u003cem\u003eRab27a\u003c/em\u003e, that is required for the secretion of exosomes\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e, in B16F10 melanoma cells, using CRISPR-Cas9-mediated mutagenesis. When \u003cem\u003eRab27a\u003c/em\u003e-deficient cells were subcutaneously injected into syngeneic immunocompetent C57BL/6J mice, their abilities to form tumors were significantly attenuated, compared to B16F10 cells transduced with scramble single guide RNA (Scramble sgRNA), consistent with previous report (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea)\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Meanwhile, deletion of \u003cem\u003eRab27a\u003c/em\u003e in B16F10 cells dramatically extended the survival of tumor-bearing mice (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). As Rab27a controls both exosomes secretion and secretory vesicle exocytosis, it could promote tumor progression through both exosome-dependent and -independent mechanisms\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. To directly evaluate the effect of TDEs in tumor growth, we then subcutaneously injected B16F10 or MC38 cells together with extra purified syngeneic TDEs into C57BL/6J mice. In both tumor models, co-inoculation of syngeneic TDEs significantly accelerated tumor growth and shortened host survival (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec-f). Together, these results suggest that the overall effect of TDEs is to strongly promote tumor growth.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo examine the effect of TDEs on the tumor immune microenvironment (TIME), we performed single-cell RNA-sequencing (scRNA-seq) analysis of intratumoral CD45\u003csup\u003e+\u003c/sup\u003e immune cells from B16F10 tumors of C57BL/6J mice co-inoculated with or without extra purified B16F10-derived exosomes, using 10\u0026times; Genomics platform. Unsupervised clustering led to identification of 15 unique cell populations, including αβ T cells, γδ T cells, natural killer T cells (NKT), B cells, macrophages, monocytes, neutrophils, dendritic cells (DC),, natural killer cells (NK), and innate lymphoid cells (ILC) (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eg-h and Supplementary Table\u0026nbsp;3). Co-inoculation of syngeneic TDEs strongly expanded B cells with higher activity score for immune inhibitory signature genes as well as immunosuppressive subpopulations within macrophages (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ei-m)\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. By contrast, some immune-stimulatory cell populations, including ILC1, ILC3, CD8\u003csup\u003e+\u003c/sup\u003e T cells and CD4\u003csup\u003e+\u003c/sup\u003e T cells, decreased in B16F10 tumors co-inoculated with syngeneic TDEs (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eg-h). Within CD8\u003csup\u003e+\u003c/sup\u003e T cells, scRNA-seq analysis revealed reduction in the abundance of intermediately exhausted, exhausted effector, innate-like and interferon-stimulated CD8\u003csup\u003e+\u003c/sup\u003e T cells, with a concomitant increase in naive/central memory-like and memory-like CD8\u003csup\u003e+\u003c/sup\u003e T cell subsets\u003csup\u003e\u003cspan additionalcitationids=\"CR48 CR49\" citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e, in B16F10 tumors co-inoculated with syngeneic TDEs (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea-b). Correspondingly, co-inoculation of syngeneic TDEs resulted in lower activity scores for gene signatures related to early activation, exhaustion and effector/cytokine signaling of intratumoral CD8\u003csup\u003e+\u003c/sup\u003e T cells (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec and Supplementary Table\u0026nbsp;3). These results suggested that TDEs had a global impact on most of immune cells in the TME, consistent with previous reports. However, the pro-tumoral effect of TDEs, was completely dependent on CD8\u003csup\u003e+\u003c/sup\u003e T cells, as it was still observed in \u003cem\u003eIgh-j\u003c/em\u003e\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e\u003cem\u003eIgk\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u0026minus;/\u0026minus;\u003c/em\u003e\u003c/sup\u003e (B cell deficient, BCD) mice (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed), but not in other immunodeficient mice including \u003cem\u003eRag1\u003c/em\u003e\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e (lacking mature T and B cells) and \u003cem\u003eCD8a\u003c/em\u003e\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e (lacking CD8\u003csup\u003e+\u003c/sup\u003e T cells) (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee-h). Taken together, these results suggest that TDEs suppress CD8\u003csup\u003e+\u003c/sup\u003e T cell function directly and indirectly through other immune cells in the TME.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWe next further analyzed tumor-infiltrating T cells using flow cytometry. In line with the results of scRNA-seq analysis, co-inoculation of extra syngeneic TDEs resulted in a remarkable decrease in total CD8\u003csup\u003e+\u003c/sup\u003e T cells, CD44\u003csup\u003e+\u003c/sup\u003eCD62L\u003csup\u003e\u0026minus;\u003c/sup\u003e effector and PD1\u003csup\u003e+\u003c/sup\u003eTim3\u003csup\u003e+\u003c/sup\u003e terminally exhausted CD8\u003csup\u003e+\u003c/sup\u003e T subsets in both B16F10 and MC38 tumor models (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea-d). Accordingly, the production of effector cytokines in CD8\u003csup\u003e+\u003c/sup\u003e T cells, including IFN-γ, TNF-α and Granzyme B, was also dramatically impaired in both types of tumors co-inoculated with syngeneic TDEs (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ee-h). Interestingly, the frequencies of both CD4\u003csup\u003e+\u003c/sup\u003e T cells and CD8\u003csup\u003e+\u003c/sup\u003e T cells were significantly lower in the tumor-draining lymph nodes (TdLN) of MC38-bearing mice with co-inoculation of syngeneic TDEs than in the counterparts without co-inoculation of TDEs (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ei-j). Therefore, these data demonstrate that TDEs suppress CD8\u003csup\u003e+\u003c/sup\u003e T cell activity in both TME and TdLN.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eTmem176b on TDEs directly suppressed T cell early activation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eGiven that the early activation of intratumoral CD8\u003csup\u003e+\u003c/sup\u003e T cells was inhibited by co-inoculation of syngeneic TDEs (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec), we next investigated whether TDEs directly obstructs T cell early activation, as the failure in the priming and activation of T cells is one of the major mechanisms of tumor-intrinsic resistance to ICB therapy\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. To address this, we treated naive T cells with or without B16F10-derived exosomes before or 24 hours after \u003cem\u003ein-vitro\u003c/em\u003e stimulation with anti-CD3 and anti-CD28 antibodies (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea). Treatment of TDEs before stimulation significantly inhibited proliferation and early activation of CD8\u003csup\u003e+\u003c/sup\u003e T cells in a dose-dependent manner, as demonstrated by the decreased proportion of cells containing diluted carboxyfluorescein diacetate succinimidyl ester (CFSE), the decreased cell numbers (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb-c), and the reduced expression of T cell activation markers (CD25, CD69, CD71, CD44) (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ed). In contrast, TDEs treatment after stimulation scarcely affected CD8\u003csup\u003e+\u003c/sup\u003e T cell proliferation (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb-c). Likewise, treatment of TDEs before but not after stimulation caused a significant but milder reduction in early activation and proliferation of CD4\u003csup\u003e+\u003c/sup\u003e T cells (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ee-g). Thus, these findings suggest that TDEs directly suppress early activation and proliferation of CD8\u003csup\u003e+\u003c/sup\u003e T cells.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn order to identify the key molecules that mediate suppression of T cell activation by TDEs, we selected dozens of candidate genes including \u003cem\u003eTmem176b\u003c/em\u003e that encode proteins more than two-fold enriched in B16F10-derived exosomes (Supplementary Table\u0026nbsp;1), which were identified in aforementioned proteomic profiling of TDEs by mass spectrometry, to construct sgRNA-expressing lentiviral vectors (Supplementary Table\u0026nbsp;4). B16F10 cells were individually infected with lentiviruses containing sgRNA to generate candidate gene knockout B16F10 cell lines. we then performed a small-scale CRISPR-Cas9 arrayed screen using an \u003cem\u003ein-vitro\u003c/em\u003e T cell activation system, in which na\u0026iuml;ve CD8\u003csup\u003e+\u003c/sup\u003e T cells were treated with or without B16F10-derived exosomes in the presence of anti-CD3 and anti-CD28 antibodies. We measured protein levels of early activation markers (CD25, CD69, CD71 and PD1) of T cells by flow cytometry as functional readouts. Pretreatment of exosomes from wild-type (WT) or scramble sgRNA-transduced B16F10 cells significantly inhibited early activation of CD8\u003csup\u003e+\u003c/sup\u003e T cells, while vehicle treatment or pretreatment of exosomes from non-malignant fibroblast NIH3T3 cells did not suppress the early activation (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eh). The suppression of T cell activation by exosomes from B16F10 cells was unleashed by two independent sgRNAs for \u003cem\u003eTmem176b\u003c/em\u003e (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eh). By contrast, exosomes from B16F10 cells transduced with sgRNA for \u003cem\u003eCd274\u003c/em\u003e (encoding PD-L1) still maintained the capability to suppress T cell activation (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eh), suggesting that this suppression was not mediated by the PD1/PD-L1 checkpoint, as na\u0026iuml;ve CD8\u003csup\u003e+\u003c/sup\u003e T cells do not express PD1. Thus, Tmem176b appear to be a key mediator of suppression of T cell early activation by TDEs .\u003c/p\u003e\u003cp\u003e\u003cb\u003eGenetic ablation of Tmem176b in cancer cells inhibits tumor growth\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo assess the effects of Tmem176b on tumor growth, we generated monoclonal mouse malignant cancer cell lines (B16F10 and MC38) lacking \u003cem\u003eTmem176b\u003c/em\u003e by CRISPR-Cas9 technology, using three different sgRNAs (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ei). On the one hand, deletion of Tmem176b did not significantly affect the \u003cem\u003ein-vitro\u003c/em\u003e growth rate and the exosome secretion of cancer cells (Extended Data Fig.\u0026nbsp;7a-b). On the other hand, neither the nanoscale and morphology, nor the protein composition of exosomes including the exosome markers and protein cargoes directly involved in immune signaling, was altered by \u003cem\u003eTmem176b\u003c/em\u003e deficiency (Extended Data Fig.\u0026nbsp;7c-f and Supplementary Table\u0026nbsp;5). After inoculation into syngeneic C57BL/6J hosts, all the strains of \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 cells exhibited much slower tumor growth and all the strains of \u003cem\u003eTmem176b\u003c/em\u003e-deficient MC38 cells hardly formed tumors, compared to the corresponding scramble cancer cells; Meanwhile, deletion of \u003cem\u003eTmem176b\u003c/em\u003e in both B16F10 and MC38 cells largely extended the survival of tumor-bearing mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea-d). In pulmonary metastasis model of intravenous injection of B16F10 cells, which seed the lung with tumors, deletion of Tmem176b in B16F10 cells greatly reduced the numbers of lung metastases (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee-f). Furthermore, reintroducing \u003cem\u003eTmem176b\u003c/em\u003e into \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 and MC38 cells completely restored the tumor progression, thereby excluding the possibility that CRISPR-Cas9-mediated off-target mutagenesis might be responsible for the delayed tumor growth (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eg-j). Consistent with the previous study\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e, when B16F10 cells were inoculated into germline \u003cem\u003eTmem176b\u003c/em\u003e\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice, dendritic cell-specific \u003cem\u003eTmem176b\u003c/em\u003e-deficient and \u003cem\u003eTmem176a/b\u003c/em\u003e-deficient mice (\u003cem\u003eTmem176b\u003c/em\u003e \u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e CD11c-Cre, \u003cem\u003eTmem176a/b\u003c/em\u003e \u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e CD11c-Cre, called Tmem176b-dcKO, Tmem176a/b-dcKO here, respectively) on pure C57BL/6J background, the growth of tumors was comparable to that in WT mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ek-l and Extended Data Fig.\u0026nbsp;7g). Therefore, tumor-derived Tmem176b, rather than host Tmem176b facilitates tumor progression.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTumor-derived exosomal Tmem176b facilitates tumor growth\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo examine whether the pro-tumoral effect of Tmem176b was mediated by TDEs, when \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 or MC38 cells were inoculated into C57BL/6J mice, extra syngeneic TDEs were supplemented, either by co-inoculation with cancer cells, or by independent intravenous (tail vein) injection. Exogenous introduction of exosomes from WT rather than \u003cem\u003eTmem176b\u003c/em\u003e-deficient cancer cells by both approaches, accelerated growth of \u003cem\u003eTmem176b\u003c/em\u003e-deficient tumors in both tumor models (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003em-o). Exosomes from tumor at one site can potentially influence tumor growth at distant sites, by the travel of their own or immune cells educated at the same sites, throughout the body\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. We next asked whether exosomal Tmem176b secreted by WT cancer cells promote growth of the cancer cells at a distant site, or whether immune cells activated by \u003cem\u003eTmem176b\u003c/em\u003e-deficient cancer cells suppress growth of the cancer cells at a distant site. To this end, WT MC38 cells were co-injected in the right flank of each C57BL/6J mouse with Scramble, or \u003cem\u003eTmem176b\u003c/em\u003e-deficient, or \u003cem\u003eRab27a\u003c/em\u003e-deficient MC38 cells in the left flank (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ep). Remarkably, WT MC38 cells on the right flank that were co-injected with Scramble cells in the left flank grew much faster than WT cells injected alone in the right flank. In contrast, co-injection of \u003cem\u003eTmem176b\u003c/em\u003e-deficient or \u003cem\u003eRab27a\u003c/em\u003e-deficient MC38 cells in the left flank significantly delayed the growth of WT MC38 cell in the right flank (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eq). Taken together, these findings strongly supported the notion that Tmem176b acts on TDEs to accelerate the growth of tumors at both local and distant sites.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTmem176b ablation in tumors remodels the TME\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTDEs that are released into TME and body fluids can be taken up by recipient cells through fusion with the plasma membrane, or through endocytosis\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. To visualize the transfer of Tmem176b from tumor cells to the recipient cells, we injected B16F10 or MC38 cells that stably express Tmem176b-GFP fusion protein into C57BL/6J mice. Flow cytometry analysis of tumor-infiltrating immune cells showed that Tmem176b accumulated in all types of immune cells tested, including T cells, B cells and conventional dendritic cells (cDCs), with the highest frequency and density in cDCs (Extended Data Fig.\u0026nbsp;8a-b). The transfer of Tmem176b was completely dependent on Rab27a, as it was eliminated when Rab27a was deleted in tumor cells (Extended Data Fig.\u0026nbsp;8c-d). Although cDCs have strong capacity to uptake TDEs, the absence of Tmem176b on TDEs did not enhance cross-presentation in type 1 cDCs (cDC1s) (Extended Data Fig.\u0026nbsp;8e).\u003c/p\u003e\u003cp\u003eTo determine the involvement of the immune system, we inoculated \u003cem\u003eTmem176b\u003c/em\u003e-deficient or Scramble B16F10 and MC38 cancer cells into \u003cem\u003eRag1\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u0026minus;/\u003c/em\u003e\u0026minus;\u003c/sup\u003e (no mature T and B cells), \u003cem\u003eTcrb\u003c/em\u003e\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e\u003cem\u003eTcrd\u003c/em\u003e\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e (T cell deficient, TCD), or \u003cem\u003eCD8a\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u0026minus;/\u0026minus;\u003c/em\u003e\u003c/sup\u003e (no CD8\u003csup\u003e+\u003c/sup\u003e T cells) mice. Our results demonstrated that Tmem176b deficiency had no effect on tumor growth in these immunodeficient mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea-d), suggesting that the increased growth control of \u003cem\u003eTmem176b\u003c/em\u003e-deficient tumors was mainly mediated by CD8\u003csup\u003e+\u003c/sup\u003e T cells. We next sought to investigate the cellular consequence of Tmem176b deficiency on TIME. To this end, we profiled intratumoral CD45\u003csup\u003e+\u003c/sup\u003e immune cells from mice bearing scramble or \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 tumors, using scRNA-seq.\u0026nbsp;Unsupervised clustering analysis revealed few pronounced variations in most of cell populations (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee-g and Supplementary Table\u0026nbsp;3). The proportions of CD8\u003csup\u003e+\u003c/sup\u003e T cells and non-MDSC neutrophils were greatly increased (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee-g and Extended Data Fig.\u0026nbsp;8f-g)\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e,\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e, with a concomitant increase in all subsets of CD8\u003csup\u003e+\u003c/sup\u003e T cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eh-i), whereas ILC1, ILC3 and monocytes were mildly decreased in \u003cem\u003eTmem176b\u003c/em\u003e-deficient tumors relative to scramble tumors (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee-g). The increased infiltration of CD8\u003csup\u003e+\u003c/sup\u003e T cells in \u003cem\u003eTmem176b\u003c/em\u003e-deficient MC38 tumors was also observed by immunofluorescence staining (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ej-k). Therefore, unlike the global effects of TDEs on TIME, the most affected population by Tmem176b ablation is CD8\u003csup\u003e+\u003c/sup\u003e T cells. Furthermore, the loss of increased growth control of \u003cem\u003eTmem176b\u003c/em\u003e-deficient tumors in \u003cem\u003eRag1\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u0026minus;/\u003c/em\u003e\u0026minus;\u003c/sup\u003e mice was restored by adoptive transfer of antigen-specific P14 CD8\u003csup\u003e+\u003c/sup\u003e T cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003el), confirming that the increased growth control of \u003cem\u003eTmem176b\u003c/em\u003e-deficient tumors was due to the enhanced antitumor CD8\u003csup\u003e+\u003c/sup\u003e T cell immunity.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTmem176b deficiency in tumors enhances antitumor CD8\u003c/b\u003e\u003csup\u003e\u003cb\u003e+\u003c/b\u003e\u003c/sup\u003e \u003cb\u003eT cell immunity\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe next performed flow cytometry to validate the difference of intratumoral T cells in scramble and \u003cem\u003eTmem176b\u003c/em\u003e-deficient tumors. In accord with the results of scRNA-seq analysis, flow cytometry analysis also demonstrated a marked increase in CD8\u003csup\u003e+\u003c/sup\u003e T cells, CD44\u003csup\u003e+\u003c/sup\u003eCD62L\u003csup\u003e\u0026minus;\u003c/sup\u003e effector and PD1\u003csup\u003e+\u003c/sup\u003eTim3\u003csup\u003e+\u003c/sup\u003e terminally exhausted CD8\u003csup\u003e+\u003c/sup\u003e T subsets, and a mild increase in those of CD4\u003csup\u003e+\u003c/sup\u003e T cells in \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 and MC38 tumors relative to scramble tumors (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea-b and Extended Data Fig.\u0026nbsp;9a-b). Correspondingly, both the percentages and numbers of IFN-γ- and TNF-α-producing CD8\u003csup\u003e+\u003c/sup\u003e T cells were dramatically increased in \u003cem\u003eTmem176b\u003c/em\u003e-deficient tumors, while the production of such cytokines in CD4\u003csup\u003e+\u003c/sup\u003e T cells was slightly enhanced (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec-d and Extended Data Fig.\u0026nbsp;9c-d). Furthermore, the frequencies of both CD4\u003csup\u003e+\u003c/sup\u003e T cells and CD8\u003csup\u003e+\u003c/sup\u003e T cells were significantly higher in the TdLN of mice bearing \u003cem\u003eTmem176b\u003c/em\u003e-deficient MC38 tumors than in counterparts of scramble MC38 tumors (Extended Data Fig.\u0026nbsp;9e-f). Not only the increased numbers and activities of effector CD8\u003csup\u003e+\u003c/sup\u003e T cells in \u003cem\u003eTmem176b\u003c/em\u003e-deficient tumors (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee-f and Extended Data Fig.\u0026nbsp;9g-l), but also the higher frequencies of T cells in the corresponding TdLN (Extended Data Fig.\u0026nbsp;9m-n), were repressed by re-expression of Tmem176b in \u003cem\u003eTmem176b\u003c/em\u003e-deficient cancer cells, thereby further confirming the on-target effect of CRISPR-Cas9-mediated \u003cem\u003eTmem176b\u003c/em\u003e gene deletion on the antitumor T cell immunity. We next asked whether exogenously introduced exosomal Tmem176b could suppress the antitumor T cell immunity. Co-inoculation of syngeneic exosomes from WT rather than \u003cem\u003eTmem176b\u003c/em\u003e-deficient cancer cells reduced CD8\u003csup\u003e+\u003c/sup\u003e T cells, CD44\u003csup\u003e+\u003c/sup\u003eCD62L\u003csup\u003e\u0026minus;\u003c/sup\u003e effector and PD1\u003csup\u003e+\u003c/sup\u003eTim3\u003csup\u003e+\u003c/sup\u003e terminally exhausted CD8\u003csup\u003e+\u003c/sup\u003e T subsets, and their cytokine-producing capacities in \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 and MC38 tumors (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eg-h and Extended Data Fig.\u0026nbsp;10a-f). Correspondingly, the higher frequencies of T cells in the TdLN of mice bearing \u003cem\u003eTmem176b\u003c/em\u003e-deficient MC38 tumors were also suppressed by co-inoculation of syngeneic exosomes from WT rather than \u003cem\u003eTmem176b\u003c/em\u003e-deficient MC38 cells (Extended Data Fig.\u0026nbsp;10g-h). These results further confirmed that TDEs are functioning through Tmem176b to suppress antitumor T cell response and thus facilitate tumor growth.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTumor-derived exosomal Tmem176b attenuates proximal TCR signaling\u003c/b\u003e\u003c/p\u003e\u003cp\u003eConsistent with the finding that TDEs are functioning through Tmem176b to suppress antitumor T cell response (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), we identified tumor-derived exosomal Tmem176b as a negative regulator of T cell early activation in the aforementioned small-scale CRISPR-Cas9 arrayed \u003cem\u003ein-vitro\u003c/em\u003e T cell activation screen (Extended Data Fig.\u0026nbsp;10h). The inhibitory role of tumor-derived exosomal Tmem176b on T cell early activation was further confirmed using exosomes purified from monoclonal \u003cem\u003eTmem176b\u003c/em\u003e knockout (T8KO) murine cancer cells (B16F10 and MC38) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea-b). More importantly, this function of Tmem176b is conserved between mouse and human, because treatment of exosomes from human cancer cells (HeLa and SW480) substantially inhibited early activation of human primary T cells while treatment of exosomes from monoclonal \u003cem\u003eTMEM176B\u003c/em\u003e knockout (T176B-KO) human cancer cells failed (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec-d). We next sought to test whether tumor-derived exosomal Tmem176b could affect TCR signaling, which is responsible for T cell activation and proliferation. To this end, we treated naive T cells with or without exosomes from \u003cem\u003eTmem176b\u003c/em\u003e-deficient (T8KO) or \u003cem\u003eTmem176b\u003c/em\u003e-overexpressed (T-OE) B16F10 cells, followed by stimulation with anti-CD3 antibodies. Notably, after stimulation with TCR, phosphorylation of proximal TCR signaling components (including PLC-γ1, SLP76, LAT) was markedly compromised in response to treatment of exosomes from \u003cem\u003eTmem176b\u003c/em\u003e-overexpressed B16F10 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ee). By contrast, treatment of exosomes from \u003cem\u003eTmem176b\u003c/em\u003e-deficient cells failed to attenuate these proximal TCR signaling events (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ee). Therefore, these results suggested that tumor-derived exosomal Tmem176b inhibits T cell early activation by attenuating proximal TCR signaling.\u003c/p\u003e\u003cp\u003eTo delineate the molecular mechanism by which tumor-derived exosomal Tmem176b attenuates TCR signaling and suppresses early T cell activation, we used a proteomics approach to identify binding partners of Tmem176b in mouse T cell lymphoma EL4 cells before and after TCR stimulation. Mass spectrometry of immunocomplexes purified by affinity chromatography of Flag-tagged Tmem176b stably expressed in EL4 cells, identified 357 and 346 proteins associated with Tmem176b before or after TCR stimulation respectively, including proteins involved in the regulation of T cell activation and TCR signaling, in addition to proteins involved in vesicle transport (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ef and Supplementary Table\u0026nbsp;6). Among these, LAT and non-receptor protein tyrosine phosphatase Shp1 were the most noteworthy, because LAT is the core of TCR signalsome to transduce antigenic signaling and Shp1 is thought to have a predominantly, if not exclusively, inhibitory role in TCR signaling\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. Co-immunoprecipitation assay confirmed the interaction between Flag-tagged Tmem176b and endogenous Shp1 or LAT in EL4 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eg-h). Deletion mapping of Tmem176b showed that the absence of the C-terminus (amino acids 218\u0026ndash;263) and, in particular, of amino acids 218\u0026ndash;227, completely abolished the binding to Shp1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ei-j). In contrast, deletion of N-terminus of Tmem176b, which contains an ITIM motif, did not reduce the binding to Shp1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ei-j). Deletion of either side of the large loop of Tmem176b showed almost complete loss of binding to LAT (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ek). To demonstrate the functional importance of the Shp1 binding region of Tmem176b, we reintroduced WT or mutant Tmem176b (with a deletion of amino acids 218\u0026ndash;227, called TΔ218\u0026ndash;227) into \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 cells. In tumor growth experiments, reintroduction of WT Tmem176b (T-OE) restored tumor growth rate of \u003cem\u003eTmem176b\u003c/em\u003e-deficient cells to the levels of scramble tumor cells, while that of mutant Tmem176b (TΔ218-227-OE) had no effect (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003el).\u003c/p\u003e\u003cp\u003eTo understand how tumor-derived exosomal Tmem176b attenuates proximal TCR signaling by recruiting Shp1, we next sought to examine its subcellular localization in CD8\u003csup\u003e+\u003c/sup\u003e T cells by immunofluorescence staining. When na\u0026iuml;ve CD8\u003csup\u003e+\u003c/sup\u003e T cells were incubated with Tmem176b-GFP-carrying B16F10 exosomes labeled with a self-quenched probe, octadecyl rhodamine B chloride (R18), fluorescence was triggered and colocalized with Tmem176b, suggesting that B16F10 exosomes fused with plasma membranes of na\u0026iuml;ve CD8\u003csup\u003e+\u003c/sup\u003e T cells and that exosomal Tmem176b was delivered to T cell plasma membranes (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003em). After stimulation with cognate peptide-pulsed B cells, tumor-derived exosomal Tmem176b accumulated at the immunological synapse of CD8\u003csup\u003e+\u003c/sup\u003e T cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003en). Moreover, pretreatment of na\u0026iuml;ve CD8\u003csup\u003e+\u003c/sup\u003e T cell with Tmem176b-carrying TDEs led to more recruitment of Shp1 to the immunological synapse of CD8\u003csup\u003e+\u003c/sup\u003e T cells after conjugation with peptide-pulsed B cells. By contrast, in T cell-B cell conjugates without TDEs pretreatment, Shp1 was more diffusely spread out of the immunological synapse (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003en-o).\u003c/p\u003e\u003cp\u003eWe then investigated whether inhibition of antitumor T cell immunity by tumor-derived Tmem176b was mediated by Shp1. To address this, we inoculated Scramble or \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 or MC38 cells subcutaneously into WT or T cell-specific Shp1 conditional knockout mice (\u003cem\u003ePtpn6\u003c/em\u003e \u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e dLck-Cre, called Shp1-tKO here). In both tumor models, \u003cem\u003eTmem176b\u003c/em\u003e-deficient tumors grew much slower than Scramble tumors in WT mice. Ablation of Shp1 in T cells markedly restrained the growth of Scramble tumors, but deletion of Tmem176b in tumor cells did not further improve tumor control in Shp1-tKO mice, suggesting Shp1 was required for inhibition of T cell activity by Tmem176b (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ep-q). Together, these data demonstrated that tumor-derived exosomal Tmem176b attenuates TCR signaling by recruiting Shp1 to the immunological synapse of T cells via LAT and thus suppresses antitumor T cell immunity.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTmem176b blockade restrains tumor growth\u003c/b\u003e\u003c/p\u003e\u003cp\u003eGiven that the region of amino acids 218\u0026ndash;227 in C terminus of Tmem176b was responsible for the interaction between Tmem176b and Shp1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ei-j), we generated a cell-permeable competitive peptide by fusing cell-penetrating peptide with amino acids 218\u0026ndash;232 of Tmem176b (called CPP-Pep hereinafter). Addition of CPP-Pep to the cell culture significantly disrupted the interaction between Tmem176b and Shp1 in EL4 cells (Extended Data Fig.\u0026nbsp;11a). After treating EL4 cells with the CPP-Pep, immunofluorescence staining showed that the CPP-Pep co-localized with Shp1 in the cytoplasm of EL4 cells (Extended Data Fig.\u0026nbsp;11b). To examine the effect of CPP-Pep on the inhibition of T cell early activation by TDEs, we treated na\u0026iuml;ve CD8\u003csup\u003e+\u003c/sup\u003e T cells with B16F10 exosomes plus CPP-Pep or Scramble peptide (Cpp-Scr), in the presence of anti-CD3 and anti-CD28 antibodies. CPP-Pep addition significantly enhanced early activation of CD8\u003csup\u003e+\u003c/sup\u003e T cells, suggesting that the inhibitory effect of TDEs on T cells was relieved (Extended Data Fig.\u0026nbsp;11c). We next sought to evaluate the therapeutic effect of CPP-Pep on tumor growth in immunocompetent mice. We administrated B16F10 tumor-bearing C57BL/6J mice with CPP-Pep via twice intraperitoneal injection after tumor size reaching about 200 mm\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Consistent with the observed growth retardation of \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 tumors, CPP-Pep administration resulted in significant tumor rejection and host survival extension compared with Scramble and vehicle treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea-b). Similar results were obtained in MC38 tumor models, in which triple intraperitoneal injection of CPP-Pep strongly delayed tumor growth and prolonged animal survival (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ec-d). We then tested the efficacy of CPP-Pep in lung metastasis models. CPP-Pep administration at day 3 post injection, substantially reduced the numbers of lung metastases, compared to Scramble and vehicle treatment (Extended Data Fig.\u0026nbsp;11d-e).\u003c/p\u003e\u003cp\u003eAs tumor-derived exosomal Tmem176b recruited Shp1 in CD8\u003csup\u003e+\u003c/sup\u003e T cells though its C-terminus (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ei-j), we speculated that the large loop of Tmem176b could be exposed in the extracellular space of CD8\u003csup\u003e+\u003c/sup\u003e T cells when Tmem176b-carrying TDEs fuse with CD8\u003csup\u003e+\u003c/sup\u003e T cells. We screened high-affinity neutralizing antibodies against the large loop of murine Tmem176b or human TMEM176B using \u003cem\u003ein vitro\u003c/em\u003e T cell activation system, since the large loop of Tmem176b is responsible for its binding to LAT (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ek). Like CPP-Pep treatment, addition of monoclonal antibody (6E8) against Tmem176b to CD8\u003csup\u003e+\u003c/sup\u003e T cell culture abrogated B16F10-derived exosomes-induced attenuation of CD8\u003csup\u003e+\u003c/sup\u003e T cell activation (Extended Data Fig.\u0026nbsp;11c). Similarly, addition of monoclonal antibody against human TMEM176B (2F2) also abolished the suppression of human T cell activation by exosomes from human cancer cells (HeLa and SW480) (Extended Data Fig.\u0026nbsp;11f). Triple intraperitoneal administration of anti-Tmem176b (6E8) antibody into B16F10-bearing C57BL/6J mice markedly inhibited tumor growth and extended host survival (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ee-f). Moreover, we observed analogous tumor rejection and animal survival extension in MC38-bearing mice after 6E8 treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eg-h). Furthermore, 6E8 treatment had no effect on the growth of \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 tumors (Extended Data Fig.\u0026nbsp;11g), indicating that tumor-derived Tmem176b, instead of host Tmem176b, is the real target of 6E8. Given the normal tumor growth in \u003cem\u003eTmem176b\u003c/em\u003e\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e and dendritic cell-specific \u003cem\u003eTmem176b\u003c/em\u003e-deficient mice, these data further confirmed that tumor-drived Tmem176b, rather than host Tmem176b, facilitates tumor progression.\u003c/p\u003e\u003cp\u003eWe then further evaluate the antitumor effects of Tmem176b blockade in Hepa1-6 orthotopic mouse model, in which mouse hepatocellular carcinoma Hepa1-6 cells were orthotopically implanted in the livers of C57BL/6J mice. Triple intraperitoneal administration of either CPP-Pep or 6E8 significantly inhibited tumor growth as tumor volumes were dramatically reduced, compared with vehicle treatment or CPP-Scr treatment (Extended Data Fig.\u0026nbsp;11h-i). Collectively, these findings demonstrate that Tmem176b blockade is therapeutically effective in tumor rejection in both heterotopic and orthotopic transplanted tumor models.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSynergy with anti-PD1/PD-L1 therapy\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePD1 is expressed after T cell activation and acts as a brake for the function of activated T cells\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e. Our study demonstrated that tumor-derived exosomal Tmem176b is a negative regulator in proximal TCR signaling and T cell early activation. PD1\u003csup\u003e+\u003c/sup\u003eTim3\u003csup\u003e+\u003c/sup\u003e terminally exhausted CD8\u003csup\u003e+\u003c/sup\u003e T cells were significantly increased in \u003cem\u003eTmem176b\u003c/em\u003e-deficient tumors compared with Scramble tumors (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea-b, g and Extended Data Fig.\u0026nbsp;10a,c-d). This prompted us to test whether Tmem176b blockade may have a synergistic effect with anti-PD1 therapy. B16F10 melanoma is a low immunogenic tumor model that poorly responds to anti-PD1/PD-L1 therapy. Administration of anti-PD1 antibody into B16F10-bearing C57BL/6J mice only slightly reduced tumor growth with lower efficacy than that of CPP-Pep administration. However, administration of CPP-Pep in combination with treatment with anti-PD1 exhibited stronger capability to inhibit tumor growth and to extend host survival than either single treatment did, suggesting that CPP-Pep has a synergistic antitumor effect with anti-PD1 therapy (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ei-j). MC38 is a highly immunogenic colon carcinoma model. Notably, treating MC38-bearing C57BL/6J mice with anti-PD1 antibody substantially delay tumor growth, although its efficacy is lower than CPP-Pep treatment. Combination of PD1 blockade with CPP-Pep treatment had an additive effect, resulting in more rapid tumor rejection and longer survival extension in MC38 bearing mice than either treatment alone (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ek-l). We next examined whether the observed synergy between Tmem176b competitive peptide (CPP-Pep) and anti-PD1 antibody treatment could be recapitulated by using Tmem176b neutralizing antibody 6E8. Similar to CPP-Pep treatment, 6E8 administration alone was already more efficient in tumor growth control than anti-PD1 therapy, in both B16F10 and MC38 tumor models (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003em-p). Furthermore, the efficacies of single treatments were enhanced significantly when combined 6E8 treatment with anti-PD1 antibody, with much longer extension of host survival (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003em-p). We then applied monoclonal antibody against human TMEM176B (2F2) to humanized mice models. Immunodeficient NCG mice were transplanted with human hematopoietic stem cells (HSCs) to generate huHSC-NCG mice, followed by inoculation with A375 human melanoma cells. We then administrated these A375-bearing huHSC-NCG mice with anti-TMEM176B (2F2) antibody or anti-PD-L1 antibody (atezolizumab) alone, or their combination, via intraperitoneal injection after tumor size reaching about 200 mm\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eq). Anti-TMEM176B treatment showed remarkable tumor growth inhibition and host survival extension, with significant superiority over anti-PD-L1 antibody treatment, whereas the combination treatment had a large synergistic effect, with a higher level of tumor rejection and host survival extension than either single treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003er-s). Taken together, these data suggest TMEM176B blockade could be a promising strategy to boost the therapeutic efficacy of ICB therapy in human cancer treatment.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTDEs have been not only implicated in immunosuppression and tumor progression, but also considered as multiparameter biomarker platforms of liquid biopsy for cancer diagnosis and prognosis. However, a reliable target on TDEs that can be used for both liquid biopsy and immunotherapy is still lacking. In this study, we identified TMEM176B\u003csup\u003e+\u003c/sup\u003e circulating exosomes in the plasma from various types of patients with early- and late-stage cancer but not from healthy subjects, whose levels negatively correlated with patient survival and clinical outcomes of anti-PD1 therapy. We have also demonstrated that Tmem176b on TDEs suppressed T cell early activation and thus promoted tumor progression, which provides a promising target to overcome tumor-intrinsic resistance to immunotherapy (Extended Data Fig. 12).\u003c/p\u003e\n\u003cp\u003eEarly cancer diagnosis is critical for improving patient survival and reducing mortality rates. However, routine imaging tests would be prohibitively expensive and have low sensitivity and specificity, and the utility of tissue biopsies is limited by the requirement that the tumor should be surgically accessible\u003csup\u003e36,56\u003c/sup\u003e. To address these challenges, researchers have developed liquid biopsy platforms including circulating tumor cells (CTC), cell-free tumor DNA (ctDNA) and EVs. Unlike CTC and ctDNA that are typically associated with later or even more advanced disease stage, EVs are actively released by growing cells and\u0026nbsp;contain cargoes closely reflecting the cells of origin associated with health or very early stages of disease\u003csup\u003e57\u003c/sup\u003e. EVs, especially exosomes, may confer superior diagnostic and prognostic performance relative to other liquid biopsies, because the abundance and composition of circulating exosomes are usually altered in individuals with cancer. Cancer cells secrete more exosomes than their nonmalignant conterparts\u003csup\u003e29,36,58\u003c/sup\u003e, which are further enhanced by various tumor microenvironment characteristics such as hypoxia\u003csup\u003e59-61\u003c/sup\u003e. A recent study demonstrated that phosphorylation of Hrs by oncogenic signaling leads to selective loading of cargo proteins including PD-L1 to exosomes in cancer cells\u003csup\u003e30\u003c/sup\u003e. As Tmem176b was also found to interact with Hrs, highly phosphorylated Hrs in cancer cells might also help sort Tmem176b to exosomes. Consistently, TMEM176B\u003csup\u003e+\u003c/sup\u003e circulating exosomes were specifically detected in the plasma of patients with early- and late-stage cancer but not in that of healthy subjects. Furthermore, the levels of TMEM176B\u003csup\u003e+\u003c/sup\u003e circulating exosomes inversely correlated with cancer patient survival. Thus, our results suggested that TMEM176B\u003csup\u003e+\u003c/sup\u003e circulating exosomes may serve as a potential non-invasive diagnostic and screening tool to detect early cancer. As the expression of any single biomarker can be variable across individuals, combined panels of biomarkers can better reflect a disease\u0026rsquo;s multiple biological processes in the setting of cancer. For example, a five-marker panel (including LMP1, LMP2A, PD-L1, EGFR and EpCAM) of analysis on plasma EVs by NanoFCM significantly surpassed the traditional assay in discriminating\u0026nbsp;nasopharyngeal carcinoma (NPC) from both healthy donors and\u0026nbsp;nasopharyngitis (NPG) patients\u003csup\u003e62\u003c/sup\u003e. As such, combination of the pan-cancer biomarker TMEM176B and any cancer-type-specific markers may help more accurately differentiate cancer patients from healthy donors in clinical practice.\u003c/p\u003e\n\u003cp\u003eTmem176b has been originally identified as an immune regulatory cation channel in immature dendritic cells\u003csup\u003e63,64\u003c/sup\u003e. A previous study revealed that Tmem176b inhibited inflammasome activation by controlling cytosolic Ca\u003csup\u003e2+\u003c/sup\u003e in dendritic cells, and tumor growth was suppressed in \u003cem\u003eTmem176b\u003c/em\u003e-deficient mice, originally generated in 129 background and \u0026nbsp;backcrossed onto C57BL/6 background for 10 times, due to enhanced antitumor CD8\u003csup\u003e+\u003c/sup\u003e T cell immunity\u003csup\u003e65\u003c/sup\u003e. However, the role of host Tmem176b in antitumor immunity remains controversial. Two other groups failed to observe the enhanced antitumor capacity in \u003cem\u003eTmem176b\u003c/em\u003e- or \u003cem\u003eTmem176a/b\u003c/em\u003e-deficient mice in pure C57BL/6 background generated by CRISPR-Cas9 technology\u003csup\u003e41,66\u003c/sup\u003e. We also did not observe enhanced tumor control in either germline \u003cem\u003eTmem176b-\u003c/em\u003edeficient or DC-specific \u003cem\u003eTmem176b\u003c/em\u003e- or \u003cem\u003eTmem176ba/b-\u003c/em\u003edeficient mice in pure C57BL/6 background. Therefore, this discrepancy need further investigation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn patients with solid tumors, ICB nonresponders often exhibit a \u0026lsquo;immunologically cold\u0026rsquo; or \u0026lsquo;immune-desert\u0026rsquo; phenotype, characterized by the absence or exclusion of T cells in the tumor parenchyma\u003csup\u003e3\u003c/sup\u003e. Extensive endeavors are underway to turn \u0026lsquo;cold\u0026rsquo; tumors into \u0026lsquo;hot\u0026rsquo; tumors to achieve better response to immunotherapy\u003csup\u003e6\u003c/sup\u003e. Targeting tumor-intrinsic resistance has emerged as an attractive strategy to increase the response rate and efficacy of ICB therapy for cancers. Prevention of MHC-Ⅰdegradation in tumor, by inhibition of PCSK9 or autophagy, or deletion of \u0026nbsp;SUSD6/TMEM127/WWP2 inhibitory axis, enhances intratumoral infiltration of CD8\u003csup\u003e+\u003c/sup\u003e T cells, thereby sensitizing tumor to immune checkpoint blockade\u003csup\u003e13-15\u003c/sup\u003e. Genetic ablation or pharmaceutical inhibition of TBK1 or Ptpn2 in tumor enhances the response of tumor to effector cytokines, and thus increases efficacy of immunotherapy\u003csup\u003e67-69\u003c/sup\u003e. Although TDEs have been shown to modulate many types of immune cells including T cells, whether TDEs directly impede the priming, early activation and proliferation of T cells remains unclear. We presented evidence that tumor-derived exosomal Tmem176b suppressed T cell early activation by recruiting Shp1 to TCR proximal signalosome. Genetic ablation of Tmem176b increased intratumoral infiltration by both effector and exhausted CD8\u003csup\u003e+\u003c/sup\u003e T cells, thereby providing a compelling rationale for the combination of anti-PD1 antibody and Tmem176b blockade. Tmem176b normally localizes on the membrane of intracellular vesicular compartments such as endosome and Golgi, but not on the plasma membrane\u003csup\u003e41,70\u003c/sup\u003e, and is secreted via exosoms only in cancer cells. Similar to our findings, other group has reported that host Tmem176b does not promote tumor growth\u003csup\u003e41\u003c/sup\u003e. It is reasonable to speculate that therapeutic administration of monoclonal antibody against TMEM176B could have very low toxicity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn summary, our study has demonstrated that tumor-derived exosomal Tmem176b suppresses T cell early activation and facilitates tumor progression. Blocking Tmem176b exhibits potent antitumor efficacy as well as synergistic effects with immune checkpoint blockade, providing a convincing strategy for cancer immunotherapy. The selectively enrichment of TMEM176B on circulating exosomes in peripheral blood of various types of cancer patients opens a new avenue for non-invasive cancer diagnosis and prognosis, with promising clinical application.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eKey Resources Tables\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eREAGENT or RESOURCE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eSOURCE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eIDENTIFIER\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAntibodies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eClone#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.8609%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBiotin anti-mouse CD28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e37.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e102104, RRID:AB_312868\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBiotin anti-mouse CD3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e145-2C11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e100304, RRID:AB_312669\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBiotin anti-mouse CD4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eGK1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e100404, RRID:AB_312689\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBiotin anti-mouse CD5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e53-7.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e100604, RRID:AB_312732\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBiotin anti-mouse CD8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e53-6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e100704, RRID:AB_312742\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBiotin anti-mouse CD9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eMZ3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e124804, RRID:AB_2076036\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBiotin anti-mouse CD11b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eM1/70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e101204, RRID:AB_312787\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBiotin anti-mouse CD11c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eN418\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e117304,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_313772\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBiotin anti-mouse CD25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003ePC61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e102004,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_312852\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBiotin anti-mouse CD43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e1B11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e121204,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_493384\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBiotin anti-mouse CD44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eIM7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e103004,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_312955\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBiotin anti-mouse CD45R/B220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eRA3-6B2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e103204,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_312988\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBiotin anti-mouse CD93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eVIMD2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e336104,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_2076050\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBiotin anti-mouse Ly-6G/Ly-6C\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eRB6-8C5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e108404,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_313368\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBiotin anti-mouse CD105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eMJ7/18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e120404,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_961062\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBiotin anti-mouse F4/80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eBM8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e123106,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_893499\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBiotin anti-mouse TCRg/d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eGL3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e118103,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_313827\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBiotin anti-mouse NK-1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003ePK136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e108704,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:\u0026nbsp;AB_313390\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBiotin anti-mouse TER-119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eTER-119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e116204,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_313704\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eLEAF\u0026trade; Purified anti-mouse CD3e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e145-2C11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e100359,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_2800555\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eLEAF\u0026trade; Purified anti-mouse CD28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e37.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e102121, RRID:AB_11147170\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-Mouse CD279 (PD-1)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eRMP1-14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eLeinco technologies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eP372,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_2749820\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003ePurified anti-mouse CD16/32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e101302,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_312800\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse CD3, Alexa Fluor647\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e145-2C11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e100209,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_389323\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse CD3e, PE-Cyanine7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e145-2C11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eebioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e25-0031-82, RRID:AB_469572\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse TCR \u0026beta; chain, BV785\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eH57-597\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBiolegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e109249,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_2810347\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse CD4, FITC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eRM4-4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eebioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e11-0043-85,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_464901\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse CD4 , PerCP-Cy5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eRM4-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eebioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e45-0042-82,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_1107001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse CD4, eFluor450\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eRM4-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eebioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e48-0042-82,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_1272194\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse CD4, APC-eFluor780\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eRM4-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eeBioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e47-0042-82,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_1272183\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse CD8a, APC-eFluor780\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e53-6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eebioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e47-0081-82,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_1272185\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse CD8, Percp/cy5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e53-6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBD Bioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e551162,\u0026nbsp;RRID:AB_394081\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse CD8, Alexa Fluor647\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e53-6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBiolegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e100724,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_389326\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse CD19, APC-eFluor780\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eeBio1D3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eeBioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e47-0193-82,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_10853189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse CD19, PE-Cy7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eeBio1D3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eeBioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e25-0193-82,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_657663\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse CD19, PE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eeBio1D3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eeBioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e12-0193-81,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_657661\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse CD19, FITC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eeBio1D3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eeBioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e11-0193-85,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_657668\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse CD25, APC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003ePC61.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eeBioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e17-0251-82,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_469366\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse CD25, PE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003ePC61.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eeBioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e12-0251-83,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_465608\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse CD44, PE-Cy7\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eIM7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBD Bioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e560569,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_1727484\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse CD69, PE\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eH1.2F3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBD Bioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e561932,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_394726\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse CD44, BV650\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eIM7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBD Bioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e740455,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_2740182\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eContinued\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.8609%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eREAGENT or RESOURCE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eSOURCE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eIDENTIFIER\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse CD62L, APC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eMEL-14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eeBioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e17-0621-83,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_469411\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse CD62L, PE/Cy7\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eMEL-14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e104418,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_313102\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse CD71, APC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eR17217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eeBioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e17-0711-82,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_1834355\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse B220, BV510\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eRA3-6B2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBD Bioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e563103,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_2738007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse B220, BV650\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eRA3-6B2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBD Bioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e563893,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_2738471\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse B220, PerCP/Cy5.5\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eRA3-6B2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e103236,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_893354\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-human/mouse B220 APC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eRA3-6B2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eeBioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e17-0452-83,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_469396\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-human/mouse B220 eFluor450\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eRA3-6B2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eeBioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e48-0452-82,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_1548761\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse ICOS, PE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e7E.17G9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eeBioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e12-9942-82,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_466274\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse CD279 (PD-1), PE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e29F.1A12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e135206,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_1877231\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse CD279 (PD-1), FITC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e29F.1A12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e135214,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_10680238\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse Tim-3, BV 421\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eRMT3-23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e119723,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_2616908\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse IFN-\u0026gamma;, APC\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eXMG1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e505810,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_315403\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse TNF alpha, PE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eTN3-19.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eeBioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e12-7423-41,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_11149178\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse Granzyme B, eFluor450\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eNGZB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eeBioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e48-8898-82,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_11149362\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse FOXP3, PE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eFJK-16S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eeBioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e15-5773-82,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_468806\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-GFP, Alexa Fluor488\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eFM264G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioLegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e338008,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:\u0026nbsp;AB_2563287\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eFixable Viability Dye, eFluor506\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eebioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e65-0866-18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBiotin anti-human CD11b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eICRF44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBiolegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e301304,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_314156\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBiotin anti-human CD16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e3G8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBiolegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e302004,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_314204\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBiotin anti-human CD19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eH1B19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBiolegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e302204,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_314233\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBiotin anti-human CD41a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eHIP8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBiolegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e303734,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_2687174\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBiotin anti-human CD56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eMEM-188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBiolegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e304620,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_528851\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBiotin anti-human CD235a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eHIR2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBiolegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e306618,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_2565773\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBiotin anti-human CD36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e5-271\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBiolegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e336218,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_2565771\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBiotin anti-human CD45RO antibody\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eUCHL1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBiolegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e304220,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_893359\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eUltra-LEAF\u0026trade; Purified anti-human CD28 Antibody\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eCD28.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBiolegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e302934,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_11148949\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eUltra-LEAF\u0026trade; Purified anti-human CD3 Antibody\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eOKT3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBiolegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e317326,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_11150592\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-human CD69, FITC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eFN50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBiolegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e310904,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_314838\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-human CD3, PE/Cy7\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eUCH71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBiolegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e300420,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_439780\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-human CD25, APC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eM-A251\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBiolegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e356110,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_2561976\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-human CD71, PE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eCY1G4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBiolegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e334106,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_2271603\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-human CD45RA, FITC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eHI100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBiolegend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e304105,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_314410\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAlix Rabbit mAb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eABclonal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eA2215,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_2764230\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBeta Actin Monoclonal antibody\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eproteintech\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e66009-1-Ig,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_2687938\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eCD63 Rabbit pAb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eABclonal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eA5271,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_2766092\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eCD63 Monoclonal Antibody\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e3D4D1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eProteintech\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e67605-1-Ig,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_2882811\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eLAMP1 Rabbit pAb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eABclonal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eA2582,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_2770145\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eHGS (Hrs) Rabbit mAb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eABclonal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eA1790,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_2763831\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eContinued\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.8609%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eREAGENT or RESOURCE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eSOURCE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eIDENTIFIER\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eGoat anti-Rabbit IgG (H+L) Highly Cross-Adsorbed Secondary Antibody, Alexa Fluor\u0026trade;488\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eInvitrogen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eA-11034,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_2576217\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eFLAG\u0026reg; M2 mouse monoclonal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eSigma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eF1804\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eLAT Polyclonal antibody\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eProteintech\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e11326-1-AP, RRID:AB_10695624\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eLCK Rabbit pAb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eABclonal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eA2177,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_2764195\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003ePhospho-LAT (Tyr220) Antibody\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eCST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e3584T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003ePhospho-PLC\u0026gamma;1 (Tyr783) Antibody\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eCST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e2821T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003ePhospho-SHP1-Y564 Rabbit pAb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eABclonal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eAP0787,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_2771481\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003ePhospho-SLP-76 (Ser376) (E3G9U) XP\u0026reg; Rabbit mAb\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eCST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e76384T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003ePhospho-Zap-70 (Tyr493)/Syk (Tyr526) Antibody\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eCST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e2704T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003ePhospho-ZAP70 (Y493) Antibody\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eRD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eMAB7694-SP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003ep-LAT(Tyr220) (E3S5L) Rabbit mAb\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eCST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e20172S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003epLCK(Y505) Rabbit pAb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eABclonal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eAP0285,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_2771264\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003ePLC\u0026gamma;-1 Rabbit mAb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eABclonal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eA8899,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_2863625\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eRAB27A Rabbit pAb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eABclonal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eA1934,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_2862644\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eRab5 (C8B1) Rabbit mAb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eCST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e3547T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eRAB7 Rabbit pAb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eABclonal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eA12784,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_2759627\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eSHP1 Rabbit pAb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eABclonal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eA19111, RRID:AB_2862604\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eT Cell Signaling Antibody Sampler Kit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eCST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e14541T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eTMEM176B Rabbit pAb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eABclonal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eA16118,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRRID:AB_2763562\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse Tmem176b\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e6E8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eABclonal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eThis paper\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-human TMEM176b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e2F2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eABclonal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eThis paper\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse PD1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eRMP1-14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eLeinco technologies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eP362, \u0026nbsp; \u0026nbsp; \u0026nbsp;RRID:AB_2749820\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-Human PD-L1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003eAtezolizumab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBioXCell\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eSIM0009, RRID:AB_2894730\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eTSG101 Rabbit mAb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eABclonal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eA2216, \u0026nbsp;RRID:AB_2764231\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eHRP Goat Anti-Mouse IgG (H+L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eABclonal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eAS003, \u0026nbsp;RRID:AB_2769851\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eHRP Goat Anti-Rabbit IgG (H+L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eABclonal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eAS014, RRID:AB_2769854\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-mouse IgG (H+L), F(ab\u0026apos;)2Fragment (Alexa Fluor\u0026reg;488 Conjugate)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eCST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e4408S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAnti-rabbit IgG (H+L), F(ab\u0026apos;)2 Fragment (Alexa Fluor\u0026reg;594 Conjugate)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eCST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e8889S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eGoat anti-Rabbit IgG (H+L) Highly Cross-Adsorbed Secondary Antibody, Alexa Fluor\u0026trade; 555\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eInvitrogen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eA-21429, RRID:AB_2535850\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eStreptavidin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003e4A biotech\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eFXP024-010\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eREAGENT or RESOURCE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eSOURCE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eIDENTIFIER\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eChemicals and recombinant proteins\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eFoxp3 / Transcription Factor Fixation / Permeabilization Concentrate and Diluent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eeBioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e00-5523-00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBD Cytofix/Cytoperm\u0026trade; Fixation /Permeabilization Solution Kit\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBD Bioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e554714\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eCellTrace\u0026trade; CFSE Cell Proliferation Kit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eInvitrogen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eC34554\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eECL select\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eGE healthcare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eRPN2235\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36.2583%;\"\u003e\n \u003cp\u003ePercoll\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eGE Healthcare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e17-0891-01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eDNase I\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eRoche\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e10104159001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eCollagenase D\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eRoche\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e11088882001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 36.2583%;\"\u003e\n \u003cp\u003ephorbol 12-Myristate 13-Acetate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eSigma-Aldrich\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eP1585-1MG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eIonomycin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eYEASEN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e50401ES03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eGolgiPlug\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBD Biosciences\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e555029\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eCellTrace\u0026trade; CFSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eInvitrogen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eC34554\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003ePierce\u0026trade; BCA Protein Assay Kits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eThermo Scientific\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eA55864\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eFluo-4, AM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eInvitrogen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eF14201\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eANTI-FLAG\u0026reg; M2 Affinity Gel, purified immunoglobulin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eSigma-Aldrich\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eA2220\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBiosci\u0026trade; Human Lymphocyte Separation Medium I (Ficoll)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eDAKEWEI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e7111011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eSignalUpTM Super Sensitive ELISA Assay Kit with Fluorescent HRP Substrate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBeyotime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eP0205\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eAntifade Mounting Medium with DAPI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eBeyotime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eP0131\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eStreptavidin-POD Kit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eSolarbio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eSP0041\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eDAB Substrate kit,20\u0026times;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eSolarbio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eDA1010\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eNeutral balsam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eSolarbio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eG8590\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eDMEM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eYuanpei\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eL110KJ\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eRPMI-1640\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eYuanpei\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eL210KJ\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eMEM NEAA\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eGibco\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e11140050\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eSodium pyruvate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eGibco\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e11360070\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eHEPES\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eGibco\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e15630080\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003ePenicillin and Streptomycin\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eGibco\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e15140122\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eRecombinant Human FLT3LG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eNovoprotein\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eCA82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eRecombinant Mouse IFN gamma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eNovoprotein\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eCM40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eRecombinant human IFN gamma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eNovoprotein\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eC014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eExperimental models: Cell lines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eREAGENT or RESOURCE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eSOURCE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eIDENTIFIER\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eB16F10 (mouse melanoma)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eATCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eCRL-6475, RRID:CVCL_0159\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eMC38 (mouse colon adenocarcinoma)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eDr. John Teijaro (The Scripps Research Institute)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eRRID:CVCL_B288\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eB16GP33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eDr. Ananda Goldrath (University of California, San Diego)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eHepa1-6 (mouse hepatoma)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eATCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eCRL-1830, RRID:CVCL_0327\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eNIH3T3 (murine\u0026nbsp;embryonic fibroblast)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eATCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eCRL-1658,\u0026nbsp;RRID:CVCL_0594\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eHeLa (human cervical carcinoma)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eATCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eCCL-2, RRID:CVCL_0030\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eEL4 (mouse T lymphoma)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eATCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eTIB-39, RRID:CVCL_0255\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eSW480\u0026nbsp;(human colorectal adenocarcinoma)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eATCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eCCL-228, RRID:CVCL_0546\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003e293T (human kidney epithelial-like cells)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eATCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eCRL-3216, RRID:CVCL_0063\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eA549 (human Non-small cell lung cancer cells)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eATCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eCCL-185, RRID:CVCL_0023\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eA375 (human melanoma)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eATCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eCRL-1619, RRID:CVCL_0132\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eBEAS-2B (human normal lung epithelial cells)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eATCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eCRL-3588, RRID:CVCL_0168\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eMCF-10A (human normal mammary epithelial cells)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eATCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eCRL-10317, RRID:CVCL_0598\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eExperimental models: Mouse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eC57BL/6J\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eJackson Laboratory\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e000664, RRID:IMSR_JAX:000664\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003e\u003cem\u003eRag1\u003csup\u003e-/-\u003c/sup\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eJackson Laboratory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e002216, RRID:IMSR_JAX:002216\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003e\u003cem\u003eTcrb\u003c/em\u003e\u003csup\u003e-/-\u003c/sup\u003e\u003cem\u003eTcrd\u003c/em\u003e\u003csup\u003e-/-\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eJackson Laboratory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e002122, RRID:IMSR_JAX:002122\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003e\u003cem\u003eIgh-j\u003c/em\u003e\u003csup\u003e-/-\u003c/sup\u003e\u003cem\u003eIgk\u003csup\u003e-/-\u003c/sup\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eJackson Laboratory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e002438\u0026amp;011074\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003e\u003cem\u003eCD8a\u003csup\u003e-/-\u003c/sup\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eJackson Laboratory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e002665, RRID:IMSR_JAX:002665\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003e\u003cem\u003edLck\u003c/em\u003e-Cre\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eJackson Laboratory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e012837, RRID:IMSR_JAX:012837\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003e\u003cem\u003eCD11c\u003c/em\u003e-Cre\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eJackson Laboratory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e008068, RRID:IMSR_JAX:008068\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003e\u003cem\u003eEIIA-cre\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eJackson Laboratory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e003724, RRID:IMSR_JAX:003724\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eP14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eJackson Laboratory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e004694, RRID:IMSR_JAX:004694\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eOT-I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eJackson Laboratory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e003831, RRID:IMSR_JAX:003831\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003e\u003cem\u003ePtpn6\u003csup\u003efl/fl\u003c/sup\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eZhongjun Dong (Tsinghua University)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e008336, RRID:IMSR_JAX:008336\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003e\u003cem\u003eTmem176b\u003csup\u003efl/fl\u003c/sup\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eCyagen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eS-CKO-12834\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003e\u003cem\u003eTmem176a/b\u003csup\u003efl/fl\u003c/sup\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eCyagen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eAIBM0240\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eRecombinant DNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003epMD2.G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eAddgene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e12259\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003epsPAX2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eAddgene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e12260\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eLentiCRISPRv2-mTmem176b-sgRNA2-mCherry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eThis paper\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eLentiCRISPRv2-mTmem176b-sgRNA3-mCherry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eThis paper\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eLentiCRISPRv2-mTmem176b-sgRNA8-mCherry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eThis paper\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eContinued\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.8609%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.6623%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eREAGENT or RESOURCE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eSOURCE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eIDENTIFIER\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eLentiCRISPRv2-hTMEM176B-sgRNA3-mCherry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eThis paper\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eLentiCRISPRv2-m\u003cem\u003eRab27a\u003c/em\u003e-sgRNA1-mCherry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eThis paper\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eLentiCRISPRv2-m\u003cem\u003eRab27a\u003c/em\u003e-sgRNA2-mCherry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eThis paper\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eLentiCRISPRv2-m\u003cem\u003eRab27a\u003c/em\u003e-sgRNA3-mCherry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eThis paper\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eplv-Tmem176b-3\u0026times;Flag-IRES-eGFP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eThis paper\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eplv-eGFP-Tmem176b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eThis paper\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36.2583%;\"\u003e\n \u003cp\u003eplv-eBFP-Shp1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.2185%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.8609%;\"\u003e\n \u003cp\u003eThis paper\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.6623%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHuman sample preparation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eColorectal cancer tissues and adjacent normal tissues from patients, and peripheral blood from cancer patients and healthy donors, were collected by the First Affiliated Hospital of Xiamen University (Xiamen, China) with written informed consent from either subjects or their legal authorized representatives prior to sample collection. Tumor specimens were used for protein and RNA transcript detection, and peripheral blood samples from cancer patients or healthy donors were used for exosome isolation. Human peripheral blood mononuclear cells (PBMCs) were harvested from peripheral blood of health donors, by density gradient centrifugation with Ficoll (DAKEWE, 7111011). The use of all tissue and blood samples in this study were all approved by the Ethics Committees at the First Affiliated Hospital of Xiamen University (Xiamen, China).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnimals\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eC57BL/6J (B6) (#000664), \u003cem\u003eRag1\u003csup\u003e-/-\u003c/sup\u003e\u0026nbsp;\u003c/em\u003e(#002216),\u0026nbsp;\u003cem\u003eTcrb\u003c/em\u003e\u003csup\u003e-/-\u003c/sup\u003e\u003cem\u003eTcrd\u003c/em\u003e\u003csup\u003e-/-\u0026nbsp;\u003c/sup\u003e(TCD, #002122), \u003cem\u003eIgh-j\u003c/em\u003e\u003csup\u003e-/-\u003c/sup\u003e\u003cem\u003eIgk\u003csup\u003e-/-\u003c/sup\u003e\u003c/em\u003e (BCD, #002438\u0026amp;#011074), \u003cem\u003eCD8a\u003csup\u003e-/-\u003c/sup\u003e\u003c/em\u003e (#002665), dLck-Cre (#012837), CD11c-Cre (#008068), EIIA-cre (#003724), P14 (#004694) and OT-I (#003831) TCR transgenic mice were originally from the Jackson Laboratory. \u003cem\u003ePtpn6\u003csup\u003efl/fl\u0026nbsp;\u003c/sup\u003e\u003c/em\u003emice (Jax #008336) were kindly provided by Dr. Zhongjun Dong at Tsinghua University. \u003cem\u003eTmem176b\u003csup\u003efl/fl\u003c/sup\u003e\u003c/em\u003e (S-CKO-12834) and \u003cem\u003eTmem176a/b\u003csup\u003efl/fl\u003c/sup\u003e\u003c/em\u003e (AIBM0240) mice were generated in C57BL/6J background using CRISPR-Cas9 technology, by Cyagen. \u003cem\u003eTmem176b\u003csup\u003e-/-\u0026nbsp;\u003c/sup\u003e\u003c/em\u003emice were generated by crossing \u003cem\u003eTmem176b\u003csup\u003efl/fl\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003eto EIIA-cre (#003724) mice. HuHSC-NCG(NOD/ShiLtJGpt-\u003cem\u003ePrkdc\u003csup\u003eem26Cd52\u003c/sup\u003eIl2rg\u003csup\u003eem26Cd22\u003c/sup\u003e\u003c/em\u003e/Gpt)(CH) mice (#T037620) were purchased from GemPharmatech (Nanjing, China). All mice (gender matched) were littermates and were 8-12 weeks old, unless otherwise indicated in the text. The mice were housed in specific pathogen-free facilities of Xiamen University Laboratory Animal Center with a light-dark cycle of 12 h, at a temperature about 22\u0026nbsp;℃, humidity of 40-70%, and were fed with standard mouse chew diet. All animal experiments were performed in accordance with protocols approved by the Institutional Animal Care and Use Committee of Xiamen University.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell lines\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe B16F10 (mouse melanoma), EL4 (mouse T lymphoma), NIH3T3 (mouse embryonic fibroblast), HeLa (\u003ca href=\"javascript%3A;\"\u003ehuman cervical carcinoma\u003c/a\u003e), SW480 (human colorectal adenocarcinoma), A549 (human lung carcinoma\u0026nbsp;cells), MCF-10A (human\u0026nbsp;mammary gland epithelia\u0026nbsp;cells), 293T (human kidney epithelial-like cell) were originally from American Type Culture Collection (ATCC). BEAS-2B human\u0026nbsp;bronchial\u0026nbsp;epithelial cells were from Servicebio (Wuhan, China). MC38 (mouse colon adenocarcinoma) cell line was kindly provided by Dr. John Teijaro at The Scripps Research Institute. B16GP33 cell line was kindly provided by\u0026nbsp;Dr. Ananda Goldrath at University\u0026nbsp;of\u0026nbsp;California,\u0026nbsp;San\u0026nbsp;Diego. A375 (human melanoma) cell line was a gift from Dr. Yan Li at Nanjing University. B16F10 cells were infected with lentivirus encoding \u003cem\u003eTmem176b-Flag\u003c/em\u003e to generate Tmem176b-Flag-expressing B16F10 cells. Tumor cell lines were cultured in DMEM (Yuanpei, L110KJ) supplemented with 10% Fetal Bovine Serum (FBS), 1% MEM NEAA (Gibco, 11140050), 100 U/mL penicillin and 100 \u0026mu;g/mL streptomycin\u0026nbsp;(Gibco, 15140122). EL4 cell line were cultured in RPMI-1640 Medium (Yuanpei, L210KJ) supplemented with 10% FBS, 1 mM sodium pyruvate (Gibco, 11360070), 10 mM HEPES (Gibco, 15630080), 50 \u0026mu;M \u0026beta;-mercaptoethanol,\u0026nbsp;100 U/ml penicillin and 100 \u0026mu;g/ml streptomycin\u0026nbsp;(Gibco, 15140122). All cells were cultured at 37\u0026nbsp;℃\u0026nbsp;in a humidified atmosphere containing 5% CO\u003csub\u003e2\u003c/sub\u003e. Unless otherwise denoted, knockout cell lines were cultured in the same condition of the corresponding parental cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLentiviral transduction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLentiCRISPRv2-mCherry was used for construction of candidate gene knockout cell lines, and plv-Tmem176b-3\u0026times;Flag-IRES-eGFP, plv-eGFP-Tmem176b, plv-eBFP-Shp1 were used to establish stable gene-overexpression cell lines.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e293T cells were seeded at 1\u0026times;10\u003csup\u003e6\u003c/sup\u003e cells per well of 6-well dish before transfection. Cells were transfected with 200 \u0026mu;l Opti-MEM mixed with 2 \u0026mu;g lentiviral plasmids, lentiviral packing plasmids including 0.5 \u0026mu;g pMD2.G (Addgene, 12259) and 1.5 \u0026mu;g psPAX2 (Addgene, 12260), and 8 \u0026mu;l polyethylenimine (PEI) (1 mg/mL). The mixture was incubated 15 min at room temperature and then dropwise added to cells. After 6-8 h, the culture medium was replaced with pre-warmed fresh DMEM complete medium. Viral supernatant was collected at 48 h and 72 h post-transfection. Cell debris was removed by centrifugation with 1,000 \u003cem\u003eg\u003c/em\u003e for 3 min. The aliquot of virus stock was stored at -80\u0026nbsp;℃.\u003c/p\u003e\n\u003cp\u003e2\u0026times;10\u003csup\u003e5\u0026nbsp;\u003c/sup\u003eadherent cells (B16F10 or MC38) were cultured in 2 ml DMEM complete medium in 6-well plate to 40-50% confluency and were then changed to 1 ml fresh medium before infection. For suspension cells (EL4), 2\u0026times;10\u003csup\u003e5\u003c/sup\u003e cells were resuspended with 100 \u0026mu;l RPMI-1640 complete medium in 24-well plate. 1 ml or 400 \u0026mu;l of virus supernatant containing 10 \u0026mu;g/ml polybrene was added into each well of 6-well or 24-well plates, respectively. Cells were centrifuged at 2,500 rpm for 30 min at 37\u0026nbsp;℃\u0026nbsp;in a pre-warmed centrifuge. After being incubated at 37\u0026nbsp;℃\u0026nbsp;for 12 h, cells were being cultured in fresh complete media until cell sorting. Cells then were resuspended in sorting buffer (PBS supplemented with 1 mM EDTA, 25 mM HEPES, and 1% FBS) and then sorted with a BD Aria III sorter.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCRISPR-Cas9-mediated gene knockout\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKnockout cell lines were generated with lentivirus-mediated CRISPR-Cas9 technology. Single guide RNA (sgRNA) sequences were designed using CrisprGold systems\u0026nbsp;\u003cs\u003e\u003c/s\u003e(https://crisprgold.mdc-berlin.de/index.php) and the sequences of sgRNA oligonucleotides are listed in \u003cstrong\u003eTable S3\u003c/strong\u003e.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eScrambled sgRNA served as a non-target control. Double-stranded oligonucleotides encoding the sgRNA sequences were cloned into the LentiCRISPRv2-mCherry, which co-express Cas9 and sgRNA in the same vector. To generate the gene knockout cancer cell lines, target cells (B16F10, MC38, HeLa or SW480) were infected with sgRNA-encoding CRISPR-Lentivirus. The positively infected cells were sorted by flow cytometry based on mCherry fluorescence and were seeded into 96-well plates for single-cell expansion. The expression of target proteins in infected cells was examined by western blot (for other candidates) or flow cytometry (for Tmem176b) to validate the knockout. Successful genomic editing was verified by sequencing of PCR products of the targeted region.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMouse tumor models\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor subcutaneous tumor models, 2\u0026times;10\u003csup\u003e5\u003c/sup\u003e B16F10 or 1\u0026times;10\u003csup\u003e6\u003c/sup\u003e MC38 cells were resuspended in 100\u0026thinsp;\u0026mu;l of phosphate-buffered saline solution (PBS) and were subcutaneously (\u003cem\u003es.c.\u003c/em\u003e) inoculated into the right flank of each C57BL/6J or immune-deficient mouse, and tumor size was measured every other day using a caliper. Tumor volume was calculated as length\u0026times;(width\u003csup\u003e2\u003c/sup\u003e)/2. Survival was monitored each day. For survival curve analysis, mice with tumor size reaching 2,000 mm\u003csup\u003e3\u0026nbsp;\u003c/sup\u003ewere euthanized with carbon dioxide and were defined as humane endpoints. To analyze the tumor-infiltrating immune cells, tumors were harvested at day 14 (for B16F10) or day 18 (for MC38).\u003c/p\u003e\n\u003cp\u003eIn tumor models with supplementation of syngeneic exosomes, 20 \u0026mu;g of\u0026nbsp;syngeneic exosomes were mixed with 2\u0026times;10\u003csup\u003e5\u003c/sup\u003e B16F10 or 1\u0026times;10\u003csup\u003e6\u003c/sup\u003e MC38 cells in 100\u0026thinsp;\u0026mu;l of PBS, and were subcutaneously (\u003cem\u003es.c\u003c/em\u003e) inoculated into the right flank of each C57BL/6J or immune-deficient mouse, and tumor size was measured every other day using a caliper. Otherwise, 100 \u0026mu;g of syngeneic exosomes were\u0026nbsp;intravenously (\u003cem\u003ei.v.\u003c/em\u003e) injected every 3 days for 3 times into the tumor-bearing mice 3 days after subcutaneous inoculation of B16F10 cells.\u003c/p\u003e\n\u003cp\u003eFor metastatic melanoma studies, 1\u0026times;\u0026thinsp;10\u003csup\u003e6\u003c/sup\u003e of B16F10-Scr or \u003cem\u003eTmem176b\u003c/em\u003e-deficient cells were injected \u003cem\u003ei.v.\u0026nbsp;\u003c/em\u003einto the tail vein of each C57BL/6J mouse. Mice were euthanized\u0026nbsp;at day 14 after tumor inoculation and surface metastatic nodules in the lung were counted under a dissecting microscope.\u003c/p\u003e\n\u003cp\u003eTo test the antitumor function of Tmem176b competitive peptide, chimeric Tmem176b or scramble peptides (cell-penetrating peptide fused with amino acids 218-232 of Tmem176b (RXRRBRRXRRBRXB-ASLGLSLRSMYGRSS) or scramble peptide (RXRRBRRXRRBRXB-MLSGSRYSGLSARLS), called CPP-Pep or CPP-Scr hereinafter)\u0026nbsp;\u003csup\u003e71\u003c/sup\u003e (10 mg/kg) were injected \u003cem\u003ei.v.\u0026nbsp;\u003c/em\u003einto B16F10 or MC38 tumor-bearing mice after tumor volume reaching 200 mm\u003csup\u003e3\u003c/sup\u003e, every 3 days for 3 times. The same dosage was used to in B16F10 lung metastasis tumor models at day 3 after tumor inoculation. To test the therapeutic efficacy of Tmem176b-neutralizing antibody, anti-Tmem176b (Abclonal, Clone# 6E8), anti-PD1 (Leinco technologies, Clone# RMP1-14) or Rabbit isotype antibody (200 \u0026mu;g/mouse) were injected \u003cem\u003ei.p.\u0026nbsp;\u003c/em\u003einto B16F10 or MC38 tumor-bearing mice after tumors volume reaching 200 mm\u003csup\u003e3\u003c/sup\u003e, every 3 days for 3 times. For the therapeutic efficacy of combination of CPP-Pep with anti-PD1 therapy, CPP-Pep or CPP-Scr (\u003cem\u003ei.v\u003c/em\u003e injection, 10 mg/kg), or CPP-Pep (\u003cem\u003ei.v\u003c/em\u003e injection, 10 mg/kg) plus anti-PD1 antibody (\u003cem\u003ei.p.\u0026nbsp;\u003c/em\u003einjection, 200 \u0026mu;g/mouse) were injected into tumor-bearing mice when the tumor volume reaching 200 mm\u003csup\u003e3\u003c/sup\u003e, every 3 days for 3 times\u003csub\u003e.\u0026nbsp;\u003c/sub\u003eFor the therapeutic efficacy of combination of anti-Tmem176b with anti-PD1 therapy, 6E8 or isotype antibody, or 6E8 plus anti-PD1 antibody (200 \u0026mu;g each antibody per mouse) were injected \u003cem\u003ei.p.\u0026nbsp;\u003c/em\u003einto B16F10 or MC38 tumor-bearing mice after tumor volume reaching 200 mm\u003csup\u003e3\u003c/sup\u003e, every 3 days for 3 times.\u003c/p\u003e\n\u003cp\u003eTo establish orthotopic hepatocellular carcinoma (HCC)\u0026nbsp;mouse models, subcutaneous tumors were peeled from Hepa1-6 tumor-bearing mice. Tumor tissues were cut into about 1 mm\u003csup\u003e3\u003c/sup\u003e/piece, three tumor pieces were implanted in the liver of each recipient C57BL/6J mouse under anesthesia, and tumor size were monitored by the magnetic resonance images (MRI). Tumor-bearing mice were randomized into treatment groups based on MRI. The mice were treated 3 weeks after inoculation, with CPP-Pep or CPP-Scr (10 mg/kg) via\u0026nbsp;intravenous (\u003cem\u003ei.v.\u003c/em\u003e) injection, or with anti-Tmem176b (Abclonal, Clone# 6E8) or isotype antibody (200 \u0026mu;g/mouse) via intraperitoneal (\u003cem\u003ei.p.\u003c/em\u003e) injection, every 3 days for 3 times. Tumor-bearing mice were euthanized\u0026nbsp;at 6 weeks after inoculation and tumor size was measured using a caliper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA375 tumor model in humanized mice\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHuHSC-NCG mice were constructed by transplanting human hematopoietic stem cells (10\u003csup\u003e5\u0026nbsp;\u003c/sup\u003eCD34\u003csup\u003e+\u003c/sup\u003e Hu-HSC per mouse) into irradiated and myeloablated severe immunodeficient NCG (NOD/ShiLtJGpt-\u003cem\u003ePrkdc\u003csup\u003eem26Cd52\u003c/sup\u003eIl2rg\u003csup\u003eem26Cd22\u003c/sup\u003e\u003c/em\u003e/Gpt)(CH) mice (4 week old). 18 weeks after hu-HSC reconstitution, a total of 10\u003csup\u003e6\u003c/sup\u003e A375 human melanoma cells were implanted into the right dorsal flanks of huHSC-NCG mice. When the tumor volumes were over 200 mm\u003csup\u003e3\u003c/sup\u003e, the A375-bearing-huHSC-NCG mice were treated with anti-human TMEM176B (Abclonal, Clone# 2F2), or anti-human PD-L1 (BioXCell, Clone#\u0026nbsp;Atezolizumab), or isotype antibody, or anti-human TMEM176B plus anti-human PD-L1 (100 \u0026mu;g each antibody per mouse) via intraperitoneal (\u003cem\u003ei.p.\u003c/em\u003e) injection, every 3 days for 5 times.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExosome isolation, characterization, and quantification\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExosomes were isolated from conditioned medium using a protocol as previously described \u003csup\u003e72\u003c/sup\u003e. Briefly, cancer cells (B16F10, MC38, HeLa, SW480) or non-malignant\u0026nbsp;NIH3T3 cells were cultured in DMEM medium containing 10% exosome-depleted FBS,\u0026nbsp;100 U/ml penicillin and 100 \u0026mu;g/ml streptomycin for 24-48 h to 80% confluence. Culture supernatants was collected and centrifugated at 500 \u003cem\u003eg\u003c/em\u003e for 15 min to remove cell debris, and then centrifugated at 10,000 \u003cem\u003eg\u003c/em\u003e for 30 min, followed by filtration with 0.22 \u0026mu;m filter. Exosome were pelleted by ultracentrifugation (Beckman Optima L-100 XP, Beckman Coulter) at 100,000 \u003cem\u003eg\u003c/em\u003e for 70 min, washed with PBS using the same ultracentrifugation conditions, and resuspended in PBS. For human plasma exosome isolation, plasma from cancer patients or health volunteers were sequentially centrifuged at 3,000 \u003cem\u003eg\u003c/em\u003e, and 10,000 \u003cem\u003eg\u003c/em\u003e for 30 min twice to remove cell debris, followed by filtration with 0.22 \u0026mu;m filter, and exosomes were pelleted by ultracentrifugation (Beckman Optima L-100 XP, Beckman Coulter) at 100,000 \u003cem\u003eg\u003c/em\u003e for 70 min, and washed with PBS using the same ultracentrifugation conditions, and resuspended in PBS. Exosomes were quantified as protein measurement using BCA protein assay kit (Thermo Scientific, A55864). Transmission electron microscopy (Hitachi, HT-7800), nanoparticle tracking analysis\u0026nbsp;(Nanosight NS300, Malvern) and Nano-Flow cytometry (Flow NanoAnalyzer, NanoFCM, Fujian, China) were performed to characterize the isolated exosomes. For quantitative mass spectrometry, centrifugated exosomes were lysed in 1% sodium deoxycholate and quantified using BCA protein assay kit.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIsolation of tissue leukocytes for flow cytometry\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor the isolation of leukocytes from spleen and draining lymph nodes, tissues were dissected from mice, and were minced with dissection scissors, and were mashed and filtered. Red blood cells were removed by ACK (Ammonium-Chloride-Potassium) lysis buffer. For the isolation of leukocytes from tumor tissues, tumors were dissected from mice, and were minced with dissection scissors, then were digested in RPMI 1640 containing 20 \u0026mu;g/ml of DNase I (Roche, 10104159001) and 200 \u0026mu;g/ml of Collagenase D (Roche, 11088882001) at 37\u0026nbsp;℃\u0026nbsp;with 220 rpm shaking for 1 h. After digestion, the tissues were then ground, filtered, collected by centrifugation at 500 \u003cem\u003eg\u003c/em\u003e for 5 min. Supernatant was aspirated and the mononuclear immune cells were isolated by centrifugation on a 40 to 72% Percoll gradient. Red blood cells were removed by ACK lysis buffer. Single cell suspensions were then washed, filtered and then collected by centrifugation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell enrichment and purification\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe purification (\u0026gt;95% purity) of naive polyclonal CD4\u003csup\u003e+\u003c/sup\u003e or CD8\u003csup\u003e+\u003c/sup\u003e T cells from B6 mice or naive CD8\u003csup\u003e+\u003c/sup\u003e T cells from OT-Ⅰ\u0026nbsp;mice were performed by negative selection using Beaverbeads\u003csup\u003eTM\u003c/sup\u003e Streptavidin (Cat#22307; Beaver). Briefly, single cell suspensions were incubated with different cocktails of biotin-conjugated antibodies (BioLegend) in Cell Staining Buffer (2 % FBS, 2 mM EDTA in PBS) at 4\u0026nbsp;℃\u0026nbsp;for 15 min, and then washed with Cell Staining Buffer. After washing, cells were resuspended in Staning Buffer and incubated with Beaverbeads\u003csup\u003eTM\u003c/sup\u003e Streptavidin on rotator at 4\u0026nbsp;℃\u0026nbsp;for 10 min. Then cells were separated by placing the labeled cells in tube on DynaMag\u0026trade;-2 Magnet (Cat# 12321D; Invitrogen) for 5 min.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFlow cytometry and cell sorting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor blocking of Fc receptors, single cell suspensions were incubated with purified anti-CD16/32 for 15 min on ice prior to immunostaining. For surface staining, cells stained with fluorochrome-conjugated antibodies and live/dead Fixable Viability Dye (eBioscience, 65-0866-18) in flow cytometry buffer (PBS containing 0.5% BSA) for 30 min at 4\u0026nbsp;℃. For intracellular cytokine staining, cells were incubated in media containing 50 ng/ml of phorbol 12-Myristate 13-Acetate (PMA, Sigma-Aldrich, P1585-1MG) and 1 \u0026mu;g/ml of Ionomycin (YEASEN, 50401ES03), and 1 \u0026mu;g/ml of GolgiPlug (BD Biosciences, 555029) at 37\u0026nbsp;℃\u0026nbsp;for 4 h. After restimulation, cells were spun down and blocked by anti-CD16/32, and stained with antibodies against cell surface markers and live/dead Fixable Viability Dye (eBioscience, 65-0866-18). After washing with 1\u0026times;BD Perm/Wash buffer, cells were fixed and permeabilized with BD Cytofix/Cytoperm solution (BD Biosciences, 51-2090KZ) for 30 min, and then stained with antibodies against indicated cytokines in 1\u0026times;BD Perm/Wash buffer.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor carboxyfluorescein diacetate succinimidyl ester (CFSE) dilution assay, cells were labeled with 0.5 \u0026mu;M of CFSE (Invitrogen, C34554) in PBS at 37\u0026nbsp;℃\u0026nbsp;for 15 min. Then, the cells were washed with PBS to remove the excess dye\u0026nbsp;before culture.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll flow cytometry data were acquired on LSRFortessa (BD), NovoCyte or Quanteon (ACEA) flow cytometry analyzer and were analyzed using FlowJo V10.10.0 software (BD Biosciences).\u003c/p\u003e\n\u003cp\u003eFor cell sorting, single-cell suspensions were stained with fluorochrome-conjugated antibodies in sorting buffer (1 mM EDTA, 25 mM HEPES, 1% FBS in PBS) and then sorted with BD FACSAria\u0026nbsp;Ⅲ\u0026nbsp;and FACSAria Fusion cell sorter.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNano-Flow Cytometry\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor detection of the proportions of Tmem176b\u003csup\u003e+\u003c/sup\u003e exosomes harvested from cancer cell culture supernatant or peripheral blood from cancer patients, 50 \u0026mu;g of purified exosomes were stained with 1 \u0026mu;g/ml of Alexa Fluor 647-labled antibodies against Tmem176b\u0026nbsp;(Abclonal, clone# 6E8) and incubated at\u0026nbsp;4℃ in the dark for 1 h. Isotype control antibody was used to test for unspecific binding. Then exosomes were washed with 12 ml of 0.22 \u0026micro;m-filtered PBS and collected by ultracentrifugation (Beckman Optima L-100 XP, Beckman Coulter) at 100,000 \u003cem\u003eg\u003c/em\u003e for 1 h to remove unbinding antibodies. Supernatant was aspirated\u0026nbsp;and exosomes in pellet were resuspended in 50 \u0026micro;l of 0.22 \u0026micro;m-filtered PBS and subjected to Nano-flow cytometry on Flow NanoAnalyzer (NanoFCM, Fujian, China)\u003csup\u003e40,62\u003c/sup\u003e, and data analysis was performed using FlowJo V10.10.0 software.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMurine T Cell Stimulation Assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePrimary T cells were cultured in RPMI-1640 medium supplemented with 10% FBS, glutamine (1 mM), HEPES (10 mM), sodium pyruvate (1 mM), \u0026beta;-mercaptoethanol (50 \u0026mu;M), penicillin (100 U/ml) and streptomycin (100 \u0026mu;g/ml). To examine TCR signaling, purified na\u0026iuml;ve CD8\u003csup\u003e+\u0026nbsp;\u003c/sup\u003eT cells were rested on ice in FBS-depleted medium for 60 min, then incubated with biotin-conjugated anti-CD3 (Clone# 145-2C11) and anti-CD28 (Clone# 37.51) antibodies (3 \u0026mu;g each antibody/10\u003csup\u003e7\u003c/sup\u003e cells) plus 5 \u0026mu;g of exosomes on ice for 30 min. Then the cells were crosslinked by streptavidin (3 \u0026mu;g/10\u003csup\u003e7\u003c/sup\u003e cells, FXP024-010, 4A biotech) in shaking heat block at 400 rpm, at 37\u0026nbsp;℃\u0026nbsp;for indicated time. After being stimulated, reactions were immediately stopped by ice-cold PBS and cells were collected by centrifugation at 500 \u003cem\u003eg\u003c/em\u003e for 5 min. Finally, cells were lysed with 1\u0026times;SDS loading buffer diluted by NP-40 lysis buffer (20 mM tris-HCl (pH 7.5), 150 mM NaCl, 1% NP-40, 5 mM EDTA (pH 8.0), 5 mM Na\u003csub\u003e4\u003c/sub\u003eP\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e7\u003c/sub\u003e, 1 mM Na\u003csub\u003e3\u003c/sub\u003eVO\u003csub\u003e4\u003c/sub\u003e, 5 mM NaF, and protease inhibitor cocktail).\u003c/p\u003e\n\u003cp\u003eFor \u003cem\u003ein vitro\u003c/em\u003e T cell activation assays, purified na\u0026iuml;ve CD4\u003csup\u003e+\u003c/sup\u003e or CD8\u003csup\u003e+\u003c/sup\u003e T cells were activated by plate-bound anti-CD3 (1 \u0026mu;g/ml) and anti-CD28 (1 \u0026mu;g/ml) in the absence or presence of B16F10 or MC38-derived exosomes in T cell culture medium. After being stimulated for indicated time, the cells were collected and analyzed by flow cytometry.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHuman T Cell Stimulation Assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHuman PBMCs were isolated from peripheral blood of healthy donor, and human primary na\u0026iuml;ve T cells were also purified (\u0026gt;95% purity) by negative selection using Beaverbeads\u003csup\u003eTM\u003c/sup\u003e Streptavidin. T cells were cultured in X-VIVO\u003csup\u003eTM\u0026nbsp;\u003c/sup\u003e15 medium (Lonza, 04-418Q) supplemented with 5% FBS and recombinant human IL-2 (100 U/ml). Na\u0026iuml;ve T cells were activated by plate-bound anti-CD3 (Clone# OKT3) (3 \u0026mu;g/ml) and \u0026alpha;-CD28 (Clone# CD28.2) (3 \u0026mu;g/ml) antibodies in the absence or presence of exosomes derived from the indicated WT or \u003cem\u003eTMEM176B\u003c/em\u003e-deficeint human cancer cells. After being stimulated for indicated time, the cells were collected and analyzed by flow cytometry.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDC generation and antigen cross-presentation assays\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBone marrow (BM) cells were harvest B6 mice by flushing out tibias and femurs with RPMI-1640 medium. Red blood cells were lysed by ACK buffer and BM cells were cultured in 24-well plates at 1\u0026times;10\u003csup\u003e6\u003c/sup\u003e cells/ml in complete RPMI-1640 medium containing 10% FBS, 100 ng/ml Flt3L (Novoprotein, CA82), 1%\u0026nbsp;NEAA\u0026nbsp;(Gibco, 11140050), 1 mM sodium pyruvate (Gibco, cat. 11360070), 2 mM GlutaMAX (Gibco, 35050061), 100 U/ml\u0026nbsp;Penicillin and\u0026nbsp;100 \u0026mu;g/ml\u0026nbsp;Streptomycin (Gibco, 15140122) and 50 \u0026mu;M \u0026beta;-mercaptoethanol for 9-11 days without disturbance. The medium was refreshed on day 5. cDC1s were sorted as L/D\u003csup\u003e-\u003c/sup\u003eB220\u003csup\u003e-\u003c/sup\u003eMHCⅡ\u003csup\u003e+\u003c/sup\u003eCD11c\u003csup\u003e+\u003c/sup\u003eCD24\u003csup\u003e+\u003c/sup\u003eSIRP-\u0026alpha;\u003csup\u003e-\u0026nbsp;\u003c/sup\u003efrom Flt3L-cultured BM cells and were pre-treated with 5 \u0026mu;g of exosomes derived from Scramble or \u003cem\u003eTmem176b\u003c/em\u003e-deficient B16F10 or MC38 cells for 6 h. Unbound exosomes were removed by washing with RPMI-1640 medium, and Flt3L-cDC1s were cocultured with 2.5\u0026times;10\u003csup\u003e4\u003c/sup\u003e CFSE-labelled na\u0026iuml;ve OT-Ⅰ\u0026nbsp;CD8\u003csup\u003e+\u0026nbsp;\u003c/sup\u003eT cells, in the presence of HKLM-OVA for 3 days. OT-Ⅰ\u0026nbsp;CD8\u003csup\u003e+\u0026nbsp;\u003c/sup\u003eT cells were then analyzed by flow cytometry for CFSE dilution.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImmunoprecipitation and Mass spectrometry\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eB16F10 and EL4 cell lines were lentivirally transduced with plv-Tmem176b-3\u0026times;Flag-IRES-eGFP to overexpress Tmem176b fusion protein with Flag-tag at C-terminus. 1\u0026times;10\u003csup\u003e7\u003c/sup\u003e cells were collected and centrifuged at 300 \u003cem\u003eg\u003c/em\u003e for 5 min. After aspiration of supernatant, the cells were lysed with 1 ml NP-40 lysis buffer for 30 min in the ice, followed by ultrasonication. The cell lysates were incubated with 10 \u0026mu;l Anti-Flag M2 beads (Sigma-Aldrich, A2220) overnight on a rotator at 4\u0026nbsp;℃. After washing with lysis buffer 5-6 times, the protein complexes were competitively eluted with Flag peptides in shaking heat block at 1,200 rpm at 25\u0026nbsp;℃\u0026nbsp;for 30 min. The immunoprecipitation samples were stored in -80℃\u0026nbsp;for following assays, such as western blot and mass spectrometry.\u003c/p\u003e\n\u003cp\u003eTo identify Tmem176b-interacting proteins, the immunoprecipitation samples were subjected to SDS-PAGE. After staining with Coomassie Brilliant Blue, excised gel segments were subjected to in-gel trypsin digestion and dried. Samples were analyzed on a nanoElute (Bruker) coupled to a timsTOF Pro (Bruker) equipped with a CaptiveSpray source. Peptides were dissolved in 10 \u0026mu;l formic acid (0.1%) and were loaded onto a homemade C18 column (35cm\u0026times;75\u0026mu;m i.d., 1.9\u0026mu;m 100\u0026Aring;). Samples were then eluted with linear gradients of 3%\u0026ndash;35% acetonitrile in 0.1% formic acid for 60 min at a flow rate of 300 \u0026mu;l/min. Mass spectrum data were acquired with a timsTOF Pro mass spectrometer (Bruker) operated in PASEF mode and were analyzed by Peaks Studio X software against uniprot database.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor the proteomic profiling of exosomes, the exosomes and cells were lysed with 1% sodium deoxycholate in 0.1 M Tris-HCl (pH8.5), and 100 \u0026mu;g sample were subjected to acquire protein quantitative mass spectrum. Liquid chromatography was performed with an ultra-high-pressure nano flow chromatography system (Elute UHPLC, Bruker Daltonics). Peptides were digested in 5 \u0026mu;l 0.1% formic acid and were loaded onto a homemade made C18 column (35 cm \u0026times; 75 \u0026mu;m, ID 1.9 \u0026mu;m 100\u0026Aring;). Samples were then eluted with linear gradients of 3-35% acetonitrile in 0.1% formic acid for 60 min at a flow rate of 0.3 \u0026mu;l/min. LC was coupled online to a hybrid TIMS quadrupole time-of-flight mass spectrometer (Bruker timsTOF Pro) by a CaptiveSpray nanoelectrospray ion source. For data-independent acquisition, we used a 25m/z precursor isolation width to cover 400\u0026minus;1200 mz. diaPASEF (.d) files were searched using DIA-NN (V.1.8.1) against the mouse UniProt Reference Proteome database.\u003c/p\u003e\n\u003cp\u003eThe following parameters of dia-nn software were set: 1, \u0026ldquo;FASTA digest for library-free search\u0026rdquo; and \u0026ldquo;Deep learning-based spectra and RTs prediction\u0026rdquo; were used: 2, Protease, \u0026ldquo;Trypsin/P\u0026rdquo;; Missed cleavage, \u0026ldquo;2\u0026rdquo;; N-termM excision, \u0026ldquo;checked\u0026rdquo;; c carbamido methylation, \u0026ldquo;checked\u0026rdquo;; M-oxidation, \u0026ldquo;checked\u0026rdquo;. 3, The maximum mass accuracy tolerances were set to 10 ppm for both MS1 and MS2 spectra. 4, Protein inference in DIA-NN was the protein name (from fasta). 5, Quantification mode was set to\u0026ldquo;Robust LC (high accuracy)\u0026rdquo;. 6, All other settings were left default.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWestern Blot Analysis\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCells were lysed using NP-40 cell lysis buffer followed by addition of SDS loading buffer, or were directly lysed by 1\u0026times;SDS loading buffer diluted with NP-40 cell lysis buffer. Cell lysates were denatured by being boiled for 10 min. samples were separated by SDS-polyacrylamide gel electrophoresis, followed by electrotransfer to polyvinylidene difluoride (PVDF) membranes (Merck Millipore). The membranes were blocked with TBS containing 5% nonfat milk in and 0.1% Tween20 (TBST). After washing with TBST, membranes were incubated with appropriate primary antibodies at 4\u0026nbsp;℃\u0026nbsp;overnight, followed by horseradish peroxidase-conjugated second antibody (AS003 or AS014; ABclonal) and development with an enhanced chemiluminescence detection reagent (RPN2235; GE healthcare). Images were acquired with Amersham Imager 600 (GE Healthcare).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eELISA assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor detection of TMEM176B on exosomes harvested from patients\u0026rsquo; plasma or cell culture supernatant, 96-well ELISA plates were coated with 1 \u0026mu;g/ml of antibody against CD63 (Proteintech, 67605-1-Ig) (50 \u0026mu;l/well) overnight at 4\u0026nbsp;℃. Next day, free binding sites were blocked with 200 \u0026mu;l blocking buffer (PBS containing 0.5% BSA) for 1 h at room temperature. Then 5 \u0026mu;g of exosomes were added to each well. After incubation for 10 h at 4\u0026nbsp;℃, 0.5 \u0026mu;g/ml of rabbit monoclonal antibody against TMEM176B (6E8) diluted in PBS containing 0.5% BSA was added and incubated overnight at 4\u0026nbsp;℃. After washing with PBS, 100 \u0026mu;l of horseradish peroxidase-conjugated secondary antibody against rabbit (ABclonal, AS014) diluted in PBS containing 0.5% BSA was added into each well and incubated for 1 h at room temperature. After each step, the wells were washed by PBS three times. Plates were developed with SignalUp Super Sensitive ELISA Kit (Beyotime, P0205) and read within 30 min at 570/600 nm at Tecan Infinite E pelx. Recombinant TMEM176B protein was used to make a standard curve, and the result of standard curve demonstrated that the established ELISA exhibited a reliable linear detection range from 0.0078 to 1 \u0026mu;g/ml.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImmunofluorescence\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe adherent cells were seeded in advance on glass coverslips in 24-well plate, and suspension cells can be used immediately. Cells were fixed with 4% paraformaldehyde and permeabilized with 0.1% Triton X-100 for 30 min, and then blocked with PBS containing 0.1% Tween-20 and 5% BSA for 30 min at room temperature. Cells were then incubated with primary antibodies overnight at 4℃, followed by staining with fluorochrome-conjugated secondary antibodies for 1 h at room temperature. After washing with PBS, the stained slides were mounted with mounting medium containing DAPI (Beyotime, P0131). Confocal microscopy images were acquired with a Zeiss LSM 780 confocal microscope, and images were processed and analyzed using ZEN 2.0 software.\u003c/p\u003e\n\u003cp\u003ePurified B cells were activated with 1 \u0026mu;M of CpG DNA in RPMI-1640 complete medium for 48 h, and then pulsed with LCMV GP33 peptide for 1 h at 37\u0026thinsp;℃. 40 \u0026mu;g of exosomes carrying with Tmem176b-GFP fusion protein, were added into 3\u0026times;10\u003csup\u003e6\u003c/sup\u003e na\u0026iuml;ve P14 CD8\u003csup\u003e+\u003c/sup\u003e T and incubated for 24 h at 37\u0026thinsp;℃. After washing with PBS, exosome-pretreated na\u0026iuml;ve CD8\u003csup\u003e+\u003c/sup\u003e T cells were mixed with equal amount of GP33-pulsed B cells, and incubated for 10 min at 37\u0026thinsp;℃\u0026nbsp;in tubes to allow conjugate formation. Hereafter, the pellet was carefully resuspended and were plated on a poly-L-lysine-coated coverslip by spin at 2,000 rpm for 2 min. Then cells were fixed and permeabilized with precooled methanol for 10 min, washed 3 times with PBS, and blocked in PBS containing 1% BSA for 1 h at room temperature. Cells were incubated with primary antibody against Shp1 (Abclonal, A19111, 1:200) overnight at 4\u0026nbsp;℃, washed 4\u0026ndash;5 times, followed by staining with Alexa Fluor\u0026trade; 555-labelled Goat anti-Rabbit IgG (Invitrogen, A21429) for 1 h at room temperature. Cells were washed with PBS, and stained with Alexa Fluor\u003csup\u003e\u0026reg;\u003c/sup\u003e 647-labelled antibody against CD8 (Clone# 53-6.7, Biolegend, 100724) at 4\u0026nbsp;℃\u0026nbsp;for 2h. After three washings with PBS, cells were stained with DAPI in mounting medium (Beyotime, P0131) for 15 min at room temperature. Confocal microscopy images were acquired with a Zeiss LSM 780 confocal microscope, and images were processed and analyzed using ZEN 2.0 software. The Shp1 enrichment in the immune synapse was determined by using the equation: Shp1 enrichment (%)= Intensity\u003csub\u003esynapse\u003c/sub\u003e/Intensity\u003csub\u003eT cell\u0026nbsp;\u003c/sub\u003e\u0026times;100.\u003c/p\u003e\n\u003cp\u003eTo examine the presence of tumor-infiltrating CD8\u003csup\u003e+\u003c/sup\u003e T cells, tumors with suitable size were harvested and embedded in optimal cutting temperature compound (O.C.T., SAKURA, 4583). Sections of 15 \u0026mu;m were cut and mounted on coated slides, and the sections were fixed with BD Cytoperm/Cytofix (BD Bioscience, Cat#: 554722) solution (diluted with PBS at 1:2) for 30 min at room temperature, then washed twice for 10 min each with PBS. Nonspecific unions were blocked with PBS containing 1% normal mouse serum, 1% bovine serum albumin, and 0.3% Triton X-100 for 60\u0026thinsp;min at room temperature. Tissue sections were sequentially incubated with Alexa Fluor\u003csup\u003e\u0026reg;\u003c/sup\u003e 647 anti-mouse CD8\u0026alpha; (Clone# 53-6.7, Biolegend, Cat#100724) overnight at 4℃\u0026nbsp;and Hoechst 33342 (Thermo Fischer Scientific, Cat# H21492) for 10 min. After washing with PBS, the sections were mounted with Fluormount G (Southern Biotech, Cat#: 0100-01) and images were acquired on a Leica TCS SP8 confocal microscope. Images were analyzed with Imaris software (Bitplane).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImmunohistochemistry\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo validate the expression discrepancy of TMEM176B in human cancer clinical specimens, a tissue microarray containing 82 paired human colon cancer tissues (Superbiotek, Cat No. COC1601) were sequentially stained with an anti-TMEM176B antibody (Abclonal, Clone# 2F2), biotin-conjugated goat-anti-rabbit IgG antibody and Streptavidin-POD (Solarbio, SP0041) for 30 min at room temperature. Tissue microarray were then incubated with diaminobenzidine (Solarbio, DA1010) for 10\u0026thinsp;min, and were counterstained with haematoxylin and mounted with Neutral balsam (Solarbio, G8590). The slides were examined with a microscope (Leica, DM4B), digitally imaged using Zeiss AxioScan7 and analyzed using ImageJ software.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSingle-cell RNA-seq analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eB16F10 melanoma tumors were harvested from tumor-bearing mice as denoted and single-cell suspensions were prepared as described above. Viable CD45\u003csup\u003e+\u003c/sup\u003e tumor-infiltrating immune cells were sorted with BD Aria sorter, and then cells were counted and separated into droplet emulsions using the automated Chromium Controller (10\u0026times;Genomics). Libraries were constructed using the Single Cell 3\u0026prime; Library prepare protocol (10\u0026times;Genomics). The transcriptome profiles of individual cells were sequenced through combinatorial Probe-Anchor Synthesis (cPAS) on an DNBseq platform (MGI, China), and 100 bp paired end reads was generated. Sample demultiplexing, barcode processing, alignment, filtering, unique molecular identifier counting and aggregation of sequencing runs were performed using the Cell Ranger analysis pipeline (v6.1.2).\u003c/p\u003e\n\u003cp\u003eRaw unfiltered matrix was performed in R (v4.3.0) using the Seurat package (v4.3.0). Cell quality control was conducted based on the detected number of genes and the proportion of mitochondrial reads, following these specific steps:\u0026nbsp;ⅰ) Filtering out cells with fewer than 200 identified genes or more than 90% of the maximum gene count.\u0026nbsp;ⅱ) Sorting cells in descending order based on the proportion of mitochondrial reads and filtering out the top 6% (B16F10 tumors co-inoculated with exosomes or PBS) or 10% (Scramble or\u003cem\u003e\u0026nbsp;Tmem176b\u003c/em\u003e-deficient B16F10 tumors) of cells individually for each set of samples. Doublets were identified and removed using doublet detection R package DobuletFinder (v2.0.3), while cell cycle analysis was performed using the Seurat package\u0026apos;s CellCycleScoring function.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAfter scaling using the SCTransform function, the highly variable genes were identified using the Find Variable Features function. Subsequently, principal component analysis (PCA) was performed on the dataset using the top 2000 variable genes. To further reduce dimensionality and cluster the data, the UMAP (Uniform Manifold Approximation and Projection) method from the Seurat package was utilized to visualize the top 30 (B16F10 tumors co-inoculated with exosomes or PBS) or 40 (Scrambles or\u003cem\u003e\u0026nbsp;Tmem176b\u003c/em\u003e-deficient B16F10 tumor) principal components of each dataset. The UMAP analysis was performed with n.neighbors value of 50 and a learning rate of 100 for both sets of data.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe employed the Harmony algorithm, which was directly obtained from the R package harmony (v1.2.0), for data integration and batch effect correction. This algorithm allowed us to effectively align and harmonize different batches of single-cell RNA sequencing data, mitigating batch-specific variation and enhancing the comparability and reliability of our analyses.\u003c/p\u003e\n\u003cp\u003eThe \u0026quot;Find Clusters\u0026quot; functionality was utilized to perform clustering analysis. Unsupervised clustering employing a shared nearest neighbor modularity optimization-based algorithm with a resolution parameter of 0.8 (B16F10 tumors co-inoculated with exosomes or PBS) or 0.5 (Scramble or\u003cem\u003e\u0026nbsp;Tmem176b\u003c/em\u003e-deficient B16F10 tumors) resulted in the identification of 19 or 14 distinct clusters, respectively. To classify immune cell populations, differential expression analysis using the Wilcoxon rank-sum test was conducted to assess differential gene expression between each cluster and all other cells. The top differentially expressed genes for each cluster were cross-referenced with canonical markers representing various immune cell populations, allowing the generation of identifiable transcriptional marker sets for each of the 16 (B16F10 tumors co-inoculated with exosomes or PBS) or 11 (Scramble or\u003cem\u003e\u0026nbsp;Tmem176b\u003c/em\u003e-deficient B16F10 tumors) clusters in the two datasets, respectively. Dimplots were generated summarizing the features of 16 or 11 immune cell clusters. All visualizations were created using the ggplot2 (v3.4.4) R package.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGene signatures scoring\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe gene signatures utilized in this study were derived from the gene signature database summarized in Table S3. For CD8\u003csup\u003e+\u003c/sup\u003e T cells, gene signatures of \u0026lsquo;early activation\u0026rsquo;, \u0026lsquo;effector/cytokine\u0026rsquo; \u0026nbsp; and \u0026lsquo;Exhaustion\u0026rsquo; were described in previous publications\u003csup\u003e47,73\u003c/sup\u003e. For B cells, gene signature of \u0026lsquo;Exhaustion\u0026rsquo; was\u0026nbsp;curated by previous studies\u003csup\u003e46,74\u003c/sup\u003e. To assess the activity of each gene set, we employed the R package AUCell (v1.22.0). Initially, for each cell, we computed gene expression rankings using the AUCell_buildRankings function with default parameters based on the expression matrix. For each gene set and cell, area-under-the-curve (AUC) values were calculated using the AUCell_calcAUC function, utilizing the gene expression rankings. The AUC values represent the proportion of genes within the top-ranking genes of each cell that are defined as part of the corresponding gene set. Furthermore, for visualization purposes, we utilized the plot_density function from the Nebulosa (v1.10.0) R package to generate faceted plots.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn addition, we employed the \u0026quot;ssGSEA\u0026quot; method from the R package GSVA (v1.48.3) to calculate the scores/activities of the gene signatures. To examine the differences in gene feature score activities, we conducted Wilcoxon rank-sum tests. The results were visualized using violin plots to help data representation and visualization.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSurvival analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe metadata of ESCA (esophageal carcinoma), GBM (glioblastoma multiforme), HNSC (head and neck squamous cell carcinoma), KIRC (kidney renal clear cell carcinoma), KIRP (kidney renal papillary cell carcinoma), STAD (stomach adenocarcinoma), SKCM (skin cutaneous melanoma) were obtained from the TCGA database at the National Cancer Institute (https://gdc.cancer.gov). Patients were stratified into two groups based on the median expression level of the TMEM176B gene signature. Kaplan-Meier survival analysis was performed to estimate overall survival, and a log-rank test was employed to compare the differences in survival between the two patient groups.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll statistical analyses were performed using GraphPad Prism (v.8.2.1) or R software (v4.3.0). Unpaired two-sided student t-test was used to calculate significance, unless stated otherwise. Tumor growth were assessed by two-way ANOVA. Survival comparison was performed using log-rank (Mantel-Cox) test. scRNA-seq analysis was used two-sided Wilcoxon rank-sum test. Significance was assumed to be reached at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05. *P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ***P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, ****P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001. ns, not significant.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eScRNA-seq datasets that support the findings of this study have been deposited in the Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi) with accession number GSE254953 with a secure token ‘mzorcikevjwnbgt’. All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Xiufeng Sun, Lixin Hong, Xiaohong Ma, Qingfeng Liu, Lei Huang, Luming Yao, Changchuan Xie, Yaying Wu, Zheni Xu at the Core Facility of Biomedical Sciences, Xiamen University and Suqin Wu at the Xiamen University Laboratory Animal Center for technical assistance. We thank Dr. Zhongjun Dong at Tsinghua University for kindly providing \u003cem\u003ePtpn6\u003csup\u003efl/fl\u003c/sup\u003e\u003c/em\u003emice. This study was supported by the National Natural Science Foundation of China (31570883, 31770955, 31970851 to N.X., 82303111 to A.Y., 32070877 to W.-H.L., 81971557 to K.M., 32394003 to H.H.), the Fundamental Research Funds for the Central Universities of China-Xiamen University (20720150065 to N.X.), Xiamen Municipal Bureau of Science and Technology (3502Z20204003 to F.Y.), the National Key R\u0026amp;D Program of China (2020YFA0803500 to K.M., 2023YFC2306400 to H.H.) and and Major Project of Guangzhou National Laboratory (GZNL2024A02004 to H.H).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eX.G. and F.L. designed and executed the experiments, analyzed the data and prepared manuscript; A.Y., N.D., N.Y., C.N., F.Y. provided clinical samples and performed related experiments; Q.Z. analyzed high-throughput sequencing data under supervision of Q.L.; Y.J., F.X.L., Z.L., J.X., Q.Z., R.H., Y.Y.W., J.L., S.Z., Y.W., F.M., S.P.L. performed the experiments; S.Q.L. and X.C. helped in Immunofluorescence experiments; Y.C., Q.Y., Y.H., H.H., K.M. and W.-H.L. provided materials and study advices; F.Y. supervised and supported the project; N.X. conceived the study, designed the experiments, analyzed the data and wrote the manuscript with input from all authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eN.X., X.G., F.L. and Y.H. are inventors on pending patent applications filed by Xiamen University that cover the use of TMEM176B competitive peptides and anti-TMEM176B antibodies in cancer immunotherapy and cancer diagnosis. 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One major obstacle is tumor-driven impairment of T cell priming and early activation, however, the underlying mechanism remains elusive. Here we identify TMEM176B-positive exosomes specifically secreted by cancer cells in plasma of cancer patients rather than healthy donors, high levels of which correlate with worse prognosis and unfavorable outcomes of anti-PD1 therapy. A small-scale CRISPR-Cas9 screen discovers Tmem176b on tumor-derived exosomes as a negative regulator of T cell early activation. Genetic ablation of Tmem176b in mouse cancer cells substantially suppresses tumour growth in a CD8\u003csup\u003e+\u003c/sup\u003e T cell-dependent manner. Mechanistically, tumour-derived exosomal Tmem176b attenuates proximal T cell receptor signaling in CD8\u003csup\u003e+\u003c/sup\u003e T cells by recruiting tyrosine phosphatase Shp1 to immunological synapse. Blocking TMEM176B, either using neutralizing antibody or using competitive peptide to disrupt Tmem176b-Shp1 interaction, remarkably restrains tumour progression in models of mouse and human cancers, and synergizes with anti-PD1/PD-L1 therapy. Our findings not only uncover tumor-derived Tmem176b as a promising target for cancer immunotherapy, but also provide a potential non-invasive diagnostic tool to detect early cancer and predict clinical response to anti-PD1 therapy.\u003c/p\u003e","manuscriptTitle":"Cancer cells impede T cell early activation and drive immune evasion by transferring Tmem176b","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-07 07:45:37","doi":"10.21203/rs.3.rs-6199894/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-cancer","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"natcancer","sideBox":"Learn more about [Nature Cancer](http://www.nature.com/natcancer/)","snPcode":"","submissionUrl":"","title":"Nature Cancer","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Research","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"bcc0edec-8af8-4336-a271-3c4a68e872d9","owner":[],"postedDate":"July 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":45820933,"name":"Biological sciences/Immunology/Immune evasion"},{"id":45820934,"name":"Health sciences/Oncology/Cancer/Cancer microenvironment"},{"id":45820935,"name":"Health sciences/Oncology/Cancer/Cancer therapy/Cancer immunotherapy"},{"id":45820936,"name":"Health sciences/Oncology/Cancer/Tumour immunology"},{"id":45820937,"name":"Biological sciences/Immunology/Adaptive immunity/Cellular immunity/Lymphocyte activation"}],"tags":[],"updatedAt":"2026-01-05T15:54:30+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-07 07:45:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6199894","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6199894","identity":"rs-6199894","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}