HSP47 Destabilizes CD155 Through TRAF2 in Synergistic Anti-TIGIT Treatment of Osteosarcoma

HSP47 Destabilizes CD155 Through TRAF2 in Synergistic Anti-TIGIT Treatment of Osteosarcoma | 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 HSP47 Destabilizes CD155 Through TRAF2 in Synergistic Anti-TIGIT Treatment of Osteosarcoma Zhaoming Ye, Haochen Mou, Wenkan Zhang, Shixin Chen, Liang Chen, and 21 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3927870/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Heat shock protein 47 (HSP47) plays an essential role in correcting protein folding, and abnormal protein folding is closely related to tumorigenesis. However, the relationship between HSP47 and cancer immune response is poorly studied. Herein, HSP47 was found to be frequently overexpressed in human osteosarcomas. In animal models, HSP47 inhibition resulted in enhanced immune cell infiltration and function. Transcriptome data revealed that HSP47 negatively regulated CD155, a ligand of TIGIT. Immune checkpoint blockade therapy targeting the novel immune checkpoint molecule TIGIT is effective in limited patients. Further investigations are urgently needed to harness a robust response of this treatment. TIGIT antibody and HSP47-targeted therapy significantly inhibited the progression of osteosarcoma in mice and consequently prolonged survival. Mechanistically, inhibition of HSP47 attenuated TRAF2 protein ubiquitination and subsequently facilitated NF-κB-mediated CD155 transcription in HSP47-overexpressed osteosarcomas. Similarly, CD155 expression was significantly weakened in TRAF2-inhibited osteosarcoma cells. Collectively, our data revealed that targeting HSP47 could reinforce the expression of CD155 and therefore enhance the efficacy of anti-TIGIT treatment, providing a promising strategy for cancer immunotherapy. Biological sciences/Cancer/Oncogenes Biological sciences/Cancer/Sarcoma Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 INTRODUCTION Osteosarcoma (OS) is a malignant mesenchymal tumor with high heterogeneity characterized by rapid progression, early metastasis, poor prognosis, complex treatment and susceptibility to recurrence[ 1 , 2 ]. Currently, the standard treatment for osteosarcoma is intensive chemotherapy in combination with surgery. However, there has been limited promotion in patient survival over the past decades, with only 20% survival at five years for patients with metastatic or recurrent osteosarcoma[ 3 , 4 ]. Heat shock proteins (HSPs) play important roles in the biology nature of cancers[ 5 – 7 ]. Our work herein identified HSP47 as a highly expressed target in OS. This protein has been described as an essential component for the proper protein folding. Several types of cancer were reported to be associated with abnormal protein folding [ 8 – 12 ], which may be conducted by HSPs. The role of HSP47 in the development and progression of osteosarcoma remains unknown, and whether it plays an important role in the tumor immune response is also poorly understood. Immunotherapy, primarily immune checkpoint blockade (ICB), has been shown to be effective in a sheer volume of malignant tumors and has been hailed as the "fourth therapy" beyond conventional treatment[ 13 – 15 ]. T-cell immune receptor with immunoglobulin and ITIM structural domains (TIGIT) is a promising new target for cancer immunotherapy[ 16 ]. Preclinical studies have shown that TIGIT blockade can prevent the progression of various solid and hematologic cancers[ 17 – 24 ]. TIGIT interacts with the CD155 expressed on antigen-presenting or tumor cells to impair T-cell and natural killer (NK) cell function[ 16 , 17 , 25 – 30 ]. Interestingly, TIGIT also acts to regulate the activity of CD226, a second costimulatory recept or that works in parallel with CD28 [ 4 , 31 ]. CD226 can promote functional interactions between effector immune cells and tumor cells expressing CD155[ 32 ], while this CD226-CD155 interaction is interrupted by TIGIT-CD155 axis. Therefore, modalities facilitate CD155 expression may strengthen the effect of anti-TIGIT therapy in cancers. Tumor necrosis factor (TNF) receptor-associated factor-2 (TRAF2) is a protein that interacts with TNF receptor 2 (TNFR2) and is involved in the activation of the classical nuclear factor-kappa B (NF-κB) pathway[ 33 – 35 ]. It has been reported that the NF-κB signaling pathway regulates the expression immune checkpoints [ 36 ]. However, whether it may be involved in the regulation of other immune checkpoints remains unknown. In this study, we studied TRAF2 regulation by HSP47-mediated ubiquitination and its role in mediating NF-κB/CD155 axis to control CD8 + T-cell-mediated immune surveillance in osteosarcoma. We revealed that HSP47 altered CD155 levels and that HSP47 upregulation was strongly associated with mortality in osteosarcoma patients. We also elucidated the regulatory relationship of NF-κB with the immune checkpoint CD155. Therapeutically, targeting HSP47 with TIGIT antibody showed favored results in treating osteosarcoma. METHODS Ethical approval The Ethics Committee of SAHZU approved this study, which complied with the Declaration of Helsinki. All patients were informed and signed an informed consent form. Patients, fresh osteosarcoma tissue collection and peripheral blood extraction Patients diagnosed with OS from 2017 to 2023 at the Musculoskeletal Tumor Center of SAHZU were included in this study for IHC staining, and OS patients from 2020-2023 were included for fresh tissue flow cytometry. Formalin was used to preserve tumor tissue requiring paraffin sectioning, and tissue preservation solution (Solarbio, SR0020) was used for flow cytometry. Peripheral blood from osteosarcoma patients was collected prior to the start of surgery, and the specimen was processed for further studies within 4 hours (details below). Reagents, cell lines and cell culture Five human osteosarcoma cell lines (MNNG/HOS (hereafter referred to as HOS), U2OS, MG63, 143B, and SAOS2), the BALB/C mouse osteosarcoma cell line K7M2, human umbilical vein endothelial cells (HUVECs), and the human embryonic kidney cell line 293T were purchased from the Cell Collection of the Chinese Academy of Sciences and used in this study. All cells were tested for mycoplasma by a mycoplasma detection kit (#4460626, Thermo Fisher) and were guaranteed to be free of contamination. DNA short tandem repeat (DNA STR) genotyping was performed to authenticate the osteosarcoma cell lines. HOS, MG63, 143B, SAOS2, K7M2, and 293T cells and HUVECs were cultured in a 5% CO 2 atmosphere at 37 °C in DMEM with 10% FBS. U2OS cells were cultured in RPMI 1640 medium. Transfection of stable cell lines using lentivirus Short hairpin RNA (shRNA) constructs targeting HSP47 (human and mouse) and TRAF2 (human) and the overexpression plasmid (human) were purchased from OBiO Technology Corp., Ltd. (Shanghai, China). The mature antisense sequence of HSP47 (human) was 5’-TGCTAGTCAACGCCATGTTCT-3’. The mature antisense sequence of HSP47 (mouse) was 5’-TCCCTGGGTCTTGTGTCACT-3’. The mature antisense sequence of TRAF2 (human) was 5’-CCTTCCCAGATAATGCTGCCC-3’. Lentiviruses with ineffective shRNA (pHBLVshCtrl, pGMLV-shCtrl, pGV248-shCtrl) provided by the manufacturer were used during the knockdown study as a control. The antisense sequence was 5’-TTCTCCGAACGTGTCACGT-3’. In general, cells were seeded into six-well plates at a density of 2 x 10 5 cells per well to generate cell lines with stable silencing or overexpression of the targeted genes using shRNAs and overexpression plasmids. After incubation for 24 h, the cells were transfected with lentiviral particles. After that, the culture medium without lentivirus or plasmid was replaced, and the culture was continued for two days. Then, the transfected cells were selected using puromycin at the indicated concentrations before use. Quantitative real-time PCR TRIzol reagent (#15596018, Thermo Fisher) was used to extract total RNA, and reverse transcription was achieved with a cDNA Synthesis Kit (#6610, Takara). Gene-specific primers and SYBR Premix Ex TaqTM kits (#RR420, Takara) were used to measure mRNA levels with an ABI StepOnePlus System (Applied Biosystems). Real-time PCR software (version 2.4) was used to acquire and analyze the data. The relative expression results were normalized to GADPH levels by the ΔΔCT method. The HSP47 primers were as follows: human HSP47 forward 5’-TCAGTGAGCTTCGCTGATGAC-3’ and reverse 5’-CATGGCGTTGACTAGCAGGG-3’; human GADPH forward 5’-GGAGCGAGATCCCTCCAAAAT-3’ and reverse 5’-GGCTGTTGTCATACTTCTCATGG-3’. Coimmunoprecipitation (co-IP) and Western blot Osteosarcoma tissues or cells were lysed in precooled RIPA lysis buffer (#89901, Thermo Fisher Scientific) with phosphatase inhibitors (#78420, Thermo Fisher Scientific) and protease (#78428 Thermo Fisher Scientific). Centrifugation was performed at 15000 x g for 15 minutes at 4 °C to remove insoluble components. The concentration of extracted protein lysate was measured by the BCA Protein Assay Kit (#23227, Thermo Fisher Scientific). For co-IP, the cell supernatant was incubated with magnetic A/G beads (Beyotime, P2179M) for 12 h at 4 °C. After washing with IP buffer, the beads were boiled in SDS buffer to denature and elute the bound protein. Immunoblotting was performed to detect coimmunoprecipitates. For Western blotting, quantitated lysates were separated through SDS‒PAGE and transferred to methanol-pretreated PVDF membranes (#LC2002, Thermo Fisher). The membrane was then blocked with 5% nonfat milk for 60 mins at room temperature and immunoblotted with primary antibodies at 4 °C for 10-15 hours. The washing buffer used for all procedures consisted of Tris-buffered saline with 0.1% Tween-20 (TBST; #P9416, Sigma). After incubation with a specific HRP-conjugated secondary antibody for 1 hour at room temperature, the protein bands were detected with ECL detection kits and an AmershamTM ImageQuantTM 800 Western blot imaging system (ImageQuant 800 Control software v2.0.0). Flow cytometry and fluorescence-activated cell sorting (FACS) Adherent cell CD155 level measurement. The adhered cells growing in plates were digested using pancreatic enzymes or collected with a cell scraper. Tumor infiltrating T-cell (TIL) and organ analysis. Tumor, lung, spleen and liver tissue samples were cut into tiny pieces using sharp blades and then dissociated in RPMI 1640 medium containing collagenase type IV (2 mg/ml; Sigma), hyaluronidase (0.1 mg/ml; Sigma), DNase (0.1 mg/ml; Sigma), and BSA (2 mg/ml; Sigma). All the dissociated tissues were passed through 100-μm filters to acquire single cells. Peripheral blood mononuclear cells (PBMCs) Blood collected in an anticoagulation tube was diluted 1:1 with PBS and gently added to the top of the lymphocyte isolate. A fast ascending and slow descending centrifugation procedure was applied to obtain a single layer of lymphocyte cells. For cell surface protein staining, cells were incubated with suitable antibodies in a light-proof environment for 20-30 min at room temperature. To detect CD107a expression, cells were cultured in medium containing myristate acetate (PMA, 5 µg/ml, MCE, HY-18739 ) and monensin (NSC, 343257) for 5 hours at 37 °C. For intracellular protein staining, after surface staining, the cells were fixed with Fix/Perm solution (BD Biosciences) for 15 min and permeabilized with Perm/Wash buffer (BD Biosciences) for 20 min. Then, the cells were incubated with antibodies in a light-proof environment for 20-30 min at room temperature. Flow cytometry data analysis was performed using Beckman Coulter CytoFLEX LX and CytExpert v2.4 software and analyzed with FlowJo v10. S Beckman MoFlo Astrios EQs instrument and Summit v6.3.1 software were used to perform FACS. Histology, hematoxylin and eosin (H&E), immunofluorescence and immunohistochemical staining Human or mouse osteosarcoma tissues were collected and soaked in a 4% paraformaldehyde solution. After dehydration and paraffin embedding, the tissues were sliced into continuous sections of 5 µm thickness. Hematoxylin and eosin (H&E) staining was performed using a standard protocol in a Leica Autostainer XL. Cell lysates were placed in 24-well plates in advance for immunofluorescence, and cells were inoculated into the wells. Osteosarcoma cells were fixed in 4% formaldehyde for 15 minutes at room temperature. Sections with tissue were treated with xylene and graded alcohol and then boiled in citric acid buffer for antigen repair. Then, specimens or cells were incubated with 0.03% Triton X-100 (#X100, Sigma) in PBS for 10 min at room temperature and blocked with 5% BSA (Sigma) for 20 min at room temperature. Then, the specimens or cells were incubated with primary antibodies at 4 °C for 10-15 h. After returning to room temperature, the tissue or cells were incubated with specific secondary antibodies for one hour. Finally, slides were coverslipped with DAPI-containing mountant 237 (#P36971, Thermo Fisher). PBS washes were performed between each of the above processes, and the final high-resolution images were captured with a Leica DMi8 microscope. For immunohistochemistry, antigen repair, permeabilization, blocking of tissue sections and incubation with primary antibodies were performed as described above. The appropriate histochemistry-specific HRP-conjugated secondary antibody was selected and incubated with the tissue sections at 37 °C for 20 mins. Then, DAB reagent was used for color development. Finally, the sections were counterstained with hematoxylin. A microscope (Leica) and Leica Application Suite X v3.7.4 software were used to capture high-definition images. Statistical analysis GraphPad Prism (version 9) was used for statistical analysis. Two-tailed Student’s t test, one-way ANOVA and two-way ANOVA were performed to compare significant differences between the two groups. Values of P < 0.05 were considered to indicate statistical significance. The log-rank (Mantel‒Cox) test as described in the figure legend was performed to analyze the Kaplan‒Meier survival curves of the mice. The P value indicates * P＜0.05, **, P＜0.01, ***, P＜0.001 and ****, P＜0.0001. Mice, animal orthotopic osteosarcoma model and in vivo drug treatment Four- to six-week-old female BALB/C mice and four- to six-week-old female BALB/C nude mice were purchased from Hangzhou Medical College. All strains of mice were raised under specific-pathogen-free (SPF) conditions, and the Institutional Animal Care and Use Committee (SAHZU) approved all the animal studies. For the BALB/C nude mouse subcutaneous graft tumor model, each 4-week-old female BALB/c nude mouse was injected subcutaneously near the scapula with 2 × 10 6 shCtrl K7M2 and shHSP47 K7M2 cells suspended in 100 μl PBS; the mice were sacrificed 21 days later. For the BALB/C mouse tibia orthotopic osteosarcoma model, shCtrl or shHSP47 K7M2 cells were injected into the tibia through the tibial plateau, and intraperitoneal (i.p.) TIGIT (BioXCell, BE0274) treatment started 7 days after tumor injection at 200 μg/g of body weight every 3 days for 15 days. The mice were sacrificed 5 days after stopping the treatment. None of the above-obtained tumors exceeded the maximum tumor size (1500 mm 3 ) approved by the ethics committee. RNA-seq analysis RNA-seq analysis was performed for U2OS cells or U2OS cells treated with HSP47 shRNA. The density of cells in the 6-well plate was 2 × 10 5 cells/well. Total RNA was isolated using RNAiso plus (Thermo Fisher, 15596018) according to the manufacturer’s instructions. After three washes with PBS to remove platelets, the cells were harvested with TRIzol and stored at -80 °C. Total RNA was used to construct sequencing libraries. After rRNA removal, mRNA was enriched with fragment buffer, cut into short fragments, and then reverse-transcribed into cDNA with random primers. The cDNA fragment was purified, end-repaired, poly(A) tailed, and ligated to the Illumina sequencing adapter. The cDNA library was sequenced by Gene Denovo Biotech Co. (Guangzhou, China) using an Illumina NovaSeq 6000. Differentially expressed genes (DEGs) were identified by analyzing the differential RNA expression between the two groups. Transcripts with FDR <0.05 and absolute fold changes greater than or equal to 2 were considered to be differentially expressed. All the genetic changes are summarized in Supplementary file 1. Antibodies Information on all antibodies used in this study is provided in Supplementary Table 1. RESULTS TIGIT is highly expressed on CD8+ T cells especially in tumor environment TIGIT expression was evaluated in PBMC, intratumoral (IT) regions and in peritumoral (PT) regions in patients with OS. Sample collection criteria was shown in Figure 3A. TIGIT was expressed by a large percentage of OS-infiltrating CD8+ T cells, and its expression was significantly higher than that on CD4+ T cells (Figure 3B-E). Similarly, the expression of TIGIT in OS was also found in IT and negative in PT and control from immunohistochemistry (Figure 3F-G). Spatially, the expression of TIGIT showed a colocalization relationship with IT CD8+ T-cells as illustrated by immunofluorescence in human and mouse specimens (Figure 3H, Figure S6). Similarly, orthotopic osteosarcoma mouse model , revealed high-frequency of TIGIT expression on CD8+ T cells in the tumor, spleen, liver and lungs, and TIGIT expression increased with increasing tumor-bearing days (Figure 3I-J). These results indicated that TIGIT is highly expressed in osteosarcoma and is significantly correlated with CD8+ T cells. TIGIT-positive CD8+ T cells displayed impaired function in osteosarcoma patients. The phenotypes of TIGIT+ T-cells were studied. We found that TIGIT expression on OS patient PBMCs was higher than that on CD8+ T cells from healthy donor PBMCs (Figure 3K). TIGIT+CD8+ T cells from OS patients exhibited decreased PD-1 IL-2, CD69, perforin (PFP), and CD107a expression (Figure 3L-N, Figure S7A-B). Moreover, we found that CD226 expression was significantly reduced in cells with high TIGIT expression, suggesting that TIGIT regulates CD226 (Figure 3O). We also compared the phenotypes of TIGIT+ CD8+ T-cell subsets with that of TIGIT– CD8+ T-cell subsets. The expression of lysosome marker CD107a, glycoprotein PFP, and the costimulant receptor CD226 were weakened in TIGIT+ T-cells, suggesting that the TIGIT+ CD8+ T cells possessed reduced effector function and antitumor potential (Figure S7C-F). In addition, a lower proportion of TIGIT+ CD8+ cells had surface expression of the activating receptor CD226, and a higher proportion expressed inhibitory receptors, including PD-1. T he e xpression of HSP47 is upregulated in osteosarcoma and associated with poor prognosis. To investigate the role HSPs play in OS, we screened altered gene expression in cancers. We observed that SEPINH1 (HSP47) showed a correlation with survival in both the univariate Cox test and Kaplan‒Meier (KM) survival analysis in the TARGET-OS and GSE datasets. Moreover, HSP47 was highly expressed in osteogenic cells of relapse samples compared with primary samples and showed a higher positive expression rate in osteosarcoma samples than in healthy bone marrow (Figure S1 A-C).HSP47 was upregulated in most cancers (Figure 1A) and sarcomas (Figure 1B) according to GEPIA tools. The CCLE online web tool showed the transcription level of HSP47 in different osteosarcoma cell lines (Figure 1C). HUVECs were used as a control (Figure 1D). The protein expression levels of HSP47 in HUVECs and different osteosarcoma cell lines were consistent with the transcript levels (Figure 1E). Similarly, the protein expression of HSP47 in osteosarcoma tissues was higher than that in adjacent nontumor tissues according to Western blot analysis (Figure 1F-G) and IHC (Figure 1H-I) staining of patient samples. Finally, the survival data indicated that overexpression of HSP47 shortened the disease-free survival time (log-rank P = 0.019) and overall survival time (log-rank P = 0.016) of osteosarcoma patients (Figure 1J-K). HSP47 activation correlates with CD155 downregulation in multiple cancers. As HSP47 was discovered to be associated with the prognosis of OS, the mechanism by which HSP47 regulates tumor progression needs to be further explored. RNA-seq data analysis was performed in U2OS cells with or without shHSP47 treatment (Figure 2A). In addition, CD155 upregulation mediated by HSP47 small molecule inhibitor col003 was observed in osteosarcoma cell lines. Osteosarcoma cell CD155 levels were significantly upregulated in U2OS and K7M2 cells treated with col003, whereas there was no obvious increase in CD155 expression levels in the HOS cell line, which has lower HSP47 levels (Figure 2B-C). After constructing the shHSP47-transfected U2OS cells and HSP47-overexpression vector-transfected HOS cells (Figure S2A), we revealed that the expression level of CD155 was increased after HSP47 knockdown by shRNAs in the U2OS and K7M2 cell lines. In contrast, the expression level of CD155 was decreased in HOS cells overexpressing HSP47 (Figure 2D-F). The results also showed that the HSP47 small molecule inhibitor Col003 did not affect CD155 expression in HUVECs (Figure S3A). Strikingly, HSP47 knockdown by shRNAs and HSP47 overexpression were associated with the growth and proliferation of osteosarcoma cells in vitro and in vivo (Figure S2B-E). At the same time, HSP47 also affected the epithelial–mesenchymal transition process in osteosarcoma, which may provide some value for future research (Figure S2F-K). To verify our findings in other tumor cell lines, we selected two other reported lung cancer A549 cell lines and breast cancer BT-474 cell lines with high expression of HSP47 (Figure S3B). In vivo study showed similar results. We analyzed the correlation between the expression of HSP47 and CD155 in immunodeficient mice (WT or shHSP47 K7M2 subcutaneous tumor-bearing model). CD155 expression was elevated in K7M2 osteosarcoma mouse models with HSP47 knockdown compared with WT (Figure 2G). These findings supported the clinical relevance of HSP47 activation associated with CD155 downregulation. The TNF-related pathway is involved in the regulation of CD155 expression by HSP47. To identify the regulatory factor that bridges HSP47 and CD155, we first analyzed the differences between U2OS and HSP47 shRNA-treated U2OS cells by RNA-seq. RNA-seq results and KEGG pathway enrichment analysis suggested that the DEGs in OS cell lines treated with HSP47 shRNA were correlated with negative regulation of TNF-related pathways (Figure 4A-B). Therefore, we hypothesized that the TNF-related pathway regulated the change in CD155 protein levels by HSP47 regulation. After stimulating osteosarcoma cells with exogenous TNF-α, we observed by immunofluorescence, western blot, and flow cytometry that changes in CD155 protein levels in osteosarcoma cells were concentration- and time-dependent (Figure 4C-G). Upon evaluating the effect of HSP47 activation on TNF regulation of CD155 expression, we found that the expression of p65 protein was downregulated or increased in HOS and U2OS cells treated with HSP47 overexpression or shHSP47, respectively (Figure 4H), which indicated that HSP47 negatively regulated p65 pathway proteins. To verify whether the changes in CD155 protein expression levels caused by the TNF-related pathway were dominated by HSP47, a rescue experiment was performed to confirm that CD155 could be restored (Figure 4I-J). Meanwhile, the application of exogenous TNF-α and its specific inhibitor etanercept also rescued CD155 expression in HOS and U2OS cells according to Western blot analyses (Figure 4K). The results above showed that the TNF-related pathway was involved in the regulation of CD155 expression by HSP47. HSP47 negatively regulates TRAF2 through the ubiquitin‒proteasome pathway. To understand how HSP47 regulated the TNF-related pathway and thereby regulated CD155, we transfected osteosarcoma cells with HSP47 shRNA and performed RNA-seq data analysis, which revealed that the RNA level of TRAF2, an essential protein regulating the TNF-related pathway, did not change significantly (Figure 5A). In contrast, the protein expression level of TRAF2 was significantly increased, as shown by Western blotting (Figure 5B), immunohistochemistry in the shHSP47 K7M2 subcutaneous tumor-bearing mouse model (Figure 5C) and immunofluorescence in U2OS or K7M2 cell lines (Figure S8A). These results showed that the level of TRAF2 mRNA with HSP47 shRNA was not substantially upregulated in accordance with the protein levels. Based on this observation, we sought to determine whether a posttranslational pathway was the most relevant to TRAF2 upregulation in osteosarcoma cells by screening common protein degradation pathways using a proteasome inhibitor (MG132) and several autophagy inhibitors (Figure S9A-B). Our results revealed that only MG132 significantly increased TRAF2 in osteosarcoma cells and that this change could be reversed by cycloheximide (CHX) (Figure S9C-D). Overall, this suggested that changes in TRAF2 levels might be related to a posttranslational modification of the protein, specifically, that HSP47 might be involved in the ubiquitination-mediated degradation of the TRAF2 protein, thereby regulating the expression of the CD155 protein. These results confirmed that HSP47 might participate in TRAF2 degradation mediated by the ubiquitin‒proteasome pathway (UPP). TRAF2 in osteosarcoma cells was pulled down by immunoprecipitation and subjected to ubiquitination analysis. Although TRAF2 had notable basal ubiquitination, HSP47 interference abolished the ubiquitination of TRAF2 in U2OS and K7M2 cells (Figure 5D, Figure S9E). Consistent with this observation, treatment with the HSP47 inhibitor col003 also significantly inhibited TRAF2 ubiquitination (Figure 5E, Figure S9F). In contrast, HSP47 overexpression aggravated the ubiquitination of TRAF2 in HOS cells (Figure 5F). These results supported the notion that HSP47 activation induced TRAF2 ubiquitination in osteosarcoma cells. Moreover, TRAF2 protein was degraded when HSP47 was overexpressed in HOS cells (Figure 5G) and accumulated after treatment with HSP47 shRNA in U2OS cells (Figure 5H), as shown by immunofluorescence, a finding consistent with Western blot and immunohistochemistry data. Pulse-chase analysis using cycloheximide (CHX) revealed that HSP47 deletion significantly prolonged the half-life of the TRAF2 protein in U2OS and K7M2 cells, whereas HSP47 overexpression significantly shortened the TRAF2 protein half-life (Figure 5I-K). These findings demonstrated that a proteasome-regulated mechanism in HSP47-expressing osteosarcoma cells degraded TRAF2. To confirm the relationship between HSP47 and TRAF2, we performed co-IP experiments. The results showed that HSP47 could interact with TRAF2 (Figure S10A-C). In addition, confocal immunofluorescence microscopy also revealed that HSP47 colocalized with TRAF2 at the cell surface of osteosarcoma cells (Figure S10D-F). TRAF2 regulates the expression of CD155 protein through N f- κB. To further explore the potential connection between TRAF2 and CD155, we first examined the CD155 protein expression levels in shCtrl HOS and shTRAF2 HOS cells. Flow cytometric imaging, immunofluorescence microscopy, and Western blotting revealed that the expression level of CD155 in HOS cells was downregulated after silencing the TRAF2 protein compared with that in the control group (Figure 6A-D) Interestingly, the changes in the protein level of CD155 could be reversed by exogenous TNF-α stimulation (Figure 6E). Simultaneously, the expression levels of the p65 channel and phosphorylated p65 protein in HOS cells were downregulated with shTRAF2 treatment (Figure 6D). CD155 rescue upon the stimulation of exogenous TNF-α in HOS and U2OS cells was further enhanced by the p65-specific inhibitor Bay (Figure 6F). These results suggested that TRAF2 regulated the expression of CD155 protein through NF-κB. HSP47 blockade showed synergistic effects with a nti-TIGIT therapy in cancer by facilitating CD8+ T-cells response Because HSP47 inhibition could simultaneously inhibit tumor growth(Figure S4) and regulate the stability of CD155, we sought to determine whether HSP47 inhibition could facilitate anti-TIGIT treatment. Immune competent tumor-bearing mouse models were established (Figure 7A). Macroscopic imaging showed that the tumor volume was lower in the anti-TIGIT and shHSP47 groups than in the untreated group. The combination of anti-TIGIT and shHSP47 significantly improved the treatment of tibial osteosarcoma (Figure 7B-D). The combined therapy also notably prolonged the survival of mice with tumors (Figure 7E). These results all indicated that anti-TIGIT and shHSP47 therapies have an antitumor effect that is most apparent when they are combined. The status of tumor-infiltrate T-cells were evaluated The results from flow cytometric analysis showed that K7M2 osteosarcoma-bearing mice treated with combination therapy could experience tumor growth suppression through the inhibition of cell proliferation and stimulation of antitumor immune responses centered around CD8+ T cells (Figure 7F-K). IHC also demonstrated the same results, which showed that CD8+ T cells in the combination treatment group had increased infiltration and more substantial immune killing function (Figure 7L-M). DISCUSSION Dysfunction in immune surveillance plays an essential role in the occurrence and development of cancer[37, 38]. A few immune checkpoints were identified for potential therapeutic targets to prompt a robust anti-cancer immune response. Among them, medicines targeting TIGIT was being tested in clinical trials. However, the interaction between CD155 and TIGIT/CD226 immune checkpoint receptors and ligands is complicated[26, 39-43]. Some studies have highlighted that the expression of CD155 plays a vital role in anti-TIGIT therapy[39-41] and that the expression of CD155 is related to the poor survival and prognosis of sarcoma patients (Figure S4). Our study showed that downregulation of CD155 was regulated by the activation of HSP47-related pathway. In osteosarcoma activated by HSP47, CD155 expression levels were elevated after inhibition of HSP47. More importantly, we found that HSP47-silenced animal models of osteosarcoma were more sensitive to CD8+ T cells in the presence of TIGIT monoclonal antibodies. Therefore, HSP47 might be a promising predictive biomarker and therapeutic target for immunotherapy or combination therapy. However, the detailed mechanism of CD155 regulation by HSP47 was still unclear. Here, we elucidated the internal pathway of CD155 regulation through a series of in vivo and in vitro experiments. Abnormal regulation of HSP47 plays a key role in tumorigenesis and tumor progression, and HSP47 is overexpressed in various tumors and is associated with poor prognosis[8, 44-48]. However, there are limited studies on the effect of HSP47 on immune checkpoints. In our study, we found that HSP47 knockout slowed tumor growth and promoted the infiltration of immune cells (Figure S5A-D). Moreover, HSP47-knockout tumors had a more sensitive response against TIGIT mAb than did wild-type tumors. As a novel immune checkpoint, the regulatory mechanism of CD155 is poorly understood. Our data herein indicated that transcriptional and posttranscriptional modifications of CD155 were implemented via the HSP47/TRAF2/NF-κB axis. The activation of HSP47 in osteosarcoma degrades the TRAF2 protein by ubiquitination and downregulates phosphorylation in the NF-κB pathway and that activation or phosphorylation of NF-κB activates its ability to transcribe the CD155 protein. High expression of TRAF2 is associated with better overall survival in sarcoma, and TRAF2 regulates HSP47-dependent NF-κB activation to enhance CD155 transcription levels. High expression of TRAF2 is associated with better overall survival in sarcoma (Figure S8B), and TRAF2 regulates HSP47-dependent NF-κB activation to enhance CD155 transcription levels. Here, we found that ubiquitination by HSP47 led to the degradation of the TRAF2 protein, thereby reducing NF-κB pathway activation and CD155 protein transcription. Meanwhile, exogenous TNF-α enhanced TRAF2/NF-κB pathway activation and increased CD155 protein expression, which modulated the sensitivity to the TIGIT/CD226 interaction between osteosarcoma and CD8+ T cells. This finding highlighted the role of TRAF2 in cell communication in a tumor-friendly environment and the mutual regulation between immune and tumor cells. Finally, in a mouse model, the combination of TIGIT mAb and HSP47 shRNA significantly improved the effectiveness of this current ICB and targeted therapy. In summary, this work identified that HSP47-targeted therapy increased the sensitivity of osteosarcoma to TIGIT monoclonal therapy through a bypass mechanism of HSP47-activated and TRAF2/NF-κB-dependent CD155 downregulation. This regulation conferred a change in cancer cell immune sensitivity along the CD155/CD226/TIGIT axis. In osteosarcoma cells, HSP47-mediated inhibition of the CD155/TIGIT axis enhanced the toxic effects of CD8+ T cells and promoted immune cell infiltration. Therefore, these results might change our understanding of TIGIT mAb combination therapy and target-free combination therapy in osteosarcoma and provide an attractive way to make cancer cells more susceptible to target-free combination therapy. The efficacy of this combination therapy in patients with OS should be further evaluated to determine whether it can eradicate tumors, delay tumor progression, or delay tumor recurrence. Declarations Conflict of interest : The authors declare no potential conflicts of interest. References Bielack, S.S., et al., Prognostic factors in high-grade osteosarcoma of the extremities or trunk: an analysis of 1,702 patients treated on neoadjuvant cooperative osteosarcoma study group protocols . J Clin Oncol, 2002. 20(3): p. 776–90. Beird, H.C., et al., Osteosarcoma. Nat Rev Dis Primers, 2022. 8(1): p. 77. Isakoff, M.S., et al., Osteosarcoma: Current Treatment and a Collaborative Pathway to Success . J Clin Oncol, 2015. 33(27): p. 3029–35. Wang, Z., et al., Metabolic control of CD47 expression through LAT2-mediated amino acid uptake promotes tumor immune evasion . Nat Commun, 2022. 13(1): p. 6308. Dudeja, V., S.M. Vickers, and A.K. Saluja, The role of heat shock proteins in gastrointestinal diseases . Gut, 2009. 58(7): p. 1000–9. Calderwood, S.K., et al., Heat shock proteins in cancer: chaperones of tumorigenesis . Trends Biochem Sci, 2006. 31(3): p. 164–72. Calderwood, S.K. and J. Gong, Heat Shock Proteins Promote Cancer: It's a Protection Racket . Trends Biochem Sci, 2016. 41(4): p. 311–323. Zhu, J., et al., Chaperone Hsp47 Drives Malignant Growth and Invasion by Modulating an ECM Gene Network . Cancer Res, 2015. 75(8): p. 1580–91. Yoneda, A., K. Minomi, and Y. Tamura, HSP47 promotes metastasis of breast cancer by interacting with myosin IIA via the unfolded protein response transducer IRE1alpha . Oncogene, 2020. 39(23): p. 4519–4537. Zhao, D., et al., Heat shock protein 47 regulated by miR-29a to enhance glioma tumor growth and invasion . J Neurooncol, 2014. 118(1): p. 39–47. Cao, D., et al., Expression of novel markers of pancreatic ductal adenocarcinoma in pancreatic nonductal neoplasms: additional evidence of different genetic pathways . Mod Pathol, 2005. 18(6): p. 752–61. Poschmann, G., et al., Identification of proteomic differences between squamous cell carcinoma of the lung and bronchial epithelium . Mol Cell Proteomics, 2009. 8(5): p. 1105–16. Olson, B., et al., Mouse Models for Cancer Immunotherapy Research . Cancer Discov, 2018. 8(11): p. 1358–1365. Pan, C., et al., Next-generation immuno-oncology agents: current momentum shifts in cancer immunotherapy . J Hematol Oncol, 2020. 13(1): p. 29. Marabelle, A., et al., Intratumoral immunotherapy: using the tumor as the remedy . Ann Oncol, 2017. 28(suppl_12): p. xii33-xii43. Chauvin, J.M. and H.M. Zarour, TIGIT in cancer immunotherapy . J Immunother Cancer, 2020. 8(2). Chauvin, J.M., et al., TIGIT and PD-1 impair tumor antigen-specific CD8(+) T cells in melanoma patients . J Clin Invest, 2015. 125(5): p. 2046–58. Zhou, G., et al., Antibodies Against Immune Checkpoint Molecules Restore Functions of Tumor-Infiltrating T Cells in Hepatocellular Carcinomas . Gastroenterology, 2017. 153(4): p. 1107–1119 e10. Tassi, E., et al., Early Effector T Lymphocytes Coexpress Multiple Inhibitory Receptors in Primary Non-Small Cell Lung Cancer . Cancer Res, 2017. 77(4): p. 851–861. O'Brien, S.M., et al., Function of Human Tumor-Infiltrating Lymphocytes in Early-Stage Non-Small Cell Lung Cancer . Cancer Immunol Res, 2019. 7(6): p. 896–909. Lee, W.J., et al., Expression of lymphocyte-activating gene 3 and T-cell immunoreceptor with immunoglobulin and ITIM domains in cutaneous melanoma and their correlation with programmed cell death 1 expression in tumor-infiltrating lymphocytes . J Am Acad Dermatol, 2019. 81(1): p. 219–227. Kong, Y., et al., T-Cell Immunoglobulin and ITIM Domain (TIGIT) Associates with CD8 + T-Cell Exhaustion and Poor Clinical Outcome in AML Patients . Clin Cancer Res, 2016. 22(12): p. 3057–66. Guillerey, C., et al., TIGIT immune checkpoint blockade restores CD8(+) T-cell immunity against multiple myeloma . Blood, 2018. 132(16): p. 1689–1694. Raphael, I., et al., TIGIT and PD-1 Immune Checkpoint Pathways Are Associated With Patient Outcome and Anti-Tumor Immunity in Glioblastoma . Front Immunol, 2021. 12: p. 637146. Freed-Pastor, W.A., et al., The CD155/TIGIT axis promotes and maintains immune evasion in neoantigen-expressing pancreatic cancer . Cancer Cell, 2021. 39(10): p. 1342–1360 e14. Lupo, K.B. and S. Matosevic, CD155 immunoregulation as a target for natural killer cell immunotherapy in glioblastoma . J Hematol Oncol, 2020. 13(1): p. 76. Kucan Brlic, P., et al., Targeting PVR (CD155) and its receptors in anti-tumor therapy . Cell Mol Immunol, 2019. 16(1): p. 40–52. He, W., et al., CD155T/TIGIT Signaling Regulates CD8(+) T-cell Metabolism and Promotes Tumor Progression in Human Gastric Cancer . Cancer Res, 2017. 77(22): p. 6375–6388. Yu, X., et al., The surface protein TIGIT suppresses T cell activation by promoting the generation of mature immunoregulatory dendritic cells . Nat Immunol, 2009. 10(1): p. 48–57. Johnston, R.J., et al., The immunoreceptor TIGIT regulates antitumor and antiviral CD8(+) T cell effector function . Cancer Cell, 2014. 26(6): p. 923–937. Chiang, E.Y. and I. Mellman, TIGIT-CD226-PVR axis: advancing immune checkpoint blockade for cancer immunotherapy . J Immunother Cancer, 2022. 10(4). Gilfillan, S., et al., DNAM-1 promotes activation of cytotoxic lymphocytes by nonprofessional antigen-presenting cells and tumors . J Exp Med, 2008. 205(13): p. 2965–73. Siegmund, D., J. Wagner, and H. Wajant, TNF Receptor Associated Factor 2 (TRAF2) Signaling in Cancer. Cancers (Basel), 2022. 14(16). Vallabhapurapu, S., et al., Nonredundant and complementary functions of TRAF2 and TRAF3 in a ubiquitination cascade that activates NIK-dependent alternative NF-kappaB signaling . Nat Immunol, 2008. 9(12): p. 1364–70. Zarnegar, B.J., et al., Noncanonical NF-kappaB activation requires coordinated assembly of a regulatory complex of the adaptors cIAP1, cIAP2, TRAF2 and TRAF3 and the kinase NIK . Nat Immunol, 2008. 9(12): p. 1371–8. Lim, S.O., et al., Deubiquitination and Stabilization of PD-L1 by CSN5 . Cancer Cell, 2016. 30(6): p. 925–939. Feng, M., et al., Phagocytosis checkpoints as new targets for cancer immunotherapy . Nat Rev Cancer, 2019. 19(10): p. 568–586. Waldman, A.D., J.M. Fritz, and M.J. Lenardo, A guide to cancer immunotherapy: from T cell basic science to clinical practice . Nat Rev Immunol, 2020. 20(11): p. 651–668. Braun, M., et al., CD155 on Tumor Cells Drives Resistance to Immunotherapy by Inducing the Degradation of the Activating Receptor CD226 in CD8(+) T Cells . Immunity, 2020. 53(4): p. 805–823 e15. Briukhovetska, D., et al., T cell-derived interleukin-22 drives the expression of CD155 by cancer cells to suppress NK cell function and promote metastasis . Immunity, 2023. 56(1): p. 143–161 e11. Banta, K.L., et al., Mechanistic convergence of the TIGIT and PD-1 inhibitory pathways necessitates co-blockade to optimize anti-tumor CD8(+) T cell responses . Immunity, 2022. 55(3): p. 512–526 e9. O'Donnell, J.S., et al., Tumor intrinsic and extrinsic immune functions of CD155 . Semin Cancer Biol, 2020. 65: p. 189–196. Feng, M., et al., BCL9 regulates CD226 and CD96 checkpoints in CD8(+) T cells to improve PD-1 response in cancer . Signal Transduct Target Ther, 2021. 6(1): p. 313. Pan, X., et al., Circular RNA circ-TNPO3 inhibits clear cell renal cell carcinoma metastasis by binding to IGF2BP2 and destabilizing SERPINH1 mRNA . Clin Transl Med, 2022. 12(7): p. e994. Tian, S., et al., SERPINH1 regulates EMT and gastric cancer metastasis via the Wnt/beta-catenin signaling pathway . Aging (Albany NY), 2020. 12(4): p. 3574–3593. Cai, H.Q., et al., FKBP10 promotes proliferation of glioma cells via activating AKT-CREB-PCNA axis . J Biomed Sci, 2021. 28(1): p. 13. Maloney, A., et al., Gene and protein expression profiling of human ovarian cancer cells treated with the heat shock protein 90 inhibitor 17-allylamino-17-demethoxygeldanamycin . Cancer Res, 2007. 67(7): p. 3239–53. Xiong, G., et al., Hsp47 promotes cancer metastasis by enhancing collagen-dependent cancer cell-platelet interaction . Proc Natl Acad Sci U S A, 2020. 117(7): p. 3748–3758. Tables Table 1 is available in the Supplementary Files section. Additional Declarations There is no duality of interest Supplementary Files Table1.pdf supplement.pdf Supplementary material S1.HSP47 is highly expressed on osteosarcoma in TARGET and GSE, which is associated with poor prognosis. A. Survival curves of HSP47 high and low groups in TARGET and GSE databases. B. SEPINH1(HSP47) has a higher expression in osteogenic cells of relapse samples compared with primary samples, and shows a higher positive expressing rate in OS sample compared with healthy bone marrow. S2. HSP47 regulates the biological behavior of OS. A. Western-blot images show that HSP47 protein levels are significantly increased or reduced in U2OS cells, HOS cells, shHSP47 transfected U2OS cells, HSP47-overexpression vector transfected HOS cells, and their corresponding controls. GAPDH was used as a control. B. Representative images of colonies in shHSP47 transfected U2OS cells, HSP47-overexpression vector transfected HOS cells, and their corresponding controls. C. Weight of OS in tumor-bearing WT or shHSP47 Immune deficiency mice (mean ± s.d., n=4) D. Immunohistochemical staining images for HSP47 and Ki67 expression in WT or shHSP47 K7M2 cells of balb/c Immune deficiency mouse. E. CCK-8 assays show proliferation of U2OS cells, HOS cells, shHSP47 transfected U2OS cells, HSP47-overexpression vector transfected HOS cells, and their corresponding controls for 24h, 48h,72h, 96h. Scale bars in images indicate 45 μm. F. Transwell invasion assays show increased invasion of HSP47-overexpression vector transfected HOS cells and reduced invasion of shHSP47 transfected U2OS cells. G. Histogram plots show the total number of invasion shHSP47 transfected U2OS cells, HSP47-overexpression vector transfected HOS cells, and their corresponding controls. H. Wound healing assays show the distance between shHSP47 transfected U2OS cells, HSP47-overexpression vector transfected HOS cells, and their corresponding controls. I. Quantitative analysis of wound healing assay in shHSP47 transfected U2OS cells, HSP47-overexpression vector transfected HOS cells, and their corresponding controls. J. Western-blot images show EMT-related protein(claudin, vimentin, WNT) levels in HOS or U2OS cells treated with HSP47-overexpressed plasmid or HSP47 shRNA. GAPDH is used as a control. K. Immunohistochemical staining images for E-cadherin and N-cadherin expression in WT or shHSP47 K7M2 cells of balb/c Immune deficiency mouse. Scale bars in images indicate 60 μm. P<0.05, ** P<0.01, *** P<0.001, **** P<0.0001, and ns not significant. S3. HSP47 downregulates CD155 expression in lung and breast cancer but doesn’t work on normal cells. A. Western blot representative images show the CD155 expression in HUVECs cells with different concentrations of Col003 treatment. GAPDH is used as a control. B. Western blot representative images show the CD155 expression in A549, or BT-474, cells with HSP47 shRNA treatment. GAPDH is used as a control. S4. Survival curve of CD155 expression level in OS. The overall survival rate in the low/high CD155 group is analyzed by the GEPIA web tool ( href="http://gepia.cancer-pku.cn/" target="/Users/haochenmou/Documentsx/_blank">http://gepia.cancer-pku.cn/). S5. HSP47 prevents the invasion of CD8+T cells in OS. A. Weight of OS in tumor-bearing mice (mean ± s.d., n=5). B. Correlation between HSP47 and infiltrating immune cells in sarcoma, with different colors representing different immune cell types. C. Flow cytometry analysis and a statistical diagram showing the total proportion of CD8+ T cells in mice OS (mean ± s.d., n=5). P<0.05, ** P<0.01, *** P<0.001, **** P<0.0001, and ns not significant. S6. Representative multiplexed immunofluorescence image of Balb/C mice primary OS samples. TIGIT (green) is distributed broadly within the human or mouse OS tissues. Tumor-infiltrating lymphocyte cells were revealed by CD8a (red) positivity. The merged image shows the colocalization of TIGIT and CD8a. Nuclei are stained with DAPI (blue). Scale bars in images indicate 300 μm (above). S7. TIGIT is highly expressed on human PBMCs and impaires immune function of CD8+T cells. A. Representative and quantitation of flow cytometry plots of TIGIT and PD-1 coexpression on CD8+ T cells from human OS peripheral blood (n=13). B. Representative and quantitation of flow cytometry plots of TIGIT and IL-2coexpression on CD8+ T cells from human OS peripheral blood (n=13). C. CD107a and PFP production by CD8+ T cells were measured by flow cytometry. Representative flow charts are shown. D. Percentages and quantitation of CD107a and PFP producing CD8+TIGIT+ or CD8+TIGIT- cells (n=8). E. CD69 and CD226 production by CD8 T cells was measured by flow cytometry. Representative flow charts are shown. F. Percentages and quantitation of CD69 and CD226 producing CD8+TIGIT+ or CD8+TIGIT- cells (n=8). P<0.05, ** P<0.01, *** P<0.001, **** P<0.0001, and ns not significant. S8. HSP47 negatively regulates TRAF2 and the survival curve of TRAF2 in OS. A. Immunofluorescence microscopy images for TRAF2 (red) and DAPI (blue) of U2OS and HOS cells with HSP47 overexpression processing or HSP47 shRNA treatment. Scale bars in images indicate 20 μm. B. The overall survival rate in the low/high TRAF2 group is analyzed by the GEPIA web tool ( href="http://gepia.cancer-pku.cn/">http://gepia.cancer-pku.cn/). S9. HSP47 participates in the ubiquitination process of TRAF2. A-B. Western-blot analysis for TRAF2 levels in HOS (A), U2OS (B) cells with different treatments. GAPDH is used as a control. C. Western-blot images show that after adding proteasome inhibitor MG132 in HOS (left), U2OS (middle) and K7M2 (right) cell lines, TRAF2 expression is detected at 0h,3h,6h,9h. GAPDH is used as a control. D. Western-blot images show that TRAF2 expression levels HOS (left), U2OS (middle) and K7M2 (right) cells with or without MG132 or CHX culture. GAPDH is used as a control. E-F. Co-immunoprecipitation analysis of the ubiquitination of endogenous TRAF2 in K7M2 cells treated with HSP47 shRNA (E) or Col003 (F). S10. HSP47 interactes with TRAF2. A-C. Immunofluorescence images for TRAF2 (red), HSP47 (green) and DAPI (blue) of HOS, U2OS and K7M2 cells. Scale bars in images indicate 30 μm. Intensity profiles of TRAF2 (red lines) and HSP47 (green lines) co-localization signals are shown in plotted lines at three random sites. D. The immunoprecipitation analysis of the TRAF2 in the HOS, HOS-HSP47. (Continuation of Figure 6. F) E. The immunoprecipitation analysis of the HSP47 in the HOS, HOS-HSP47, U2OS, shHSP47-U2OS. Non-silencing shRNA or vector-blank is used as a control. S11. Gating strategies of flow cytometry analyses. A. Gating logic for tumour-infiltrating immune cells. B. Gating logic for Flow fluorescence intensity of CD155+ OS cells. 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Medicine","correspondingAuthor":false,"prefix":"","firstName":"Binghao","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2024-02-04 14:20:57","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3927870/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3927870/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":51388075,"identity":"186fc97c-951b-4fa0-91e5-95195fdc9444","added_by":"auto","created_at":"2024-02-20 18:03:13","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1257720,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHSP47 expression is upregulated in tumors and OS, associated with poor prognosis.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. mRNA expression of HSP47 level of Pan-cancer and normal tissue are analyzed by online GEPIA web tool (\u003ca href=\"http://gepia.cancer-pku.cn/\" target=\"/Users/haochenmou/Documentsx/_blank\"\u003ehttp://gepia.cancer-pku.cn/\u003c/a\u003e).\u003c/p\u003e\n\u003cp\u003eB. mRNA expression of HSP47 of sarcoma and normal tissue are analyzed by GEPIA web tool (\u003ca href=\"http://gepia.cancer-pku.cn/\" target=\"/Users/haochenmou/Documentsx/_blank\"\u003ehttp://gepia.cancer-pku.cn/\u003c/a\u003e).\u003c/p\u003e\n\u003cp\u003eC. mRNA expression of HSP47 in 5 OS cell lines are analyzed by CCLE web tool (\u003ca href=\"http://sites.broadinstitute.org/ccle\" target=\"/Users/haochenmou/Documentsx/_blank\"\u003ehttp://sites.broadinstitute.org/ccle\u003c/a\u003e).\u003c/p\u003e\n\u003cp\u003eD. QT-PCR detection of HSP47 expression in HUVECS and OS cells.\u003c/p\u003e\n\u003cp\u003eE. Western blot analysis of the protein level of HSP47 in HUVECs and OS cell lines. GAPDH is used as a control.\u003c/p\u003e\n\u003cp\u003eF-G. The protein level of HSP47 in OS specimens and adjacent non-tumor tissues (n=7) are detected by Western blot analysis. GAPDH is used as a control.\u003c/p\u003e\n\u003cp\u003eH-I. IHC detection and quantitation of HSP47 level in human OS (n=21) and adjacent non-tumor tissues (n=20). Scale bars in images indicate 120 μm.\u003c/p\u003e\n\u003cp\u003eJ-K. The disease-free survival and overall survival rate in low/high HSP47 group are analyzed by the GEPIA web tool (\u003ca href=\"http://gepia.cancer-pku.cn/\" target=\"/Users/haochenmou/Documentsx/_blank\"\u003ehttp://gepia.cancer-pku.cn/\u003c/a\u003e).\u003c/p\u003e\n\u003cp\u003e* P\u0026lt;0.05, ** P\u0026lt;0.01, *** P\u0026lt;0.001, **** P\u0026lt;0.0001, and ns not significant.\u003c/p\u003e","description":"","filename":"figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-3927870/v1/3991849a6575ce1d589d2927.png"},{"id":51388073,"identity":"83f73cc8-5110-4342-af07-e8aa0da05fd4","added_by":"auto","created_at":"2024-02-20 18:03:13","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1320582,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHSP47 downregulates CD155 expression in OS in vitro and in vivo.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. RNA-seq analysis is performed using U2OS and HSP47 knocked-down U2OS cells.\u003c/p\u003e\n\u003cp\u003eB. Flow cytometric images and the quantification diagrams of CD155 expression levels of HOS and U2OS cells after Col003 (50um) are stimulated for 24h compared to non-stimulated (mean ± s.d., n=5).\u003c/p\u003e\n\u003cp\u003eC. Western blot representative image show the CD155 expression in HOS U2OS cells with Col003 treatment. GAPDH is used as a control.\u003c/p\u003e\n\u003cp\u003eD. Immunofluorescence microscopy images for CD155 (red) and DAPI (blue) of U2OS and HOS cells with HSP47 overexpression processing or HSP47 shRNA treatment. Scale bars in images indicate 45μm.\u003c/p\u003e\n\u003cp\u003eE. Flow cytometric images and the quantification diagrams of CD155 expression levels of U2OS and U2OS cells after HSP47 knockdown by shRNA or HOS and overexpression HSP47 HOS cells (mean ± s.d., n=5).\u003c/p\u003e\n\u003cp\u003eF. Western blot images show the CD155 expression in HOS, HOS-HSP47 cells and U2OS, shHSP47 U2OS cells. GAPDH is used as a control.\u003c/p\u003e\n\u003cp\u003eG. Immunohistochemical staining images for CD155 expression in WT or shHSP47 K7M2 cells of balb/c mouse. Scale bars in images indicate 45 μm.\u003c/p\u003e\n\u003cp\u003e* P\u0026lt;0.05, ** P\u0026lt;0.01, *** P\u0026lt;0.001, **** P\u0026lt;0.0001, and ns not significant.\u003c/p\u003e","description":"","filename":"figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-3927870/v1/1c1adb0f8ccc1d59ee50737b.png"},{"id":51388076,"identity":"e6ada039-50bd-4baf-bd5f-578f044cd881","added_by":"auto","created_at":"2024-02-20 18:03:13","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1946595,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTIGIT is highly expressed on OS TILs and PBMCs, which impaires immune function of CD8+T cells.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. Surgically resected chemotherapy-free osteosarcomas or biopsy tissues and peripheral blood were used to analyze the expression of TIGIT.\u003c/p\u003e\n\u003cp\u003eB. Representative flow cytometry plots of TIGIT expression on CD4+T cells from human osteosarcoma tissue and peripheral blood.\u003c/p\u003e\n\u003cp\u003eC. Quantitation of TIGIT expression as a percentage of total CD4+T cells from human osteosarcoma tissue and peripheral blood.\u003c/p\u003e\n\u003cp\u003eD. Representative flow cytometry plots of TIGIT expression on CD8+T cells from human osteosarcoma tissue and peripheral blood.\u003c/p\u003e\n\u003cp\u003eE. Quantitation of TIGIT expression as a percentage of total CD8+T cells from human osteosarcoma tissue and peripheral blood.\u003c/p\u003e\n\u003cp\u003eF. Different grade and negative control of immunohistochemistry images for TIGIT in human osteosarcoma and adjacent specimen.Scale bars in images indicate 400 μm and 120μm.\u003c/p\u003e\n\u003cp\u003eG. Quantitation of immunohistochemistry images for TIGIT in human osteosarcoma and adjacent specimen.\u003c/p\u003e\n\u003cp\u003eH. Representative multiplexed immunofluorescence image of human primary osteosarcoma samples. TIGIT (green) was distributed broadly within the human or mouse osteosarcoma tissues. Tumor-infiltrating lymphocyte cells were revealed by CD8a (red) positivity. The merged image shows the colocalization of TIGIT and CD8a. Nuclei were stained with DAPI (blue). Scale bars in images indicate 300 μm (above).\u003c/p\u003e\n\u003cp\u003eI. Various times after tibial injection of 2×10\u003csup\u003e6\u003c/sup\u003e K7M2 cells (n=5 mice per group) of immunohistochemistry images for TIGIT in bearing mice model. Scale bars in images indicate 100 μm.\u003c/p\u003e\n\u003cp\u003eJ. Frequency of TIGIT+ CD8+T cells in mice's spleen, liver, lungs and TILs at various times after tibial injection of 2×10\u003csup\u003e6\u003c/sup\u003e K7M2 cells (n=5 mice per group).\u003c/p\u003e\n\u003cp\u003eK. Representative flow cytometry contour plots of TIGIT expression on CD8+ T cells from healthy donor peripheral blood and human OS peripheral blood.\u003c/p\u003e\n\u003cp\u003eL.Representative and quantitation of flow cytometry plots of TIGIT and CD69 coexpression on CD8+ T cells from human OS peripheral blood (n=13).\u003c/p\u003e\n\u003cp\u003eM. Representative and quantitation of flow cytometry plots of TIGIT and CD107a coexpression on CD8+ T cells from human OS peripheral blood (n=12).\u003c/p\u003e\n\u003cp\u003eN. Representative and quantitation of flow cytometry plots of TIGIT and perforin (PFP) coexpression on CD8+ T cells from human OS peripheral blood (n=13).\u003c/p\u003e\n\u003cp\u003eO. Representative and quantitation of flow cytometry plots of TIGIT and CD226 coexpression on CD8+ T cells from human OS peripheral blood (n=14).\u003c/p\u003e\n\u003cp\u003e* P\u0026lt;0.05, ** P\u0026lt;0.01, *** P\u0026lt;0.001, **** P\u0026lt;0.0001, and ns not significant.\u003c/p\u003e","description":"","filename":"figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-3927870/v1/f1337344fe1fa3e65736b07f.png"},{"id":51388080,"identity":"8d5af031-b0fe-492a-89b7-283fa11c9cb4","added_by":"auto","created_at":"2024-02-20 18:03:14","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1068170,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTNF-α\u003c/strong\u003e \u003cstrong\u003erelated pathway is involved in the level expression of CD155 regulated by HSP47.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. KEGG pathway enrichment in significantly down-regulated or up-regulated genes, the change of TNF signalling is the most obvious.\u003c/p\u003e\n\u003cp\u003eB. Gene set enrichment analysis (GSEA), the TNF signalling pathway significantly differed in the HSP47 lentivirus transfection group.\u003c/p\u003e\n\u003cp\u003eC. Immunofluorescence microscopy images for CD155 (red) and DAPI (blue) of different concentrations (10ng/ml, 20ng/ml, 30ng/ml) of TNF-α factor stimulated HOS (left) or U2OS (right) cell line for 24h. Scale bars in images indicate 60 μm.\u003c/p\u003e\n\u003cp\u003eD-E. Flow cytometry analysis and statistical plots of CD155 expression in U2OS and K7M2 cells treated with TNF-α (mean ± s.d., n=5).\u003c/p\u003e\n\u003cp\u003eF. CD155 and TRAF2 expression of Western blot analysis of K7M2 (left), HOS (middle), and U2OS (right) cells treated with TNF-α (20 ng/ml) for concentration (10ng/ml, 20ng/ml, 30ng/ml). GAPDH is used as a control.\u003c/p\u003e\n\u003cp\u003eG. Western blot analysis of K7M2 (left), HOS (middle), and U2OS (right) cells treated with TNF-α (20 ng/ml) for different times (0h, 6h,12h,24h). GAPDH is used as a control.\u003c/p\u003e\n\u003cp\u003eH. Western blot representative images show the p-65 expression in HOS and U2OS treated with HSP47 overexpression or HSP47 shRNA.\u003c/p\u003e\n\u003cp\u003eI. Western blot representative images show the CD155 expression in HOS-ctrl, HOS-HSP47 or treated with TNF-α. GAPDH is used as a control.\u003c/p\u003e\n\u003cp\u003eJ. Western blot representative images show the CD155 expression in K7M2 and U2OS (ctrl, shHSP47, and treated with TNF-α-induced pathway inhibitors, BAY). GAPDH is used as a control.\u003c/p\u003e\n\u003cp\u003eK. Western blot representative images show the CD155 expression in HOS and U2OS (treated with TNF-α and its inhibitor Etanercept). GAPDH is used as a control.\u003c/p\u003e\n\u003cp\u003e* P\u0026lt;0.05, ** P\u0026lt;0.01, *** P\u0026lt;0.001, **** P\u0026lt;0.0001, and ns not significant.\u003c/p\u003e","description":"","filename":"figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-3927870/v1/9510645ab777b6cbb79a8714.png"},{"id":51388079,"identity":"d23eb7c2-4365-4cc2-9bd9-6ac3cff12235","added_by":"auto","created_at":"2024-02-20 18:03:14","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1159773,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHSP47 negatively regulates TRAF2 through the ubiquitin-proteasome.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. RNA-seq analysis shows the RNA expression of TRAF2 in U2OS and shHSP47 U2OS cells.\u003c/p\u003e\n\u003cp\u003eB. Western blot representative images show the CD155 expression in HOS or U2OS cell lines treated with HSP47 overexpression or shHSP47. GAPDH is used as a control.\u003c/p\u003e\n\u003cp\u003eC. Immunohistochemistry images for TRAF2 of WT or shHSP47 K7M2 tumor-bearing mice. Scale bars in images indicate 45 μm.\u003c/p\u003e\n\u003cp\u003eD-F. Co-immunoprecipitation analysis of the ubiquitination of endogenous TRAF2 in U2OS cells treated with HSP47 shRNA (D) or Col003 (E), HOS (F) cells treated with overexpressed plasmid.\u003c/p\u003e\n\u003cp\u003eG-H. Immunofluorescence of HOS (G) from ctrl or HSP47 overexpressed plasmid and U2OS (H) from ctrl or shHSP47-treated cells stained for TRAF2 (red), DAPI (blue). Dotted regions provide magnified insets. Scale bars in images indicate 20 μm.\u003c/p\u003e\n\u003cp\u003eI-K.Western blot representative images show the expression of TRAF2 and HSP47 in HOS (I), U2OS (J), and K7M2 (K) cells treated with HSP47 overexpression or shHSP47 in the presence of cycloheximide (CHX) for an indicated period. GAPDH is used as a control. The quantification of TRAF2 degradation kinetics in indicated groups after treatment with CHX is the below.\u003c/p\u003e\n\u003cp\u003e* P\u0026lt;0.05, ** P\u0026lt;0.01, *** P\u0026lt;0.001, **** P\u0026lt;0.0001, and ns not significant.\u003c/p\u003e","description":"","filename":"figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-3927870/v1/8e0e703201559704dc39aa6b.png"},{"id":51388081,"identity":"d2b1b94f-1b0e-466d-bb06-e1d08c3c18a6","added_by":"auto","created_at":"2024-02-20 18:03:14","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":713656,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTRAF2 regulated the expression of CD155 protein through NF-κB.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA-B. Flow cytometric images and the quantification diagrams of CD155 expression levels of HOS and HOS cells after TRAF2 knockdown by shRNA (mean ± s.d., n=5).\u003c/p\u003e\n\u003cp\u003eC. Immunofluorescence microscopy images for CD155(red) and DAPI (blue) of HOS cells with TRAF2 shRNA treatment. Scale bars in images indicate 45 μm.\u003c/p\u003e\n\u003cp\u003eD. Western blot representative images show the TRAF2, CD155, p65, and p-p65 expression in shCtrl or shTRAF2 HOS cells. GAPDH was used as a control.\u003c/p\u003e\n\u003cp\u003eE. Western blot representative images show the CD155 expression in shCtrl or shTRAF2 HOS (treated with or without TNF-α ). GAPDH is used as a control.\u003c/p\u003e\n\u003cp\u003eF. Western blot representative images show the CD155 expression in HOS or U2OS (treated with TNF-α and Bay). GAPDH is used as a control.\u003c/p\u003e\n\u003cp\u003e* P\u0026lt;0.05, ** P\u0026lt;0.01, *** P\u0026lt;0.001, **** P\u0026lt;0.0001, and ns not significant.\u003c/p\u003e","description":"","filename":"figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-3927870/v1/f7c772667f68a150074696c4.png"},{"id":51388082,"identity":"ed55c068-d66d-4a01-82aa-727ea821d84e","added_by":"auto","created_at":"2024-02-20 18:03:14","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1646070,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA combination of HSP47 blockade and anti-TIGIT therapy displays excellent anti-tumor activity in Balb/C mice.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. Design of experiments to assess the combined therapeutic efficacy in a Balb/C mice model implanted with tibia OS K7M2 cells. Schematic representation of experimental design, group allocation and treatment regimens.\u003c/p\u003e\n\u003cp\u003eB. Kaplan–Meier survival analysis of groups with different treatment.\u003c/p\u003e\n\u003cp\u003eC. Macroscopic image of Balb/C mice bearing K7M2/sh-HSP47 K7M2 in different groups.\u003c/p\u003e\n\u003cp\u003eD. Weight of tibia with OS in tumor-bearing mice (mean ± s.d., n=5).\u003c/p\u003e\n\u003cp\u003eE. Volume of tibia with OS in tumor-bearing mice (mean ± s.d., n=5).\u003c/p\u003e\n\u003cp\u003eF-I. Flow cytometry analysis and statistical diagram showing the total proportion of CD226+CD8+ T cells, CD107a+CD8+ T cells and PFP+CD8+ T cells in tumor (mean ± s.d., n=7).\u003c/p\u003e\n\u003cp\u003eJ-K. Flow cytometry analysis and a statistical diagram showing the INF-γ and TNF-α mean fluorescence intensity of CD8+ T cells in tumor (mean ± s.d., n=5).\u003c/p\u003e\n\u003cp\u003eL. H\u0026amp;E-stained sections of tumors, and immunohistochemistry images for CD8, Granzyme B, in different K7M2 tibia OS-bearing mice model groups. Scale bars in images indicate 60 μm.\u003c/p\u003e\n\u003cp\u003eM. Statistical analyses of IHC quantification results for samples depicted in (L) (n = 5 mice per group).\u003c/p\u003e\n\u003cp\u003e* P\u0026lt;0.05, ** P\u0026lt;0.01, *** P\u0026lt;0.001, **** P\u0026lt;0.0001, and ns not significant.\u003c/p\u003e","description":"","filename":"figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-3927870/v1/7907cfc67354d2a1812fc094.png"},{"id":51388077,"identity":"2f31671b-bab7-47a2-956a-905df7265790","added_by":"auto","created_at":"2024-02-20 18:03:13","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":5713,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSchematic showing HSP47-TRAF2-CD155 axis in HSP47 activated osteosarcoma cancer and the specific mechanism of combined anti-TIGIT treatment of osteosarcoma.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"placeholderimage.png","url":"https://assets-eu.researchsquare.com/files/rs-3927870/v1/bce4783362365954eaebffa3.png"},{"id":52753301,"identity":"fd05d646-2582-4839-aec2-3496af96d79e","added_by":"auto","created_at":"2024-03-15 10:59:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4707852,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3927870/v1/f7d6ea88-015d-4736-ad5c-5285e39573be.pdf"},{"id":51389459,"identity":"15c20357-01ca-4606-9fa1-f7cd73aedd2d","added_by":"auto","created_at":"2024-02-20 18:11:13","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":318592,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3927870/v1/1f9653ce3e9e187f5141aa5b.pdf"},{"id":51388083,"identity":"da9e5ad5-ad80-4b91-958e-e655c3cb9014","added_by":"auto","created_at":"2024-02-20 18:03:14","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":7779578,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eS1.HSP47 is highly expressed on osteosarcoma in TARGET and GSE, which is associated with poor prognosis.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. Survival curves of HSP47 high and low groups in TARGET and GSE databases.\u003c/p\u003e\n\u003cp\u003eB. SEPINH1(HSP47) has a higher expression in osteogenic cells of relapse samples compared with primary samples, and shows a higher positive expressing rate in OS sample compared with healthy bone marrow.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eS2. HSP47 regulates the biological behavior of OS.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. Western-blot images show that HSP47 protein levels are significantly increased or reduced in U2OS cells, HOS cells, shHSP47 transfected U2OS cells, HSP47-overexpression vector transfected HOS cells, and their corresponding controls. GAPDH was used as a control.\u003c/p\u003e\n\u003cp\u003eB. Representative images of colonies in shHSP47 transfected U2OS cells, HSP47-overexpression vector transfected HOS cells, and their corresponding controls.\u003c/p\u003e\n\u003cp\u003eC. Weight of OS in tumor-bearing WT or shHSP47 Immune deficiency mice (mean ± s.d., n=4)\u003c/p\u003e\n\u003cp\u003eD. Immunohistochemical staining images for HSP47 and Ki67 expression in WT or shHSP47 K7M2 cells of balb/c Immune deficiency mouse.\u003c/p\u003e\n\u003cp\u003eE. CCK-8 assays show proliferation of U2OS cells, HOS cells, shHSP47 transfected U2OS cells, HSP47-overexpression vector transfected HOS cells, and their corresponding controls for 24h, 48h,72h, 96h. Scale bars in images indicate 45 μm.\u003c/p\u003e\n\u003cp\u003eF. Transwell invasion assays show increased invasion of HSP47-overexpression vector transfected HOS cells and reduced invasion of shHSP47 transfected U2OS cells.\u003c/p\u003e\n\u003cp\u003eG. Histogram plots show the total number of invasion shHSP47 transfected U2OS cells, HSP47-overexpression vector transfected HOS cells, and their corresponding controls.\u003c/p\u003e\n\u003cp\u003eH. Wound healing assays show the distance between shHSP47 transfected U2OS cells, HSP47-overexpression vector transfected HOS cells, and their corresponding controls.\u003c/p\u003e\n\u003cp\u003eI. Quantitative analysis of wound healing assay in shHSP47 transfected U2OS cells, HSP47-overexpression vector transfected HOS cells, and their corresponding controls.\u003c/p\u003e\n\u003cp\u003eJ. Western-blot images show EMT-related protein(claudin, vimentin, WNT) levels in HOS or U2OS cells treated with HSP47-overexpressed plasmid or HSP47 shRNA. GAPDH is used as a control.\u003c/p\u003e\n\u003cp\u003eK. Immunohistochemical staining images for E-cadherin and N-cadherin expression in WT or shHSP47 K7M2 cells of balb/c Immune deficiency mouse. Scale bars in images indicate 60 μm.\u003c/p\u003e\n\u003cp\u003e* P\u0026lt;0.05, ** P\u0026lt;0.01, *** P\u0026lt;0.001, **** P\u0026lt;0.0001, and ns not significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eS3. HSP47 downregulates CD155 expression in lung and breast cancer but doesn’t work on normal cells.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. Western blot representative images show the CD155 expression in HUVECs cells with different concentrations of Col003 treatment. GAPDH is used as a control.\u003c/p\u003e\n\u003cp\u003eB. Western blot representative images show the CD155 expression in A549, or BT-474, cells with HSP47 shRNA treatment. GAPDH is used as a control.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eS4. Survival curve of CD155 expression level in OS.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe overall survival rate in the low/high CD155 group is analyzed by the GEPIA web tool (\u003ca href=\"http://gepia.cancer-pku.cn/\" target=\"/Users/haochenmou/Documentsx/_blank\"\u003ehttp://gepia.cancer-pku.cn/\u003c/a\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eS5. HSP47 prevents the invasion of CD8+T cells in OS.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. Weight of OS in tumor-bearing mice (mean ± s.d., n=5).\u003c/p\u003e\n\u003cp\u003eB. Correlation between HSP47 and infiltrating immune cells in sarcoma, with different colors representing different immune cell types.\u003c/p\u003e\n\u003cp\u003eC. Flow cytometry analysis and a statistical diagram showing the total proportion of CD8+ T cells in mice OS (mean ± s.d., n=5).\u003c/p\u003e\n\u003cp\u003e* P\u0026lt;0.05, ** P\u0026lt;0.01, *** P\u0026lt;0.001, **** P\u0026lt;0.0001, and ns not significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eS6. Representative multiplexed immunofluorescence image of Balb/C mice primary OS samples.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTIGIT (green) is distributed broadly within the human or mouse OS tissues. Tumor-infiltrating lymphocyte cells were revealed by CD8a (red) positivity. The merged image shows the colocalization of TIGIT and CD8a. Nuclei are stained with DAPI (blue). Scale bars in images indicate 300 μm (above).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eS7. TIGIT is highly expressed on human PBMCs and impaires immune function of CD8+T cells.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. Representative and quantitation of flow cytometry plots of TIGIT and PD-1 coexpression on CD8+ T cells from human OS peripheral blood (n=13).\u003c/p\u003e\n\u003cp\u003eB. Representative and quantitation of flow cytometry plots of TIGIT and IL-2coexpression on CD8+ T cells from human OS peripheral blood (n=13).\u003c/p\u003e\n\u003cp\u003eC. CD107a and PFP production by CD8+ T cells were measured by flow cytometry. Representative flow charts are shown.\u003c/p\u003e\n\u003cp\u003eD. Percentages and quantitation of CD107a and PFP producing CD8+TIGIT+ or CD8+TIGIT- cells (n=8).\u003c/p\u003e\n\u003cp\u003eE. CD69 and CD226 production by CD8 T cells was measured by flow cytometry. Representative flow charts are shown.\u003c/p\u003e\n\u003cp\u003eF. Percentages and quantitation of CD69 and CD226 producing CD8+TIGIT+ or CD8+TIGIT- cells (n=8).\u003c/p\u003e\n\u003cp\u003e* P\u0026lt;0.05, ** P\u0026lt;0.01, *** P\u0026lt;0.001, **** P\u0026lt;0.0001, and ns not significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eS8. HSP47 negatively regulates TRAF2 and the survival curve of TRAF2 in OS.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. Immunofluorescence microscopy images for TRAF2 (red) and DAPI (blue) of U2OS and HOS cells with HSP47 overexpression processing or HSP47 shRNA treatment. Scale bars in images indicate 20 μm.\u003c/p\u003e\n\u003cp\u003eB. The overall survival rate in the low/high TRAF2 group is analyzed by the GEPIA web tool (\u003ca href=\"http://gepia.cancer-pku.cn/\"\u003ehttp://gepia.cancer-pku.cn/\u003c/a\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eS9. HSP47 participates in the ubiquitination process of TRAF2.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA-B. Western-blot analysis for TRAF2 levels in HOS (A), U2OS (B) cells with different treatments. GAPDH is used as a control.\u003c/p\u003e\n\u003cp\u003eC. Western-blot images show that after adding proteasome inhibitor MG132 in HOS (left), U2OS (middle) and K7M2 (right) cell lines, TRAF2 expression is detected at 0h,3h,6h,9h. GAPDH is used as a control.\u003c/p\u003e\n\u003cp\u003eD. Western-blot images show that TRAF2 expression levels HOS (left), U2OS (middle) and K7M2 (right) cells with or without MG132 or CHX culture. GAPDH is used as a control.\u003c/p\u003e\n\u003cp\u003eE-F. Co-immunoprecipitation analysis of the ubiquitination of endogenous TRAF2 in K7M2 cells treated with HSP47 shRNA (E) or Col003 (F).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eS10. HSP47 interactes with TRAF2.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA-C. Immunofluorescence images for TRAF2 (red), HSP47 (green) and DAPI (blue) of HOS, U2OS and K7M2 cells. Scale bars in images indicate 30 μm. Intensity profiles of TRAF2 (red lines) and HSP47 (green lines) co-localization signals are shown in plotted lines at three random sites.\u003c/p\u003e\n\u003cp\u003eD. The immunoprecipitation analysis of the TRAF2 in the HOS, HOS-HSP47. (Continuation of Figure 6. F)\u003c/p\u003e\n\u003cp\u003eE. The immunoprecipitation analysis of the HSP47 in the HOS, HOS-HSP47, U2OS, shHSP47-U2OS. Non-silencing shRNA or vector-blank is used as a control.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eS11. Gating strategies of flow cytometry analyses.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. Gating logic for tumour-infiltrating immune cells.\u003c/p\u003e\n\u003cp\u003eB. Gating logic for Flow fluorescence intensity of CD155+ OS cells.\u003c/p\u003e","description":"","filename":"supplement.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3927870/v1/c52ede29a4501f8b132d94db.pdf"}],"financialInterests":"There is no duality of interest","formattedTitle":"HSP47 Destabilizes CD155 Through TRAF2 in Synergistic Anti-TIGIT Treatment of Osteosarcoma","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eOsteosarcoma (OS) is a malignant mesenchymal tumor with high heterogeneity characterized by rapid progression, early metastasis, poor prognosis, complex treatment and susceptibility to recurrence[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Currently, the standard treatment for osteosarcoma is intensive chemotherapy in combination with surgery. However, there has been limited promotion in patient survival over the past decades, with only 20% survival at five years for patients with metastatic or recurrent osteosarcoma[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHeat shock proteins (HSPs) play important roles in the biology nature of cancers[\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Our work herein identified HSP47 as a highly expressed target in OS. This protein has been described as an essential component for the proper protein folding. Several types of cancer were reported to be associated with abnormal protein folding [\u003cspan additionalcitationids=\"CR9 CR10 CR11\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], which may be conducted by HSPs. The role of HSP47 in the development and progression of osteosarcoma remains unknown, and whether it plays an important role in the tumor immune response is also poorly understood.\u003c/p\u003e \u003cp\u003eImmunotherapy, primarily immune checkpoint blockade (ICB), has been shown to be effective in a sheer volume of malignant tumors and has been hailed as the \"fourth therapy\" beyond conventional treatment[\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. T-cell immune receptor with immunoglobulin and ITIM structural domains (TIGIT) is a promising new target for cancer immunotherapy[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Preclinical studies have shown that TIGIT blockade can prevent the progression of various solid and hematologic cancers[\u003cspan additionalcitationids=\"CR18 CR19 CR20 CR21 CR22 CR23\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. TIGIT interacts with the CD155 expressed on antigen-presenting or tumor cells to impair T-cell and natural killer (NK) cell function[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan additionalcitationids=\"CR26 CR27 CR28 CR29\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Interestingly, TIGIT also acts to regulate the activity of CD226, a second costimulatory recept or that works in parallel with CD28 [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. CD226 can promote functional interactions between effector immune cells and tumor cells expressing CD155[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], while this CD226-CD155 interaction is interrupted by TIGIT-CD155 axis. Therefore, modalities facilitate CD155 expression may strengthen the effect of anti-TIGIT therapy in cancers.\u003c/p\u003e \u003cp\u003eTumor necrosis factor (TNF) receptor-associated factor-2 (TRAF2) is a protein that interacts with TNF receptor 2 (TNFR2) and is involved in the activation of the classical nuclear factor-kappa B (NF-κB) pathway[\u003cspan additionalcitationids=\"CR34\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. It has been reported that the NF-κB signaling pathway regulates the expression immune checkpoints [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. However, whether it may be involved in the regulation of other immune checkpoints remains unknown. In this study, we studied TRAF2 regulation by HSP47-mediated ubiquitination and its role in mediating NF-κB/CD155 axis to control CD8\u0026thinsp;+\u0026thinsp;T-cell-mediated immune surveillance in osteosarcoma. We revealed that HSP47 altered CD155 levels and that HSP47 upregulation was strongly associated with mortality in osteosarcoma patients. We also elucidated the regulatory relationship of NF-κB with the immune checkpoint CD155. Therapeutically, targeting HSP47 with TIGIT antibody showed favored results in treating osteosarcoma.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eEthical approval\u003c/p\u003e\n\u003cp\u003eThe Ethics Committee of SAHZU approved this study, which complied with the Declaration of Helsinki. All patients were informed and signed an informed consent form.\u003c/p\u003e\n\u003ch4\u003ePatients, fresh osteosarcoma tissue collection and peripheral blood extraction\u003c/h4\u003e\n\u003cp\u003ePatients diagnosed with OS from 2017 to 2023 at the Musculoskeletal Tumor Center of SAHZU were included in this study for IHC staining, and OS patients from 2020-2023 were included for fresh tissue flow cytometry. Formalin was used to preserve tumor tissue requiring paraffin sectioning, and tissue preservation solution (Solarbio, SR0020) was used for flow cytometry. Peripheral blood from osteosarcoma patients was collected prior to the start of surgery, and the specimen was processed for further studies within 4 hours (details below).\u003c/p\u003e\n\u003ch4\u003eReagents, cell lines and cell culture\u003c/h4\u003e\n\u003cp\u003eFive human osteosarcoma cell lines (MNNG/HOS (hereafter referred to as HOS), U2OS, MG63, 143B, and SAOS2), the BALB/C mouse osteosarcoma cell line K7M2, human umbilical vein endothelial cells (HUVECs), and the human embryonic kidney cell line 293T were purchased from the Cell Collection of the Chinese Academy of Sciences and used in this study. All cells were tested for mycoplasma by a mycoplasma detection kit (#4460626, Thermo Fisher) and were guaranteed to be free of contamination. DNA short tandem repeat (DNA STR) genotyping was performed to authenticate the osteosarcoma cell lines. HOS, MG63, 143B, SAOS2, K7M2, and 293T cells and HUVECs were cultured in a 5% CO\u003csub\u003e2\u003c/sub\u003e atmosphere at 37\u0026thinsp;\u0026deg;C in DMEM with 10% FBS. U2OS cells were cultured in RPMI 1640 medium.\u003c/p\u003e\n\u003ch4\u003eTransfection of stable cell lines using lentivirus\u003c/h4\u003e\n\u003cp\u003eShort hairpin RNA (shRNA) constructs targeting HSP47 (human and mouse) and TRAF2 (human) and the overexpression plasmid (human) were purchased from OBiO Technology Corp., Ltd. (Shanghai, China). The mature antisense sequence of HSP47 (human) was 5\u0026rsquo;-TGCTAGTCAACGCCATGTTCT-3\u0026rsquo;. The mature antisense sequence of HSP47 (mouse) was 5\u0026rsquo;-TCCCTGGGTCTTGTGTCACT-3\u0026rsquo;. The mature antisense sequence of TRAF2 (human) was 5\u0026rsquo;-CCTTCCCAGATAATGCTGCCC-3\u0026rsquo;.\u003c/p\u003e\n\u003cp\u003eLentiviruses with ineffective shRNA (pHBLVshCtrl, pGMLV-shCtrl, pGV248-shCtrl) provided by the manufacturer were used during the knockdown study as a control. The antisense sequence was 5\u0026rsquo;-TTCTCCGAACGTGTCACGT-3\u0026rsquo;. In general, cells were seeded into six-well plates at a density of 2 x 10\u003csup\u003e5\u003c/sup\u003e cells per well to generate cell lines with stable silencing or overexpression of the targeted genes using shRNAs and overexpression plasmids. After incubation for 24 h, the cells were transfected with lentiviral particles. After that, the culture medium without lentivirus or plasmid was replaced, and the culture was continued for two days. Then, the transfected cells were selected using puromycin at the indicated concentrations before use.\u003c/p\u003e\n\u003ch4\u003eQuantitative real-time PCR\u003c/h4\u003e\n\u003cp\u003eTRIzol reagent (#15596018, Thermo Fisher) was used to extract total RNA, and reverse transcription was achieved with a cDNA Synthesis Kit (#6610, Takara). Gene-specific primers and SYBR Premix Ex TaqTM kits (#RR420, Takara) were used to measure mRNA levels with an ABI StepOnePlus System (Applied Biosystems). Real-time PCR software (version 2.4) was used to acquire and analyze the data. The relative expression results were normalized to GADPH levels by the \u0026Delta;\u0026Delta;CT method. The HSP47 primers were as follows: human HSP47 forward 5\u0026rsquo;-TCAGTGAGCTTCGCTGATGAC-3\u0026rsquo; and reverse 5\u0026rsquo;-CATGGCGTTGACTAGCAGGG-3\u0026rsquo;; human GADPH forward 5\u0026rsquo;-GGAGCGAGATCCCTCCAAAAT-3\u0026rsquo; and reverse 5\u0026rsquo;-GGCTGTTGTCATACTTCTCATGG-3\u0026rsquo;.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCoimmunoprecipitation (co-IP) and Western blot\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOsteosarcoma tissues or cells were lysed in precooled RIPA lysis buffer (#89901, Thermo Fisher Scientific) with phosphatase inhibitors (#78420, Thermo Fisher Scientific) and protease (#78428 Thermo Fisher Scientific). Centrifugation was performed at 15000 x g for 15 minutes at 4 \u0026deg;C to remove insoluble components. The concentration of extracted protein lysate was measured by the BCA Protein Assay Kit (#23227, Thermo Fisher Scientific).\u003c/p\u003e\n\u003cp\u003eFor co-IP, the cell supernatant was incubated with magnetic A/G beads (Beyotime, P2179M) for 12 h at 4 \u0026deg;C. After washing with IP buffer, the beads were boiled in SDS buffer to denature and elute the bound protein. Immunoblotting was performed to detect coimmunoprecipitates.\u003c/p\u003e\n\u003cp\u003eFor Western blotting, quantitated lysates were separated through SDS‒PAGE and transferred to methanol-pretreated PVDF membranes (#LC2002, Thermo Fisher). The membrane was then blocked with 5% nonfat milk for 60 mins at room temperature and immunoblotted with primary antibodies at 4 \u0026deg;C for 10-15 hours. The washing buffer used for all procedures consisted of Tris-buffered saline with 0.1% Tween-20 (TBST; #P9416, Sigma). After incubation with a specific HRP-conjugated secondary antibody for 1 hour at room temperature, the protein bands were detected with ECL detection kits and an AmershamTM ImageQuantTM 800 Western blot imaging system (ImageQuant 800 Control software v2.0.0).\u003c/p\u003e\n\u003ch4\u003eFlow cytometry and fluorescence-activated cell sorting (FACS)\u003c/h4\u003e\n\u003cp\u003e\u003cstrong\u003eAdherent \u003c/strong\u003e\u003cstrong\u003ecell CD155 level measurement. \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe adhered cells growing in plates were digested using pancreatic enzymes or collected with a cell scraper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTumor infiltrating T-cell (TIL) and organ analysis.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTumor, lung, spleen and liver tissue samples were cut into tiny pieces using sharp blades and then dissociated in RPMI 1640 medium containing collagenase type IV (2\u0026thinsp;mg/ml; Sigma), hyaluronidase (0.1\u0026thinsp;mg/ml; Sigma), DNase (0.1\u0026thinsp;mg/ml; Sigma), and BSA (2\u0026thinsp;mg/ml; Sigma). All the dissociated tissues were passed through 100-\u0026mu;m filters to acquire single cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePeripheral blood mononuclear cells (PBMCs)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBlood collected in an anticoagulation tube was diluted 1:1 with PBS and gently added to the top of the lymphocyte isolate. A fast ascending and slow descending centrifugation procedure was applied to obtain a single layer of lymphocyte cells.\u003c/p\u003e\n\u003cp\u003eFor cell surface protein staining, cells were incubated with suitable antibodies in a light-proof environment for 20-30 min at room temperature. To detect CD107a expression, cells were cultured in medium containing myristate acetate (PMA, 5 \u0026micro;g/ml, MCE, \u003ca href=\"https://www.medchemexpress.cn/Phorbol-12-myristate-13-acetate.html\"\u003eHY-18739\u003c/a\u003e) and monensin (NSC, 343257) for 5 hours at 37 \u0026deg;C. For intracellular protein staining, after surface staining, the cells were fixed with Fix/Perm solution (BD Biosciences) for 15 min and permeabilized with Perm/Wash buffer (BD Biosciences) for 20 min. Then, the cells were incubated with antibodies in a light-proof environment for 20-30 min at room temperature. Flow cytometry data analysis was performed using Beckman Coulter CytoFLEX LX and CytExpert v2.4 software and analyzed with FlowJo v10. S Beckman MoFlo Astrios EQs instrument and Summit v6.3.1 software were used to perform FACS.\u003c/p\u003e\n\u003ch4\u003eHistology, hematoxylin and eosin (H\u0026amp;E), immunofluorescence and immunohistochemical staining\u003c/h4\u003e\n\u003cp\u003eHuman or mouse osteosarcoma tissues were collected and soaked in a 4% paraformaldehyde solution. After dehydration and paraffin embedding, the tissues were sliced into continuous sections of 5 \u0026micro;m thickness. Hematoxylin and eosin (H\u0026amp;E) staining was performed using a standard protocol in a Leica Autostainer XL.\u003c/p\u003e\n\u003cp\u003eCell lysates were placed in 24-well plates in advance for immunofluorescence, and cells were inoculated into the wells. Osteosarcoma cells were fixed in 4% formaldehyde for 15 minutes at room temperature. Sections with tissue were treated with xylene and graded alcohol and then boiled in citric acid buffer for antigen repair. Then, specimens or cells were incubated with 0.03% Triton X-100 (#X100, Sigma)\u003c/p\u003e\n\u003cp\u003ein PBS for 10 min at room temperature and blocked with 5% BSA (Sigma) for 20 min at room temperature. Then, the specimens or cells were incubated with primary antibodies at 4 \u0026deg;C for 10-15 h. After returning to room temperature, the tissue or cells were incubated with specific secondary antibodies for one hour. Finally, slides were coverslipped with DAPI-containing mountant 237 (#P36971, Thermo Fisher). PBS washes were performed between each of the above processes, and the final high-resolution images were captured with a Leica DMi8 microscope.\u003c/p\u003e\n\u003cp\u003eFor immunohistochemistry, antigen repair, permeabilization, blocking of tissue sections and incubation with primary antibodies were performed as described above. The appropriate histochemistry-specific HRP-conjugated secondary antibody was selected and incubated with the tissue sections at 37 \u0026deg;C for 20 mins. Then, DAB reagent was used for color development. Finally, the sections were counterstained with hematoxylin. A microscope (Leica) and Leica Application Suite X v3.7.4 software were used to capture high-definition images.\u003c/p\u003e\n\u003ch4\u003eStatistical analysis\u003c/h4\u003e\n\u003cp\u003eGraphPad Prism (version 9) was used for statistical analysis. Two-tailed Student\u0026rsquo;s t test, one-way ANOVA and two-way ANOVA were performed to compare significant differences between the two groups. Values of P \u0026lt; 0.05 were considered to indicate statistical significance. The log-rank (Mantel‒Cox) test as described in the figure legend was performed to analyze the Kaplan‒Meier survival curves of the mice. The P value indicates * P＜0.05, **, P＜0.01, ***, P＜0.001 and ****, P＜0.0001.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMice, animal orthotopic osteosarcoma model and in vivo drug treatment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFour- to six-week-old female BALB/C mice and four- to six-week-old female BALB/C nude mice were purchased from Hangzhou Medical College. All strains of mice were raised under specific-pathogen-free (SPF) conditions, and the Institutional Animal Care and Use Committee (SAHZU) approved all the animal studies.\u003c/p\u003e\n\u003cp\u003eFor the BALB/C nude mouse subcutaneous graft tumor model, each 4-week-old female BALB/c nude mouse was injected subcutaneously near the scapula with 2 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e shCtrl K7M2 and shHSP47 K7M2 cells suspended in 100 \u0026mu;l PBS; the mice were sacrificed 21 days later. For the BALB/C mouse tibia orthotopic osteosarcoma model, shCtrl or shHSP47 K7M2 cells were injected into the tibia through the tibial plateau, and intraperitoneal (i.p.) TIGIT (BioXCell, BE0274) treatment started 7 days after tumor injection at 200 \u0026mu;g/g of body weight every 3 days for 15 days. The mice were sacrificed 5 days after stopping the treatment. None of the above-obtained tumors exceeded the maximum tumor size (1500 mm\u003csup\u003e3\u003c/sup\u003e) approved by the ethics committee.\u003c/p\u003e\n\u003ch4\u003eRNA-seq analysis\u003c/h4\u003e\n\u003cp\u003eRNA-seq analysis was performed for U2OS cells or U2OS cells treated with HSP47 shRNA. The density of cells in the 6-well plate was 2 \u0026times; 10\u003csup\u003e5 \u003c/sup\u003ecells/well. Total RNA was isolated using RNAiso plus (Thermo Fisher, 15596018) according to the manufacturer\u0026rsquo;s instructions. After three washes with PBS to remove platelets, the cells were harvested with TRIzol and stored at -80 \u0026deg;C. Total RNA was used to construct sequencing libraries. After rRNA removal, mRNA was enriched with fragment buffer, cut into short fragments, and then reverse-transcribed into cDNA with random primers. The cDNA fragment was purified, end-repaired, poly(A) tailed, and ligated to the Illumina sequencing adapter. The cDNA library was sequenced by Gene Denovo Biotech Co. (Guangzhou, China) using an Illumina NovaSeq 6000. Differentially expressed genes (DEGs) were identified by analyzing the differential RNA expression between the two groups. Transcripts with FDR \u0026lt;0.05 and absolute fold changes greater than or equal to 2 were considered to be differentially expressed. All the genetic changes are summarized in Supplementary file 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAntibodies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformation on all antibodies used in this study is provided in Supplementary Table 1.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cstrong\u003eTIGIT is highly expressed on CD8+ T cells especially in tumor environment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTIGIT expression was evaluated in PBMC, intratumoral (IT) regions and in peritumoral (PT) regions in patients with OS. Sample collection criteria was shown in Figure\u0026nbsp;3A. TIGIT was expressed by a large percentage of OS-infiltrating CD8+ T cells, and its expression was significantly higher than that on CD4+ T cells (Figure\u0026nbsp;3B-E). Similarly, the expression of TIGIT in OS was also found in IT and negative in PT and control from immunohistochemistry (Figure\u0026nbsp;3F-G). Spatially, the expression of TIGIT showed a colocalization relationship with IT CD8+ T-cells as illustrated by immunofluorescence\u0026nbsp;in human and mouse specimens\u0026nbsp;(Figure\u0026nbsp;3H, Figure S6).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSimilarly, orthotopic osteosarcoma mouse model , revealed high-frequency of TIGIT expression on CD8+ T cells in the tumor, spleen, liver and lungs, and TIGIT expression increased with increasing tumor-bearing days (Figure\u0026nbsp;3I-J). These results indicated that TIGIT is highly expressed in osteosarcoma and is significantly\u0026nbsp;correlated\u0026nbsp;with CD8+ T cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTIGIT-positive CD8+ T cells displayed impaired function in\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eosteosarcoma\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;patients.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe phenotypes of TIGIT+ T-cells were studied. We found that TIGIT expression on OS patient PBMCs was higher than that on CD8+ T cells from healthy donor PBMCs (Figure\u0026nbsp;3K).\u0026nbsp;TIGIT+CD8+ T cells from OS patients exhibited decreased PD-1 IL-2, CD69, perforin (PFP), and CD107a expression (Figure\u0026nbsp;3L-N, Figure S7A-B). Moreover, we found that CD226 expression was significantly reduced in cells with high TIGIT expression, suggesting that TIGIT regulates CD226\u0026nbsp;(Figure\u0026nbsp;3O). We also compared the phenotypes of TIGIT+ CD8+ T-cell subsets with that of TIGIT\u0026ndash; CD8+ T-cell subsets. The expression of lysosome marker CD107a, glycoprotein PFP, and the costimulant receptor CD226 were weakened in TIGIT+ T-cells, suggesting that the TIGIT+ CD8+ T cells possessed reduced effector function and antitumor potential (Figure S7C-F). In addition, a lower proportion of TIGIT+ CD8+ cells had surface expression of the activating receptor CD226, and a higher proportion expressed inhibitory receptors, including PD-1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eT\u003c/strong\u003e\u003cstrong\u003ehe e\u003c/strong\u003e\u003cstrong\u003expression of HSP47 is upregulated in osteosarcoma and associated with poor prognosis.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo investigate the role HSPs play in OS, we screened altered gene expression in cancers. We observed that SEPINH1 (HSP47) showed\u0026nbsp;a\u0026nbsp;correlation with survival in both the univariate Cox test and Kaplan‒Meier (KM) survival analysis in the TARGET-OS and GSE datasets. Moreover, HSP47 was highly expressed in osteogenic cells of relapse samples compared with primary samples and showed a higher positive expression rate in osteosarcoma samples than in healthy bone marrow\u0026nbsp;(Figure S1\u0026nbsp;A-C).HSP47 was upregulated in most cancers (Figure\u0026nbsp;1A) and sarcomas (Figure\u0026nbsp;1B) according to GEPIA tools. The CCLE online web tool showed the transcription level of HSP47 in different osteosarcoma cell lines (Figure\u0026nbsp;1C). HUVECs were used as a control (Figure\u0026nbsp;1D). The protein expression levels of HSP47 in HUVECs and different osteosarcoma cell lines were consistent with the transcript levels (Figure\u0026nbsp;1E). Similarly, the protein expression of HSP47 in osteosarcoma tissues was higher than that in adjacent nontumor tissues according to Western blot analysis (Figure\u0026nbsp;1F-G) and IHC (Figure\u0026nbsp;1H-I) staining of patient samples. Finally, the survival data indicated that overexpression of HSP47 shortened the disease-free survival time (log-rank P = 0.019) and overall survival time (log-rank P = 0.016) of osteosarcoma patients (Figure\u0026nbsp;1J-K).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHSP47 activation correlates with CD155 downregulation in multiple cancers.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs HSP47 was discovered to be associated with the prognosis of OS, the mechanism by which HSP47 regulates tumor progression needs to be further explored. RNA-seq data analysis was performed in U2OS cells with or without shHSP47 treatment (Figure\u0026nbsp;2A). In addition, CD155 upregulation mediated by HSP47 small molecule inhibitor col003 was observed in osteosarcoma cell lines. Osteosarcoma cell CD155 levels were significantly upregulated in U2OS and K7M2 cells treated with col003, whereas there was no obvious increase in CD155 expression levels in the HOS cell line, which has lower HSP47 levels (Figure\u0026nbsp;2B-C). After constructing the shHSP47-transfected U2OS cells and HSP47-overexpression vector-transfected HOS cells (Figure S2A), we revealed that the expression level of CD155 was increased after HSP47 knockdown by shRNAs in the U2OS and K7M2 cell lines. In contrast, the expression level of CD155 was decreased in HOS cells overexpressing HSP47 (Figure\u0026nbsp;2D-F). The results also showed that the HSP47 small molecule inhibitor Col003 did not affect CD155 expression in HUVECs (Figure S3A). Strikingly, HSP47 knockdown by shRNAs and HSP47 overexpression were associated with the growth and proliferation of osteosarcoma cells in vitro and in vivo (Figure S2B-E). At the same time, HSP47 also affected the epithelial\u0026ndash;mesenchymal transition process in osteosarcoma, which may provide some value for future research (Figure S2F-K). To verify our findings in other tumor cell lines, we selected\u0026nbsp;two\u0026nbsp;other reported lung cancer A549 cell lines and breast cancer BT-474 cell lines with high expression of HSP47 (Figure S3B). In vivo study showed similar results. We analyzed the correlation between the expression of HSP47 and CD155 in immunodeficient mice (WT or shHSP47 K7M2 subcutaneous tumor-bearing model). CD155 expression was elevated in K7M2 osteosarcoma mouse models with HSP47 knockdown compared with WT (Figure\u0026nbsp;2G). These findings supported the clinical relevance of HSP47 activation associated with CD155 downregulation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe\u003c/strong\u003e \u003cstrong\u003eTNF-related pathway is involved in the regulation of CD155 expression by HSP47.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo identify the regulatory factor that bridges HSP47 and CD155, we first analyzed the differences between U2OS and HSP47 shRNA-treated U2OS cells by RNA-seq. RNA-seq results and KEGG pathway enrichment analysis suggested that the DEGs in OS cell lines treated with HSP47 shRNA were correlated with negative regulation of TNF-related pathways (Figure 4A-B). Therefore, we hypothesized that the TNF-related pathway regulated the change in CD155 protein levels by HSP47 regulation. After stimulating osteosarcoma cells with exogenous TNF-\u0026alpha;, we observed by immunofluorescence, western blot, and flow cytometry that changes in CD155 protein levels in osteosarcoma cells were concentration- and time-dependent (Figure 4C-G). Upon evaluating the effect of HSP47 activation on TNF regulation of CD155 expression, we found that the expression of p65 protein was downregulated or increased in HOS and U2OS cells treated with HSP47 overexpression or shHSP47, respectively (Figure 4H), which indicated that HSP47 negatively regulated p65 pathway proteins. To verify whether the changes in CD155 protein expression levels caused by the TNF-related pathway were dominated by HSP47, a rescue experiment was performed to confirm that CD155 could be restored (Figure 4I-J). Meanwhile, the application of exogenous TNF-\u0026alpha; and its specific inhibitor etanercept also rescued CD155 expression in HOS and U2OS cells according to Western blot analyses (Figure 4K). The results above showed that the TNF-related pathway was involved in the regulation of CD155 expression by HSP47.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHSP47 negatively regulates TRAF2 through the ubiquitin‒proteasome pathway.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo understand how HSP47 regulated the TNF-related pathway and thereby regulated CD155, we transfected osteosarcoma cells with HSP47 shRNA and performed RNA-seq data analysis, which revealed that the RNA level of TRAF2, an essential protein regulating the TNF-related pathway, did not change significantly (Figure\u0026nbsp;5A). In contrast, the protein expression level of TRAF2 was significantly increased, as shown by Western blotting (Figure\u0026nbsp;5B), immunohistochemistry in the shHSP47 K7M2 subcutaneous tumor-bearing mouse model (Figure\u0026nbsp;5C) and immunofluorescence in U2OS or K7M2 cell lines (Figure S8A). These results showed that the level of TRAF2 mRNA with HSP47 shRNA was not substantially upregulated in accordance with the protein levels.\u003c/p\u003e\n\u003cp\u003eBased on this observation, we sought to determine whether a posttranslational pathway was the most relevant to TRAF2 upregulation in osteosarcoma cells by screening common protein degradation pathways using a proteasome inhibitor (MG132) and several autophagy inhibitors (Figure S9A-B). Our results revealed that only MG132 significantly increased TRAF2 in osteosarcoma cells and that this change could be reversed by cycloheximide (CHX) (Figure S9C-D). Overall, this suggested that changes in TRAF2 levels might be related to a posttranslational modification of the protein, specifically, that HSP47 might be involved in the ubiquitination-mediated degradation of the TRAF2 protein, thereby regulating the expression of the CD155 protein. These results confirmed that HSP47 might participate in TRAF2 degradation mediated by the ubiquitin‒proteasome pathway (UPP). TRAF2 in osteosarcoma cells was pulled down by immunoprecipitation and subjected to ubiquitination analysis. Although TRAF2 had notable basal ubiquitination, HSP47 interference abolished the ubiquitination of TRAF2 in U2OS and K7M2 cells (Figure\u0026nbsp;5D, Figure S9E). Consistent with this observation, treatment with the HSP47 inhibitor col003 also significantly inhibited TRAF2 ubiquitination (Figure\u0026nbsp;5E, Figure S9F). In contrast, HSP47 overexpression aggravated the ubiquitination of TRAF2 in HOS cells (Figure\u0026nbsp;5F). These results supported the notion that HSP47 activation induced TRAF2 ubiquitination in osteosarcoma cells. Moreover, TRAF2 protein was degraded when HSP47 was overexpressed in HOS cells (Figure\u0026nbsp;5G) and accumulated after treatment with HSP47 shRNA in U2OS cells (Figure\u0026nbsp;5H), as shown by immunofluorescence, a finding consistent with Western blot and immunohistochemistry data. Pulse-chase analysis using cycloheximide (CHX) revealed that HSP47 deletion significantly prolonged the half-life of the TRAF2 protein in U2OS and K7M2 cells, whereas HSP47 overexpression significantly shortened the TRAF2 protein half-life (Figure\u0026nbsp;5I-K). These findings demonstrated that a proteasome-regulated mechanism in HSP47-expressing osteosarcoma cells degraded TRAF2.\u003c/p\u003e\n\u003cp\u003eTo confirm the relationship between HSP47 and TRAF2, we performed co-IP experiments. The results showed that HSP47 could interact with TRAF2 (Figure S10A-C). In addition, confocal immunofluorescence microscopy also revealed that HSP47 colocalized with TRAF2 at the cell surface of osteosarcoma cells (Figure S10D-F).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTRAF2 regulates the expression of CD155 protein through N\u003c/strong\u003e\u003cstrong\u003ef-\u003c/strong\u003e\u003cstrong\u003e\u0026kappa;B.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo further explore the potential connection between TRAF2 and CD155, we first examined the CD155 protein expression levels in shCtrl HOS and shTRAF2 HOS cells. Flow cytometric imaging, immunofluorescence microscopy, and Western blotting revealed that the expression level of CD155 in HOS cells was downregulated after silencing the TRAF2 protein compared with that in the control group (Figure\u0026nbsp;6A-D) Interestingly, the changes in the protein level of CD155 could be reversed by exogenous\u0026nbsp;TNF-\u0026alpha;\u0026nbsp;stimulation (Figure\u0026nbsp;6E). Simultaneously, the expression levels of the p65 channel and phosphorylated p65 protein in HOS cells were downregulated with shTRAF2 treatment (Figure\u0026nbsp;6D). CD155 rescue upon the stimulation of exogenous\u0026nbsp;TNF-\u0026alpha;\u0026nbsp;in HOS and U2OS cells was further enhanced by the p65-specific inhibitor Bay (Figure\u0026nbsp;6F). These results suggested that TRAF2 regulated the expression of CD155 protein through NF-\u0026kappa;B.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHSP47 blockade showed synergistic effects with\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ea\u003c/strong\u003e\u003cstrong\u003enti-TIGIT therapy in cancer by facilitating CD8+ T-cells response\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBecause HSP47 inhibition could simultaneously inhibit tumor growth(Figure S4)\u0026nbsp;and regulate the stability of CD155, we sought to determine whether HSP47 inhibition could facilitate anti-TIGIT treatment. Immune competent tumor-bearing mouse models were established (Figure\u0026nbsp;7A). Macroscopic imaging showed that the tumor volume was lower in the anti-TIGIT and shHSP47 groups than in the untreated group. The combination of anti-TIGIT and shHSP47 significantly improved the treatment of tibial osteosarcoma (Figure\u0026nbsp;7B-D). The combined therapy also notably prolonged the survival of mice with tumors (Figure\u0026nbsp;7E). These results all indicated that anti-TIGIT and shHSP47 therapies have an antitumor effect that is most apparent when they are combined.\u003c/p\u003e\n\u003cp\u003eThe status of tumor-infiltrate T-cells were evaluated The results from flow cytometric analysis showed that K7M2 osteosarcoma-bearing mice treated with combination therapy could experience tumor growth suppression through the inhibition of cell proliferation and stimulation of antitumor immune responses centered around CD8+ T cells (Figure 7F-K). IHC also demonstrated the same results, which showed that CD8+ T cells in the combination treatment group had increased infiltration and more substantial immune killing function (Figure 7L-M).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eDysfunction in immune surveillance plays an essential role in the occurrence and development of cancer[37, 38]. A few immune checkpoints were identified for potential therapeutic targets to prompt a robust anti-cancer immune response. Among them, medicines targeting TIGIT was being tested in clinical trials. However, the interaction between CD155 and TIGIT/CD226 immune checkpoint receptors and ligands is complicated[26, 39-43]. Some studies have highlighted that the expression of CD155 plays a vital role in anti-TIGIT therapy[39-41]\u0026nbsp;and that the expression of CD155 is related to the\u0026nbsp;poor\u0026nbsp;survival and prognosis of sarcoma patients (Figure S4).\u003c/p\u003e\n\u003cp\u003eOur study showed that downregulation of CD155 was regulated by the activation of HSP47-related pathway. In osteosarcoma activated by HSP47, CD155 expression levels were elevated after inhibition of HSP47. More importantly, we found that HSP47-silenced animal models of osteosarcoma were more sensitive to CD8+ T cells in the presence of TIGIT monoclonal antibodies. Therefore, HSP47 might be a promising predictive biomarker and therapeutic target for immunotherapy or combination therapy. However, the detailed mechanism of CD155 regulation by HSP47 was still unclear. Here, we elucidated the internal pathway of CD155 regulation through a series of in vivo and in vitro experiments.\u003c/p\u003e\n\u003cp\u003eAbnormal regulation of HSP47 plays a key role in tumorigenesis and tumor progression, and HSP47 is overexpressed in various tumors and is associated with poor prognosis[8, 44-48]. However, there are limited studies on the effect of HSP47 on immune checkpoints. In our study, we found that HSP47 knockout slowed tumor growth and promoted the infiltration of immune cells (Figure S5A-D). Moreover, HSP47-knockout tumors had a more sensitive response against TIGIT mAb than did wild-type tumors. As a novel immune checkpoint, the regulatory mechanism of CD155 is poorly understood. Our data herein indicated that transcriptional and posttranscriptional modifications of CD155 were implemented via the HSP47/TRAF2/NF-\u0026kappa;B axis.\u0026nbsp;The activation of HSP47 in osteosarcoma degrades the TRAF2 protein by ubiquitination and downregulates phosphorylation in the NF-\u0026kappa;B pathway and that activation or phosphorylation of NF-\u0026kappa;B activates its ability to transcribe the CD155 protein. High expression of TRAF2 is associated with better overall survival in sarcoma, and TRAF2 regulates HSP47-dependent NF-\u0026kappa;B activation to enhance CD155 transcription levels.\u003c/p\u003e\n\u003cp\u003eHigh expression of TRAF2 is associated with better overall survival in sarcoma (Figure S8B), and TRAF2 regulates HSP47-dependent NF-\u0026kappa;B activation to enhance CD155 transcription levels. Here, we found that ubiquitination by HSP47 led to the degradation of the TRAF2 protein, thereby reducing NF-\u0026kappa;B pathway activation and CD155 protein transcription. Meanwhile, exogenous TNF-\u0026alpha; enhanced TRAF2/NF-\u0026kappa;B pathway activation and increased CD155 protein expression, which modulated the sensitivity to the TIGIT/CD226 interaction between osteosarcoma and CD8+ T cells. This finding highlighted the role of TRAF2 in cell communication in a tumor-friendly environment and the mutual regulation between immune and tumor cells. Finally, in a mouse model, the combination of TIGIT mAb and HSP47 shRNA significantly improved the effectiveness of this current ICB and targeted therapy.\u003c/p\u003e\n\u003cp\u003eIn summary, this work identified that HSP47-targeted therapy increased the sensitivity of osteosarcoma to TIGIT monoclonal therapy through a bypass mechanism of HSP47-activated and TRAF2/NF-\u0026kappa;B-dependent CD155 downregulation. This regulation conferred a change in cancer cell immune sensitivity along the CD155/CD226/TIGIT axis. In osteosarcoma cells, HSP47-mediated inhibition of the CD155/TIGIT axis enhanced the toxic effects of CD8+ T cells and promoted immune cell infiltration. Therefore, these results might change our understanding of TIGIT mAb combination therapy and target-free combination therapy in osteosarcoma and provide an attractive way to make cancer cells more susceptible to target-free combination therapy. The efficacy of this combination therapy in patients with OS should be further evaluated to determine whether it can eradicate tumors, delay tumor progression, or delay tumor recurrence.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e: The authors declare no potential conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBielack, S.S., et al., \u003cem\u003ePrognostic factors in high-grade osteosarcoma of the extremities or trunk: an analysis of 1,702 patients treated on neoadjuvant cooperative osteosarcoma study group protocols\u003c/em\u003e. J Clin Oncol, 2002. 20(3): p. 776\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeird, H.C., et al., \u003cem\u003eOsteosarcoma.\u003c/em\u003e Nat Rev Dis Primers, 2022. 8(1): p. 77.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIsakoff, M.S., et al., \u003cem\u003eOsteosarcoma: Current Treatment and a Collaborative Pathway to Success\u003c/em\u003e. J Clin Oncol, 2015. 33(27): p. 3029\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang, Z., et al., \u003cem\u003eMetabolic control of CD47 expression through LAT2-mediated amino acid uptake promotes tumor immune evasion\u003c/em\u003e. Nat Commun, 2022. 13(1): p. 6308.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDudeja, V., S.M. Vickers, and A.K. Saluja, \u003cem\u003eThe role of heat shock proteins in gastrointestinal diseases\u003c/em\u003e. Gut, 2009. 58(7): p. 1000\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCalderwood, S.K., et al., \u003cem\u003eHeat shock proteins in cancer: chaperones of tumorigenesis\u003c/em\u003e. Trends Biochem Sci, 2006. 31(3): p. 164\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCalderwood, S.K. and J. Gong, \u003cem\u003eHeat Shock Proteins Promote Cancer: It's a Protection Racket\u003c/em\u003e. Trends Biochem Sci, 2016. 41(4): p. 311\u0026ndash;323.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhu, J., et al., \u003cem\u003eChaperone Hsp47 Drives Malignant Growth and Invasion by Modulating an ECM Gene Network\u003c/em\u003e. Cancer Res, 2015. 75(8): p. 1580\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYoneda, A., K. Minomi, and Y. Tamura, \u003cem\u003eHSP47 promotes metastasis of breast cancer by interacting with myosin IIA via the unfolded protein response transducer IRE1alpha\u003c/em\u003e. Oncogene, 2020. 39(23): p. 4519\u0026ndash;4537.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao, D., et al., \u003cem\u003eHeat shock protein 47 regulated by miR-29a to enhance glioma tumor growth and invasion\u003c/em\u003e. J Neurooncol, 2014. 118(1): p. 39\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCao, D., et al., \u003cem\u003eExpression of novel markers of pancreatic ductal adenocarcinoma in pancreatic nonductal neoplasms: additional evidence of different genetic pathways\u003c/em\u003e. Mod Pathol, 2005. 18(6): p. 752\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePoschmann, G., et al., \u003cem\u003eIdentification of proteomic differences between squamous cell carcinoma of the lung and bronchial epithelium\u003c/em\u003e. Mol Cell Proteomics, 2009. 8(5): p. 1105\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOlson, B., et al., \u003cem\u003eMouse Models for Cancer Immunotherapy Research\u003c/em\u003e. Cancer Discov, 2018. 8(11): p. 1358\u0026ndash;1365.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePan, C., et al., \u003cem\u003eNext-generation immuno-oncology agents: current momentum shifts in cancer immunotherapy\u003c/em\u003e. J Hematol Oncol, 2020. 13(1): p. 29.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarabelle, A., et al., \u003cem\u003eIntratumoral immunotherapy: using the tumor as the remedy\u003c/em\u003e. Ann Oncol, 2017. 28(suppl_12): p. xii33-xii43.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChauvin, J.M. and H.M. Zarour, \u003cem\u003eTIGIT in cancer immunotherapy\u003c/em\u003e. J Immunother Cancer, 2020. 8(2).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChauvin, J.M., et al., \u003cem\u003eTIGIT and PD-1 impair tumor antigen-specific CD8(+) T cells in melanoma patients\u003c/em\u003e. J Clin Invest, 2015. 125(5): p. 2046\u0026ndash;58.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou, G., et al., \u003cem\u003eAntibodies Against Immune Checkpoint Molecules Restore Functions of Tumor-Infiltrating T Cells in Hepatocellular Carcinomas\u003c/em\u003e. Gastroenterology, 2017. 153(4): p. 1107\u0026ndash;1119 e10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTassi, E., et al., \u003cem\u003eEarly Effector T Lymphocytes Coexpress Multiple Inhibitory Receptors in Primary Non-Small Cell Lung Cancer\u003c/em\u003e. Cancer Res, 2017. 77(4): p. 851\u0026ndash;861.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eO'Brien, S.M., et al., \u003cem\u003eFunction of Human Tumor-Infiltrating Lymphocytes in Early-Stage Non-Small Cell Lung Cancer\u003c/em\u003e. Cancer Immunol Res, 2019. 7(6): p. 896\u0026ndash;909.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee, W.J., et al., \u003cem\u003eExpression of lymphocyte-activating gene 3 and T-cell immunoreceptor with immunoglobulin and ITIM domains in cutaneous melanoma and their correlation with programmed cell death 1 expression in tumor-infiltrating lymphocytes\u003c/em\u003e. J Am Acad Dermatol, 2019. 81(1): p. 219\u0026ndash;227.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKong, Y., et al., \u003cem\u003eT-Cell Immunoglobulin and ITIM Domain (TIGIT) Associates with CD8\u0026thinsp;+\u0026thinsp;T-Cell Exhaustion and Poor Clinical Outcome in AML Patients\u003c/em\u003e. Clin Cancer Res, 2016. 22(12): p. 3057\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuillerey, C., et al., \u003cem\u003eTIGIT immune checkpoint blockade restores CD8(+) T-cell immunity against multiple myeloma\u003c/em\u003e. Blood, 2018. 132(16): p. 1689\u0026ndash;1694.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRaphael, I., et al., \u003cem\u003eTIGIT and PD-1 Immune Checkpoint Pathways Are Associated With Patient Outcome and Anti-Tumor Immunity in Glioblastoma\u003c/em\u003e. Front Immunol, 2021. 12: p. 637146.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFreed-Pastor, W.A., et al., \u003cem\u003eThe CD155/TIGIT axis promotes and maintains immune evasion in neoantigen-expressing pancreatic cancer\u003c/em\u003e. Cancer Cell, 2021. 39(10): p. 1342\u0026ndash;1360 e14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLupo, K.B. and S. Matosevic, \u003cem\u003eCD155 immunoregulation as a target for natural killer cell immunotherapy in glioblastoma\u003c/em\u003e. J Hematol Oncol, 2020. 13(1): p. 76.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKucan Brlic, P., et al., \u003cem\u003eTargeting PVR (CD155) and its receptors in anti-tumor therapy\u003c/em\u003e. Cell Mol Immunol, 2019. 16(1): p. 40\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHe, W., et al., \u003cem\u003eCD155T/TIGIT Signaling Regulates CD8(+) T-cell Metabolism and Promotes Tumor Progression in Human Gastric Cancer\u003c/em\u003e. Cancer Res, 2017. 77(22): p. 6375\u0026ndash;6388.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYu, X., et al., \u003cem\u003eThe surface protein TIGIT suppresses T cell activation by promoting the generation of mature immunoregulatory dendritic cells\u003c/em\u003e. Nat Immunol, 2009. 10(1): p. 48\u0026ndash;57.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJohnston, R.J., et al., \u003cem\u003eThe immunoreceptor TIGIT regulates antitumor and antiviral CD8(+) T cell effector function\u003c/em\u003e. Cancer Cell, 2014. 26(6): p. 923\u0026ndash;937.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChiang, E.Y. and I. Mellman, \u003cem\u003eTIGIT-CD226-PVR axis: advancing immune checkpoint blockade for cancer immunotherapy\u003c/em\u003e. J Immunother Cancer, 2022. 10(4).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGilfillan, S., et al., \u003cem\u003eDNAM-1 promotes activation of cytotoxic lymphocytes by nonprofessional antigen-presenting cells and tumors\u003c/em\u003e. J Exp Med, 2008. 205(13): p. 2965\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSiegmund, D., J. Wagner, and H. Wajant, \u003cem\u003eTNF Receptor Associated Factor 2 (TRAF2) Signaling in Cancer.\u003c/em\u003e Cancers (Basel), 2022. 14(16).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVallabhapurapu, S., et al., \u003cem\u003eNonredundant and complementary functions of TRAF2 and TRAF3 in a ubiquitination cascade that activates NIK-dependent alternative NF-kappaB signaling\u003c/em\u003e. Nat Immunol, 2008. 9(12): p. 1364\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZarnegar, B.J., et al., \u003cem\u003eNoncanonical NF-kappaB activation requires coordinated assembly of a regulatory complex of the adaptors cIAP1, cIAP2, TRAF2 and TRAF3 and the kinase NIK\u003c/em\u003e. Nat Immunol, 2008. 9(12): p. 1371\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLim, S.O., et al., \u003cem\u003eDeubiquitination and Stabilization of PD-L1 by CSN5\u003c/em\u003e. Cancer Cell, 2016. 30(6): p. 925\u0026ndash;939.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFeng, M., et al., \u003cem\u003ePhagocytosis checkpoints as new targets for cancer immunotherapy\u003c/em\u003e. Nat Rev Cancer, 2019. 19(10): p. 568\u0026ndash;586.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWaldman, A.D., J.M. Fritz, and M.J. Lenardo, \u003cem\u003eA guide to cancer immunotherapy: from T cell basic science to clinical practice\u003c/em\u003e. Nat Rev Immunol, 2020. 20(11): p. 651\u0026ndash;668.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBraun, M., et al., \u003cem\u003eCD155 on Tumor Cells Drives Resistance to Immunotherapy by Inducing the Degradation of the Activating Receptor CD226 in CD8(+) T Cells\u003c/em\u003e. Immunity, 2020. 53(4): p. 805\u0026ndash;823 e15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBriukhovetska, D., et al., \u003cem\u003eT cell-derived interleukin-22 drives the expression of CD155 by cancer cells to suppress NK cell function and promote metastasis\u003c/em\u003e. Immunity, 2023. 56(1): p. 143\u0026ndash;161 e11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBanta, K.L., et al., \u003cem\u003eMechanistic convergence of the TIGIT and PD-1 inhibitory pathways necessitates co-blockade to optimize anti-tumor CD8(+) T cell responses\u003c/em\u003e. Immunity, 2022. 55(3): p. 512\u0026ndash;526 e9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eO'Donnell, J.S., et al., \u003cem\u003eTumor intrinsic and extrinsic immune functions of CD155\u003c/em\u003e. Semin Cancer Biol, 2020. 65: p. 189\u0026ndash;196.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFeng, M., et al., \u003cem\u003eBCL9 regulates CD226 and CD96 checkpoints in CD8(+) T cells to improve PD-1 response in cancer\u003c/em\u003e. Signal Transduct Target Ther, 2021. 6(1): p. 313.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePan, X., et al., \u003cem\u003eCircular RNA circ-TNPO3 inhibits clear cell renal cell carcinoma metastasis by binding to IGF2BP2 and destabilizing SERPINH1 mRNA\u003c/em\u003e. Clin Transl Med, 2022. 12(7): p. e994.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTian, S., et al., \u003cem\u003eSERPINH1 regulates EMT and gastric cancer metastasis via the Wnt/beta-catenin signaling pathway\u003c/em\u003e. Aging (Albany NY), 2020. 12(4): p. 3574\u0026ndash;3593.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCai, H.Q., et al., \u003cem\u003eFKBP10 promotes proliferation of glioma cells via activating AKT-CREB-PCNA axis\u003c/em\u003e. J Biomed Sci, 2021. 28(1): p. 13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaloney, A., et al., \u003cem\u003eGene and protein expression profiling of human ovarian cancer cells treated with the heat shock protein 90 inhibitor 17-allylamino-17-demethoxygeldanamycin\u003c/em\u003e. Cancer Res, 2007. 67(7): p. 3239\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXiong, G., et al., \u003cem\u003eHsp47 promotes cancer metastasis by enhancing collagen-dependent cancer cell-platelet interaction\u003c/em\u003e. Proc Natl Acad Sci U S A, 2020. 117(7): p. 3748\u0026ndash;3758.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-3927870/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3927870/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHeat shock protein 47 (HSP47) plays an essential role in correcting protein folding, and abnormal protein folding is closely related to tumorigenesis. However, the relationship between HSP47 and cancer immune response is poorly studied. Herein, HSP47 was found to be frequently overexpressed in human osteosarcomas. In animal models, HSP47 inhibition resulted in enhanced immune cell infiltration and function. Transcriptome data revealed that HSP47 negatively regulated CD155, a ligand of TIGIT. Immune checkpoint blockade therapy targeting the novel immune checkpoint molecule TIGIT is effective in limited patients. Further investigations are urgently needed to harness a robust response of this treatment. TIGIT antibody and HSP47-targeted therapy significantly inhibited the progression of osteosarcoma in mice and consequently prolonged survival. Mechanistically, inhibition of HSP47 attenuated TRAF2 protein ubiquitination and subsequently facilitated NF-κB-mediated CD155 transcription in HSP47-overexpressed osteosarcomas. Similarly, CD155 expression was significantly weakened in TRAF2-inhibited osteosarcoma cells. Collectively, our data revealed that targeting HSP47 could reinforce the expression of CD155 and therefore enhance the efficacy of anti-TIGIT treatment, providing a promising strategy for cancer immunotherapy.\u003c/p\u003e","manuscriptTitle":"HSP47 Destabilizes CD155 Through TRAF2 in Synergistic Anti-TIGIT Treatment of Osteosarcoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-20 18:03:08","doi":"10.21203/rs.3.rs-3927870/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7d661d4c-2180-460c-9aeb-503766fe0ed2","owner":[],"postedDate":"February 20th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":28795687,"name":"Biological sciences/Cancer/Oncogenes"},{"id":28795688,"name":"Biological sciences/Cancer/Sarcoma"}],"tags":[],"updatedAt":"2024-03-15T10:51:11+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-20 18:03:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3927870","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3927870","identity":"rs-3927870","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}