Tumor glycosylation engages CD301b-mediated myeloid regulation in breast cancer

Tumor glycosylation engages CD301b-mediated myeloid regulation in breast cancer | 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 Tumor glycosylation engages CD301b-mediated myeloid regulation in breast cancer Ahmet Ozdilek, Amy V. Paschall, Fathima Z. Nawaz, Afaq M. M. Niyas, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9347231/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Aberrant tumor glycosylation can alter immune recognition; however, the specific influence of glycan-lectin interactions on tumor progression remains poorly understood. Here, we identify the C-type lectin receptor CD301b (encoded by Mgl2 ) as a regulator of immune activity within the breast tumor microenvironment (TME) and identify a cross-species myeloid regulatory program associated with its human ortholog CLEC10A. Using a murine triple-negative breast cancer model, we demonstrate that tumors expressing the Tn glycoantigen grow more rapidly, and this growth is facilitated by CD301b⁺ immune cells. Depletion or genetic loss of CD301b markedly suppressed tumor growth, indicating that CD301b promotes tumor progression, potentially through myeloid-tumor interactions. Phenotypic analyses revealed that tumor-infiltrating CD301b⁺ cells are predominantly type 2 conventional dendritic cells (cDC2s) and exhibit IL-10 expression within the TME. Transcriptomic profiling of tumors developed in Mgl2 -KO mice revealed a shift toward an inflammatory, interferon-dominant transcriptional state, consistent with altered antitumor immune programming. Single-cell RNA sequencing of human breast cancers revealed that CLEC10A is expressed in cDC2 and select macrophage subsets. Additionally, CLEC10A-positive cDC2 and macrophages share a transcriptional state characterized by enhanced antigen presentation and immune-regulatory functions compared to CLEC10A-negative cells. Together, these findings support a relationship between tumor glycosylation and CLEC10A/CD301b-associated myeloid regulation, highlighting this axis as a potential target for reprogramming the breast tumor immune microenvironment. Biological sciences/Cancer Biological sciences/Computational biology and bioinformatics Biological sciences/Immunology Health sciences/Oncology Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction A major setback observed in many cancers arises from immune modulation within the tumor microenvironment (TME), preventing effective anti-cancer responses. Vaccines, CAR T cells, and checkpoint blockade prime the immune system against cancer-associated antigens, promoting cancer cell destruction through immune cytotoxicity 1 . Immune therapies for breast cancer remain largely ineffective due to the ability of the tumor to grow unimpeded and eventually metastasize. Immune regulation can occur through cytokine secretion, signaling mechanisms, or checkpoints (such as through PD-1) 2–5 . During the malignant transformation of a mammalian cell, a dramatic and aberrant modification of cellular glycosylation is observed. Tumor-associated carbohydrate antigens, or TACAs, can induce immune suppression, allowing cancer cells to evade immune cells 6–8 . Lectins are carbohydrate-binding proteins that function as receptors for immune cells and can activate immune regulatory pathways through their interactions with TACAs 9–11 . Similarly, modulating immune profiles in the TME by engaging sialic-acid-binding immunoglobulin-like lectins (Siglecs) is a known TACA mechanism 12–14 . Thus, elucidating the roles of lectins in regulating the immune response within the TME is becoming increasingly important. Tn antigen is a TACA ranked as a high-priority cancer-associated antigen based on its antigenicity and oncogenicity 11,15–19 . Tn is a truncated form of the cell surface O-glycan, consisting of the terminal O-linked N-acetylgalactosamine (GalNAc) attached to serine or threonine. The aberrant glycosylation associated with Tn may occur when the enzyme responsible for O-glycan elongation, T-synthase or its associated chaperone, Cosmc (C1GALT1C1), becomes functionally inhibited 20,21 . Tn-expressing mucin 1 (MUC1) has been associated with breast cancer cells 22,23 , especially in triple-negative breast cancer 24,25 . Modulating MUC1 expression or Tn glycosylation can inhibit tumor growth 26–28 . However, developing immune responses against Tn-MUC1 has been problematic 29 . Human CLEC10A, also known as macrophage galactose-type lectin (MGL), is a C-type lectin receptor (CLR) that binds to Tn antigen on the surface proteins in humans 19,30 . In mice, the Tn-recognizing homolog of the human CLEC10A is CD301b, also known as MGL2 19,31 . CD301b is primarily expressed by myeloid cells such as dendritic cells (DCs) and macrophages 17 . Previously, CD301b-expressing myeloid cell populations have been linked with immunosuppressive responses 16,17,19,32–34 . DCs and macrophages can suppress the proliferation of CD4 + effector T lymphocytes through the interaction of MGL with terminal GalNAc residues on CD45 expressed by T cells 17 . This cell-specific glycosylation of CD45 provided an immunoregulatory pathway, mediated by MGL, thereby controlling effector T cell function. In another study, CD301b + dendritic cells suppressed T follicular helper cells and antibody responses to protein antigens 32 . Recently, an immunosuppressive DC subset expressing CD301b was shown to accumulate at secondary sites and promote metastasis in pancreatic cancer 34 and lung cancer 35 . Breast cancer-focused studies further support a functional Tn-CD301b/CLEC10A axis by showing that ligand display can be induced by clinically relevant tumor-cell perturbations, including endocrine manipulation (e.g., tamoxifen exposure), oxidative stress, and DNA damage, linking stress signaling to increased presentation of truncated O-glycan ligands 36 . In the same context, receptor-ligand readouts have been associated with breast cancer outcomes, suggesting that these glycan-lectin interactions reflect biologically meaningful variation in tumor-immune dynamics 36 . Complementing these observations, transcriptomic and immunoinformatics analyses across breast cancer cohorts and pan-cancer datasets indicate that CLEC10A expression tracks immune infiltration patterns and immune regulatory networks and is frequently associated with a more favorable prognosis, supporting further investigation into how tumor glycan presentation intersects with CLEC10A/CD301b signaling in vivo 37–39 . In this study, we investigated the role of CD301b in a murine model of triple-negative breast cancer and found that the loss of CD301b expression significantly restricted tumor growth. Within the tumor microenvironment, CD301b-expressing immune cells were identified as type 2 conventional dendritic cells. To further explore the mechanisms underlying the observed tumor growth restriction, we performed bulk RNA sequencing (bulk RNA-seq) on murine tumors, which showed heightened inflammatory immune responses when CD301b was absent. Analysis of publicly available single-cell RNA sequencing (scRNA-seq) datasets revealed CLEC10A-expressing myeloid cell populations in human breast cancer tissues, suggesting that this regulatory axis extends beyond the murine model. Here, we examine whether the Tn-CD301b/CLEC10A axis links tumor glycosylation to a conserved myeloid regulatory program in breast cancer. Results CD301b/Tn Axis Impacts Tumor Growth. We first aimed to investigate the relationship between CD301b + immune cells and Tn glycoantigen-expressing breast cancer cells. We used a CRISPR-Cas9 gene editing model to knock out Cosmc expression in AT3 murine breast cancer cells. Cosmc is a chaperone essential in elongating the core O-glycan beyond the truncated Tn form of α-GalNAc 20,21,40 . When the Cosmc function/expression is disrupted, elongation of the O-glycan is not observed; instead, the Tn antigen is observed at significantly higher levels. After disrupting Cosmc expression in these cell lines, we confirmed increased Tn cell surface expression through flow cytometry using a reBaGs6 IgM antibody (Suppl. Figure 1A) 41 , a biotinylated VVL lectin coupled with fluorescent streptavidin (Suppl. Figure 1B), and a recombinant biotinylated Mgl2 carbohydrate binding domain (CBD)-GFP fusion protein coupled with streptavidin (Suppl. Figure 1C). All staining methods indicated significantly higher Tn expression on the Cosmc KO cell line. We also isolated RNA from each cell line and confirmed decreased Cosmc expression in the Tn hi cell line through qPCR using Cosmc primers (Suppl. Figure 1D). We then tested whether knocking out Cosmc expression changes the proliferation rate of the AT3 breast cancer cells in vitro . After culturing both cell lines at the same concentrations for three days, we observed no significant differences in cell proliferation between the two lines (Suppl. Figure 1E), indicating that Tn expression alone does not promote cancer cell growth. To determine in vivo tumor cell growth, we injected AT3 (Tn lo ) and AT3 Cosmc KO (Tn hi ) murine breast tumor cells into the mammary pads of C57BL/6 mice and monitored tumor growth. We observed that Tn hi tumors grew significantly faster than Tn lo tumors (Fig. 1 A), indicating that Tn expression impacts tumor growth rate. To examine the contribution of CD301b-expressing immune cells to tumor growth, we employed heterozygous Mgl2 +/DTReGFP mice (Mgl2-DTR), in which CD301b+ immune cells can be selectively depleted by diphtheria toxin (DT) treatment 32,33 . In the first experiment (Fig. 1 B), AT3 Tn low or Tn hi tumor cells were injected into Mgl2-DTR mice with or without DT administration. Tumor growth was significantly reduced in DT-treated mice of the Tn hi group, indicating that CD301b + immune cells promote tumor progression. In a complementary experiment (Fig. 1 C), we injected AT3 Tn hi cells into homozygous Mgl2 DTReGFP/DTReGFP mice (CD301b-null, Mgl2 KO), which lack surface expression of CD301b due to the disruption of both alleles but retain the immune cell populations. These mice also exhibited markedly reduced tumor growth compared with wild-type controls. Together, these experiments indicate that the observed phenotype is associated with tumor Tn expression and facilitated by the CD301b protein. Tumor-infiltrating CD301b + cells display a type 2 conventional dendritic cell (cDC2) phenotype. We next characterized tumor-infiltrating CD45 + CD301b + immune cells in the murine triple-negative breast cancer model. These cells expressed CD11c, a canonical dendritic cell (DC) marker 42,43 (Fig. 2 A) and were strongly positive for MHCII, confirming their DC identity (Fig. 2 B). CD301b⁺ cells also expressed CD11b, a defining marker of mouse type 2 conventional dendritic cells (cDC2s) 44 (Fig. 2 B). Mouse cDC2s can be distinguished from cDC1s by CD103 and SIRP-alpha expressions 42,45 . We examined the expression of these markers by tumor-infiltrating CD301b + cells, which display a cDC2 phenotype (Fig. 2 C). Although CD301b + cells are primarily cDC2s, not all DCs or cDC2s express CD301b in the TME (Fig. 2 D and 2 E). cDC2s constitute a subset of antigen-presenting cells that play key roles in coordinating adaptive immune responses. In contrast to cDC1s, which specialize in cross-presentation and cytotoxic T cell activation, cDC2s promote CD4⁺ T cell priming and modulate immune polarization within tissues 46–48 . Recent studies have shown that cDC2s exhibit remarkable plasticity in the tumor microenvironment, where they can adopt either immunostimulatory or tolerogenic phenotypes in response to local cues 48 . Tumor-infiltrating CD301b + dendritic cells exhibit enhanced IL-10 expression and remain responsive to TLR4 stimulation Because CD301b + dendritic cells have been linked to immunoregulatory activity in multiple settings, we next asked whether tumor-infiltrating CD301b + DCs display an IL-10-associated regulatory phenotype. IL-10 is a central anti-inflammatory cytokine that restrains excessive inflammation and suppresses T-cell effector programs through several mechanisms, including inhibition of antigen-presenting cell activation, inflammatory cytokine production, and downstream T-cell priming functions 49,50 . Prior studies have also associated CD301b/CLEC10A-expressing myeloid cells with immunosuppressive or regulatory functions, including suppression of T follicular helper responses, promotion of metastasis-associated immune suppression, and induction of regulatory programs in CD301b + antigen-presenting cells 34,51,52 . In addition, tumor-associated glycan-lectin interactions involving the CD301b/CLEC10A axis have been linked to immune modulation in cancer, including breast cancer and Tn-driven tumor models 35,37 . To test whether CD301b + DCs in the breast tumor microenvironment (TME) are positioned to contribute to this regulatory axis, we compared IL-10 expression in CD301b + DCs isolated from tumors of wild-type mice under unstimulated conditions and after short-term stimulation with LPS, a TLR4 agonist. Unstimulated CD301b + DCs obtained from the spleens of naïve mice served as the control group. Tumor-derived CD301b + DCs showed a detectable IL-10 + expression at baseline, and this population increased further after LPS stimulation, indicating that these cells may contribute to immune regulation within the TME and remain capable of augmenting IL-10 production in response to inflammatory cues. This observation is consistent with prior work showing that CLEC10A/CD301b engagement can cooperate with innate stimuli to enhance IL-10 production in dendritic cells and promote regulatory programming 51 . Notably, CD301b + DCs isolated from the TME displayed a greater frequency of IL-10-expressing cells than their splenic counterparts under both unstimulated and LPS-stimulated conditions. These findings suggest that the tumor microenvironment either enriches for an IL-10-competent CD301b + DC population or licenses infiltrating CD301b + DCs toward a more suppressive phenotype after tumor entry. Together, these data support IL-10 production as a functional feature of tumor-associated CD301b + DCs and offer a plausible mechanistic link between CD301b + myeloid cell accumulation and the suppression of productive anti-tumor inflammation. Although these data do not establish IL-10 as the sole mediator of the phenotype, they support IL-10 competence as a functional feature of tumor-associated CD301b + dendritic cells. The lack of CD301b is associated with a strong inflammatory immune signature in the breast TME Since CD301b directly associates with tumor growth and identifies cDC2 and macrophage populations within the breast tumor microenvironment (TME), we examined how its loss impacts immune signaling and tumor–immune interactions. To this end, we performed bulk RNA sequencing (bulk RNA-seq) on tumors derived from wild-type (WT) and Mgl2 knockout ( Mgl2 KO) mice following injection of AT3 Tn hi tumor cells. The global transcriptomic heatmap (Fig. 4 A) revealed distinct clustering and clear separation between WT and Mgl2 KO mouse tumors, indicating a strong transcriptional divergence associated with Mgl2 loss. This observation provided the foundation for downstream pathway and gene-level analyses to elucidate how CD301b influences immune regulation within the TME. To dissect these transcriptomic differences, Gene Set Enrichment Analysis (GSEA) was performed using the Hallmark and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment gene set databases (Fig. 4 B–C). Mgl2 KO tumors displayed significant enrichment of immune and inflammatory pathways, including TNF-α/NF-κB, IL-6/JAK-STAT3, interferon-α/γ, and IL-17 signaling—pathways broadly associated with myeloid activation, cytokine production, and tumor immunosurveillance 53,54 . Despite the slower tumor growth observed in the knockout mice, complement/coagulation, hypoxia, and glycolytic pathways were also upregulated, suggesting a compensatory increase in metabolic and inflammatory activity within the TME. Collectively, these data suggest that CD301b functions as an immunoregulatory node that tempers cytokine and interferon responses, whereas its loss enhances pro-inflammatory signaling. The dominance of interferon- and NF-κB–driven programs aligns with the slower tumor progression observed in KO mice, implying that CD301b deficiency reprograms the TME toward a functionally immune-active, tumor-controlling state. The pathway-focused volcano plot (Fig. 4 D) highlights key upregulated genes underpinning these responses, including Cxcl3, Il1a, Il23a, Il36g, Csf3, Nos2, S100a8, S100a9 , and Lcn2 . These represent canonical NF-κB and IL-17 targets known to mediate myeloid recruitment, nitric oxide production, and acute-phase inflammation—hallmarks of innate immune activation 55–57 . The upregulation of the serine protease inhibitor and matrix metalloproteinase genes Serpinb2 and Mmp10 in the tumor microenvironment of knockout mice suggests a tumor-suppressive function through the regulation of extracellular matrix remodeling and modulation of immune responses 58,59 . Thus, CD301b loss is associated with a more inflammatory transcriptional profile in the tumor microenvironment, characterized by innate immune activation, interferon-associated programs, and concurrent tissue-remodeling features. The volcano plot of all differentially expressed genes (DEGs) (Fig. 4 E) contextualizes these changes within the full transcriptome. Upregulated genes largely mirrored those driving enriched pathways, confirming that Cxcl3, Il1a, Il23a, Nos2, S100a8/a9 , and Csf3 constitute the core Mgl2 KO transcriptional program rather than isolated pathway artifacts. On the other hand, downregulation of the TGF-β family growth differentiation factor 3 and the apelin receptor genes Gdf3 and Aplnr may be relevant to pathways involved in tumor growth, angiogenesis, and metastasis 60,61 . Together, these results suggest that CD301b deficiency reprograms the TME toward an inflammatory and interferon-dominant transcriptional state associated with delayed tumor growth. These findings support the interpretation that CD301b functions as an immunoregulatory myeloid node whose loss releases inflammatory immune programs within the breast tumor microenvironment. CLEC10A⁺ myeloid cells in the human breast cancer TME include both dendritic cells and macrophages To determine how CLEC10A maps onto human breast tumor myeloid populations, we next analyzed publicly available single-cell RNA sequencing (scRNA-seq) data (GSE161529) from 20 patients, including triple-negative (n = 8), ER⁺ (n = 6), and HER2⁺ (n = 6) tumors 62 . Following quality control, data integration, and annotation, we focused on CD45⁺ immune cells to map CLEC10A expression across myeloid populations (Fig. 5 A; Suppl. Figure 3A). CLEC10A expression was most prominent in dendritic cells and was also detectable in macrophage/monocyte populations, with negligible expression in other immune cells (Fig. 5 B–C). Across breast cancer subtypes, dendritic cells consistently showed higher CLEC10A expression than macrophages (Suppl. Figure 3B). Within the dendritic cell compartment, we identified four subsets—cDC1, cDC2, cDC-LAMP3⁺, and plasmacytoid DC (pDC)—and found that CLEC10A expression was highest in cDC2 (56.9%) and moderate in cDC-LAMP3⁺ (11.3%), but low in cDC1 (1.9%) and absent in pDCs (0%) (Fig. 5 D–F; Suppl. Figure 3C–D). We next examined tumor-associated macrophages (TAMs). TAMs are key regulators of tumor inflammation, tissue remodeling, and immune suppression 63 . TAMs were subdivided into transcriptionally defined subsets reflecting distinct functional programs: C1QC⁺ macrophages, associated with immunosuppression 64–66 ; NLRP3⁺ macrophages, associated with poor prognosis and tumor growth 67,68 ; and INHBA⁺ macrophages, linked to angiogenesis, matrix remodeling, and tumor progression 69 (Fig. 5 G; Suppl. Figure 3E). Among these subsets, CLEC10A transcription distributed similarly in C1QC⁺ macrophages (11%), NLRP3⁺ macrophages (9%), and INHBA⁺ macrophages (7%) (Fig. 5 H–I). Interestingly, CLEC10A-positive NLRP3⁺ macrophages were detected exclusively in triple-negative breast cancers, where expression levels were comparable to those in INHBA⁺ macrophages (Suppl. Figure 3F). This enrichment suggests that CLEC10A expression extends beyond dendritic cells to macrophage populations, particularly those engaged in inflammatory and tissue-remodeling responses within aggressive tumor subtypes. Taken together, these results indicate that CLEC10A expression in the human breast cancer microenvironment is concentrated within myeloid lineages—encompassing both cDC2-like dendritic cells and specialized macrophage subsets. This pattern mirrors the cellular distribution observed in the mouse TME, suggesting that CLEC10A/CD301b marks a conserved myeloid program potentially involved in coordinating immune regulation and tissue remodeling during tumor progression. CLEC10A marks a convergent transcriptional state across human breast cancer cDC2 and macrophages To define the transcriptional programs associated with CLEC10A expression in human breast tumor myeloid cells, we performed differential expression analysis on a per-patient basis comparing CLEC10A⁺ and CLEC10A⁻ cells within the cDC2 and macrophage compartments from all human breast cancer samples shown in Fig. 5 (Fig. 6 A-B). In cDC2, CLEC10A⁺ cells were enriched for canonical antigen-presentation and cDC2-associated genes, including CLEC10A, CD1C, CD1B, FCER1A, and multiple HLA class II genes, confirming that CLEC10A identifies a differentiated antigen-presenting cDC2 state. CLEC10A⁺ cDC2 also upregulated IL1R2, FCGR2B, MRC1, and MMP12, consistent with an immune-regulatory and tumor-conditioning program. In contrast, CLEC10A⁻ cDC2 showed relatively higher expression of genes such as LTB, PLAC8, CST3, FCGBP, and IL22RA2, indicating a transcriptionally distinct state with less canonical antigen-presentation identity and greater inflammatory or tissue-reactive features. A parallel pattern emerged in macrophages. CLEC10A⁺ macrophages upregulated CLEC10A together with CD1E, CD1B, LGALS2, IDO1, and LYVE1, supporting a state linked to antigen handling, immune regulation, and tissue-remodeling functions. By contrast, CLEC10A⁻ macrophages preferentially expressed inflammatory mediators and monocyte/TAM-associated genes, including SPP1, CCL2, CCL3, CCL4, TNF, IL1B, CXCL8, VCAN, PLAUR, HIF1A, ANGPTL4, and SERPINE1, consistent with a more inflammatory and tumor-promoting phenotype. Thus, the human cDC2 and macrophage datasets are concordant in showing that CLEC10A marks a shared myeloid state characterized by stronger antigen-presentation features but restrained inflammatory cytokine and chemokine programs. This interpretation is consistent with the mouse data: CD301b prominently marked cDC2s in tumors, whereas in vivo loss of CD301b was associated with a broad induction of inflammatory pathways and innate cytokine programs, as inferred from bulk RNA-seq. Together, the human single-cell and mouse bulk RNA-seq data support a model in which CLEC10A/CD301b identifies a conserved myeloid program associated with stronger antigen-presentation features and reduced inflammatory cytokine and chemokine expression, consistent with a more regulatory state in the breast tumor microenvironment. Discussion Aberrant glycosylation is a hallmark of malignant transformation, and our findings identify CD301b as a key immunoregulatory lectin that links breast tumor-associated Tn antigens to myeloid immune modulation. CD301b⁺ cells, primarily cDC2s, promoted breast tumor growth, whereas their depletion or genetic loss limited progression. These observations align with previous studies demonstrating that TACAs interact with lectins to influence myeloid differentiation and immune regulation 19,21,22,70–72 . In breast cancer, the Tn-CD301b/CLEC10A axis can now be traced across tumor glycosylation, murine in vivo tumor growth, tumor transcriptomic reprogramming, and human myeloid single-cell states. Transcriptomic profiling of tumors developed in Mgl2 -KO mice revealed broad activation of NF-κB, IL-6–JAK–STAT3, and interferon pathways, consistent with a shift toward a more inflammatory transcriptional state within the TME 73 . These data position CD301b as an immunoregulatory node that tempers innate activation, similar in concept to a checkpoint-like mechanism operating within the myeloid compartment 9,10,74,75 . While this study does not define the signaling circuitry involved, it indicates that CD301b-expressing myeloid populations, particularly cDC2s and potentially macrophages, contribute to an immunoregulatory phenotype in the breast cancer TME. In support of this interpretation, tumor-infiltrating CD301b⁺ dendritic cells displayed higher IL-10 expression than splenic CD301b⁺ DCs at baseline and after LPS stimulation, indicating that the tumor microenvironment enriches for, or licenses, a CD301b⁺ DC population with enhanced regulatory cytokine competence. The complex and pleiotropic nature of CD301b’s activity may explain its influence on the immune landscape of cancer 74–76 . CD301b’s modulatory behavior mirrors that of other C-type lectin receptors 77 . CD301b-mediated restraint may protect against chronic inflammation, but in tumors, it can inadvertently favor immune escape 78,79 . Conversely, CD301b loss triggers NF-κB- and interferon-associated inflammation, while also imposing metabolic and hypoxic stress on the TME 80 . Together, these findings support a model in which CD301b functions as a molecular regulator balancing immune activation and tolerance in breast cancer. A growing mechanistic literature contextualizes the downstream programming capacity of the CLEC10A/CD301b lectin axis. In human antigen-presenting cells, CLEC10A engagement has been repeatedly linked to regulatory polarization, often characterized by enhanced IL-10 production and consequent dampening or redirection of effector T-cell responses 37,51 . Importantly for mouse interpretation, CD301b pathways have been linked to IL-10 induction across multiple experimental systems, indicating that IL-10 skewing is a conserved output that should be integrated into models of CD301b-driven immune modulation 35,51 . A recent ligand-centric study further shows that distinct GalNAc-containing ligands can tune CLEC10A signaling strength and dendritic cell transcriptional outputs, supporting the idea that qualitative features of tumor-associated glycan ligands may shift the balance between inflammatory and regulatory programs in the TME 81 . Our findings are consistent with this concept at both functional and transcriptional levels: in mice, tumor-associated CD301b⁺ DCs exhibited enhanced IL-10 competence, whereas in human breast cancer, CLEC10A⁺ cDC2s and macrophages displayed a distinct transcriptional state enriched for canonical cDC2 genes and genes associated with immune dampening and tumor conditioning. Therefore, our findings support CD301b-Tn interactions as an immune-regulatory axis in the breast TME that may regulate antigen processing, cytokine release, or costimulatory signaling within dendritic cells, thereby shaping T cell activation thresholds 77 . These possibilities highlight the clinical potential of CD301b as a new immune-regulatory axis distinct from canonical checkpoints, such as PD-1 or CTLA-4. A limitation of the current study is that the downstream effects of this myeloid program on lymphocytes remain unresolved. Thus, while our data support a primary role for CD301b-associated myeloid reprogramming, they do not yet define how this state influences T-cell or NK-cell recruitment, activation, spatial organization, or effector function in the tumor microenvironment. Future studies will be needed to determine whether altered cytokine or chemokine production, antigen presentation, or other indirect mechanisms link CD301b-dependent myeloid states to downstream antitumor immunity. A key next step will be to define how specific TACA ligand structures and intracellular adaptors determine signaling strength, pathway selection, and the balance between immunoregulatory signaling, cytokine outputs, and anti-tumor effector programs in vivo. Further single-cell and spatial analyses of the breast TME transcriptome, with and without CD301b, will help define how CD301b⁺ subsets integrate into existing immune networks across tumor stages. From a translational perspective, targeting the CLEC10A/CD301b-Tn interaction offers a promising route to modulate the breast cancer immune microenvironment. Pharmacologic blockade or glycomimetic interference could complement checkpoint inhibitors by dismantling glycan-mediated myeloid suppression, whereas selective induction of this pathway may have therapeutic relevance in autoimmune disease 82 . Ultimately, elucidating the intricate mechanisms that govern immune modulation through CD301b will be essential to selectively induce these properties in disease-specific contexts, enabling the development of knowledge-based, precision immunotherapies. In summary, this study identifies an immunomodulatory CD301b⁺ myeloid phenotype that contributes to breast cancer growth and whose loss induces a robust inflammatory program in the breast TME. Our results further suggest that this phenotype includes tumor-associated CD301b⁺ dendritic cells with enhanced IL-10 expression and conserved human CLEC10A⁺ cDC2 and macrophage transcriptional states linked to immune dampening and tumor conditioning. While the molecular mechanisms remain to be defined, our data indicate that CD301b acts as a glycan-sensitive, checkpoint-like regulator of myeloid activity. Elucidating its ligand specificity and downstream signaling will clarify how breast tumor glycosylation reshapes the TME and may reveal new strategies to enhance immunotherapy efficacy. Materials and Methods Mice Eight-week-old female C57BL/6 mice were obtained from Jackson Laboratories (Bar Harbor, ME) and housed at Emory University Whitehead Biomedical Research Building. Mgl2 DTReGFP/DTReGFP mice were a generous gift from Akiko Iwasaki at Yale University. To obtain heterozygous Mgl2 +/DTReGFP mice, C57BL/6 were bred with Mgl2 DTReGFP/DTReGFP mice. Mice were kept in microisolator cages and handled under biosafety level 2 (BSL2) hoods. For tissue processing and subsequent flow cytometry, mice were euthanized by carbon dioxide inhalation in accordance with IACUC guidelines. Where applicable, cell suspensions were generated through mechanical tissue disruption and collagenase D digestion. Red blood cells were lysed, and samples were filtered through 60 µm nylon filters to obtain single-cell suspensions. For depletion of CD301b + cells, heterozygous Mgl2-DTR mice were treated with diphtheria toxin (0.5µg/mouse) in sterile PBS intraperitoneally every two to three days, starting at day − 1 before tumor injection. All mouse experiments were in compliance with the Emory University Institutional Animal Care and Use Committee under an approved animal use protocol. Our animal use protocol adheres to the principles outlined in U.S. Government Principles for the Utilization and Care of Vertebrate Animals Used in Testing , Research and Training , the Animal Welfare Act, the Guide for the Care and Use of Laboratory Animals , and the AVMA Guidelines for the Euthanasia of Animals . Generation of Tn breast cancer cells To express Tn glycans at high levels in tumor cells, we used a CRISPR/Cas9 methodology to stably silence Cosmc expression in AT3 cells using established protocols and reagents. Mouse Cosmc guide RNA and CRISPR/Cas9 plasmid were obtained from Santa Cruz Technology (sc-425587). AT3 murine breast cancer cells were a generous gift from the Kebin Liu lab at Augusta University. AT3 cells were transfected with Cosmc CRISPR/Cas9 KO plasmid according to the manufacturer’s protocol. Puromycin was used to select transfected cells. We then used flow cytometry to confirm higher expression of Tn on the AT3 cell surfaces using the ReBaG6 antibody (generously provided by Richard Cummings at Harvard University) (Suppl. Figure 1A) 41 and VVL lectin (Vector Laboratories) (Suppl. Figure 1B). The proliferations of transfected and untransfected cell lines (AT3 Tn hi and AT3 Tn low ) were tested in an MTT proliferation assay for three days, and colorimetric analysis was performed with a CytoTek plate reader according to protocol; no significant differences in proliferation compared to parent cells were observed (Suppl. Figure 1D). Cell lines were maintained in RPMI media supplemented with 10% FBS, sodium pyruvate, HEPES buffer, NEAA, β-mercaptoethanol, and penicillin/streptomycin at 37 o C, 5% CO2. AT3 Tn and/or AT3 Tn Tumor Challenge AT3 cells were harvested and washed in sterile PBS. Cells were suspended in a final concentration of 2.5E6/ml sterile PBS. Cells were subcutaneously injected into the mammary pads of mice at 2.5E5/100µl/mouse. Mice were monitored throughout the experiment and euthanized at the tumor endpoint, defined as the maximum tumor dimension of 0.9–1.2 cm. Tumor volumes were calculated as ((length x width x width)/2) in mm 3 . Flow Cytometry Cells were stained in PBS with TruStain fcX (BioLegend, Cat. No. 101320) to reduce non-specific antibody binding. Cell samples were stained with the following antibodies and stains: CD11c-PacBlue (BioLegend, clone N418), CD11b-Alexa Fluor 488 (BioLegend, clone M1/70), CD11b-BUV 805 (Invitrogen, clone M1/70), SIRPα-Alexa Fluor 700 (BioLegend, clone P84), CD103-PE/Dazzle 594 (BioLegend, clone 2E7), MHCII-BV785 (BioLegend, clone M5/114.15.2), CD45-Spark UV 387 (BioLegend, clone 30-F11), CD45-Alexa Fluor 647 (BioLegend, clone 30-F11), IL-10-APC (BioLegend, clone JES5-16E3), CD301b-PE (BioLegend, clone URA-1), and LIVE/DEAD Fixable Blue (Invitrogen). All isotype controls were obtained from BioLegend. Samples were washed and analyzed with flow cytometry (Cytek Aurora). Fluorescence minus one (FMO) plus specific isotype control antibody-stained samples were used as negative staining controls, and single stains were used for compensation. Flow cytometry data were analyzed using FlowJo Single Cell Analysis Software. For IL-10 staining, cells were incubated for 4 hours in the presence of GolgiStop and GolgiPlug. The concentration of LPS used for in vitro stimulation was 1 µg/ml. Bulk RNA-seq and Bioinformatics Tumors were harvested from wild-type C57BL/6J and Mgl2 KO mice (n = 3 per group) at the experimental endpoint defined in the tumor challenge protocol. Total RNA was extracted using the MagMAX™ mirVana™ Total RNA Isolation Kit in combination with the KingFisher Apex system (Thermo Fisher Scientific). RNA integrity and concentration were assessed with a Qubit 3.0 fluorometer (Thermo Fisher Scientific). High-quality RNA samples were used for library preparation, followed by quality control and sequencing using Novogene’s standard protocol. Libraries were sequenced on the Illumina NovaSeq X Plus platform to generate paired-end 150 bp reads (PE150) at Novogene Inc. Raw FASTQ files were retrieved and subjected to quality control with FastQC 83 . Reads were aligned to the Mus musculus reference genome (GRCm39/mm39) using HISAT2 84 . A gene-level count matrix was generated with featureCounts 85 . The count matrix was imported to the downstream differential expression analysis using the DESeq2 R package 86 . Significantly differentially expressed genes were defined by adjusted p-value < 0.05. Gene Set Enrichment Analysis (GSEA) was performed on the RNA-seq dataset using the clusterProfiler R package 87 to identify significantly enriched KEGG and hallmark pathways between Mgl2 KO and wild-type tumors. To focus on cancer-relevant biology, enrichment results were refined to include immune- and cancer-related pathways. Analyzing the scRNA-seq data scRNA-seq data generated using the 10X Genomics Chromium platform were obtained from the Gene Expression Omnibus (GEO; accession GSE161529) 88 . Data processing was performed using the Seurat R package (version 5). Low-quality cells were excluded based on standard Seurat quality-control metrics, 89 and putative doublets were removed using DoubletFinder. 90 The datasets were integrated using the Seurat reciprocal PCA (RPCA)-based integration workflow. Cell-type annotation was subsequently performed using scATOMIC, 91 and dendritic cell and macrophage subsets were further confirmed using canonical lineage markers from CellMarker 2.0. 92,93 For differential expression analysis, cDC2 and macrophage populations were analyzed separately by generating donor-level pseudobulk profiles, with CLEC10A-positive and CLEC10A-negative cells defined as the comparison groups within each cell type. Differential expression testing was then performed using edgeR 94 with a design matrix including group and donor as covariates, thereby controlling for inter-donor variability. Statistical Analysis GraphPad Prism v8 was used for statistical analyses. Two-way ANOVA with Tukey’s multiple comparisons test was used to determine statistical significance between experimental groups in each of the applicable experimental models (Fig. 1 B). An unpaired parametric two-tailed t-test was used for Fig. 1 A, 1 C, 2 A, 2 B, 2 C, 2 D, 2 E, and Suppl. Figure 1C. Significance is indicated on each graph based on p-value: >0.05 = ns; <.05 = *; <0.01 = **; <0.001 = ***; <0.0001 = ****. Declarations Author Contribution A.O., A.V.P., and F.Y.A. conceptualized and wrote the manuscript; A.O., A.V.P, F.Z.N. prepared Figures 1-3; A.O., A.M.N prepared Figures4-6; F.Y.A supervised the research and acquired funds. Acknowledgement We acknowledge the following individuals for their contributions of transgenic mice, cell lines, and monoclonal antibodies: Dr. Akiko Iwasaki, Dr. Kebin Liu, and Dr. Richard Cummings. National Institutes of Health grants (R01AI123383 and R01AI152766) and the Winship Cancer Institute Winship Invest $ Pilot Grant supported this work. 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Paschall","email":"","orcid":"","institution":"Emory University","correspondingAuthor":false,"prefix":"","firstName":"Amy","middleName":"V.","lastName":"Paschall","suffix":""},{"id":630867497,"identity":"d3be3e09-d76d-476f-b9cd-eefd84c80ccd","order_by":2,"name":"Fathima Z. Nawaz","email":"","orcid":"","institution":"Emory University","correspondingAuthor":false,"prefix":"","firstName":"Fathima","middleName":"Z.","lastName":"Nawaz","suffix":""},{"id":630867499,"identity":"d7aa1b21-6ad5-4870-8ff4-71807a98818d","order_by":3,"name":"Afaq M. M. Niyas","email":"","orcid":"","institution":"Emory University","correspondingAuthor":false,"prefix":"","firstName":"Afaq","middleName":"M. M.","lastName":"Niyas","suffix":""},{"id":630867500,"identity":"1dbbadf5-fa1f-44a0-8442-c6352dd19498","order_by":4,"name":"Fikri Y. Avci","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAsUlEQVRIiWNgGAWjYBAC9gYgkVAB47IRoYXnAEjLGZK1MLaRpIX9jOGHh/NsovmlzxgwfCg7TIQWnhxjicRtabkz+3IMGGecI0KLPUNaGkPitsO5G87wGDDzthFjC/8zoJY5/yFa/hKlRSL5GENiwwGIFkbitDw+LJFwLDl3Zg9bwcGec+nEOCyx8eOPGrvcfh7mjQ9+lFkT1oIEOAwOkKQeCNgfkKpjFIyCUTAKRggAAIRbORX6+0gGAAAAAElFTkSuQmCC","orcid":"","institution":"Emory University","correspondingAuthor":true,"prefix":"","firstName":"Fikri","middleName":"Y.","lastName":"Avci","suffix":""}],"badges":[],"createdAt":"2026-04-07 15:38:38","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9347231/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9347231/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108542681,"identity":"bf318be6-837c-4535-8151-8e320a0cf0c7","added_by":"auto","created_at":"2026-05-05 19:12:26","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":92676,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCD301b/Tn Axis Impacts Tumor Growth\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA.\u003c/strong\u003e AT3 (Tn\u003csup\u003elow\u003c/sup\u003e) and AT3 \u003cem\u003eCosmc\u003c/em\u003e KO cells (Tn\u003csup\u003ehi\u003c/sup\u003e) (2.5E5/mouse) were injected into the mammary pads of C57BL/6 mice (n = 25). Tumor sizes were monitored. Tumor sizes were calculated based on (length times width\u003csup\u003e2\u003c/sup\u003e)/2 for volumes in mm\u003csup\u003e3\u003c/sup\u003e. \u003cstrong\u003eB.\u003c/strong\u003e AT3 (Tn\u003csup\u003elow\u003c/sup\u003e) and AT3 \u003cem\u003eCosmc\u003c/em\u003e KO cells (Tn\u003csup\u003ehi\u003c/sup\u003e) tumor cells (2.5x10\u003csup\u003e5\u003c/sup\u003e/mouse) were injected into the mammary pads of WT mice and heterozygous Mgl2-DTR mice (n= 4 or 5) with or without CD301b\u003csup\u003e+\u003c/sup\u003e cells depleted. Tumor sizes were monitored. \u003cstrong\u003eC.\u003c/strong\u003e AT3 \u003cem\u003eCosmc\u003c/em\u003e KO cells (Tn\u003csup\u003ehi\u003c/sup\u003e) (2.5x10\u003csup\u003e5\u003c/sup\u003e/mouse) were injected into the mammary pads of \u003cem\u003eMgl2\u003c/em\u003e KO mice (n=5). Tumor sizes were monitored.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9347231/v1/06c34f73518bc46cb783221a.png"},{"id":108542687,"identity":"008b5c94-15d1-45e5-8d75-a908330d4125","added_by":"auto","created_at":"2026-05-05 19:12:27","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":220830,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCharacterization of CD45\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e+\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003eCD301b\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e+\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e immune cells in murine breast cancer TME.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSingle cell suspensions from tumors of WT mice injected with AT3 \u003cem\u003eCosmc\u003c/em\u003e KO cells (Tn\u003csup\u003ehi\u003c/sup\u003e) were stained, and expression of surface markers was analyzed with flow cytometry (gated as in Suppl. Fig. 2). \u003cstrong\u003eA.\u003c/strong\u003e Among live CD45\u003csup\u003e+\u003c/sup\u003e cells, CD301b\u003csup\u003e+\u003c/sup\u003e cells are CD11c\u003csup\u003e+\u003c/sup\u003e. \u003cstrong\u003eB.\u003c/strong\u003e CD301b\u003csup\u003e+ \u003c/sup\u003eand CD11c\u003csup\u003e+\u003c/sup\u003e cells are MHCII\u003csup\u003e+\u003c/sup\u003e and CD11b\u003csup\u003e+\u003c/sup\u003e. \u003cstrong\u003eC.\u003c/strong\u003e CD301b\u003csup\u003e+\u003c/sup\u003e and CD11c\u003csup\u003e+\u003c/sup\u003e cells are cDC2. DCs and cDC2s in the TME, \u003cstrong\u003eD and E\u003c/strong\u003e, respectively, consist of Cd301b-negative and Cd301b-positive cells.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9347231/v1/719ec4bfe6e98763772b100b.png"},{"id":108542683,"identity":"ea22d92c-36bb-4b86-ad50-bb9c9c90c6e8","added_by":"auto","created_at":"2026-05-05 19:12:26","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":112809,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCD301b+ dendritic cells in the tumor microenvironment express elevated IL-10 and remain responsive to LPS stimulation. \u003c/strong\u003eCD301b+ DCs isolated from tumors showed a greater frequency of IL-10-expressing cells than CD301b+ DCs from naïve spleens. LPS increased the proportion of IL-10+ cells in TME DCs.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9347231/v1/3d9531943412c266bf3b3a5e.png"},{"id":108542682,"identity":"eaa21f2c-b4a4-4429-bd5e-df07c803289b","added_by":"auto","created_at":"2026-05-05 19:12:26","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":242623,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe lack of CD301b is associated with a strong inflammatory immune signature in the breast TME\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA.\u003c/strong\u003eHeatmap showing differentially expressed genes (DEGs) identified by RNA-seq from tumors in \u003cem\u003eMgl2\u003c/em\u003e KO and WT mice. The blue and red bands indicate low and high gene expression quantity, respectively. Biological replicates showed the highest degree of correlation. \u003cstrong\u003eB.\u003c/strong\u003e Gene Set Enrichment Analysis (GSEA) of Hallmark pathways reveals immune-related and cancer-associated pathways, all of which are upregulated in Mgl2 KO. \u003cstrong\u003eC.\u003c/strong\u003e GSEA of KEGG pathways shows immune-related and cancer-associated pathways, and they are all upregulated in Mgl2 KO. \u003cstrong\u003eD.\u003c/strong\u003e Volcano plot showing the pathway-associated genes (from panels B and C). The genes with a log₂ fold change of 2 or greater are highlighted in purple. The X-axis represents log₂-transformed fold change, and the Y-axis represents −log₁₀-transformed significance. The VENN diagram shows the distribution of genes between Hallmark and KEGG gene sets. \u003cstrong\u003eE.\u003c/strong\u003eVolcano plot of DEGs between tumors from \u003cem\u003eMgl2\u003c/em\u003e KO and WT mice. Red points indicate upregulated DEGs, blue points indicate downregulated DEGs, gray points represent non-significant genes, and purple points indicate the pathway-associated genes (from panel D). All the genes with a log₂ fold change ≥ 2 are labeled.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-9347231/v1/df903fdedb59903e80a917e4.png"},{"id":108805136,"identity":"81e55d3b-9542-4e28-af78-49aef6b52657","added_by":"auto","created_at":"2026-05-08 15:24:56","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":264212,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCharacterization of CD45\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e+\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003eCLEC10A\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e+\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e myeloid cells in human breast cancer TME.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA.\u003c/strong\u003e UMAP of all immune cells colored by major lineage (B/Plasma cell, Dendritic cell, Macrophage/Monocyte, NK cell, T cell). \u003cstrong\u003eB.\u003c/strong\u003e Immune cells highlighting CLEC10A⁺ cells (colored) over all cells (gray). \u003cstrong\u003eC.\u003c/strong\u003e Bar plot showing the fraction of CLEC10A⁺ cells within each major lineage. \u003cstrong\u003eD.\u003c/strong\u003e UMAP of dendritic cell compartment colored by subset (cDC1, cDC2, cDC-LAMP3\u003csup\u003e+\u003c/sup\u003e, pDC). \u003cstrong\u003eE.\u003c/strong\u003e Dendritic cell subset highlighting CLEC10A⁺ cells (colored) over all DCs (gray). \u003cstrong\u003eF.\u003c/strong\u003e Bar plot showing the fraction of CLEC10A⁺ cells within each DC subset. \u003cstrong\u003eG.\u003c/strong\u003e UMAP of macrophage compartment colored by subset: C1QC⁺ macrophages, INHBA⁺ macrophages, and NLRP3⁺ macrophages. \u003cstrong\u003eH.\u003c/strong\u003e Macrophage subset highlighting CLEC10A⁺ cells (colored) over all macrophages (gray). \u003cstrong\u003eI.\u003c/strong\u003e Bar plot showing the fraction of CLEC10A⁺ cells within each macrophage subset.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eUMAP axes indicate the first two dimensions. Percentages in bar plots are calculated as (CLEC10A⁺ cells / total cells) within the indicated group.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-9347231/v1/b4d70a75c0fa611cf16aab8b.png"},{"id":108542685,"identity":"8bdcd9fe-1ff0-4b07-adc2-66a2db6b9b22","added_by":"auto","created_at":"2026-05-05 19:12:26","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":153932,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferential gene expression associated with CLEC10A expression in human breast cancer cDC2 and macrophages. A.\u003c/strong\u003e Volcano plot of differential gene expression between CLEC10A⁻ and CLEC10A⁺ cDC2 from the scRNA-seq dataset shown in Fig. 5. cDC2 from all human breast cancer samples were subsetted, pseudobulk counts were generated per patient, and differential expression was assessed using edgeR. \u003cstrong\u003eB.\u003c/strong\u003e Volcano plot of differential gene expression between CLEC10A⁻ and CLEC10A⁺ macrophages from the same scRNA-seq dataset. Macrophages were subsetted, pseudobulk counts were generated per patient, and differential expression was assessed using edgeR.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-9347231/v1/928ad1cd7cfb74162477c065.png"},{"id":108809366,"identity":"021a52df-46a4-48fc-9ea1-60272c04fb36","added_by":"auto","created_at":"2026-05-08 15:52:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1371291,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9347231/v1/a549bdf9-40ac-405e-a0d1-95bb241dbbea.pdf"},{"id":108542680,"identity":"edd1eb96-ee99-48b2-affa-ed4a4f73586a","added_by":"auto","created_at":"2026-05-05 19:12:25","extension":"pptx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":840464,"visible":true,"origin":"","legend":"","description":"","filename":"NPJBCsupplfigures0406.pptx","url":"https://assets-eu.researchsquare.com/files/rs-9347231/v1/9ff3dfc2fc770a77b261d97f.pptx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Tumor glycosylation engages CD301b-mediated myeloid regulation in breast cancer","fulltext":[{"header":"Introduction","content":"\u003cp\u003eA major setback observed in many cancers arises from immune modulation within the tumor microenvironment (TME), preventing effective anti-cancer responses. Vaccines, CAR T cells, and checkpoint blockade prime the immune system against cancer-associated antigens, promoting cancer cell destruction through immune cytotoxicity \u003csup\u003e1\u003c/sup\u003e. Immune therapies for breast cancer remain largely ineffective due to the ability of the tumor to grow unimpeded and eventually metastasize. Immune regulation can occur through cytokine secretion, signaling mechanisms, or checkpoints (such as through PD-1) \u003csup\u003e2\u0026ndash;5\u003c/sup\u003e. During the malignant transformation of a mammalian cell, a dramatic and aberrant modification of cellular glycosylation is observed. Tumor-associated carbohydrate antigens, or TACAs, can induce immune suppression, allowing cancer cells to evade immune cells \u003csup\u003e6\u0026ndash;8\u003c/sup\u003e. Lectins are carbohydrate-binding proteins that function as receptors for immune cells and can activate immune regulatory pathways through their interactions with TACAs \u003csup\u003e9\u0026ndash;11\u003c/sup\u003e. Similarly, modulating immune profiles in the TME by engaging sialic-acid-binding immunoglobulin-like lectins (Siglecs) is a known TACA mechanism \u003csup\u003e12\u0026ndash;14\u003c/sup\u003e. Thus, elucidating the roles of lectins in regulating the immune response within the TME is becoming increasingly important.\u003c/p\u003e \u003cp\u003eTn antigen is a TACA ranked as a high-priority cancer-associated antigen based on its antigenicity and oncogenicity \u003csup\u003e11,15\u0026ndash;19\u003c/sup\u003e. Tn is a truncated form of the cell surface O-glycan, consisting of the terminal O-linked N-acetylgalactosamine (GalNAc) attached to serine or threonine. The aberrant glycosylation associated with Tn may occur when the enzyme responsible for O-glycan elongation, T-synthase or its associated chaperone, Cosmc (C1GALT1C1), becomes functionally inhibited \u003csup\u003e20,21\u003c/sup\u003e. Tn-expressing mucin 1 (MUC1) has been associated with breast cancer cells \u003csup\u003e22,23\u003c/sup\u003e, especially in triple-negative breast cancer \u003csup\u003e24,25\u003c/sup\u003e. Modulating MUC1 expression or Tn glycosylation can inhibit tumor growth \u003csup\u003e26\u0026ndash;28\u003c/sup\u003e. However, developing immune responses against Tn-MUC1 has been problematic \u003csup\u003e29\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eHuman CLEC10A, also known as macrophage galactose-type lectin (MGL), is a C-type lectin receptor (CLR) that binds to Tn antigen on the surface proteins in humans \u003csup\u003e19,30\u003c/sup\u003e. In mice, the Tn-recognizing homolog of the human CLEC10A is CD301b, also known as MGL2 \u003csup\u003e19,31\u003c/sup\u003e. CD301b is primarily expressed by myeloid cells such as dendritic cells (DCs) and macrophages \u003csup\u003e17\u003c/sup\u003e. Previously, CD301b-expressing myeloid cell populations have been linked with immunosuppressive responses \u003csup\u003e16,17,19,32\u0026ndash;34\u003c/sup\u003e. DCs and macrophages can suppress the proliferation of CD4\u003csup\u003e+\u003c/sup\u003e effector T lymphocytes through the interaction of MGL with terminal GalNAc residues on CD45 expressed by T cells \u003csup\u003e17\u003c/sup\u003e. This cell-specific glycosylation of CD45 provided an immunoregulatory pathway, mediated by MGL, thereby controlling effector T cell function. In another study, CD301b\u003csup\u003e+\u003c/sup\u003e dendritic cells suppressed T follicular helper cells and antibody responses to protein antigens \u003csup\u003e32\u003c/sup\u003e. Recently, an immunosuppressive DC subset expressing CD301b was shown to accumulate at secondary sites and promote metastasis in pancreatic cancer \u003csup\u003e34\u003c/sup\u003e and lung cancer \u003csup\u003e35\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eBreast cancer-focused studies further support a functional Tn-CD301b/CLEC10A axis by showing that ligand display can be induced by clinically relevant tumor-cell perturbations, including endocrine manipulation (e.g., tamoxifen exposure), oxidative stress, and DNA damage, linking stress signaling to increased presentation of truncated O-glycan ligands\u003csup\u003e36\u003c/sup\u003e. In the same context, receptor-ligand readouts have been associated with breast cancer outcomes, suggesting that these glycan-lectin interactions reflect biologically meaningful variation in tumor-immune dynamics\u003csup\u003e36\u003c/sup\u003e. Complementing these observations, transcriptomic and immunoinformatics analyses across breast cancer cohorts and pan-cancer datasets indicate that CLEC10A expression tracks immune infiltration patterns and immune regulatory networks and is frequently associated with a more favorable prognosis, supporting further investigation into how tumor glycan presentation intersects with CLEC10A/CD301b signaling in vivo\u003csup\u003e37\u0026ndash;39\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn this study, we investigated the role of CD301b in a murine model of triple-negative breast cancer and found that the loss of CD301b expression significantly restricted tumor growth. Within the tumor microenvironment, CD301b-expressing immune cells were identified as type 2 conventional dendritic cells. To further explore the mechanisms underlying the observed tumor growth restriction, we performed bulk RNA sequencing (bulk RNA-seq) on murine tumors, which showed heightened inflammatory immune responses when CD301b was absent. Analysis of publicly available single-cell RNA sequencing (scRNA-seq) datasets revealed CLEC10A-expressing myeloid cell populations in human breast cancer tissues, suggesting that this regulatory axis extends beyond the murine model. Here, we examine whether the Tn-CD301b/CLEC10A axis links tumor glycosylation to a conserved myeloid regulatory program in breast cancer.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eCD301b/Tn Axis Impacts Tumor Growth.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWe first aimed to investigate the relationship between CD301b\u003csup\u003e+\u003c/sup\u003e immune cells and Tn glycoantigen-expressing breast cancer cells. We used a CRISPR-Cas9 gene editing model to knock out Cosmc expression in AT3 murine breast cancer cells. Cosmc is a chaperone essential in elongating the core O-glycan beyond the truncated Tn form of α-GalNAc \u003csup\u003e20,21,40\u003c/sup\u003e. When the Cosmc function/expression is disrupted, elongation of the O-glycan is not observed; instead, the Tn antigen is observed at significantly higher levels. After disrupting Cosmc expression in these cell lines, we confirmed increased Tn cell surface expression through flow cytometry using a reBaGs6 IgM antibody (Suppl. Figure\u0026nbsp;1A) \u003csup\u003e41\u003c/sup\u003e, a biotinylated VVL lectin coupled with fluorescent streptavidin (Suppl. Figure\u0026nbsp;1B), and a recombinant biotinylated Mgl2 carbohydrate binding domain (CBD)-GFP fusion protein coupled with streptavidin (Suppl. Figure\u0026nbsp;1C). All staining methods indicated significantly higher Tn expression on the \u003cem\u003eCosmc\u003c/em\u003e KO cell line. We also isolated RNA from each cell line and confirmed decreased Cosmc expression in the Tn\u003csup\u003ehi\u003c/sup\u003e cell line through qPCR using \u003cem\u003eCosmc\u003c/em\u003e primers (Suppl. Figure\u0026nbsp;1D). We then tested whether knocking out Cosmc expression changes the proliferation rate of the AT3 breast cancer cells \u003cem\u003ein vitro\u003c/em\u003e. After culturing both cell lines at the same concentrations for three days, we observed no significant differences in cell proliferation between the two lines (Suppl. Figure\u0026nbsp;1E), indicating that Tn expression alone does not promote cancer cell growth.\u003c/p\u003e \u003cp\u003eTo determine \u003cem\u003ein vivo\u003c/em\u003e tumor cell growth, we injected AT3 (Tn\u003csup\u003elo\u003c/sup\u003e) and AT3 \u003cem\u003eCosmc\u003c/em\u003e KO (Tn\u003csup\u003ehi\u003c/sup\u003e) murine breast tumor cells into the mammary pads of C57BL/6 mice and monitored tumor growth. We observed that Tn\u003csup\u003ehi\u003c/sup\u003e tumors grew significantly faster than Tn\u003csup\u003elo\u003c/sup\u003e tumors (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA), indicating that Tn expression impacts tumor growth rate.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo examine the contribution of CD301b-expressing immune cells to tumor growth, we employed heterozygous \u003cem\u003eMgl2\u003c/em\u003e\u003csup\u003e\u003cem\u003e+/DTReGFP\u003c/em\u003e\u003c/sup\u003e mice (Mgl2-DTR), in which CD301b+ immune cells can be selectively depleted by diphtheria toxin (DT) treatment \u003csup\u003e32,33\u003c/sup\u003e. In the first experiment (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB), AT3 Tn\u003csup\u003elow\u003c/sup\u003e or Tn\u003csup\u003ehi\u003c/sup\u003e tumor cells were injected into Mgl2-DTR mice with or without DT administration. Tumor growth was significantly reduced in DT-treated mice of the Tn\u003csup\u003ehi\u003c/sup\u003e group, indicating that CD301b\u003csup\u003e+\u003c/sup\u003e immune cells promote tumor progression. In a complementary experiment (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC), we injected AT3 Tn\u003csup\u003ehi\u003c/sup\u003e cells into homozygous \u003cem\u003eMgl2\u003c/em\u003e\u003csup\u003e\u003cem\u003eDTReGFP/DTReGFP\u003c/em\u003e\u003c/sup\u003e mice (CD301b-null, \u003cem\u003eMgl2\u003c/em\u003e KO), which lack surface expression of CD301b due to the disruption of both alleles but retain the immune cell populations. These mice also exhibited markedly reduced tumor growth compared with wild-type controls. Together, these experiments indicate that the observed phenotype is associated with tumor Tn expression and facilitated by the CD301b protein.\u003c/p\u003e \u003cp\u003e \u003cb\u003eTumor-infiltrating CD301b\u003c/b\u003e \u003csup\u003e \u003cb\u003e+\u003c/b\u003e \u003c/sup\u003e \u003cb\u003ecells display a type 2 conventional dendritic cell (cDC2) phenotype.\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe next characterized tumor-infiltrating CD45\u003csup\u003e+\u003c/sup\u003eCD301b\u003csup\u003e+\u003c/sup\u003e immune cells in the murine triple-negative breast cancer model. These cells expressed CD11c, a canonical dendritic cell (DC) marker \u003csup\u003e42,43\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA) and were strongly positive for MHCII, confirming their DC identity (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). CD301b⁺ cells also expressed CD11b, a defining marker of mouse type 2 conventional dendritic cells (cDC2s) \u003csup\u003e44\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Mouse cDC2s can be distinguished from cDC1s by CD103 and SIRP-alpha expressions \u003csup\u003e42,45\u003c/sup\u003e. We examined the expression of these markers by tumor-infiltrating CD301b\u003csup\u003e+\u003c/sup\u003e cells, which display a cDC2 phenotype (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). Although CD301b\u003csup\u003e+\u003c/sup\u003e cells are primarily cDC2s, not all DCs or cDC2s express CD301b in the TME (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ecDC2s constitute a subset of antigen-presenting cells that play key roles in coordinating adaptive immune responses. In contrast to cDC1s, which specialize in cross-presentation and cytotoxic T cell activation, cDC2s promote CD4⁺ T cell priming and modulate immune polarization within tissues \u003csup\u003e46\u0026ndash;48\u003c/sup\u003e. Recent studies have shown that cDC2s exhibit remarkable plasticity in the tumor microenvironment, where they can adopt either immunostimulatory or tolerogenic phenotypes in response to local cues \u003csup\u003e48\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eTumor-infiltrating CD301b\u003csup\u003e+\u003c/sup\u003e dendritic cells exhibit enhanced IL-10 expression and remain responsive to TLR4 stimulation\u003c/h2\u003e \u003cp\u003eBecause CD301b\u003csup\u003e+\u003c/sup\u003e dendritic cells have been linked to immunoregulatory activity in multiple settings, we next asked whether tumor-infiltrating CD301b\u003csup\u003e+\u003c/sup\u003e DCs display an IL-10-associated regulatory phenotype. IL-10 is a central anti-inflammatory cytokine that restrains excessive inflammation and suppresses T-cell effector programs through several mechanisms, including inhibition of antigen-presenting cell activation, inflammatory cytokine production, and downstream T-cell priming functions \u003csup\u003e49,50\u003c/sup\u003e. Prior studies have also associated CD301b/CLEC10A-expressing myeloid cells with immunosuppressive or regulatory functions, including suppression of T follicular helper responses, promotion of metastasis-associated immune suppression, and induction of regulatory programs in CD301b\u003csup\u003e+\u003c/sup\u003e antigen-presenting cells \u003csup\u003e34,51,52\u003c/sup\u003e. In addition, tumor-associated glycan-lectin interactions involving the CD301b/CLEC10A axis have been linked to immune modulation in cancer, including breast cancer and Tn-driven tumor models \u003csup\u003e35,37\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTo test whether CD301b\u003csup\u003e+\u003c/sup\u003e DCs in the breast tumor microenvironment (TME) are positioned to contribute to this regulatory axis, we compared IL-10 expression in CD301b\u003csup\u003e+\u003c/sup\u003e DCs isolated from tumors of wild-type mice under unstimulated conditions and after short-term stimulation with LPS, a TLR4 agonist. Unstimulated CD301b\u003csup\u003e+\u003c/sup\u003e DCs obtained from the spleens of na\u0026iuml;ve mice served as the control group. Tumor-derived CD301b\u003csup\u003e+\u003c/sup\u003e DCs showed a detectable IL-10\u003csup\u003e+\u003c/sup\u003e expression at baseline, and this population increased further after LPS stimulation, indicating that these cells may contribute to immune regulation within the TME and remain capable of augmenting IL-10 production in response to inflammatory cues. This observation is consistent with prior work showing that CLEC10A/CD301b engagement can cooperate with innate stimuli to enhance IL-10 production in dendritic cells and promote regulatory programming \u003csup\u003e51\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eNotably, CD301b\u003csup\u003e+\u003c/sup\u003e DCs isolated from the TME displayed a greater frequency of IL-10-expressing cells than their splenic counterparts under both unstimulated and LPS-stimulated conditions. These findings suggest that the tumor microenvironment either enriches for an IL-10-competent CD301b\u003csup\u003e+\u003c/sup\u003e DC population or licenses infiltrating CD301b\u003csup\u003e+\u003c/sup\u003e DCs toward a more suppressive phenotype after tumor entry. Together, these data support IL-10 production as a functional feature of tumor-associated CD301b\u003csup\u003e+\u003c/sup\u003e DCs and offer a plausible mechanistic link between CD301b\u003csup\u003e+\u003c/sup\u003e myeloid cell accumulation and the suppression of productive anti-tumor inflammation. Although these data do not establish IL-10 as the sole mediator of the phenotype, they support IL-10 competence as a functional feature of tumor-associated CD301b\u003csup\u003e+\u003c/sup\u003e dendritic cells.\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe lack of CD301b is associated with a strong inflammatory immune signature in the breast TME\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSince CD301b directly associates with tumor growth and identifies cDC2 and macrophage populations within the breast tumor microenvironment (TME), we examined how its loss impacts immune signaling and tumor\u0026ndash;immune interactions. To this end, we performed bulk RNA sequencing (bulk RNA-seq) on tumors derived from wild-type (WT) and \u003cem\u003eMgl2\u003c/em\u003e knockout (\u003cem\u003eMgl2\u003c/em\u003e KO) mice following injection of AT3 Tn\u003csup\u003ehi\u003c/sup\u003e tumor cells. The global transcriptomic heatmap (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA) revealed distinct clustering and clear separation between WT and \u003cem\u003eMgl2\u003c/em\u003e KO mouse tumors, indicating a strong transcriptional divergence associated with \u003cem\u003eMgl2\u003c/em\u003e loss. This observation provided the foundation for downstream pathway and gene-level analyses to elucidate how CD301b influences immune regulation within the TME.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo dissect these transcriptomic differences, Gene Set Enrichment Analysis (GSEA) was performed using the Hallmark and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment gene set databases (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB\u0026ndash;C). \u003cem\u003eMgl2\u003c/em\u003e KO tumors displayed significant enrichment of immune and inflammatory pathways, including TNF-α/NF-κB, IL-6/JAK-STAT3, interferon-α/γ, and IL-17 signaling\u0026mdash;pathways broadly associated with myeloid activation, cytokine production, and tumor immunosurveillance \u003csup\u003e53,54\u003c/sup\u003e. Despite the slower tumor growth observed in the knockout mice, complement/coagulation, hypoxia, and glycolytic pathways were also upregulated, suggesting a compensatory increase in metabolic and inflammatory activity within the TME. Collectively, these data suggest that CD301b functions as an immunoregulatory node that tempers cytokine and interferon responses, whereas its loss enhances pro-inflammatory signaling. The dominance of interferon- and NF-κB\u0026ndash;driven programs aligns with the slower tumor progression observed in KO mice, implying that CD301b deficiency reprograms the TME toward a functionally immune-active, tumor-controlling state.\u003c/p\u003e \u003cp\u003eThe pathway-focused volcano plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD) highlights key upregulated genes underpinning these responses, including \u003cem\u003eCxcl3, Il1a, Il23a, Il36g, Csf3, Nos2, S100a8, S100a9\u003c/em\u003e, and \u003cem\u003eLcn2\u003c/em\u003e. These represent canonical NF-κB and IL-17 targets known to mediate myeloid recruitment, nitric oxide production, and acute-phase inflammation\u0026mdash;hallmarks of innate immune activation \u003csup\u003e55\u0026ndash;57\u003c/sup\u003e. The upregulation of the serine protease inhibitor and matrix metalloproteinase genes \u003cem\u003eSerpinb2\u003c/em\u003e and \u003cem\u003eMmp10\u003c/em\u003e in the tumor microenvironment of knockout mice suggests a tumor-suppressive function through the regulation of extracellular matrix remodeling and modulation of immune responses \u003csup\u003e58,59\u003c/sup\u003e. Thus, CD301b loss is associated with a more inflammatory transcriptional profile in the tumor microenvironment, characterized by innate immune activation, interferon-associated programs, and concurrent tissue-remodeling features.\u003c/p\u003e \u003cp\u003eThe volcano plot of all differentially expressed genes (DEGs) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE) contextualizes these changes within the full transcriptome. Upregulated genes largely mirrored those driving enriched pathways, confirming that \u003cem\u003eCxcl3, Il1a, Il23a, Nos2, S100a8/a9\u003c/em\u003e, and \u003cem\u003eCsf3\u003c/em\u003e constitute the core \u003cem\u003eMgl2\u003c/em\u003e KO transcriptional program rather than isolated pathway artifacts. On the other hand, downregulation of the TGF-β family growth differentiation factor 3 and the apelin receptor genes \u003cem\u003eGdf3\u003c/em\u003e and \u003cem\u003eAplnr\u003c/em\u003e may be relevant to pathways involved in tumor growth, angiogenesis, and metastasis \u003csup\u003e60,61\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTogether, these results suggest that CD301b deficiency reprograms the TME toward an inflammatory and interferon-dominant transcriptional state associated with delayed tumor growth. These findings support the interpretation that CD301b functions as an immunoregulatory myeloid node whose loss releases inflammatory immune programs within the breast tumor microenvironment.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCLEC10A⁺ myeloid cells in the human breast cancer TME include both dendritic cells and macrophages\u003c/h3\u003e\n\u003cp\u003eTo determine how CLEC10A maps onto human breast tumor myeloid populations, we next analyzed publicly available single-cell RNA sequencing (scRNA-seq) data (GSE161529) from 20 patients, including triple-negative (n\u0026thinsp;=\u0026thinsp;8), ER⁺ (n\u0026thinsp;=\u0026thinsp;6), and HER2⁺ (n\u0026thinsp;=\u0026thinsp;6) tumors \u003csup\u003e62\u003c/sup\u003e. Following quality control, data integration, and annotation, we focused on CD45⁺ immune cells to map CLEC10A expression across myeloid populations (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA; Suppl. Figure\u0026nbsp;3A). CLEC10A expression was most prominent in dendritic cells and was also detectable in macrophage/monocyte populations, with negligible expression in other immune cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB\u0026ndash;C). Across breast cancer subtypes, dendritic cells consistently showed higher CLEC10A expression than macrophages (Suppl. Figure\u0026nbsp;3B). Within the dendritic cell compartment, we identified four subsets\u0026mdash;cDC1, cDC2, cDC-LAMP3⁺, and plasmacytoid DC (pDC)\u0026mdash;and found that CLEC10A expression was highest in cDC2 (56.9%) and moderate in cDC-LAMP3⁺ (11.3%), but low in cDC1 (1.9%) and absent in pDCs (0%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD\u0026ndash;F; Suppl. Figure\u0026nbsp;3C\u0026ndash;D).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe next examined tumor-associated macrophages (TAMs). TAMs are key regulators of tumor inflammation, tissue remodeling, and immune suppression \u003csup\u003e63\u003c/sup\u003e. TAMs were subdivided into transcriptionally defined subsets reflecting distinct functional programs: C1QC⁺ macrophages, associated with immunosuppression \u003csup\u003e64\u0026ndash;66\u003c/sup\u003e; NLRP3⁺ macrophages, associated with poor prognosis and tumor growth \u003csup\u003e67,68\u003c/sup\u003e; and INHBA⁺ macrophages, linked to angiogenesis, matrix remodeling, and tumor progression \u003csup\u003e69\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG; Suppl. Figure\u0026nbsp;3E). Among these subsets, \u003cem\u003eCLEC10A\u003c/em\u003e transcription distributed similarly in C1QC⁺ macrophages (11%), NLRP3⁺ macrophages (9%), and INHBA⁺ macrophages (7%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eH\u0026ndash;I). Interestingly, CLEC10A-positive NLRP3⁺ macrophages were detected exclusively in triple-negative breast cancers, where expression levels were comparable to those in INHBA⁺ macrophages (Suppl. Figure\u0026nbsp;3F). This enrichment suggests that CLEC10A expression extends beyond dendritic cells to macrophage populations, particularly those engaged in inflammatory and tissue-remodeling responses within aggressive tumor subtypes.\u003c/p\u003e \u003cp\u003eTaken together, these results indicate that CLEC10A expression in the human breast cancer microenvironment is concentrated within myeloid lineages\u0026mdash;encompassing both cDC2-like dendritic cells and specialized macrophage subsets. This pattern mirrors the cellular distribution observed in the mouse TME, suggesting that CLEC10A/CD301b marks a conserved myeloid program potentially involved in coordinating immune regulation and tissue remodeling during tumor progression.\u003c/p\u003e\n\u003ch3\u003eCLEC10A marks a convergent transcriptional state across human breast cancer cDC2 and macrophages\u003c/h3\u003e\n\u003cp\u003eTo define the transcriptional programs associated with CLEC10A expression in human breast tumor myeloid cells, we performed differential expression analysis on a per-patient basis comparing CLEC10A⁺ and CLEC10A⁻ cells within the cDC2 and macrophage compartments from all human breast cancer samples shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA-B). In cDC2, CLEC10A⁺ cells were enriched for canonical antigen-presentation and cDC2-associated genes, including CLEC10A, CD1C, CD1B, FCER1A, and multiple HLA class II genes, confirming that CLEC10A identifies a differentiated antigen-presenting cDC2 state. CLEC10A⁺ cDC2 also upregulated IL1R2, FCGR2B, MRC1, and MMP12, consistent with an immune-regulatory and tumor-conditioning program. In contrast, CLEC10A⁻ cDC2 showed relatively higher expression of genes such as LTB, PLAC8, CST3, FCGBP, and IL22RA2, indicating a transcriptionally distinct state with less canonical antigen-presentation identity and greater inflammatory or tissue-reactive features.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA parallel pattern emerged in macrophages. CLEC10A⁺ macrophages upregulated CLEC10A together with CD1E, CD1B, LGALS2, IDO1, and LYVE1, supporting a state linked to antigen handling, immune regulation, and tissue-remodeling functions. By contrast, CLEC10A⁻ macrophages preferentially expressed inflammatory mediators and monocyte/TAM-associated genes, including SPP1, CCL2, CCL3, CCL4, TNF, IL1B, CXCL8, VCAN, PLAUR, HIF1A, ANGPTL4, and SERPINE1, consistent with a more inflammatory and tumor-promoting phenotype. Thus, the human cDC2 and macrophage datasets are concordant in showing that CLEC10A marks a shared myeloid state characterized by stronger antigen-presentation features but restrained inflammatory cytokine and chemokine programs. This interpretation is consistent with the mouse data: CD301b prominently marked cDC2s in tumors, whereas in vivo loss of CD301b was associated with a broad induction of inflammatory pathways and innate cytokine programs, as inferred from bulk RNA-seq.\u0026nbsp;Together, the human single-cell and mouse bulk RNA-seq data support a model in which CLEC10A/CD301b identifies a conserved myeloid program associated with stronger antigen-presentation features and reduced inflammatory cytokine and chemokine expression, consistent with a more regulatory state in the breast tumor microenvironment.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAberrant glycosylation is a hallmark of malignant transformation, and our findings identify CD301b as a key immunoregulatory lectin that links breast tumor-associated Tn antigens to myeloid immune modulation. CD301b⁺ cells, primarily cDC2s, promoted breast tumor growth, whereas their depletion or genetic loss limited progression. These observations align with previous studies demonstrating that TACAs interact with lectins to influence myeloid differentiation and immune regulation \u003csup\u003e19,21,22,70\u0026ndash;72\u003c/sup\u003e. In breast cancer, the Tn-CD301b/CLEC10A axis can now be traced across tumor glycosylation, murine in vivo tumor growth, tumor transcriptomic reprogramming, and human myeloid single-cell states.\u003c/p\u003e \u003cp\u003eTranscriptomic profiling of tumors developed in \u003cem\u003eMgl2\u003c/em\u003e-KO mice revealed broad activation of NF-κB, IL-6\u0026ndash;JAK\u0026ndash;STAT3, and interferon pathways, consistent with a shift toward a more inflammatory transcriptional state within the TME \u003csup\u003e73\u003c/sup\u003e. These data position CD301b as an immunoregulatory node that tempers innate activation, similar in concept to a checkpoint-like mechanism operating within the myeloid compartment \u003csup\u003e9,10,74,75\u003c/sup\u003e. While this study does not define the signaling circuitry involved, it indicates that CD301b-expressing myeloid populations, particularly cDC2s and potentially macrophages, contribute to an immunoregulatory phenotype in the breast cancer TME. In support of this interpretation, tumor-infiltrating CD301b⁺ dendritic cells displayed higher IL-10 expression than splenic CD301b⁺ DCs at baseline and after LPS stimulation, indicating that the tumor microenvironment enriches for, or licenses, a CD301b⁺ DC population with enhanced regulatory cytokine competence.\u003c/p\u003e \u003cp\u003eThe complex and pleiotropic nature of CD301b\u0026rsquo;s activity may explain its influence on the immune landscape of cancer \u003csup\u003e74\u0026ndash;76\u003c/sup\u003e. CD301b\u0026rsquo;s modulatory behavior mirrors that of other C-type lectin receptors \u003csup\u003e77\u003c/sup\u003e. CD301b-mediated restraint may protect against chronic inflammation, but in tumors, it can inadvertently favor immune escape \u003csup\u003e78,79\u003c/sup\u003e. Conversely, CD301b loss triggers NF-κB- and interferon-associated inflammation, while also imposing metabolic and hypoxic stress on the TME\u003csup\u003e80\u003c/sup\u003e. Together, these findings support a model in which CD301b functions as a molecular regulator balancing immune activation and tolerance in breast cancer.\u003c/p\u003e \u003cp\u003eA growing mechanistic literature contextualizes the downstream programming capacity of the CLEC10A/CD301b lectin axis. In human antigen-presenting cells, CLEC10A engagement has been repeatedly linked to regulatory polarization, often characterized by enhanced IL-10 production and consequent dampening or redirection of effector T-cell responses\u003csup\u003e37,51\u003c/sup\u003e. Importantly for mouse interpretation, CD301b pathways have been linked to IL-10 induction across multiple experimental systems, indicating that IL-10 skewing is a conserved output that should be integrated into models of CD301b-driven immune modulation\u003csup\u003e35,51\u003c/sup\u003e. A recent ligand-centric study further shows that distinct GalNAc-containing ligands can tune CLEC10A signaling strength and dendritic cell transcriptional outputs, supporting the idea that qualitative features of tumor-associated glycan ligands may shift the balance between inflammatory and regulatory programs in the TME \u003csup\u003e81\u003c/sup\u003e. Our findings are consistent with this concept at both functional and transcriptional levels: in mice, tumor-associated CD301b⁺ DCs exhibited enhanced IL-10 competence, whereas in human breast cancer, CLEC10A⁺ cDC2s and macrophages displayed a distinct transcriptional state enriched for canonical cDC2 genes and genes associated with immune dampening and tumor conditioning.\u003c/p\u003e \u003cp\u003eTherefore, our findings support CD301b-Tn interactions as an immune-regulatory axis in the breast TME that may regulate antigen processing, cytokine release, or costimulatory signaling within dendritic cells, thereby shaping T cell activation thresholds \u003csup\u003e77\u003c/sup\u003e. These possibilities highlight the clinical potential of CD301b as a new immune-regulatory axis distinct from canonical checkpoints, such as PD-1 or CTLA-4. A limitation of the current study is that the downstream effects of this myeloid program on lymphocytes remain unresolved. Thus, while our data support a primary role for CD301b-associated myeloid reprogramming, they do not yet define how this state influences T-cell or NK-cell recruitment, activation, spatial organization, or effector function in the tumor microenvironment. Future studies will be needed to determine whether altered cytokine or chemokine production, antigen presentation, or other indirect mechanisms link CD301b-dependent myeloid states to downstream antitumor immunity. A key next step will be to define how specific TACA ligand structures and intracellular adaptors determine signaling strength, pathway selection, and the balance between immunoregulatory signaling, cytokine outputs, and anti-tumor effector programs in vivo. Further single-cell and spatial analyses of the breast TME transcriptome, with and without CD301b, will help define how CD301b⁺ subsets integrate into existing immune networks across tumor stages.\u003c/p\u003e \u003cp\u003eFrom a translational perspective, targeting the CLEC10A/CD301b-Tn interaction offers a promising route to modulate the breast cancer immune microenvironment. Pharmacologic blockade or glycomimetic interference could complement checkpoint inhibitors by dismantling glycan-mediated myeloid suppression, whereas selective induction of this pathway may have therapeutic relevance in autoimmune disease \u003csup\u003e82\u003c/sup\u003e. Ultimately, elucidating the intricate mechanisms that govern immune modulation through CD301b will be essential to selectively induce these properties in disease-specific contexts, enabling the development of knowledge-based, precision immunotherapies.\u003c/p\u003e \u003cp\u003eIn summary, this study identifies an immunomodulatory CD301b⁺ myeloid phenotype that contributes to breast cancer growth and whose loss induces a robust inflammatory program in the breast TME. Our results further suggest that this phenotype includes tumor-associated CD301b⁺ dendritic cells with enhanced IL-10 expression and conserved human CLEC10A⁺ cDC2 and macrophage transcriptional states linked to immune dampening and tumor conditioning. While the molecular mechanisms remain to be defined, our data indicate that CD301b acts as a glycan-sensitive, checkpoint-like regulator of myeloid activity. Elucidating its ligand specificity and downstream signaling will clarify how breast tumor glycosylation reshapes the TME and may reveal new strategies to enhance immunotherapy efficacy.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eMice\u003c/h2\u003e \u003cp\u003eEight-week-old female C57BL/6 mice were obtained from Jackson Laboratories (Bar Harbor, ME) and housed at Emory University Whitehead Biomedical Research Building. \u003cem\u003eMgl2\u003c/em\u003e\u003csup\u003e\u003cem\u003eDTReGFP/DTReGFP\u003c/em\u003e\u003c/sup\u003e mice were a generous gift from Akiko Iwasaki at Yale University. To obtain heterozygous \u003cem\u003eMgl2\u003c/em\u003e\u003csup\u003e\u003cem\u003e+/DTReGFP\u003c/em\u003e\u003c/sup\u003e mice, C57BL/6 were bred with \u003cem\u003eMgl2\u003c/em\u003e\u003csup\u003e\u003cem\u003eDTReGFP/DTReGFP\u003c/em\u003e\u003c/sup\u003e mice. Mice were kept in microisolator cages and handled under biosafety level 2 (BSL2) hoods. For tissue processing and subsequent flow cytometry, mice were euthanized by carbon dioxide inhalation in accordance with IACUC guidelines. Where applicable, cell suspensions were generated through mechanical tissue disruption and collagenase D digestion. Red blood cells were lysed, and samples were filtered through 60 \u0026micro;m nylon filters to obtain single-cell suspensions. For depletion of CD301b\u003csup\u003e+\u003c/sup\u003e cells, heterozygous Mgl2-DTR mice were treated with diphtheria toxin (0.5\u0026micro;g/mouse) in sterile PBS intraperitoneally every two to three days, starting at day\u0026thinsp;\u0026minus;\u0026thinsp;1 before tumor injection.\u003c/p\u003e \u003cp\u003e All mouse experiments were in compliance with the Emory University Institutional Animal Care and Use Committee under an approved animal use protocol. Our animal use protocol adheres to the principles outlined in \u003cem\u003eU.S. Government Principles for the Utilization and Care of Vertebrate Animals Used in Testing\u003c/em\u003e, \u003cem\u003eResearch and Training\u003c/em\u003e, the Animal Welfare Act, the \u003cem\u003eGuide for the Care and Use of Laboratory Animals\u003c/em\u003e, and the \u003cem\u003eAVMA Guidelines for the Euthanasia of Animals\u003c/em\u003e.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eGeneration of Tn breast cancer cells\u003c/h3\u003e\n\u003cp\u003eTo express Tn glycans at high levels in tumor cells, we used a CRISPR/Cas9 methodology to stably silence Cosmc expression in AT3 cells using established protocols and reagents. Mouse \u003cem\u003eCosmc\u003c/em\u003e guide RNA and CRISPR/Cas9 plasmid were obtained from Santa Cruz Technology (sc-425587). AT3 murine breast cancer cells were a generous gift from the Kebin Liu lab at Augusta University. AT3 cells were transfected with \u003cem\u003eCosmc\u003c/em\u003e CRISPR/Cas9 KO plasmid according to the manufacturer\u0026rsquo;s protocol. Puromycin was used to select transfected cells. We then used flow cytometry to confirm higher expression of Tn on the AT3 cell surfaces using the ReBaG6 antibody (generously provided by Richard Cummings at Harvard University) (Suppl. Figure\u0026nbsp;1A) \u003csup\u003e41\u003c/sup\u003e and VVL lectin (Vector Laboratories) (Suppl. Figure\u0026nbsp;1B). The proliferations of transfected and untransfected cell lines (AT3 Tn\u003csup\u003ehi\u003c/sup\u003e and AT3 Tn\u003csup\u003elow\u003c/sup\u003e) were tested in an MTT proliferation assay for three days, and colorimetric analysis was performed with a CytoTek plate reader according to protocol; no significant differences in proliferation compared to parent cells were observed (Suppl. Figure\u0026nbsp;1D). Cell lines were maintained in RPMI media supplemented with 10% FBS, sodium pyruvate, HEPES buffer, NEAA, β-mercaptoethanol, and penicillin/streptomycin at 37\u003csup\u003eo\u003c/sup\u003eC, 5% CO2.\u003c/p\u003e\n\u003ch3\u003eAT3 Tn and/or AT3 Tn Tumor Challenge\u003c/h3\u003e\n\u003cp\u003eAT3 cells were harvested and washed in sterile PBS. Cells were suspended in a final concentration of 2.5E6/ml sterile PBS. Cells were subcutaneously injected into the mammary pads of mice at 2.5E5/100\u0026micro;l/mouse. Mice were monitored throughout the experiment and euthanized at the tumor endpoint, defined as the maximum tumor dimension of 0.9\u0026ndash;1.2 cm. Tumor volumes were calculated as ((length x width x width)/2) in mm\u003csup\u003e3\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eFlow Cytometry\u003c/h2\u003e \u003cp\u003eCells were stained in PBS with TruStain fcX (BioLegend, Cat. No. 101320) to reduce non-specific antibody binding. Cell samples were stained with the following antibodies and stains: CD11c-PacBlue (BioLegend, clone N418), CD11b-Alexa Fluor 488 (BioLegend, clone M1/70), CD11b-BUV 805 (Invitrogen, clone M1/70), SIRPα-Alexa Fluor 700 (BioLegend, clone P84), CD103-PE/Dazzle 594 (BioLegend, clone 2E7), MHCII-BV785 (BioLegend, clone M5/114.15.2), CD45-Spark UV 387 (BioLegend, clone 30-F11), CD45-Alexa Fluor 647 (BioLegend, clone 30-F11), IL-10-APC (BioLegend, clone JES5-16E3), CD301b-PE (BioLegend, clone URA-1), and LIVE/DEAD Fixable Blue (Invitrogen). All isotype controls were obtained from BioLegend. Samples were washed and analyzed with flow cytometry (Cytek Aurora). Fluorescence minus one (FMO) plus specific isotype control antibody-stained samples were used as negative staining controls, and single stains were used for compensation. Flow cytometry data were analyzed using FlowJo Single Cell Analysis Software. For IL-10 staining, cells were incubated for 4 hours in the presence of GolgiStop and GolgiPlug. The concentration of LPS used for \u003cem\u003ein vitro\u003c/em\u003e stimulation was 1 \u0026micro;g/ml.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eBulk RNA-seq and Bioinformatics\u003c/h2\u003e \u003cp\u003eTumors were harvested from wild-type C57BL/6J and \u003cem\u003eMgl2\u003c/em\u003e KO mice (n\u0026thinsp;=\u0026thinsp;3 per group) at the experimental endpoint defined in the tumor challenge protocol. Total RNA was extracted using the MagMAX\u0026trade; mirVana\u0026trade; Total RNA Isolation Kit in combination with the KingFisher Apex system (Thermo Fisher Scientific). RNA integrity and concentration were assessed with a Qubit 3.0 fluorometer (Thermo Fisher Scientific). High-quality RNA samples were used for library preparation, followed by quality control and sequencing using Novogene\u0026rsquo;s standard protocol. Libraries were sequenced on the Illumina NovaSeq X Plus platform to generate paired-end 150 bp reads (PE150) at Novogene Inc. Raw FASTQ files were retrieved and subjected to quality control with FastQC \u003csup\u003e83\u003c/sup\u003e. Reads were aligned to the \u003cem\u003eMus musculus\u003c/em\u003e reference genome (GRCm39/mm39) using HISAT2 \u003csup\u003e84\u003c/sup\u003e. A gene-level count matrix was generated with featureCounts \u003csup\u003e85\u003c/sup\u003e. The count matrix was imported to the downstream differential expression analysis using the \u003cem\u003eDESeq2\u003c/em\u003e R package \u003csup\u003e86\u003c/sup\u003e. Significantly differentially expressed genes were defined by adjusted p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Gene Set Enrichment Analysis (GSEA) was performed on the RNA-seq dataset using the clusterProfiler R package \u003csup\u003e87\u003c/sup\u003e to identify significantly enriched KEGG and hallmark pathways between \u003cem\u003eMgl2\u003c/em\u003e KO and wild-type tumors. To focus on cancer-relevant biology, enrichment results were refined to include immune- and cancer-related pathways.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eAnalyzing the scRNA-seq data\u003c/h2\u003e \u003cp\u003escRNA-seq data generated using the 10X Genomics Chromium platform were obtained from the Gene Expression Omnibus (GEO; accession GSE161529) \u003csup\u003e88\u003c/sup\u003e. Data processing was performed using the Seurat R package (version 5). Low-quality cells were excluded based on standard Seurat quality-control metrics, \u003csup\u003e89\u003c/sup\u003e and putative doublets were removed using DoubletFinder. \u003csup\u003e90\u003c/sup\u003e The datasets were integrated using the Seurat reciprocal PCA (RPCA)-based integration workflow. Cell-type annotation was subsequently performed using scATOMIC, \u003csup\u003e91\u003c/sup\u003e and dendritic cell and macrophage subsets were further confirmed using canonical lineage markers from CellMarker 2.0.\u003csup\u003e92,93\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFor differential expression analysis, cDC2 and macrophage populations were analyzed separately by generating donor-level pseudobulk profiles, with CLEC10A-positive and CLEC10A-negative cells defined as the comparison groups within each cell type. Differential expression testing was then performed using edgeR \u003csup\u003e94\u003c/sup\u003e with a design matrix including group and donor as covariates, thereby controlling for inter-donor variability.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eGraphPad Prism v8 was used for statistical analyses. Two-way ANOVA with Tukey\u0026rsquo;s multiple comparisons test was used to determine statistical significance between experimental groups in each of the applicable experimental models (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). An unpaired parametric two-tailed t-test was used for Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA, \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC, \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB, \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC, \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD, \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE, and Suppl. Figure\u0026nbsp;1C. Significance is indicated on each graph based on p-value: \u0026gt;0.05\u0026thinsp;=\u0026thinsp;ns; \u0026lt;.05 = *; \u0026lt;0.01 = **; \u0026lt;0.001 = ***; \u0026lt;0.0001 = ****.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eA.O., A.V.P., and F.Y.A. conceptualized and wrote the manuscript; A.O., A.V.P, F.Z.N. prepared Figures 1-3; A.O., A.M.N prepared Figures4-6; F.Y.A supervised the research and acquired funds.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe acknowledge the following individuals for their contributions of transgenic mice, cell lines, and monoclonal antibodies: Dr. Akiko Iwasaki, Dr. Kebin Liu, and Dr. Richard Cummings. National Institutes of Health grants (R01AI123383 and R01AI152766) and the Winship Cancer Institute Winship Invest\u003cspan\u003e$\u003c/span\u003e Pilot Grant supported this work.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eZhang, Y. \u0026amp; Zhang, Z. The history and advances in cancer immunotherapy: understanding the characteristics of tumor-infiltrating immune cells and their therapeutic implications. \u003cem\u003eCell Mol Immunol\u003c/em\u003e \u003cstrong\u003e17\u003c/strong\u003e, 807-821 (2020). https://doi.org:10.1038/s41423-020-0488-6\u003c/li\u003e\n\u003cli\u003eSwoboda, A. \u0026amp; Nanda, R. Immune Checkpoint Blockade for Breast Cancer. \u003cem\u003eCancer Treat Res\u003c/em\u003e \u003cstrong\u003e173\u003c/strong\u003e, 155-165 (2018). https://doi.org:10.1007/978-3-319-70197-4_10\u003c/li\u003e\n\u003cli\u003eFiorentino, D. F., Bond, M. W. \u0026amp; Mosmann, T. R. Two types of mouse T helper cell. IV. 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K. edgeR v4: powerful differential analysis of sequencing data with expanded functionality and improved support for small counts and larger datasets. \u003cem\u003eNucleic Acids Res\u003c/em\u003e\u003cstrong\u003e53\u003c/strong\u003e (2025). https://doi.org:10.1093/nar/gkaf018\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"npj-breast-cancer","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"npjbcancer","sideBox":"Learn more about [npj Breast Cancer](http://www.nature.com/npjbcancer/)","snPcode":"41523","submissionUrl":"https://mts-npjbcancer.nature.com/","title":"npj Breast Cancer","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-9347231/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9347231/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAberrant tumor glycosylation can alter immune recognition; however, the specific influence of glycan-lectin interactions on tumor progression remains poorly understood. Here, we identify the C-type lectin receptor CD301b (encoded by \u003cem\u003eMgl2\u003c/em\u003e) as a regulator of immune activity within the breast tumor microenvironment (TME) and identify a cross-species myeloid regulatory program associated with its human ortholog CLEC10A. Using a murine triple-negative breast cancer model, we demonstrate that tumors expressing the Tn glycoantigen grow more rapidly, and this growth is facilitated by CD301b⁺ immune cells. Depletion or genetic loss of CD301b markedly suppressed tumor growth, indicating that CD301b promotes tumor progression, potentially through myeloid-tumor interactions. Phenotypic analyses revealed that tumor-infiltrating CD301b⁺ cells are predominantly type 2 conventional dendritic cells (cDC2s) and exhibit IL-10 expression within the TME. Transcriptomic profiling of tumors developed in \u003cem\u003eMgl2\u003c/em\u003e-KO mice revealed a shift toward an inflammatory, interferon-dominant transcriptional state, consistent with altered antitumor immune programming. Single-cell RNA sequencing of human breast cancers revealed that CLEC10A is expressed in cDC2 and select macrophage subsets. Additionally, CLEC10A-positive cDC2 and macrophages share a transcriptional state characterized by enhanced antigen presentation and immune-regulatory functions compared to CLEC10A-negative cells. Together, these findings support a relationship between tumor glycosylation and CLEC10A/CD301b-associated myeloid regulation, highlighting this axis as a potential target for reprogramming the breast tumor immune microenvironment.\u003c/p\u003e","manuscriptTitle":"Tumor glycosylation engages CD301b-mediated myeloid regulation in breast cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-05 19:12:21","doi":"10.21203/rs.3.rs-9347231/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-10T15:20:43+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-05T09:40:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"118059292215888580594518913897483444422","date":"2026-04-28T08:01:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"5341718169842800793575762499126633264","date":"2026-04-27T22:03:07+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-26T23:52:47+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-26T23:22:48+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-09T15:49:31+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Breast Cancer","date":"2026-04-07T15:34:57+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-breast-cancer","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"npjbcancer","sideBox":"Learn more about [npj Breast Cancer](http://www.nature.com/npjbcancer/)","snPcode":"41523","submissionUrl":"https://mts-npjbcancer.nature.com/","title":"npj Breast Cancer","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1bf43d9d-8c1a-43a0-975e-b63ae5bef0c5","owner":[],"postedDate":"May 5th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-10T15:20:43+00:00","index":11,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-05T09:40:15+00:00","index":10,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":67147455,"name":"Biological sciences/Cancer"},{"id":67147456,"name":"Biological sciences/Computational biology and bioinformatics"},{"id":67147457,"name":"Biological sciences/Immunology"},{"id":67147458,"name":"Health sciences/Oncology"}],"tags":[],"updatedAt":"2026-05-05T19:12:21+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-05 19:12:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9347231","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9347231","identity":"rs-9347231","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}