Fucosylation of HLA-DRB1 regulates CD4+T cell-mediated anti-melanoma immunity and enhances immunotherapy efficacy

doi:10.21203/rs.3.rs-2023267/v1

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Fucosylation of HLA-DRB1 regulates CD4⁺T cell-mediated anti-melanoma immunity and enhances immunotherapy efficacy

https://doi.org/10.21203/rs.3.rs-2023267/v1

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published 23 Jan, 2023

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Despite reports of striking outcomes, immunotherapy efficacy in melanoma is limited to subsets of patients ^{1, 2}. Combining immunotherapies with other modalities has yielded limited improvements but also adverse events requiring cessation of treatment ¹. In addition to ineffective patient stratification, efficacy can be impaired by paucity of tumor-infiltrating lymphocytes (TILs). Thus, effective strategies to safely increase TILs are urgently needed to improve immunotherapies ³. Here, we report that dietary administration of the sugar L-fucose triggers CD4⁺T cell-mediated increases in TILs, anti-tumor immunity, and enhanced immune checkpoint blockade responses. This is induced by the fucosylation and cell surface enrichment of the MHC-II protein HLA-DRB1 in melanoma. Single-cell immunofluorescent staining analysis of patient melanoma specimens demonstrates that fucosylation and fucosylated HLA-DRB1 is associated with intratumoral T cell abundance and anti-PD1 responder status. Our findings demonstrate that fucosylation is a key mediator of anti-tumor immunity, via regulation of melanoma cell surface HLA-DRB1 and induction of anti-tumor immunity, suggesting use of melanoma fucosylation as a novel strategy to stratify patients for immunotherapies. Importantly, our study suggests that L-fucose represents a powerful, non-toxic agent for safely increasing anti-tumor immunity and immunotherapy efficacy in melanoma.

Immunotherapy responsiveness can be impaired by insufficient abundance and activity of tumor-infiltrating lymphocytes (TILs) ³. Elucidating TIL biology and developing safe and effective strategies to increase TILs are crucial for improving the efficacy of immunotherapies.

Fucosylation, the conjugation of glycoproteins with the sugar L-fucose (L-fuc) at asparagine or serine/threonine residues (N- or O-linked, respectively) is mediated by 13 fucosyltransferases (FUTs) and impacts protein functions that are crucial for immune and developmental processes ^{4, 5}. Whereas altered fucosylation has been reported in a number of cancers, our understanding of its mechanisms and functional contributions is limited ^{6, 7}. We previously found that global fucosylation decreases during melanoma progression, and increased tumor fucosylation levels correlate with favorable patient survival outcomes ⁸. Further, increasing melanoma fucosylation in a syngeneic mouse model reduced tumor growth and metastasis and significantly increased intratumoral immune cells (itICs). How fucosylation regulates anti-tumor immunity, however, was unknown. Here, we report for the first time that dietary L-fuc can regulate the biology and interactions between CD4⁺T and melanoma cells, robustly inducing TILs and anti-melanoma immunity. Our findings demonstrate the ability of L-fuc to improve the efficacy of immunotherapies and identify novel fucosylation-based biomarkers that may enhance patient stratification.

Increasing melanoma fucosylation impairs tumor growth and augmentsTIL abundance, particularly CD4⁺ and CD8⁺ T cells

We initially assessed how L-fuc-induced changes in itICs might contribute to melanoma suppression using a NRAS^G13D-mutant mouse melanoma (SW1) model ^{8, 9}. Oral L-fuc administration increased tumor fucosylation (~ 2-fold), reduced tumor growth (~ 50%), and increased total itICs (~ 10-50-fold) (including CD3⁺ (CD4⁺ and CD8⁺) T, natural killer (NKs), macrophage (MΦ), dendritic (DCs), and myeloid-derived suppressor (MDSCs)-like cell subpopulations, without altering splenic lymphocyte profiles) (Extended Data Fig. 1a, Figs. 1a,b and Extended Data Fig. 1b,c, respectively). Of total itICs, CD4⁺ and CD8⁺ T cells were the most increased subpopulation (~ doubled) (Fig. 1c, d). Oral L-fuc induced similar changes in tumor fucosylation, growth, and TILs—specifically increased CD4⁺ and CD8⁺ T cells—in a BRAF^V600E-mutant mouse melanoma (SM1) model ¹⁰ (Extended Data Fig. 1d-j, respectively). In contrast, L-fuc did not reduce SW1 tumor growth in immunodeficient mice ¹¹ (Extended Data Fig. 1k), confirming that the presence and activity of itICs are essential for L-fuc-triggered tumor suppression.

We confirmed an essential role for tumor-specific fucosylation by overexpressing murine fucokinase (mFuk) in SW1 melanoma cells to exclusively increase tumor fucosylation. mFuk expression alone suppressed tumor growth and increased total itICs comparably to oral L-fuc alone. Again, CD4⁺ and CD8⁺ T cells were the most increased itICs (Extended Data Fig. 1l,m and Fig. 1e-h). These data indicate that melanoma-specific fucosylation is an essential determinant of L-fuc-triggered itIC induction and tumor suppression, regardless of any other physiological host effects that L-fuc may elicit (e.g., microbiome or metabolic).

Correlations between tumor fucosylation and CD3⁺T cells in humans by were assessed immunofluorescently analyzing a 42-patient melanoma microarray. Patients with higher than median tumor fucosylation levels exhibited significantly increased intratumoral CD3⁺T cell densities (Fig. 1i), even after adjusting for potential confounding factors including age, sex, and stage (multivariable linear regression (data not shown)). Intriguingly, average melanoma fucosylation levels were lower in male patients (Fig. 1j) but exhibited a stronger association with intratumoral CD3⁺T cells (Fig. 1k).

These data indicate that melanoma fucosylation significantly shapes itIC landscape, correlates with increased intratumoral CD3⁺T cells in mice and humans, and can be boosted by oral L-fuc to increase TILs and suppress BRAF- and NRAS-mutant melanomas.

L-fucose suppresses melanomas by triggering CD4⁺T cell-mediated increases in ITICs and altering CD4⁺T cell biology, increasing memory CD4⁺T subpopulations

The contribution of CD4⁺ and CD8⁺T cells to L-fuc-triggered tumor suppression was assessed by immunodepletion in the SW1 model. L-fucose reduced tumor growth by > 50% in control and CD8⁺T cell-depleted mice, whereas this effect was completely abrogated by CD4⁺T cell depletion (Fig. 1l-n; immunodepletion confirmed by splenic profiling, Extended Data Fig. 1n,o). Consistent with known roles for CD4⁺T cells in recruiting and activating tumor suppressive TILs ¹², CD4⁺T cell-depletion also blocked L-fuc-induced increases in total itICs, including intratumoral NK, DC, and CD8⁺T cells, observed in control mice (Extended Data Fig. 1p and Fig. 1o). Similarly, in the SM1 model, CD4⁺ but not CD8⁺T cell depletion abrogated L-fuc-triggered tumor suppression and increases in total itICs and itIC subpopulations (immunodepletion confirmed by splenic profiling, Extended Data Fig. 1q-w)).

Phosphoproteomic and fucosylated proteomic analyses revealed that L-fuc mechanistically regulates CD4⁺T cell biology by significantly altering Protein Kinase A (PKA) and (to a lesser extent) actin signaling, potentially via Integrin B5, an upstream regulator of both of these pathways ^{13, 14} that we discovered to be 1 of 5 proteins most highly bound to AAL (and likely fucosylated) in human peripheral blood monocyte (PBMC)-derived, CD3/CD28-activated CD4⁺T cells, as well as Jurkat cells treated with L-fuc (Extended Data Fig. 2a-f). That integrin, PKA, and actin signaling have been reported to mediate T cell activation, motility, and immune synapse formation ^15–17 suggests that L-fuc promotes T cell trafficking to the tumor, a notion confirmed using a SW1 melanoma C3H mouse model treated ± FTY720 (an inhibitor of lymph node egress ¹⁸). Inhibition of lymph node egress completely abrogated L-fuc-triggered tumor suppression (Fig. 2a,b). Strikingly, L-fuc-triggered tumor suppression was associated with increases in intratumoral CD4⁺T central and effector memory subpopulations that were abrogated by FTY720 (Fig. 2a,c (blue dashed boxes) and Table 1), consistent with the role that PKA plays in regulating memory phenotype in T cells ¹⁹. Intriguingly, oral L-fuc induced significant, albeit transient, increases in intratumoral monocyte-derived DCs (moDCs) and lymph node cDC2s, which can promote memory CD4⁺T phenotypes and crosstalk with CD4⁺T cells to mediate tumor suppression, respectively ^20–22 (Fig. 2a,c (orange dashed boxes) and Table 1). Finally, L-fuc also transiently but significantly increased cytotoxic CD4⁺T cells at the midpoint (Day 28) of the experiment (Fig. 2d,e).

These data confirmed that CD4⁺T cells play a key role in induction of TILs and suppression of melanomas by L-fuc, suggesting that L-fuc triggers key changes in CD4⁺T signaling and biology at the tumor and lymph node levels that are important for tumor suppression. Importantly, that mFUK expression alone in melanoma cells resulted in smaller tumors with increased TILs (Figs. 1e-h) suggests that melanoma-specific fucosylated protein(s) can also promote anti-tumor immunity, although the mechanism was unclear.

Fucosylated HLA-DRB1 mediates L-fucose-triggered TIL induction, anti-melanoma immunity, and melanoma suppression

To identify melanoma proteins that contributed to fucosylation-triggered, CD4⁺T cell-mediated melanoma suppression, we subjected fucosylated proteins from human melanoma cells to liquid chromatography mass spectrometric (LC-MS/MS) analysis followed by Ingenuity Pathway Analysis ²³ (Extended Data Fig. 3a, left). These analyses identified “Antigen presentation pathway” as the only immune-related pathway, in which the MHC-I and MHC-II proteins HLA-A and HLA-DRB1, respectively, were identified as the only antigen presentation and plasma membrane proteins with T cell-modulating functions ^{24, 25} (Extended Data Fig. 3a, right). We confirmed their expression in human melanocytes and melanoma cells by immunoblot (IB) analysis (Fig. 3a). Further, lectin pulldown (LPD) using Aleuria aurantia (AAL) and Ulex europaeus agglutinin I (UEA1) lectins, which bind to common core and terminal fucosylated glycans, respectively ^26–31, revealed association of both proteins with AAL (and to a lesser extent, UEA1), suggesting N’-linked core glycosylation-fucosylation (Fig. 3b). Finally, immunoprecipitation (IP) and IB analysis of V5-tagged HLA-A or HLA-DRB1 revealed direct recognition of HLA-DRB1 by AAL—indicating that a fraction of total HLA-DRB1, but not HLA-A, is directly fucosylated in melanoma (Fig. 3c).

To determine contributions of HLA-A or HLA-DRB1 to fucosylation-triggered anti-tumor immunity, we knocked down their C3H/HeN mouse orthologs H2K1 or EB1 ³², respectively, in SW1 tumors (Extended Data Fig. 3b) and assessed growth and TILs in vivo. Whereas L-fuc impaired control tumor growth, H2K1 knockdown suppressed tumor growth regardless of L-fuc (Fig. 3d,e), potentially reflecting tumor-protective, immunosuppressive roles of MHC-I proteins ^33–35. Notably, EB1 knockdown completely abolished L-fuc-triggered tumor suppression and induction of total itICs, including DCs, CD8⁺ and CD4⁺T cell subpopulations (Fig. 3f-h)—similar to the effects elicited by CD4⁺T cell depletion (Fig. 1l-o).

Consistent with roles of HLA-DRB1 in CD4⁺T cell activation ^36–38, our findings demonstrate that HLA-DRB1 is expressed and fucosylated in melanoma and required for L-fuc-triggered CD4⁺T cell-mediated TIL induction and melanoma suppression.

N48 fucosylation of HLA-DRB1 regulates its cell surface localization and is required for TIL induction, anti-melanoma immunity, and melanoma suppression

We reasoned that determining how HLA-DRB1 is regulated by fucosylation would provide important insight into its crucial role in L-fuc-triggered anti-tumor immunity. Using NetNGlyc and NetOGlyc (https://services.healthtech.dtu.dk) ³⁹, we predicted N- and O-linked glycosylation sites at Asn48 (N48) and Thr129 (T129), respectively, which are conserved sites within constant regions of human and mouse HLA-DRB1 (Fig. 4a, upper) ^{32, 40}. Importantly, EB1 exhibits ~ 80% sequence homology of HLA-DRB1 and contains the conserved glycosylation-fucosylation site a N46 ³². Modeling of HLA-DRB1 interactions with prominent binding partners HLA-DM or CD4/TCR suggests that fucosylation of neither site affects interaction interfaces or peptide loading/presentation (Fig. 4a, lower).

Nano-LC/MS/MS analysis of HLA-DRB1 immunoprecipitated from WM793 cells identified the fragment FLEYSTSECHFFNGTER as glycosylated-fucosylated at N48 with the predicted glycan HexNAc(4)Hex(3)Fuc(1) (Fig. 4b and Extended Data Fig. 4a). We mutated N48 or T129 to Gly or Ala, respectively, to abolish and verify fucosylation ^41–44. Unlike wild-type (WT) or the T129A “glyco-fucomutant” HLA-DRB1, the N48G glyco-fucomutant did not bind to AAL in LPD assays (Fig. 4c), confirming fucosylation at N48 on an N-linked glycan.

To determine how fucosylation might regulate HLA-DRB1, we assessed its subcellular localization in WM793 cells that were pharmacologically modulated for fucosylation by treatment with 2F-peracteyl-fucose (FUTi, a fucosyltransferase inhibitor⁴⁵) versus vehicle (dimethylsulfoxide, DMSO; control). Cells treated with FUTi exhibited dimmer, more central, endoplasmic reticulum-co-localization of HLA-DRB1 compared with vehicle-treated cells, suggesting less accumulation at the cell surface (Fig. 4d). Further, flow cytometry revealed that cell surface fucosylation and HLA-DRB1 both decreased or increased after FUTi or L-fuc treatments, respectively, whereas mRNA and protein levels remained unchanged; thus fucosylation promotes cell surface localization of HLA-DRB1 (Fig. 4e and Extended Data Fig. 4b). Finally, global proteomic profiling to identify interactors that might mediate fucosylation-regulated cell surface localization of HLA-DRB1 revealed that N48 glycosylation-fucosylation promotes binding to calnexin, which has been reported to mediate maturation and trafficking of MHC-II complexes to the surface ⁴⁶ (Extended Data Fig. 5a-d).

To assess how HLA-DRB1 glycosylation-fucosylation contributes to tumor suppression and TILs, we compared control- or EB1-knocked-down SW1 tumors reconstituted with WT or glyco-fucomutant (N46G) EB1 (confirmation of knockdown-reconstitution and fucosylation by IB and LPD, respectively in Extended Data Fig. 5e). Abrogation of L-fuc-induced TIL and tumor growth suppression by EB1 knockdown was rescued by reconstitution with only WT but not glyco-fucomutant EB1, demonstrating that glycosylation-fucosylation of EB1/HLA-DRB1 is essential for L-fuc-triggered TIL induction and melanoma suppression (Fig. 4f and Extended Data Fig. 5f,g). This is consistent with our finding that loss of glycosylation-fucosylation of HLA-DRB1/EB1 abrogates its cell surface localization and impairs its ability to induce anti-tumor immunity. Thus, despite the other fucosylated proteins identified in melanoma cells (Extended Data Fig. 3), these data confirm that the N48 glycosylation-fucosylation of HLA-DRB1 is a key regulator of anti-melanoma immunity and tumor suppression. Despite other potential host physiological effects of dietary L-fuc (e.g., microbiome, metabolome, etc.), these data confirm that L-fuc-induced itIC increases and melanoma suppression are critically mediated by melanoma-intrinsic expression and fucosylation of HLA-DRB1, which promotes its cell surface accumulation to trigger CD4⁺T cell-mediated anti-tumor immune responses.

Oral L-fucose augments anti-PD1-mediated melanoma suppression

Expression of MHC-II reportedly correlates with increased anti-PD1 efficacy ^{47, 48}. Indeed, patients who failed anti-PD1 exhibited relative > 45% reduced cell surface MHC-II but not MHC-I (Extended Data Fig. 5h). As anti-PD1 efficacy can be limited by TIL abundance ⁴⁹, particularly of CD4⁺T and memory CD4⁺T cells ^50–55, we tested if the ability to increase CD4⁺T cell-mediated TIL induction and tumor suppression using oral L-fuc could be leveraged to augment anti-PD1 efficacy. In the SW1 model, oral L-fuc suppressed tumors as much as anti-PD1 but did not enhance efficacy of anti-PD1 (~ 50–60%; Fig. 5a (left)). In contrast, in the SM1 model, L-fuc was less tumor suppressive than anti-PD1 alone but rather augmented durable suppression in combination with anti-PD1 (Fig. 5a (right)).

To clarify how the L-fuc + anti-PD1 combination enhanced suppression, we characterized immune cell profiles in the tumors and lymph nodes of SM1 tumor-bearing mice over a timecourse of treatment with L-fuc ± anti-PD1. Administration of L-fuc (i) alone increased intratumoral CD4⁺T central and effector memory cells, an effect that was increased when combined with anti-PD1 (Fig. 5b (blue dashed boxes)), and (ii), initially expanded intratumoral cDC2s, followed by later expansion of cDC2s and moDCs in the lymph nodes when combined with anti-PD1 (Fig. 5b (orange dashed boxes)). In addition to expanding the absolute numbers of intratumoral CD4⁺ and CD8⁺ T cells at endpoint (Day 63), combination L-fuc + anti-PD1 increased the relative percentage of intratumoral CD8⁺T central memory cells (Fig. 5b (green dashed box)). Thus, L-fuc can suppress some melanomas as effectively as anti-PD1, whereas in others, it can enhance efficacy, which is associated with increased intratumoral CD4⁺T central and effector memory subpopulations and lymph node cDC2 and moDC populations, consistent with the effects of L-fuc observed in Fig. 2.

Melanoma fucosylation and fucosylated HLA-DRB1 as potential biomarkers of anti-PD1 response

Given the potent enhancement of anti-PD1 efficacy by oral L-fuc in mice, we assessed if tumor fucosylation or total/fucosylated HLA-DRB1 might correlate at all with responsiveness to anti-PD1 in human patient biopsies, as the identification of preliminary correlations might support their subsequent development in into predictive biomarkers for anti-PD1 responsiveness. To this end, we devised a new technique: we modified conventional proximity ligation assay (PLA) ⁵⁶ to facilitate immunofluorescent visualization of fucosylated HLA-DRB1 by implementing anti-HLA-DRB1 antibody together with biotinylated AAL, which has previously been successfully used to stain tissues specifically for core-fucosylated glycans ⁵⁷ (Fig. 6a). This technique, lectin-mediated PLA (L-PLA), revealed cytoplasmic/membranous localization of endogenous fucosylated HLA-DRB1 in melanoma cells (Fig. 6b) that is lost upon FUTi treatment (Fig. 6c), confirming L-fuc-stimulated cell surface localization of HLA-DRB1 (Fig. 4d,e and Extended Data Fig. 4b). The cytoplasmic/”vesicular-appearing” staining is consistent with HLA-DRB1 that was fucosylated in the ER/Golgi and is en route to the surface via the secretory pathway. In applying this technique further on FFPE melanoma tissue specimens, we observed similar staining patterns for fucosylated HLA-DRB1 (Fig. 6d,e), which were completely abolished by L-fuc washing of the tissue, confirming specificity for fucosylated HLA-DRB1 (Fig. 6f).

To assess correlations of (i) tumor-specific fucosylation and total/fucosylated HLA-DRB1 of individual tumor cells, and (ii) intratumoral numbers CD4⁺T cells with responder status to single-agent anti-PD1, we implemented L-PLA on primary melanoma biopsies from 2 distinct responder and 2 non-responder patients followed by single-cell segmented signal quantitation (Fig. 7a,b). Tumors of responders clearly contained tumor cell populations with high levels of fucosylation and total HLA-DRB1 versus non-responders (Fig. 7b.i,b.ii). Although the tumor of only 1 of 2 responders contained melanoma cells with increased levels of fucosylated HLA-DRB1 compared with the non-responders (Fig. 7b.iii), this trend mirrored that of intratumoral CD4⁺T cell counts (Fig. 7b.iv), consistent with the role for fucosylated HLA-DRB1 in CD4⁺T cell-mediated tumor suppression.

We assessed potential associations between tumor fucosylation, total/fucosylated HLA-DRB1, CD4⁺T cells and responder status in expanded cohorts of anti-PD1-treated melanoma patients. Levels of tumor fucosylation and total and fucosylated HLA-DRB1 in tumor cells were generally higher in anti-PD1 responders compared with non-responders from Massachusetts General Hospital (n = 31; Fig. 7c, upper) and MD Anderson Cancer Center (n = 11; Fig. 7c, lower). Total tumor fucosylated HLA-DRB1 exhibited weak or no association with tumoral CD4⁺T cell (Figs. 7d, upper & lower), although the association was modestly increased when restricted to CD4⁺T cells localized at the periphery of the tumors (Extended Data Fig. 6a,b; absolute CD4⁺T numbers in Table 3). The lack of significant correlation may be attributed to the dynamic relationship between fucosylated HLA-DRB1 and CD4⁺T infiltration that is further weakened by suboptimal inclusion criteria/patient stratification. Comparison of these markers in 5 patient-matched pre- and post-anti-PD1 tumors revealed no significant correlation in total HLA-DRB1 levels. However, prior to treatment, tumor cell fucosylation was significantly higher in the complete responder versus partial and non-responders; this dropped to the equivalently lower levels of the other patients after treatment. With the exception of 1 non-responder, the complete responder also exhibited significantly increased fucosylated HLA-DRB1 in tumor cells prior to treatment (Extended Data Fig. 6c). The consistent trends in tumor fucosylation and fucosylated tumor HLA-DRB1 that observed across the 3 independent cancer center cohorts appear to support potential utility but importantly point to the need for further study in expanded patient pre-treatment biopsy cohorts that are controlled for a number of specific clinical variables, which will be discussed below.

For the first time, we report the administration of a dietary sugar as a way to increase TILs and enhance efficacy of the immune checkpoint blockade agent anti-PD1. These studies reveal new insights into the post-translational regulation and immunological roles of melanoma cell-expressed MHC-II proteins, further highlighting their relationship with TILs ^{47, 48, 50–54}. Specifically, fucosylation regulates the cell surface abundance of HLA-DRB1, which triggers robust CD4⁺T cell-mediated TIL induction and melanoma suppression. It is important to acknowledge that our reliance on AAL lectin predominantly focuses our study on α1,6-fucosylated proteins. Although this does not diminish the crucial role that α1,6-fucosylated HLA-DRB1—which was identified as fucosylated via lectin-agnostic click chemistry mass spectrometric screening—plays in L-fuc-triggered anti-tumor immune responses, it is possible that proteins with other fucosylation linkages might contribute to aspects of anti-tumor immunity. It is also likely that the statistical strength of our analyses of tumor fucosylation with patient outcomes (Fig. 7) was limited by use of only AAL lectin, which precludes the detection of other structural forms of fucosylation. Nonetheless, the ability to leverage this mechanism using oral L-fuc may help to enhance other immunotherapeutic modalities (i.e., other checkpoint inhibitors or adoptive cell transfer therapies). Notably, as a non-toxic dietary sugar with a past safety precedent as an experimental therapy for children with Leukocyte Adhesion Deficiency II ^{58, 59}, L-fuc appears to be a potentially safe and tolerable therapeutic agent.

The consistent trends that we observed in higher tumor fucosylation and fucosylated HLA-DRB1 across anti-PD1 responders vs. non-responders between the 3 independent cancer center cohorts support their potential utility as biomarkers of anti-PD1 responsiveness. However, further analyses in expanded patient biopsy cohorts are clearly needed. Considering the variable tumor suppressive effects of L-fuc observed in our anti-PD1 treated SM1 and SM1 mouse models, there are likely similar biological and clinical variables in patients that must be further explored and that may have precluded statistical significance in our small analyses.

In terms of biological variables, how T cell biology is regulated by fucosylation, for example, has heretofore been unclear. Reported divergent effects of fucosylation on T cell activation vs. exhaustion (i.e., via regulation of Programmed Death Ligand 1 (PD-L1) expression) point to FUT-specific expression and roles that remain to be elucidated ^60–62. L-fucose does not alter cell surface levels of PD-L1 in human or mouse melanoma cells (Extended Data Fig. 6d), suggesting that the discrepant tumor suppression by single-agent vs. combination L-fuc + anti-PD1 in our SW1 and SM1 mouse models (Fig. 5a) is attributed to determinants beyond the PD1:PD-L1 axis. Indeed, our global fucosylated and phosphoproteomic analyses suggests that fucosylation in CD4⁺T cells impacts Integrin β5, PKA, and actin signaling (Extended Data Fig. 2), and that this is associated with increased intratumoral T cell presence and memory phenotypes in our models (Figs. 2 and 5)—consistent with previous reports that those functions are regulated by those pathways in T cell biology ^{15−17, 19}. That L-fuc can increase CD4⁺T central memory cells also partially explains how it can augment anti-PD1 efficacy, which is associated with the presence of these cells ⁵⁵. How L-fuc may regulate these signaling pathways and enrich for CD4⁺T memory subsets within the tumor microenvironment, and further, how L-fuc alters DC biology and induces their intratumoral accumulation (Figs. 2 and 5) may contribute to anti-tumor immune responses and tumor suppression in this context are unclear and warrant further lines of study. In addition, sex might be a determinant, as melanoma fucosylation levels are lower but correlate more strongly with intratumoral CD3⁺T cells in male vs. female patients (Fig. 1j,k). Reduced melanoma fucosylation, which is expected to lower TILs, might explain increased lethality in male patients (American Cancer Society Facts & Figures, 2022).

The availability of pre-treatment anti-PD1 tumor tissue specimens for this study was extremely limited. Thus, the specimens that we acquired were subject to clinical variability that may have undermined statistical robustness in our analyses. Subsequent studies investigating tumor fucosylation, total/fucosylated HLA-DRB1, and CD4⁺T cells as biomarkers will need to factor for clinical variables including therapies received prior to anti-PD1, pre-existing medical conditions, as well as time from biopsy to anti-PD1 treatment. Since we were unable to control for these confounders in our specimens, it is unclear how they may have impacted tumor/HLA-DRB1 fucosylation and CD4⁺T cell biology, and thus, the strength of correlations between these markers and responsiveness to treatment. Likewise, the importance and contribution of the immune environment of the peri-tumoral stroma in this setting remains to be elucidated, as some of our biopsies contained stroma, whereas other tumor core biopsies did not. Prior studies focusing on tumor:immune interactions and immunotherapies (including anti-PD1) have highlighted the importance of analyzing biomarker staining patterns at tumor:immune/tumor:stromal interfaces contained within biopsies, as these are areas of enriched immunological activity and signaling ^63–65. Lack of sufficient stroma among several biopsies likely significantly undermined statistical robustness of our trends/correlations. Indeed, we found that some specimens containing divergent tumor:stroma content did exhibit divergent correlation strengths (e.g., core biopsies containing only tumor vs. non-core biopsies containing significant stroma) For example, a “highly correlated” anti-PD1 responder (non-core biopsy) containing significant tumor:stromal interface exhibited correlated high levels of fucosylated HLA-DRB1 and CD4⁺T cells, whereas a “non-correlated” responder (a core biopsy) did not (Extended Data Fig. 6e). The lack of stromal interface in the non-correlated responder biopsy is a likely explanation for lack of correlated levels of fuco-HLA-DRB1 and CD4⁺T cells. The acquisition of such biopsy specimens that are controlled for the variables detailed above is an important consideration for subsequent studies. Our findings highlight the need for a prospective clinical trial with defined protocols for collection of mono-therapy anti-PD1 pre-treatment biopsies at defined timepoints proximal to therapy and clear biopsy protocols to yield tumor specimens that contain significant intact stromal interface.

In conclusion, fucosylation of HLA-DRB1 is a key regulator of TIL abundance in melanomas, and this mechanism, together with fucosylation-regulated CD4⁺T cell biology, can be therapeutically exploited using oral L-fuc. Elucidation of the mechanistic determinants is expected to advance our understanding of the immunobiology of melanoma and other cancers and to inform efforts at implementing fucosylation/fucosylated HLA-DRB1 as biomarkers and of L-fuc as a therapeutic agent.

General cell culture

NHEM (normal adult epidermal melanocytes) were grown in Lonza MGM-4 growth media; prior to harvest for IB analysis, the cells were switched to the same media as the other cells overnight. WM793,1205Lu, A375, WM1366, WM164, and SW1 melanoma cells were obtained from the Ronai laboratory (Sanford-Burnham Prebys Medical Discovery Institute (La Jolla, CA), WM983A/B cells were purchased from Rockland Immunochemicals (Limerick, PA). WM115 and WM266-4 cells were purchased from ATCC (Manassas, VA). SM1 (Gift from the Smalley Laboratory at Moffitt), were cultured in Dulbecco's Modified Eagle Medium containing 10% fetal bovine serum (FBS), 1 g/mL glucose, 4 mM L-glutamine in 37^oC in 5% CO₂. Cell lines were transfected using Lipofectamine 2000 (Invitrogen, Waltham, MA). Primary CD4 + T cells were harvested using the EasySep (StemCell Technologies) Human CD4⁺ negative selection isolation kit (#17952) according to manufacturer's protocols.

Antibodies

The following antibodies were used as indicated: mouse anti-V5 (0.2 µg/mL Millipore Sigma (St. Louis, MO)), mouse anti-V5 gel (V5-10, Millipore Sigma (St. Louis, MO)), mouse anti-human HLA-DRB1 (0.2 µg/mL, IF, ab215835, Abcam (Cambridge, UK)), rabbit anti-human HLA-DRB1 (0.2 µg/mL WB, ab92371, Abcam (Cambridge, UK)), β-tubulin (0.3 µg/mL, E7, developed by M. McCutcheon and S. Carroll and obtained from Developmental Studies Hybridoma Bank (University of Iowa, Iowa City, IA)), goat anti-biotin (0.1 µg/mL Vector Labs (Burlingame, CA)), biotinylated AAL (0.4 µg/mL Vector Labs, Burlingame, CA), fluorescein-conjugated AAL (0.4 µg/mL Vector Laboratories, Burlingame, CA), Agarose UEA1 and AAL (Vector Laboratories, (Burlingame, CA)), anti-mouse CD4 (20 mg/kg, for immunodepletion, GK1.5, Bioxcell (West Lebanon, NH)), anti-mouse CD8 (20 mg/kg, for immunodepletion, 2.43, Bioxcell (West Lebanon, NH)), goat anti-mouse IgGκ horseradish peroxidase (HRP) (0.04 µg/mL, Santa Cruz Biotechnology (Dallas, TX)), mouse anti-rabbit HRP (0.04 µg/mL, Santa Cruz Biotechnology (Dallas, TX)), goat anti-rabbit AlexaFluor 488 (0.04 µg/mL, ThermoFisher Scientific (Waltham, MA)),), donkey anti-mouse AlexaFluor 594 (0.05 µg/mL, ThermoFisher Scientific (Waltham, MA)), AlexaFluor 594 donkey anti-rabbit (0.05 µg/mL, ThermoFisher Scientific (Waltham, MA)), rabbit anti-Mart1 (0.2 µg/mL, Millipore Sigma (St. Louis, MO), rabbit anti-S100 (0.2 µg/mL, Agilent Technologies (Santa Clara, CA)), APC anti-mouse CD3 (0.5 µg/mL, Biolegend (San Jose, CA)), Pacific Blue anti-mouse CD4 (0.5 µg/mL, BD Biosciences (San Jose, CA)), BV785 anti-mouse CD8 (0.5 µg/mL, BD Biosciences (San Jose, CA)), FITC anti-mouse F4/80 (0.5 µg/mL, BD Biosciences (San Jose, CA)), APC anti-mouse GR-1 (0.5 µg/mL, BD Biosciences (San Jose, CA)), PeCy7 anti-mouse CD11c (0.5 µg/mL, BD Biosciences (San Jose, CA)), PE anti-mouse NK1.1(0.5 µg/mL, BD Biosciences (San Jose, CA)), PE anti-mouse DX5 (0.5 µg/mL, BD Biosciences (San Jose, CA)), PerCP-Cy5.5 anti-mouse CD11b (0.5 µg/mL, BD Biosciences (San Jose, CA)), rabbit anti-human PD-L1 (clone #NBP1-76769; Noveus Biologicals, Centennial, CO), PE rat anti-mouse PD-L1 (clone #10F.9G2; (Biolegend, (San Diego, CA)), and phalloidin Alexafluor 488 (0.2µg/mL, ThermoFisher Scientific (Waltham, MA)), mouse anti-FLAG (0.2 µg/mL, clone M2, Millipore Sigma (St. Louis, MO)), rabbit anti-HLA-A (0.2 µg/mL, Proteintech (Rosemont, IL)), normal mouse IgG (Santa Cruz Biotechnology (Dallas, TX)), rabbit anti-KDEL (0.1 µg/mL, ThermoFisher Scientific (Waltham, MA)), mouse anti-PD1 (for in vivo studies, 20 mg/kg, clone# RMP1-14 Bioxcell (West Lebanon, NH)), donkey anti-goat plus PLA secondary antibody (Millipore Sigma (St. Louis, MO)), donkey anti-mouse plus PLA secondary antibody (Millipore Sigma (St. Louis, MO)), rat anti-mouse CD8 antibody (0.2 µg/mL, ThermoFisher Scientific (Waltham, MA)), AlexaFluor 594 goat anti-rat secondary antibody (0.05 µg/mL, ThermoFisher Scientific (Waltham, MA)), anti-CD3 (0.2 µg/mL, Clone PS1, Santa Cruz Biotechnology (Dallas, TX), PE anti-pan-MHC-I (HLA-A,B,C) (BD Pharmingen (San Jose, CA), FITC anti-pan-MHC-II (HLA-DP, DQ, DQ)(BD Pharmingen (San Jose, CA), PerPCy5.5 anti-CD45 (Invitrogen (Waltham, MA)), APC anti-CD90 (Biolegend (San Diego, CA)), and BV421 anti EpCAM (Biolegend (San Diego, CA)).

Cloning and mutagenesis

Mouse fucokinase (mFuk) was cloned using cDNA from SW1 cells into pLenti-C-Myc-DDK-IRES-Puro expression vector (Origene Technologies (Rockville, MD)) into BAMHI and NHEI restriction sites. Mouse EB1 constructs was cloned using cDNA from SW1 cells into pLenti-C-Myc-DDK-IRES-Puro expression vector (Origene Technologies (Rockville, MD)) into ASCI and XHOI restriction sites. pLKO Non-targeting shRNA (shNT), pLKO shK1-1, pLKO shK1-2, pLKO shEB1-1, and pLKO shEB1-2 were obtained from Millapore Sigma (St. Louis). pLX304::EV was obtained from Origene Technologies (Rockville, MD). pLX304::HLA-A and pLX304::HLA-DRB1 constructs were obtained from DNAasu (PMID:21706014). HLA-DRB1 N48G and T129A as well as EB1 N46G mutants were generated using QuikChange II XL site-directed mutagenesis kit according to the manufacturer’s protocol (Agilent Technologies (Santa Clara, CA)).

Proteomic mass spectrometric profiling of fucosylated proteins

WM793 cells stably transduced with pLenti-GFP empty vector (EV), pLenti-FUK-GFP, or shFUK were grown in triplicate to ~ 30–40% confluence in (3 x 15 cm³ plates each). The cells were further cultured in the presence of 50µM L-fucose-alkyne for ~ 72 h to ~ 80% confluence. The cells were lysed in 1.5% N-dodecyl-beta-D-maltoside/20mM HEPES pH 7.4/protease and phosphatase inhibitors. Lysates were sonicated and cleared by centrifugation at full speed for 5 min at 4C. Lysates were acetone precipitated overnight. The pelleted proteins were resuspended and subjected to click-chemistry labeling with biotin-azide using the Click-It kit per manufacturer's protocol (Invitrogen). For negative control, pLenti-GFP-EV cells were not labeled with L-fucose-alkyne but were lysed, pelleted, and click-reacted with biotin-azide. All biotin-azide (biotinylated-fucosylated) samples were pulled down using neutravidin beads that were pre-blocked with 2% IgG-free BSA. Samples were submitted to the Sanford-Burnham Prebys proteomics core facility for on-bead digest; supernatants from on-bead digest were analyzed by LC/MS/MS. Hits that were increased by > 1.5 fold in pLenti-FUK-GFP-expressing cells and unchanged or decreased in pLenti-EV-GFP-expressing cells or decreased in pLenti-shFUK-expressing cells. Hits were subjected to Ingenuity Pathway Analysis (Qiagen).

Lectin pulldown

Control beads and AAL or UEA1 lectin-conjugated agarose beads were pre-blocked for 2 h in blocking buffer (2% IgG-Free BSA (Jackson ImmunoResearch Laboratories (Westgrove, PA)) on a rotator at 4^oC. Cells were lysed on ice in 1% Triton-X100 lysis buffer (1% Triton-X100, 20mM Tris-HCl, pH 7.4, 150mM NaCl in ddH2O + protease and phosphatase inhibitors (ThermoFisher Scientific (Waltham, MA)), briefly sonicated, pelleted, and the resulting lysates were normalized in protein concentration to the sample with the lowest concentration and diluted to a final 0.25% Triton-X-100 with dilution buffer (0% Triton X-100, 20mM Tris-HCl, pH 7.4, 150mM NaCl in ddH₂O + protease and phosphatase inhibitors (ThermoFisher Scientific (Waltham, MA)), and incubated with 15µl of pre-blocked beads (beads were spun out of block and resuspended in dilution buffer) and rotated overnight at 4^oC. Next, the beads were washed twice with dilution buffer and subjected to (12%) SDS-PAGE and IB analysis using the indicated antibodies.

Mass spectrometric analysis of glycosylation on HLA-DRB1

Stained bands of approximately 1ug of exogenously expressed V5-HLA-DRB1 purified from WM793 cells were cut into 1-mm³ pieces and reduced and alkylated using 20mM TCEP (tris(2-carboxyehtyl)phosphine) and iodoacetamide in 50mM Tris-HCl. The gel pieces were washed in a 20mM ammonium phosphate solution with 50% methanol overnight at 4°C. The following day, the gel pieces were dehydrated for 30 minutes with 100% acetonitrile. After gel pieces were completely dry, trypsin protease solution was added to the samples (300ng trypsin). Samples were digested for 4 hours at 37°C. The digests were applied to a C-18 Zip-Tip and eluted with 50% methanol and 0.1% formic acid. Five microliters of the elution were diluted in 0.1% formic acid and then injected into a Q-Exactive Orbitrap mass spectrometer (ThermoFisher Scientific, (Waltham, MA)) equipped with an Easy nano-LC HPLC system with reverse-phase column (ThermoFisher Scientific, (Waltham, MA)). A binary gradient solvent system consisting of 0.1% formic acid in water (solvent A) an 90% acetonitrile and 0.1% formic acid in water (solvent B) was used to separate peptides. Raw data files were analyzed using both Proteome Discoverer v2.1 (ThermoFisher Scientific, (Waltham, MA)) with Byonic (Protein Metrics) as a module and Byonic standalone v2.10.5. All extracted ion chromatograms (EICs) were generated using Xcalibur Qual Browser v4.0 (ThermoFisher Scientific, (Waltham, MA)). UniProt sequence Q5Y7D1_Human was used as the reference sequence for peptide analysis.

Phosphoproteomics mass spectrometric profiling of CD4 ⁺ T cells

CD4⁺T cells cultured and treated as indicated in the main text were harvested and lysed in standard RIPA buffer + protease and phosphatase inhibitors. Protein concentration was estimated by BCA assay (Bio-Rad) and 1 mg lysates were subjected to trypsin digestion. Briefly, lysates were reduced with 4.5 mM dithiothreitol (DTT) for 30 min at 60⁰C, alkylated with 10mM iodoacetamide (IAA) at room temperature in the dark for 20 minutes, and digested overnight at 37⁰C with 1:20 enzyme-to-protein ratio of trypsin (Worthington). The resulting peptide solution was de-salted using reversed-phase Sep-Pak C₁₈ cartridge (Waters) and lyophilized for 48 hours.

Fuco-proteomic mass spectrometric profiling of CD4 ⁺ T cells

CD4⁺T cells cultured and treated as indicated in the main text were harvested, lysed in standard RIPA buffer + protease and phosphatase inhibitors, and subjected to lectin pulldown using control or AAL beads as described above. The beads were washed with PBS and subjected to on-bead trypsin digestion. Proteins bound to beads were denatured with 30mM ammonium bicarbonate at 95⁰C for 5 minutes. Samples were reduced with 4.5 mM dithiothreitol (DTT) for 30 min at 60⁰C, alkylated with 10mM iodoacetamide (IAA) at room temperature in the dark for 20 minutes, and digested overnight at 37⁰C with 1:20 enzyme-to-protein ratio of trypsin (Worthington). The resulting peptide solution was acidified with a final concentration of 1% TFA. Samples were centrifuged at high speed and the supernatants were subjected to Ziptip purification (Millipore Ziptips, #Z720070). The eluted peptides were concentrated in a SpeedVac and suspended in 15 µL loading buffer (5% ACN and 0.1% TFA) prior to auto sampling. Samples were then subjected to LC-MS/MS as described below

Mass spectrometric identification of WT vs. glycofucomutant HLA-DRB1 interactors

V5-tagged WT or N48G glycofucomutant HLA-DRB1-expressing WM793 cells were lysed and subjected to V5 bead pulldown. Five percent of pulled down protein was immunblotted to ensure for equal sample submission for LC-MS/MS (Extended Data FIg. 5a). Samples were then subjected to LC-MS/MS as described below.

Liquid chromatography-MS/MS

On-bead digestion was performed with trypsin and tryptic peptides were then analyzed using a nanoflow ultra-high-performance liquid chromatograph (RSLC, Dionex, Sunnyvale, CA) coupled to an electrospray orbitrap mass spectrometer (Q-Exactive Plus, Thermo, San Jose, CA) for tandem mass spectrometry peptide sequencing. The peptide mixtures were loaded onto a pre-column (2 cm x 100 µm ID packed with C18 reversed-phase resin, 5µm, 100Å) and washed for 5 minutes with aqueous 2% acetonitrile and 0.1% formic acid. The trapped peptides were eluted and separated on a 75 µm ID × 50 cm, 2 µm, 100Å, C18 analytical column (Dionex, Sunnyvale, CA) using a 90-minute program at a flow rate of 300 nL/min of 2–3% solvent B over 5 minutes, 3 to 30% solvent B over 27 minutes, then 30–38.5% solvent B over 5 minutes, 38.5–90% solvent B over 3 minutes, then held at 90% for 3 minutes, followed by 90–2% solvent B in 1 minute and re-equilibrated for 18 minutes. Solvent A was composed of 98% ddH₂O and 2% acetonitrile containing 0.1% FA. Solvent B was 90% acetonitrile and 10% ddH₂O containing 0.1% FA. MS resolution was set at 70,000 and MS/MS resolution was set at 17,500 with max IT of 50 ms. The top sixteen tandem mass spectra were collected using data-dependent acquisition (DDA) following each survey scan. MS and MS/MS scans were performed in an Orbitrap for accurate mass measurement using 60 second exclusion for previously sampled peptide peaks. MaxQuant ⁶⁶ software (version 1.6.2.10) was used to identify and quantify the proteins for the DDA runs.

PyMOL structural modeling

In Fig. 4a, structural modeling was performed using PyMOL (Molecular Graphics System, Version 2.0 Schrödinger, LLC) of the HLA-DRB1:HLA-DM complex (PDB ID, 4FQX); HLA-DRB1 (yellow) and DM (gray). For the CD4:HLA-DRB1:TCR complex, the model was reconstituted by superimposing the DRB1 beta chains from CD4:HLA-DR1 complex (PDB ID, 3S5L) and TCR:HLA-DR1 complex (PDB ID, 6CQR) using PyMOL. RMSD between the 163 backbone atoms is 0.497. The potential glycosylation sites, N48 and T129, of HLA-DR1 beta chain are shown as sticks. CD4 (cyan), HLA-DRB1 (yellow), antigen peptide (magenta), and TCR (green)(lower right).

TIL isolation protocol

Tumors of SW1 or SM1 melanoma cells from C3H/HeJ or C57BL/6 mice, respectively) were digested using 1X tumor digest buffer (0.5 mg/mL Collagenase I, 0.5 mg/mL Collagenase IV, 0.25 mg/mL Hyalyronidase V, 0.1 mg/ mL DNAse I in HBSS (Millipore Sigma (St. Louis, MO)). Tumors were homogenized using the Miltenyi MACs dissociator. Red blood cells were lysed using ACK lysis buffer (Life Technologies, (Grand Island, NY)). Tumor homogenate cells were counted using a standard hemocytometer.

Human donor peripheral CD4 ⁺ T cell isolation protocol

Human CD4⁺ T cells were isolated from fresh peripheral blood monocyte cells (PBMC) using a CD4⁺ T cell negative selection isolation kit (Stem Cell Technologies, (Vancouver CA)) according to manufacturer’s protocols. CD4⁺ T cells were cultured in the presence of vehicle or 250µM L-fucose and were activated using anti-CD3/CD28 Dynabeads (ThermoFisher Scientific (Waltham, MA)) in a 1:1 bead:CD4⁺ T cell ratio. After 48 h, cell pellets were collected and lysed for either lectin-based fucoproteomics or phosphoproteomics.

Flow Cytometry

Gating schemes can be found in the Supplementary Information

• itIC and splenic profiling:

Total TILs were gated first to single cells (based on forward scatter height vs width, followed by side scatter height vs. width). Live cells were gated from the Zombie negative population from the population above. TILs were gated based on splenocyte size from a control spleen. Individual immune subpopulations were sub-gated from the total TIL population using the following staining criteria: CD3⁺ for CD3⁺ T cells; CD3⁺/CD4⁺/CD8⁻ for CD4 + T cells; CD3⁺/CD4⁻/CD8⁺ for CD8⁺ T cells, CD11c⁺/CD11b⁺ for DCs; either NK1.1 (for C57/BL6 mice) or DX5 (for C3H/HeJ) for NK cells; CD11b⁺/GR1⁺ for MDSC-like cells; and F4/80⁺ for macrophages. Single-cell suspensions from tumor and spleen tissue were stained with Live/Dead Zombie NIR (Biolegend, (San Diego, CA)) at 1:1,000 in PBS for 20 min. Cell suspensions were spun down and stained with the following with antibodies at 0.5 µg/ml per antibody: APC anti-mouse CD3, Pacific Blue anti-mouse CD4, BV785 anti-mouse CD8, PerCP anti-mouse CD25, FITC anti-mouse F4/80, PeCy7 anti-mouse CD11c, PE anti-mouse NK1.1 or PE anti-mouse DX5, and PerCP-Cy5.5 anti-mouse CD11b. After staining, the cells were washed and fixed (2% formaldehyde), followed by another wash and flow cytometric analysis. The compensation controls were prepared using 0.5 µg/mL of each antibody with UltraComp eBeads, (ThermoFisher Scientific (Waltham, MA)). All samples were subject to flow cytometric profiling using a LSR Flow Cytometer (BD Biosciences (San Jose, CA)) and analysis as indicated using FlowJo software (BD Biosciences (San Jose, CA)).

• Assessment of cell surface fucosylation, HLA-DRB1, and PD-L1: Indicated cells were treated for 72 h with DMSO, 250 µM fucosyltransferase inhibitor (FUTi) (Millipore Sigma (St. Louis, MO)), or 250 µM of L-fucose (Biosynth (Oak Terrace, IL)). After 72 h, cells were stained with 0.1 µM PKH26 (Millipore Sigma (St. Louis, MO)) prior to fixation in 4% formaldehyde solution. The cells were stained with anti-HLA-DRB1 and fluorescein AAL, or anti-human or anti-mouse PD-L1 overnight. The following day the cells were washed 3 times prior to adding AlexaFluor 594 donkey anti-rabbit. Cells were washed 3 times and then subject to flow cytometric analyses using a FACSCalibur (BD Biosciences (San Jose, CA)). Samples were analyzed using FlowJo analysis software (BD Biosciences (San Jose, CA)). Median values of DRB1 and AAL were normalized to PKH26 values and statistical analysis was performed using GraphPad Prism.

• Assessment of cell surface pan-MHC-I and pan-MHC-II: Surgically resected patient tumors were minced to less than 1-mm fragments. Minced tumor sample was enzymatically digested in enzyme media comprised of RPMI with collagenase type IV (1 mg/mL), DNase type IV (30 U/mL), and hyaluronidase type V (100 µg/mL) (Sigma). Single cell suspensions were strained through 40-micron nylon mesh and counted for viability via trypan blue exclusion, followed by cryopreservation for future analysis. Tumor homogenates were thawed and stained using Live / Dead Zombie NIR, PE anti-pan-MHC-I (HLA-A,B,C), FITC anti-pan-MHC-II, PerPCy5.5 anti-CD45, APC anti-CD90, and BV421 anti EpCAM. Flow cytometric data was analyzed using FlowJo analysis software (BD Biosciences (San Jose, CA)). MHC-I and MHC-II expression was dichotomized as positive or negative based on FMO samples for each marker. Statistical analysis was performed using GraphPad Prism.

Immunoprecipitation and immunoblot analyses

Cells were lysed on ice in RIPA lysis buffer (25 mM Tris-HCl pH 7.6, 150 mM NaCl, 5 mM EDTA, 1% NP-40 or 1% Triton X-100, 1% sodium deoxycholate, 0.1% SDS in diH₂0 + protease and phosphatase inhibitors (ThermoFisher Scientific (Waltham, MA)), briefly sonicated, pelleted, and the resulting lysates were normalized by protein concentration using DC assay (BioRad Laboratories, (Hercules, CA)). The indicated samples were subjected to (12%) SDS-PAGE and immunoblot analysis using the indicated antibodies. Immunoblot imaging and analysis was performed using either an Odyssey FC scanner and ImageStudio (LiCor Biosciences, Lincoln, NE) or film.

qRT-PCR

RNA from cells subjected to the indicated treatments was extracted using Gene Elute Mammalian Total RNA Extraction System (Millipore Sigma (St. Louis, MO)). RNA was reversed transcribed to cDNA using High-Capacity cDNA Reverse Transcription Kit (ThermoFisher Scientific (Waltham, MA)). qRT-PCR analysis was performed using FastStart Universal SYBR Green Master Mix (Rox) (Roche Diagnostics, (Indianapolis, IN)) using a BioRad CFX96 Real-time system (BioRad Laboratories, (Hercules, CA)). The qRT-PCR cycles used were as follows: 95°C for 10 min, 35 cycles of 95°C for 15 seconds, 55°C for 60 seconds, and 72°C for 30 seconds. Expression of the indicated genes was normalized to histone H3A expression. Primers for qRT-PCR were generated using NCBI primer blast software (National Center for Biotechnology Information (Washington, D.C.)) as detailed the table below.

Primer	Sequence (5’ -> 3’)
Cloning Primers
Fuk (mouse)	F: cgcgcgcgGGATCCatggagcagtcagagggagtcaattggactg R: cgcgcgcgGCTAGCggtggtgcccacttcagagggcc
HLA-DRB1 N48G	F: GTCTTTGAAGGATACACAGCCACCTTAGGATGGACTCG R: tgagtgtcatttcttcggtgggacggagcggg
HLA-DRB1 T129A	F: CGAGTCCATCCTAAGGTGGCTGTGTATCCTTCAAAGAC R: GTCTTTGAAGGATACACAGCCACCTTAGGATGGACTCG
EB1	F: cgcgcccgGGCGCGCCatggtggtgtggc R: cgcgcccgCTCGAGgctcaggagtcc
EB1 N46G	F: GTGTCATTTCTACGGCGGGACGCAGCGC R: GCGCTGCGTCCCGCCGTAGAAATGACAC
qRT-PCR
H3A (human and mouse)	F: AAGCAGACTGCCGCAAAT R: GGCCTGTAACGATGAGGTTTC
Fuk (mouse)	F: ACTTCCGCCGAGATCTGTTC R: GGATCAGTGGACGTAGGCAG
EB1	F: GAACACGCTTCTTCCTTGGG R: CAGGCTCCTTACCTTTCTGGT
H2-K1	F: CCGCGGACGCTGGATA R: GGCGATTCGCGACTTCTG
HLA-DRB1	F: CCATAGTAGCTCAGCACCCG R: GTCCTGTCCTGTTCTCCAGC

Fluorescent immunocytochemical and immunohistological staining and analysis

• General fluorescent immunocytochemical staining protocol: Melanoma cells were grown on German glass coverslips (Electron Microscopy Services (Hatfield, PA)) and fixed in fixation buffer (4% formaldehyde, 2% sucrose in phosphate buffered saline (PBS) for 20 min at room temperature (RT). The coverslip-grown cells were subject to two 5-min standing washes in PBS prior to permeabilization in permeabilization buffer (0.4% Triton-X-100 and 0.4% IgG-free bovine serum albumin (BSA, Jackson ImmunoResearch Laboratories (Westgrove, PA) in PBS) for 20 min at RT. The coverslip-grown cells were next subject to 2 PBS washes and incubated with the indicated primary antibodies.

• General fluorescent immunohistochemical tissue staining protocol: In general, paraffin-embedded FFPE tumor tissue sections (or the TMA slide) were melted at 70°C for 30 min. The slides were further de-paraffinizeded using xylene and rehydrated in serial alcohol washes. The slides were pressure cooked at 15 PSI for 15 min in a 1X DAKO antigen retrieval buffer (Agilent Technologies (Santa Clara, CA)). The tumor sections were subject to two 5-min standing washes in PBS prior to blocking in 1X Carb-Free Blocking Solution (Vector Labs (Burlingame, CA)) for 2-3h. The slides were next washed twice and incubated with indicated lectin and/or antibodies.

General fluorescent analysis of mouse tumor tissue fucosylation (Extended Data Figs. 1a,d,k):

For assessment of mouse tumor fucosylation, FFPE tumor sections were immunostained with FITC-conjugated AAL lectin (0.4 µg/mL, Vector Laboratories (Burlingame, CA)) and rabbit anti-Mart1 + rabbit anti-S100 (melanoma marker cocktail). The slides were mounted with Vectashield + DAPI (Vector Laboratories (Burlingame, CA)). Four representative microscopy images per tumor were acquired using a Keyence BZ-X710, and images were process and analyzed using FIJI (NIH) as follows: melanoma marker-positive regions were assigned as regions of interest (ROI) in which we measured Integrated density of AAL signal. Integrated densities of control tumors were assigned as 1, and Integrated AAL density values of experimental tumors were divided by control to produce relative fold changes and plotted as column charts.

• Immunofluorescent staining and analysis of melanoma tissues and TMA (Fig. 1N):

Immunostaining and image acquisition: Melanoma TMA (Serial #ME1002b; US BioMax, Inc. (Derwood, MD)) was immunostained with FITC-conjugated AAL lectin (0.4 µg/mL, Vector Laboratories (Burlingame, CA)), rabbit anti-Mart1, rabbit anti-S100, and anti-CD3 followed by AlexaFluor 568 (Cy3) donkey anti-rabbit and AlexaFluor 647 (Cy5) donkey anti-mouse secondary antibodies. The slides were mounted with Vectashield + DAPI (Vector Laboratories (Burlingame, CA)). An Aperio Scanscope FL (Leica Biosystems) was used to scan the TMA slide at 20X magnification and the digital slide saved into the Spectrum e-slide database.

Analysis: The multiplex fluorescence TMA image file was imported into Definiens Tissue Studio version 4.7 (Definiens AG, Munich, Germany), where individual cores were identified using the software’s automated TMA segmentation tool. First, nucleus segmentation (DAPI channel) and cell growth algorithms were used to segment individual cells within each core. A minimum size threshold was used to refine the cell segmentation. Next, mean fluorescence intensity (MFI) values for the FITC (fucosylation), Cy3 (melanoma markers Mart1 + S100) and Cy5 (CD3 marker) channels were extracted from each segmented cell and minimum thresholds for MFI was set to enumerate positive Cy3 and Cy5 cells. Identical thresholds were used for each core. Finally average MFI values for each core were reported for the FITC and Cy3 channels.

Melanoma-specific fucosylation (FITC in CY3-positive cells) MFI and CD3⁺ cell numbers were subject to statistical analyses and correlation with clinical parameters as follows: We used the nonparametric Wilcoxon rank sum test to compare melanoma-specific fucosylation levels between CD3⁺ T cells high vs low groups. The density values of CD3⁺ T cells were all log2 transformed in the statistical analysis. Multivariable linear regression was used to assess the association between fucosylation and T cells while adjusting for confounding factors including sex, age and stage. The Spearman correlation coefficient was used to measure the correlation between melanoma-specific fucosylation and T cells in different sex groups.

Lectin-mediated proximity ligation assay (L-PLA)

Coverslip-grown cells subjected to L-PLA were processed upfront as described in the fluorescent immunocytochemistry protocol detailed above, whereas FFPE tumor tissue sections were processed according to the fluorescent immunohistochemistry protocol detailed above. Both approaches used mouse-anti-HLA-DRB1 (applied at 0.2 µg/mL, ab215835, Abcam, Cambridge, UK), biotinylated AAL lectin (applied at 0.2 µg/mL, Vector Laboratories (Burlingame, CA)), on coverslips overnight in 4^oC. The coverslip-grown cells were again washed twice with PBS followed and then incubated with phalloidin Alexafluor 488 (applied at 0.05 µg/mL, ThermoFisher Scientific (Waltham, MA) with goat anti-biotin (applied at 0.1 µg/mL, Vector Laboratories (Burlingame, CA)) for 2h in 4^oC. Subsequent steps of the protocol were adapted from the DUOlink In Situ Green PLA kit's manufacturer’s protocol (Millipore Sigma (St. Louis, MO)). PLA anti-goat MINUS and PLA anti-mouse PLUS probes were applied at 1:5 for 1 h at 37^oC. The coverslips were washed twice with Wash Buffer A prior to ligation with 1:5 ligation buffer and 1:40 ligase in ddH2O for 30 min at 37^oC. The coverslips were washed twice with wash buffer A prior to incubation in amplification mix (1:5 amplification buffer and 1:80 polymerase in ddH2O for 1.5 h at 37^oC). Coverslips were washed twice with Wash Buffer B prior to mounting to slide with DAPI with VectaShield (Vector Labs, Burlingame, CA). Microscopy images were acquired using a Keyence BZ-X710, and images were process and analyzed using FIJI (NIH).

• Immunofluorescent staining, image acquisition, and analysis of anti-PD1-treated melanoma patients (FIG. 5c):

The indicated FFPE sections were immunostained with anti-DRB1 antibody or L-PLA stained as detailed above with the addition of anti-CD4⁺ antibody. WTS imaging was performed using the Vectra3 Automated Quantitative Pathology Imaging System (PerkinElmer, Waltham, MA). 20X ROI tiles were sequentially scanned across the slide and spectrally unmixed using InForm (PerkinElmer, Waltham, MA) and the multilayer Tiff files were exported. HALO (indica labs, Albuquerque, NM) was used to fuse the tile images together prior to WTS image analysis. For each whole tumor image, (i) every individual melanoma marker (MART1 + S100)-positive cell was segmented and quantitatively measured for total fucosylation, total HLA-DRB1, and fucosylated HLA-DRB1, and (ii) every CD4⁺T cell within the melanoma marker-positive tissue region was counted. Per patient (Pt.), these marker values were box plotted to visualize the staining distribution of individual tumor cells. The total numbers of melanoma cells per patient section measured and analyzed were as follows: Pt. 1: 557,146 cells; Pt. 2: 743,172 cells; Pt. 3: 95,628 cells; and Pt. 4: 13,423 cells.

Anti-PD1-treated patient specimens (FIGs. 5d & 5e, and EXTENDED DATA FIGs. 4D & 4E)

Moffitt Cancer Center patient specimens: Patients with advanced stage melanoma being treated at Moffitt Cancer Center were identified, and specimens collected and analyzed following patient consent under Moffitt Cancer Center Institutional Review Board approved protocols.

• For FIGs. 5d & 5e: De-identified Moffitt “Responder” patients exhibited greater than 20 months of progression-free survival, whereas “Non-Responder” patients progressed in less than 6 months after receiving anti-PD1.

• For Extended Data FIGs 4D & 4E: Non-response status to PD1 checkpoint blockade therapy (nivolumab or pembrolizumab) was defined as progression of disease by RECIST 1.1 while on PD-1 checkpoint blockade therapy or within 3 months of last dose.

MD Anderson Cancer Center patient specimens: Biospecimens were retrieved, collected and analyzed after patient consent under UT MD Anderson Cancer Center Institutional Review Board-approved protocols. Patients with advanced (stage III/IV) melanoma treated at The University of Texas MD Anderson Cancer Center between 07/01/2015 and 05/01/2020 who received at least one dose of PD-1 checkpoint blockade agent (either nivolumab or pembrolizumab) were identified from detailed retrospective and prospective review of clinic records. Responder status was defined as a complete or partial response and non-responder was defined as stable or progressive disease by RECIST 1.1. Pathologic response was defined by the presence or absence of viable tumor on pathologic review when available.

Massachusetts General Hospital patient specimens: Patients initiating anti-PD1 (Pembrolizumab) as front-line treatment for metastatic melanoma at MGH provided written informed consent for the collection of tissue and blood samples for research and genomic profiling (DF/HCC IRB approved Protocol 11–181). Patients classified as responders (R) showed clear radiographic decrease in disease at initial staging through a minimum of 12 weeks. Patients classified as non-responders (NR) did not respond to treatment radiographically and/or had clear and rapid progression. Progression free survival (PFS) is given in days from treatment start to radiographic scan when progression was first noted (uncensored) or last progression free scan (censured). Overall survival (OS) is given in days from treatment start to date of death (uncensored) or last follow-up (censored).

Animal models

All animals were housed at the Vincent A. Stabile Research building animal facility at H. Lee Moffitt Cancer Center & Research Institute, which is fully accredited by the Association for Assessment and Accreditation of Laboratory Animal Care International (AAALAC, #434), and are managed in accordance with the Guide for the Care and Use of Laboratory Animals (“The Guide”), the Animal Welfare Regulations Title 9 Code of Federal Regulations Subchapter A, “Animal Welfare”, Parts 1–3 (AWR), the Public Health Service Policy on Humane Care and Use of Laboratory Animals (PHS Policy), and by the USF Institutional Animal Care and Use Committee’s Principles and Procedures of Animal Care and Use (IACUC Principles). The experiments and protocols detailed in this study received institutional approval by the Moffitt IACUC (RIS00001625). Four-to-six-week-old female C3H/HeN and male C57BL6 mice were purchased from Charles Rivers Laboratories for the indicated experiments. Four-to-six-week-old male NSG mice from the Lau laboratory breeding colony were used for the indicated experiments. Power calculations were used to determine mouse cohort sizes to detect significant changes in tumor sizes. In general, 10 mice per indicated cohort to accommodate for incidental loss of mice due to issues beyond our control (e.g., incidental tumor ulceration that required exclusion from the study). Mouse tumor volumes were measured using length, width and depth divided by 2. At each experimental endpoint, mice were humanely euthanized using CO₂ inhalation in accordance to the American Veterinary Medical Association guidelines. Mice were observed daily and humanely euthanized if the tumor reached 2,000 mm³ or mice showed signs of metastatic disease.

For all mouse models, 1 x 10⁶ melanoma cells were injected subcutaneously in the right hind flanks of each mouse. Between 7–14 days, when the tumor volumes reached ~ 150 mm³, the mice were either supplemented with or without 100 mM L-fucose (Biosynth (Oak Terrace, IL)) via drinking water, which was provided ad libitum and which we previously demonstrated to increase tumor fucosylation and to suppress melanomas ⁸. This dosage is within previously reported ranges for dietary supplementation with L-fucose and other similar dietary sugars (e.g., D-mannose) in other rodent studies ^67–71. When the tumors reached ~ 2 cm³, the animals were sacrificed, and the tumors either processed for flow cytometric profiling or for histological analysis as indicated.

• Control vs. mFuk ± L-fucose models (Fig. 1 & Extended Data Fig. 1): SW1 or SM1 mouse melanoma cells were injected into syngeneic C3H/HeN (or NSG) female or C57BL/6 male mice, respectively, as follows: parental SW1 cells for Fig. 1A; parental SM1 cells for Fig. 1E; SW1 cells stably expressing either empty vector (EV) or mouse fucose kinase (mFuk) for Fig. 1L; and parental SW1 cells for Fig. 1M.

• Control vs. L-fucose ± FTY720 models (Fig. 2): SW1 or SM1 mouse melanoma cells were injected into syngeneic C3H/HeN (or NSG) female or C57BL/6 male mice, respectively. Cells were injected as follows: parental SW1 cells for Fig. 1A; parental SM1 cells for Fig. 1E; SW1 cells stably expressing either empty vector (EV) or mouse fucose kinase (mFuk) for Fig. 1L; and parental SW1 cells for Fig. 1M. FTY720 was administered at 20 µg every 2 days starting on Day 12, just prior to the initiation of LF, until endpoint.

• Immunodepletion mouse models (Fig. 1 & Extended Data Fig. 1): Three days prior to tumor engraftment, PBS (control) or ~ 300 µg α-CD4 (20 mg/kg, for immunodepletion, GK1.5, Bioxcell (West Lebanon, NH)) or α-CD8 (20 mg/kg, for immunodepletion, 2.43, Bioxcell (West Lebanon, NH)) was administered by intraperitoneal injection into the indicated cohorts of mice. Injections of immunodepletion antibody or PBS were continued every 3–4 days until endpoint. Syngeneic recipient C3H/HeN female or C57BL/6 male mice were injected with SW1 or SM1 cells, respectively.

• HLA-A/HLA-DRB1 knockdown and glyco-fucomutant H2-EB1 reconstitution mouse model (Figs. 2 & 3): SW1 mouse melanoma cells expressing either shNT (non-targeting shRNA), shH2K1, shEB1, shNT + EV, shEB1 + EV, shEB1 + EB1 WT, or shEB1 + EB1 N46G were injected into syngeneic C3H/HeN female mice.

• anti-PD-1 mouse model (Figs. 4): SW1 or SM1 mouse melanoma cells were injected into syngeneic C3H/HeN female or C57BL/6 male mice, respectively. After approximately 7 days, when the mice tumors reached ~ 150 mm³, the mice were either supplemented with or without 100 mM L-fucose (Biosynth (Oak Terrace, IL)) via drinking water, which was provided ad libitum. Simultaneously, PBS (control) or anti-PD1 (20 mg/kg, clone RMP1-14, Bioxcell (West Lebanon, NH)) were administered via intraperitoneal injection every 3–4 days until endpoint. Mice were sacrificed, and tumors and indicated organs were harvested for analysis at indicated timepoints.

• NSG melanoma model (Fig. 1 model): SW1 murine mouse melanoma cells were subcutaneously injected into the right rear flanks of NSG mice.

Quantification and statistical analysis

GraphPad Prism was used for statistical calculations unless otherwise indicated. For all comparisons between 2 independent conditions, t tests were performed to obtain p values and standard error of the mean (SEM). For comparisons between ≥ 2 groups, one way or two-way ANOVAs were performed, and p values and SEMs were obtained. For the TMA data, Wilcoxon signed-rank test was used to determine significance.

AUTHOR CONTRIBUTIONS

Conceptualization: E.L., D.K.L, S.A.P., V.L.; Methodologies: E.L., D.K.L., B.C., P.I., K.K., Q.L., E.A., D.B.W., M.B., A.M-M., M.M., G.W., C.MS., S.M., A.G., L.D., V.I.; Computational Analysis: Q.Q.M., D.B.W., B.C., J.J., J.N., X.W.; Resources: J.M., J.M., C.P.L, K.L.T., D.T.F., T.S., M.G.W., J.A.W., G.M.B., B.R.; Writing: E.L., D.K.L.; Supervision: E.L., S.A.P., V.L., R.S.H., X.W., B.R., J.M.K.; Funding Acquisition: E.L., R.S.H. All of the authors commented on the manuscript.

ACKNOWLEDGEMENTS

We are grateful to all Lau laboratory members and to Drs. Srikumar Chellappan, John Cleveland, José Conéjo-Garcia, Gina DeNicola, Florian Karreth, Ana Gomes, and Daniel Abate-Daga at Moffitt Cancer Center for critical readings of this manuscript. We would also like to thank Dr. Ze’ev Ronai for his mentorship, as well as Drs. Michiko Fukuda, Minoru Fukuda, and Hudson Freeze for their technical advice and guidance in glycobiological studies. We would like to acknowledge to Dr. Eva Sahakian for technical assistance and advice and Ms. Melissa Meister, Theresa Alvarez, and Tara Christie for administrative support. This work has been supported in part by the Moffitt/USF Vivarium, Flow Cytometry Core, Biostatistics, Analytical Microscopy, Tissue Core Facilities (we would like to thank in particular Mr. Noel Clark and Ms. Jodi Balasi for technical support) and Advanced Analytical and Digital Laboratory at H. Lee Moffitt Cancer Center & Research Institute, an NCI designated Comprehensive Cancer Center (P30-CA076292). We would like to acknowledge the Proteomic Shared Resource of the Sanford Burnham Prebys Medical Discovery Institute for their assistance with the fucosylated proteomic screening. Support from a NIGMS grant (GM061126 to R.S.H.), NCI grants (K99CA172705, R00CA172705, and R01CA241559 to E.L.), a Harry J. Lloyd Charitable Trust Melanoma Research grant (to E.L.) are gratefully acknowledged.

COMPETING INTERESTS

G.M.B. has SRA with Palleon Pharmaceuticals, Olink Proteomics, InterVenn Biosciences, and formerly with Takeda Oncology. She consults for Merck and InterVenn. She served on SAB and a steering committee for Nektar Therapeutics. J.M. has served on an advisory board for Array Biopharma in the past 2 years and has been PI of grants/funding to his institution from Morphogenesis Inc, Navigate Biopharma, Jackson Labs, Microba, Merck, Macrogenics, and Reata Pharmaceuticals. Moffitt Cancer Center has licensed Intellectual Property (IP) related to the proliferation and expansion of tumor infiltrating lymphocytes (TILs) to Iovance Biotherapeutics. Moffitt has also licensed IP to Tuhura Biopharma. S.P.T. is an inventor on such Intellectual Property. S.P.T. is listed as a co-inventor on a patent application with Provectus Biopharmaceuticals. S.P.T. participates in sponsored research agreements with Provectus Biopharmaceuticals, Iovance Biotherapeutics, Intellia Therapeutics, Dyve Biosciences, and Turnstone Biologics that are not related to this research. S.P.T. has received ad hoc consulting fees from Seagen Inc. and serves as an advisor for KSQ Therapeutics.

DATA AVAILABILITY

The authors declare that the main data supporting the findings of this study are available within the article and its Supplementary Information files. Additional data are available from the corresponding author upon request.

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Tables 1 to 3 are available in the Supplementary Files section.

Yes there is potential Competing Interest. G.M.B. has SRA with Palleon Pharmaceuticals, Olink Proteomics, InterVenn Biosciences, and formerly with Takeda Oncology. She consults for Merck and InterVenn. She served on SAB and a steering committee for Nektar Therapeutics.

J.M. has served on an advisory board for Array Biopharma in the past 2 years, and has been PI of grants/funding to his institution from Morphogenesis Inc, Navigate Biopharma, Jackson Labs, Microba, Merck, Macrogenics, and Reata Pharmaceuticals.

Moffitt Cancer Center has licensed Intellectual Property (IP) related to the proliferation and expansion of tumor infiltrating lymphocytes (TILs) to Iovance Biotherapeutics. Moffitt has also licensed IP to Tuhura Biopharma. S.P.T. is an inventor on such Intellectual Property. S.P.T. is listed as a co-inventor on a patent application with Provectus Biopharmaceuticals. S.P.T. participates in sponsored research agreements with Provectus Biopharmaceuticals, Iovance Biotherapeutics, Intellia Therapeutics, Dyve Biosciences, and Turnstone Biologics that are not related to this research. S.P.T. has received ad hoc consulting fees from Seagen Inc. and serves as an advisor for KSQ Therapeutics.

SupplementaryInformation.pdf
EXTENDEDDATA1.pdf
EXTENDED DATA FIG. 1: Confirming increased tumor fucosylation and TIL counts, splenic immune cell profiles, and correlations between tumor fucosylation and CD3⁺T cells in female vs. male melanoma patients Immunofluorescent (IF) staining analysis of SW1 tumor FFPE sections for intratumoral fucosylation (a). Flow cytometric profiling of intratumoral immune cell (itIC) subpopulations (CD3⁺T cells, natural killer cells (NKs), macrophages (MΦ), MDSC-like cells (MDSCs), and dendritic cells (DCs)) in (b) SW1 tumors and (c) spleens in control (Ctl)- or L-fuc (LF)-supplemented SW1 tumor-bearing C3H/HeN mice from Fig. 1a. IF staining analysis of SM1 tumor FFPE sections for intratumoral fucosylation (d). (e) Volumetric growth curves, (f) total TIL counts, (g) absolute TIL subpopulations, (h) splenic immune cell profiles, (i) % TIL subpopulations, (j) intratumoral CD4⁺ and CD8⁺T cell counts of SM1 tumors in C57BL6 mice. (k) Volumetric growth curves of SW1 tumors in NSG mice. (l) IB analysis confirming mFUK expression in SW1 cells (upper), IF staining analysis of SW1 tumor FFPE sections for intratumoral fucosylation (lower), and (m) flow cytometric profiling of indicated immune populations in EV- or mFUK-expressing SW1 tumors from Ctl- or LF-supplemented C3H/HeN mice. (n) Flow cytometric profiling of splenic CD4⁺T cells in control (PBS-injected) vs. CD4⁺T cell-depleted (CD4(-)) SW1 tumor-bearing C3H/HeN mice supplemented ± LF. (o) IF staining profiling of splenic CD8⁺T cells in control vs. CD8⁺ T cell-depleted (CD8(-)) SW1 tumor-bearing C3H/HeN mice. Flow cytometric profiling of (p) total TIL counts in control vs. CD4(-) SW1 tumor-bearing C3H/HeN mice and (q) splenic CD4⁺T cells in control vs. CD4(-) SM1 tumor-bearing C57BL6 mice supplemented ± LF. Percentages represent % CD4⁺T of total splenic cells. (r) IF profiling of splenic CD8⁺T cells in control vs. CD8(-) SM1 tumor-bearing C57BL6 mice fed ± L-fuc. Volumetric growth curves for SM1 tumors in (s) control (PBS)-injected, (t) CD8(-), or (u) CD4(-) C57BL6 mice. (v) Flow cytometric profiling of total TIL counts in control (s) vs. CD4(-) (u) mice. (w) Comparison of intratumoral NK, DC, CD8⁺T, and CD4⁺T subpopulations from control or CD4(-) (a-CD4) depleted tumors in (s) and (u). For each mouse model: when tumors reached ~150 mm³, Ctl- or LF-supplemented water (100 mM; ▼ = initiated supplementation) was provided ad libitum. The tumor growth curves are means ± SEM from ≥7 mice per group. * = p<0.05. Relative fold-changes in splenic CD8⁺T cells were determined by (total intrasplenic CD8⁺ signal area / total intrasplenic DAPI area) as a measure of relative CD8⁺T cell abundance/spleen.
EXTENDEDDATA2.pdf
EXTENDED DATA FIG. 2: Fucosylation of CD4⁺T cells affects PKA activity and actin polymerization; and the identification of Integrin b5 as a highly fucosylated protein in activated CD4⁺T cells. (a) Top 5 pathways in human CD4⁺T cells that are affected by increased fucosylation identified by Ingenuity Pathway Analysis (Qiagen; pathways were identified from phosphoproteomic analyses of CD3/CD28-activated human PBMC-derived CD4⁺T cells treated ± 250 µM L-fucose (LF) isolated from 3 independent healthy human donors (D1, D2, D3)). (b) (left) Immunoblot of PKA phosphorylated substrates (top) and Ponceau staining (bottom) of human PBMC-derived, CD3/CD28-activated CD4⁺T cells that were treated ± 250 µM LF (for 72h) ± 10 µM forskolin (Fkn, a PKA agonist; for 6h). (right) Densitometric quantification of selected bands (red dashed boxes) normalized to Ponceau staining. (c) Immunoblot of b-actin (top) and Ponceau staining (middle) of human PBMC-derived, CD3/CD28 activated CD4⁺T cells were treated ± 250 µM LF ± 25 mM DTSP crosslinker (x-link). (bottom) Densitometric quantification of high molecular weight b-actin oligomers (red dashed boxes) normalized to Ponceau intensity and then normalized to -LF, -x-link samples. (d) (i) Coverslip-grown Jurkat cells treated ± 250 µM LF (for 72h), fixed, and stained with DAPI and phalloidin-488 for actin cytoskeleton. Scale bar: 25 µm. *: p = 0.006; **: p = 0.001. (ii) Integrated actin signal densities per cell from 3 biological replicates of Jurkat cells grown/treated as in (i) were measured using FiJi (NIH) and plotted as shown using GraphPad Prism. (e) Top 5 AAL-bound (fucosylated) proteins in human PBMC-derived, CD3/CD28-activated CD4⁺T cells from (a) that were identified by Ingenuity Pathway Analysis (Qiagen). (f) Of the 5 top hits, we were only able to validate fucosylation of Integrin b5 by LPD analysis of human PBMC-derived, CD3/CD28-activated CD4⁺T cells.
EXTENDEDDATA3.pdf
EXTENDED DATA FIG. 3: Fucosylated mass spectrometric analysis and knockdown efficiency of H2K1 and H2EB1 (a) (left) Schematic for proteomic analysis of fucosylated proteins in human WM793 melanoma cells using pLenti-GFP empty vector (EV)-, pLenti-FUK-GFP (o/e)-, or shFUK-expressing WM793 cells from ⁸. Click chemistry biotinylated-fucosylated proteins that were pulled down using Neutravidin beads from the 6-alkynyl-L-fucose-labeled cells were subjected to LC-MS/MS, and hits were subjected to the indicated filtering scheme followed by Ingenuity Pathway Analysis (Qiagen). (right) Top 20 pathways, plasma membrane- and immune-related proteins identified by Ingenuity Pathway Analysis (Qiagen) to be significantly altered by fucosylation. (b) qRT-PCR analysis confirming knockdown of H2K1 (shH2K1; left) or H2EB1 (shEB1; right) using 2 shRNAs per target compared to control non-targeting (shNT) shRNA. Red arrows indicate the specific shRNA clones used in functional experiments in the remainder of the study.
EXTENDEDDATA4.pdf
EXTENDED DATA FIG. 4: nano-LC/MS spectral identification of fucosylated HLA-DRB1 peptide; and the effects of modulating fucosylation on HLA-DRB1 localization, total protein, and mRNA levels (a) nano-LC/MS/MS spectra showing fucosylated HLA-DRB1 peptide (arrow).(b) Flow cytometric analysis for relative cell surface fucosylation (upper) and cell surface HLA-DRB1 levels (upper middle), qRT-PCR analysis of relative HLA-DRB1 mRNA levels (lower middle), and IB analysis of HLA-DRB1 protein levels (lower) in indicated melanoma cell lines treated with DMSO (D), 250µM FUTi (i), or 250µM L-fuc (LF). * = p<0.05.
EXTENDEDDATA5.pdf
EXTENDED DATA FIG. 5: Proteomic analysis reveal fuco/glycosylation of HLA-DRB1 decreases binding to calnexin; knockdown/reconstitution and fucosylation of EB1 WT and N46G and its effects on TILs in vivo; loss of MHCII is associated with anti-PD1 failure in melanoma patients (a) IB analysis of 5% input of V5 IP of tagged EV, HLA-DRB1^WT, and HLA-DRB1^N48G mutant in WM793 melanoma cells. (b) (top) Top 5 pathways that are affected by HLA-DRB1 fuco/glycosylation identified by Ingenuity Pathway Analysis (Qiagen). (bottom) Individual proteins in the Antigen Presentation Pathway identified in the screen. (c) Schematic of proteins identified in the Antigen Presentation & MHC-II Loading Pathway. The schematic was created using BioRender.com. (d) (top) IP of EV, HLA-DRB1^WT, and HLA-DRB1^N48G and IB analysis of calnexin (short exposure (s.e.), calnexin (intermediate exposure (i.e.), V5, and b-tubulin. (bottom) Quantification of calnexin band intensity to V5 intensity in V5 IP lanes (relative to HLA-DRB^WT). (e) (upper) IB analysis of non-targeting shRNA + empty vector (shNT + EV) or shEB1-expressing cells (from Extended Data Fig. 3b) reconstituted with FLAG-EV (shEB1 + EV), FLAG-EB1^WT (shEB1 + EB1^WT), or FLAG-EB1^N46G (shEB1 + EB1^N46G). (lower) LPD and IB analysis of indicated cells from (upper). (f) Total TIL counts and (g) indicated immune subpopulations in the shNT or shEB1 knockdown/EB1^WT- or EB1^N46G-reconstituted SW1 tumors of the Ctl- or LF-supplemented C3H/HeN mice. * = p<0.05. (h) % of total CD45^-/CD90^-/EpCAM^- tumor cells exhibiting positive pan MHC-I (left) or pan MHC-II (lower) staining from either anti-PD1 naïve patients (black squares; n = 7) or patients who failed anti-PD1 (grey squares; n = 13).
EXTENDEDDATA6.pdf
EXTENDED DATA FIG. 6: Spatial and pre-/post-anti-PD1 trends in fucosylation, total-/fuco-HLA-DRB1 & CD4⁺T cells in patient specimens, lack of effect of fucosylation on cell surface presence of melanoma PD-L1, & examples of stromal content discrepancy among patient biopsies. EDF 6) Association of mean tumor cellular (MTC) fucosylated HLA-DRB1 with % CD4⁺T cells either inside (tumor marker (+); upper) or outside (tumor border/periphery; tumor marker (-); lower) melanoma tumors in patients from (a) Massachusetts General Hospital or (b) MD Anderson Cancer Center (MDACC). (c) Mean tumor cellular (MTC) total fucosylation (upper), total HLA-DRB1 (middle), or fucosylated HLA-DRB1 (lower) levels in MDACC patient-matched pre-/post-anti-PD1 tumor specimens. C/P/N = Complete/partial/non-responder, respectively. (d) WM793 (left), SW1 (middle), and SM1 (right) cells were treated with DMSO (D) or 250 µM FUTi (i) or L-fuc (LF) and subjected to flow cytometric assessment of changes in cell surface levels of fucosylation (upper) and PD-L1 (lower). * = p<0.05. (e) A “Highly correlated" anti-PD1 responder biopsy with high fuco-HLA-DRB1 and CD4⁺T cell (upper) vs. a "non-correlated" responder biopsy with low fuco-HLA-DRB1 and CD4⁺T cells were stained for indicated markers. Yellow dashed lines represent the tumor:stromal interface surrounding melanoma marker-negative stroma in the highly correlated responder that is absent in the non-correlated responder. Yellow asterisks indicate non-nucleated non-specific staining on the non-correlated responder slide.
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published 23 Jan, 2023

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Fucosylation of HLA-DRB1 regulates CD4⁺T cell-mediated anti-melanoma immunity and enhances immunotherapy efficacy

Status:

Journal Publication

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Abstract

Figures

Main

Results

Increasing melanoma fucosylation impairs tumor growth and augmentsTIL abundance, particularly CD4⁺ and CD8⁺ T cells

L-fucose suppresses melanomas by triggering CD4⁺T cell-mediated increases in ITICs and altering CD4⁺T cell biology, increasing memory CD4⁺T subpopulations

Fucosylated HLA-DRB1 mediates L-fucose-triggered TIL induction, anti-melanoma immunity, and melanoma suppression

N48 fucosylation of HLA-DRB1 regulates its cell surface localization and is required for TIL induction, anti-melanoma immunity, and melanoma suppression

Oral L-fucose augments anti-PD1-mediated melanoma suppression

Melanoma fucosylation and fucosylated HLA-DRB1 as potential biomarkers of anti-PD1 response

Discussion

Methods

Declarations

References

Tables

Additional Declarations

Supplementary Files

Status:

Journal Publication

Version 1

Fucosylation of HLA-DRB1 regulates CD4+T cell-mediated anti-melanoma immunity and enhances immunotherapy efficacy

Status:

Journal Publication

Version 1

Abstract

Figures

Main

Results

Increasing melanoma fucosylation impairs tumor growth and augmentsTIL abundance, particularly CD4+ and CD8+ T cells

L-fucose suppresses melanomas by triggering CD4+T cell-mediated increases in ITICs and altering CD4+T cell biology, increasing memory CD4+T subpopulations

Fucosylated HLA-DRB1 mediates L-fucose-triggered TIL induction, anti-melanoma immunity, and melanoma suppression

N48 fucosylation of HLA-DRB1 regulates its cell surface localization and is required for TIL induction, anti-melanoma immunity, and melanoma suppression

Oral L-fucose augments anti-PD1-mediated melanoma suppression

Melanoma fucosylation and fucosylated HLA-DRB1 as potential biomarkers of anti-PD1 response

Discussion

Methods

Declarations

References

Tables

Additional Declarations

Supplementary Files

Status:

Journal Publication

Version 1

Fucosylation of HLA-DRB1 regulates CD4⁺T cell-mediated anti-melanoma immunity and enhances immunotherapy efficacy

Increasing melanoma fucosylation impairs tumor growth and augmentsTIL abundance, particularly CD4⁺ and CD8⁺ T cells

L-fucose suppresses melanomas by triggering CD4⁺T cell-mediated increases in ITICs and altering CD4⁺T cell biology, increasing memory CD4⁺T subpopulations