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Introduction: Classic Hodgkin lymphoma (CHL) features a unique crosstalk between malignant cells and different types of normal immune cells in the tumor-microenvironment (TME). On the basis of histomorphologic and immunophenotypic features of the malignant Hodgkin and Reed-Sternberg (HRS) cells and infiltrating immune cells, four histological subtypes of CHL are recognized: Nodular sclerosing (NS), Mixed cellularity, Lymphocyte-rich (LR) and Lymphocyte-depleted CHL. Recently, our group described the high abundance of various types of immunosuppressive CD4+ T cells including LAG3+ and/or CTLA4+ cells in the TME of CHL using single cell RNA sequencing (scRNAseq). However, the TME of LR-CHL has not been well characterized due to the rarity of the disease. In this study, we aimed at characterizing the immune cell profile of LR-CHL at single cell resolution. METHODS: We performed scRNAseq on cell suspensions collected from lymph nodes of 28 primary CHL patients, including 11 NS, 9 MC and 8 LR samples, with 5 reactive lymph nodes (RLN) serving as normal controls. We merged the expression data from all cells (CHL and RLN) and performed batch correction and normalization. We also performed single- and multi-color immunohistochemistry (IHC) on tissue microarray (TMA) slides from the same patients. In addition, an independent validation cohort of 31 pre-treatment LR-CHL samples assembled on a TMA, were also evaluated by IHC. Results: A total of 23 phenotypic cell clusters were identified using unsupervised clustering (PhenoGraph). We assigned each cluster to a cell type based on the expression of genes described in published transcriptome data of sorted immune cells and known canonical markers. While most immune cell phenotypes were present in all pathological subtypes, we observed a lower abundance of regulatory T cells (Tregs) in LR-CHL in comparison to the other CHL subtypes. Conversely, we found that B cells were enriched in LR-CHL when compared to the other subtypes and specifically, all four naïve B-cell clusters were quantitatively dominated by cells derived from the LR-CHL samples. T follicular helper (TFH) cells support antibody response and differentiation of B cells. Our data show the preferential enrichment of TFH in LR-CHL as compared to other CHL subtypes, but TFH cells were still less frequent compared to RLN. Of note, Chemokine C-X-C motif ligand 13 (CXCL13) was identified as the most up-regulated gene in LR compared to RLN. CXCL13, which is a ligand of C-X-C motif receptor 5 (CXCR5) is well known as a B-cell attractant via the CXCR5-CXCL13 axis. Analyzing co-expression patterns on the single cell level revealed that the majority of CXCL13+ T cells co-expressed PD-1 and ICOS, which is known as a universal TFH marker, but co-expression of CXCR5, another common TFH marker, was variable. Notably, classical TFH cells co-expressing CXCR5 and PD-1 were significantly enriched in RLN, whereas PD-1+ CXCL13+ CXCR5- CD4+ T cells were significantly enriched in LR-CHL. These co-expression patterns were validated using flow cytometry. Moreover, the expression of CXCR5 on naïve B cells in the TME was increased in LR-CHL compared to the other CHL subtypes We next sought to understand the spatial relationship between CXCL13+ T cells and malignant HRS cells. IHC of all cases revealed that CXCL13+ T cells were significantly enriched in the LR-CHL TME compared to other subtypes of CHL, and 46% of the LR-CHL cases showed CXCL13+ T cell rosettes closely surrounding HRS cells. Since PD-1+ T cell rosettes are known as a specific feature of LR-CHL, we confirmed co-expression of PD-1 in the rosetting cells by IHC in these cases. Conclusions: Our results reveal a unique TME composition in LR-CHL. LR-CHL seems to be distinctly characterized among the CHL subtypes by enrichment of CXCR5+ naïve B cells and CD4+ CXCL13+ PD-1+ T cells, indicating the importance of the CXCR5-CXCL13 axis in the pathogenesis of LR-CHL. Figure Disclosures Savage: BeiGene: Other: Steering Committee; Merck, BMS, Seattle Genetics, Gilead, AstraZeneca, AbbVie: Honoraria; Roche (institutional): Research Funding; Merck, BMS, Seattle Genetics, Gilead, AstraZeneca, AbbVie, Servier: Consultancy. Scott:Janssen: Consultancy, Research Funding; Celgene: Consultancy; NanoString: Patents & Royalties: Named inventor on a patent licensed to NanoString, Research Funding; NIH: Consultancy, Other: Co-inventor on a patent related to the MCL35 assay filed at the National Institutes of Health, United States of America.; Roche/Genentech: Research Funding; Abbvie: Consultancy; AstraZeneca: Consultancy. Steidl:AbbVie: Consultancy; Roche: Consultancy; Curis Inc: Consultancy; Juno Therapeutics: Consultancy; Bayer: Consultancy; Seattle Genetics: Consultancy; Bristol-Myers Squibb: Research Funding.

Background: LAG3 is one of the immune check point receptors that are expressed on activated cytotoxic T-cells and regulatory T cells. Physiologically, T-cell proliferation and memory T-cell differentiation is negatively regulated by LAG3-MHC interaction. In cancer tissues, T-cells that are chronically exposed to tumor antigens might upregulate LAG3 and receive inhibitory stimuli to enter an exhaustion state limiting anti-tumor immune responses. Currently, clinical trials using double blockade of LAG3/PD1 are active in several solid tumours, but there are only a small number of clinical trials using LAG3 monoclonal antibodies in lymphoma. Recently, we published a characteristic LAG3+ T-cell population as a mediator of immune suppression in classical Hodgkin lymphoma (Aoki & Chong et al. Cancer Discovery 2020). However, the abundance and variability of LAG3 positive T-cell populations across a spectrum of B-cell lymphoma has not been well studied and it remains an open question if LAG3 expression is associated with treatment outcome under standard-of-care conditions. Methods: We performed a LAG3 immunohistochemical (IHC) screen in a large cohort of B-cell Non-Hodgkin lymphoma (diffuse large B-cell lymphoma (DLBCL); N=341, follicular lymphoma (FL); N=198 (grade 1-3A), transformed FL to aggressive lymphoma (tFL); N=120, mantle cell lymphoma (MCL); N=179, primary mediastinal large B-cell lymphoma (PMBCL); N=61) and classical Hodgkin lymphoma (HL; N=459) to assess LAG3 expression in the tumor microenvironment (TME). Moreover, we characterized LAG3+ T-cell populations using multi-color immmunohistochemistry (IHC) (LAG3, PD1, CD4, CD8, FOXP3, CD20) in various lymphoma subtypes. Clinical parameters including treatment outcome were correlated with the abundance of LAG3+ T-cell populations in the TME. Results: On average, HL (7%) and PMBCL (6%) showed higher LAG3+ cellular frequency than the other B-cell lymphoma subtypes studied (DLBCL and FL: 2%, MCL: 0.8%). Comparing the frequency of LAG3+ cells according to MHC class I/II status, DLBCL showed a significant correlation with MHC class I status, and LAG3 expression correlated with MHC class II status in HL. Next, we performed multi-color IHC to describe subtype-specific expression patterns of LAG3 in T cell subsets. LAG3+PD1- T-cells were predominantly found in HL and PMBCL with only rare LAG3+PD1+ cells in HL. The majority of LAG3+ T-cells co-expressed CD4 in HL, in contrast to CD8 in PMBCL. DLBCL showed a mixed population pattern with a 1:1 ratio of LAG3+PD1- and LAG3+PD1+ T-cells. In FL, the majority of LAG3+ T-cells were CD4+PD1+, suggesting a more exhausted TME phenotype in FL than in other lymphoma subtypes. Cellular distance analysis showed that LAG3+CD4+ T-cells were in close vicinity to CD20+ lymphoma cells in FL, while in DLBCL and PMBCL, the nearest neighbors of malignant cells were LAG3+CD8+. Triple-positive LAG3+PD1+CD8+ T-cells significantly correlated with high infiltrating M2 macrophage (Pearson's correlation test, P < 0.001) content and the ABC cell-of-origin subtype (Pearson's correlation test, P = 0.002) in DLBCL. The abundance of LAG3+CD8+PD1- cells correlated with a high FLIPI score (Pearson's correlation test, P = 0.033), disease specific survival (HR = 2.8, 95% CI = 1.3-5.9, P = 0.006), time to progression (HR = 2.8, 95% CI = 1.6-5.0, P = 0.001) and transformation (HR = 4.0, 95%CI = 1.7-9.6, P = 0.002) in FL treated with R-CVP (N = 135). Assessing LAG3 expression by single color IHC in FL (cut-off at 5%), patients with LAG3-positive samples showed significantly higher FL transformation rates (P = 0.023) and tFL samples showed higher abundance of LAG3+ cells than the corresponding primary pretreatment FL samples (primary FL: 1.5±1.7% vs. tFL: 4.2±3.8%, t-test, P = 0.01). The increased transformation risk was validated in an independent FL cohort treated with R-CHOP/CVP (N=97, HR = 6.2, 95% CI = 2.8-13.9, P < 0.001). Conclusion: The highest abundance of LAG3+ T-cells in the TME was found in HL and its related entity PMBCL. The differential outcome correlations and co-expression patterns in LAG3+ T cells across B-cell lymphoma subtypes indicate heterogeneity in TME composition and related pathogenic mechanisms. Our results suggest that LAG3 expression patterns will be important in the interpretation of ongoing studies and highlight populations that may benefit from LAG3 checkpoint inhibition. Disclosures Sehn: AstraZeneca: Consultancy, Honoraria; Genentech, Inc.: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Chugai: Consultancy, Honoraria; TG therapeutics: Consultancy, Honoraria; Verastem Oncology: Consultancy, Honoraria; Teva: Consultancy, Honoraria, Research Funding; Servier: Consultancy, Honoraria; F. Hoffmann-La Roche Ltd: Consultancy, Honoraria, Research Funding; MorphoSys: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Apobiologix: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Kite: Consultancy, Honoraria; Merck: Consultancy, Honoraria; Lundbeck: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Acerta: Consultancy, Honoraria. Savage:Merck, BMS, Seattle Genetics, Gilead, AstraZeneca, AbbVie, Servier: Consultancy; BeiGene: Other: Steering Committee; Roche (institutional): Research Funding; Merck, BMS, Seattle Genetics, Gilead, AstraZeneca, AbbVie: Honoraria. Scott:Celgene: Consultancy; Abbvie: Consultancy; AstraZeneca: Consultancy; NIH: Consultancy, Other: Co-inventor on a patent related to the MCL35 assay filed at the National Institutes of Health, United States of America.; Roche/Genentech: Research Funding; NanoString: Patents & Royalties: Named inventor on a patent licensed to NanoString, Research Funding; Janssen: Consultancy, Research Funding. Steidl:Bayer: Consultancy; Juno Therapeutics: Consultancy; Roche: Consultancy; Seattle Genetics: Consultancy; Bristol-Myers Squibb: Research Funding; AbbVie: Consultancy; Curis Inc: Consultancy.

INTRODUCTION: Classic Hodgkin lymphoma (cHL) is uniquely characterized by an extensively dominant microenvironment composed primarily of different types of non-cancerous immune cells with a rare population (~1%) of tumor cells. Detailed characterization of these cellular components and their spatial relationship is crucial to understand crosstalk and therapeutic targeting in the cellular ecosystem of the tumor microenvironment (TME). METHODS: In this study, we performed high dimensional and spatial profiling of immune cells in the TME of cHL. Single cell RNA sequencing (scRNA-seq) was performed with the 10x Genomics platform on cell suspensions collected from lymph nodes of 22 cHL patients, including 12 of nodular sclerosis subtype, 9 of mixed cellularity subtype and 1 of lymphocyte-rich subtype, with 5 reactive lymph nodes (RLNs) serving as normal controls. Illumina sequencing (HiSeq 2500) was performed to yield single-cell expression profiles for 127,786 cells. We also performed multicolor IHC and imaging mass cytometry (IMC) on TMA slides from the same patients. RESULTS: Unsupervised clustering using PhenoGraph identified 22 cell clusters including 12 T cell clusters, 7 B cell clusters and 1 macrophage cluster. While most immune cell populations were common between cHL and RLN, we observed an enrichment of cells from cHL in all 3 regulatory T cell (Treg) clusters. The most cHL-enriched cluster was characterized by high expression of LAG3, in addition to common Treg markers such as IL2RA (CD25) and TNFRSF18 (GITR), but lacked expression of FOXP3, consistent with a type 1 regulatory (Tr1) T cell population. LAG3+ T cells in cHL had high expression of immune-suppressive cytokines IL-10 and TGF-b . In vitro exposure of T cells to cHL cell line supernatant induced significantly higher levels of LAG3 in naïve T cells compared to co-culture with other lymphoma cell line supernatant or medium only. CD4+ LAG3+ T cells isolated by FACS also suppressed the proliferation of responder CD4+ T cells when co-cultured in vitro. Additionally, Luminex analysis revealed that cHL cell lines secrete substantial amounts of cytokines and chemokines that can promote Tr1 cell differentiation (e.g. IL-6). Our scRNA-seq analysis revealed that LAG3 expression was significantly higher in cHL cases with loss of major histocompatibility class II (MHC-II) expression on HRS cells as compared to MHC-II positive cases (P = 0.019), but was not correlated with EBV status or histological subtype. Strikingly, LAG3 was identified as the most up-regulated gene in cells from MHC-II negative cases compared to MHC-II positive cases. Topological analysis using multicolor IHC and IMC revealed that in MHC-II negative cases, HRS cells were surrounded by LAG3+ T cells. In these cases, the density of LAG3+ T cells in HRS cell-rich regions was significantly increased, and the average distance between an HRS cell and its closest LAG3+ T cell neighbor was significantly shorter. These associations were confirmed in an independent cohort of 166 cHL patients. Finally, we observed a trend towards an inferior disease-specific survival (DSS; P = 0.072) and overall survival (OS; P = 0.12) in cases with an increased number of LAG3+ T cells. A high proportion of LAG3+ T cells (> 20%) was identified as an independent prognostic factor for DSS by multivariate Cox regression. CONCLUSIONS: Our results reveal a diverse TME composition with inflammatory and immunosuppressive cellular components that are linked to MHC class II expression status on HRS cells (Figure). Unprecedented transcriptional and spatial profiling at the single cell level has established the pathogenic importance of HRS cell-induced CD4+ LAG3+ T cells as a mediator of immunosuppression in cHL, with potential implications for novel therapeutic approaches. Figure Disclosures Savage: Seattle Genetics, Inc.: Consultancy, Honoraria, Research Funding; BMS, Merck, Novartis, Verastem, Abbvie, Servier, and Seattle Genetics: Consultancy, Honoraria. Scott:Roche/Genentech: Research Funding; Celgene: Consultancy; Janssen: Consultancy, Research Funding; NanoString: Patents & Royalties: Named inventor on a patent licensed to NanoSting [Institution], Research Funding. Steidl:Bristol-Myers Squibb: Research Funding; Nanostring: Patents & Royalties: Filed patent on behalf of BC Cancer; Roche: Consultancy; Seattle Genetics: Consultancy; Bayer: Consultancy; Juno Therapeutics: Consultancy; Tioma: Research Funding.