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Introduction: Most patients diagnosed with diffuse large B cell lymphoma (DLBCL) are cured with combination chemoimmunotherapy, but 40% will develop relapsed or refractory (r/r) disease, which is often associated with a poor clinical outcome. PD-1 blockade therapy has been investigated in r/r DLBCL; however, response rates in unselected DLBCL patients are disappointing, highlighting the need for deeper understanding of DLBCL immune landscapes, as well as mechanisms that regulate the immune response to checkpoint blockade therapy (CBT) in this disease. In solid cancers, tumor-cell intrinsic oncogenic signaling strongly influences the immune environment and impacts clinical response to CBT. Despite the recent publication of large-scale genomic datasets in DLBCL, the impact of oncogenic signaling on the immune environment remains to be fully elucidated. In this study, we aimed to characterize immune landscapes associated with DLBCL, as well as the role of lymphoma-intrinsic alterations on shaping the immune environment in this disease. Methods: Using gene set variation analysis (GSVA) in a large cohort of primary DLBCLs (n = ~900), a sample-wise enrichment score was generated for gene sets associated with tumor infiltrating lymphocytes. Gene sets were manually curated to include signatures relating to IFNγ response, T helper cell subsets, CD8 + T cell exhaustion, macrophages, and dendritic cells. A DLBCL cell-of-origin (COO) signature was also included in the GSVA to control for the transcriptional and genomic effects of COO. Samples were hierarchically clustered into related groups. Multispectral immunofluorescence (mIF) for canonical T cell markers was used to confirm GSVA clustering. To mechanistically validate our findings, CRISPR/Cas9 gene editing was used to modulate candidate oncogenes and tumor suppressors genes (TSGs) in the syngeneic A20 murine lymphoma model. Results: GSVA performed on transcriptomes from a large genomic DLBCL dataset revealed four distinct DLBCL immune clusters, termed "ABC hot", "ABC cold", "GCB hot" and "GCB cold", defined by differential expression scores of immune related gene sets (Fig 1A). Concordant with our previous work, DLBCLs with PD-L1 gene amplifications, which are associated with a "T-cell inflamed" tumor microenvironment, were enriched in the "ABC hot" cluster (Fig 1B). Conversely, double hit signature DLBCLs, known to be associated with decreased immune cell infiltration and a GCB COO, were enriched in "GCB cold" DLBCLs (Fig 1C). In an internal cohort of diagnostic DLBCL samples (n = 90) for whom RNA sequencing (RNAseq) and FFPE tissue were available, mIF analysis showed that both "ABC hot" and "GCB hot" DLBCLs had significantly higher ratios of CD8 + T cells to lymphoma cells compared to cold DLBCLs. "ABC hot" DLBCLs also had a significantly higher CD4 + T cell to lymphoma cell ratio (Fig 1D). Importantly, several mutations that correlated with particular DLBCL immune clusters were identified. The "ABC cold" cluster was significantly enriched for loss-of-function (LOF) mutations in TMEM30A and MYD88, whereas LOF mutations in ATM and FOXO1 were commonly observed in "GCB cold" DLBCLs. Finally, LOF mutations in SOCS1 and B2M were significantly enriched in "GCB hot" DLBCLs (Fig 1E, 1F). As LOF SOCS1 mutations were strongly associated with "GCB hot" DLBCLs and are also prevalent in other CBT-sensitive lymphomas, we hypothesized that SOCS1 LOF mutations would enhance lymphoma cell vulnerability to CBT due to increased IFNγ sensitivity resulting from unopposed JAK/STAT activation. To test this hypothesis, we generated Socs1 deficient A20 lymphoma cells. Compared to A20 WT, A20 Socs1-/- cells were characterized by increased pStat1 levels upon IFNγ stimulation (Fig 1G). Interestingly, A20 Socs1-/- tumors showed increased sensitivity to α-PD1 therapy compared to A20 WT in syngeneic hosts. Together, these data suggest that tumor-cell intrinsic JAK/STAT activation via SOCS1 -/- increases lymphoma cell sensitivity to IFNγ and α-PD1 therapy (Fig 1H). Conclusion: We have developed a novel immunogenomic platform to define the role of tumor-cell intrinsic alterations on the immune landscape of DLBCL. Confirmatory studies using in vitro and in vivo models validated the effect of key oncogenes and TSGs on the tumor microenvironment, and suggest these candidate genes may impact response to CBT in DLBCL. Figure 1 Figure 1. Disclosures Smith: Alexion, AstraZeneca Rare Disease: Other: Study investigator; Celgene, Genetech, AbbVie: Consultancy. Steidl: Trillium Therapeutics: Research Funding; Curis Inc.: Consultancy; Epizyme: Research Funding; Seattle Genetics: Consultancy; Bayer: Consultancy; AbbVie: Consultancy; Bristol-Myers Squibb: Research Funding. Kline: Seagen: Membership on an entity's Board of Directors or advisory committees; Morphosys: Consultancy, Membership on an entity's Board of Directors or advisory committees; Kite/Gilead: Speakers Bureau; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Merck: Consultancy, Research Funding; Verastem: Research Funding; SecuraBio: Membership on an entity's Board of Directors or advisory committees; Regeneron: Membership on an entity's Board of Directors or advisory committees.

Objectives: We identified a case of follicular lymphoma (FL) that transformed into a morphologic diffuse large B-cell lymphoma (DLBCL), which by gene expression profiling showed a primary mediastinal (PMBL)-like gene expression profile (GEP) (Lymph3Cx; Blood 2018;132:2401-5). A search identified 4 additional transformed FL (tFL) cases with a PMBL-like GEP, which we further studied to determine how similar these tFLs were to classic cases of PMBL. Methods: The morphology and previously reported immunophenotype were reviewed, and CD30, CD23, MAL, CD273/PDL2, and CD200 immunohistochemical stains (IHC) were performed. Whole exome sequencing (WES) and copy number analysis (CNA) to evaluate genes typically altered in FL and PMBL were performed. Results: None of the tFLs arose in the mediastinum or had a previous history of mediastinal disease. All cases showed typical centroblastic DLBCL cytology, with fine sclerosis typical of PMBL. 3/3 were GCB by the Hans IHC algorithm, 1/3 were MYC+, 3/3 BCL2+, 1/5 CD30+, 3/5 CD23+, 4/5 MAL+, 0/5 CD273/PDL2+, 1/5 CD200+, and 0/2 EBER+. Rearrangements of MYC, BCL2, or BCL6 were identified by FISH in 0/3, 1/3, and 2/3 cases, respectively. WES demonstrated sequence variants in genes associated with both FL (CREBBP [60%], KMT2D [40%], and TNFRSF14 [40%]) and PMBL (JAK-STAT pathway genes [80%], B2M [20%], and CD58 [20%]). 2 of the mutations identified in the tFLs have previously been shown to result in JAK-STAT activation (STAT6 p.E372K [PNAS 2016;113:13015-20] and SOCS1 p.F101L [Oncogene 2002;21:4351-62] identified in 1/5 cases each). CNA showed gains/amplification of REL in 3/5 cases, gains/amplification of STAT6 in 2/5, gains of large sections of chromosome 16, including IL4R, in 2/5, and both deletions and gains of 11q in 1/5. See Figure demonstrating the 5 cases on the Y-axis and the chromosomes on the X-axis. Conclusions: The tFLs in this small series seem to represent PMBL-like DLBCLs, rather than classic PMBLs, and have a blended pattern of immunophenotypic and genomic features between FL/DLBCL and PMBL. Although the cases express some PMBL-associated markers (CD23 and MAL), there is less frequent staining for others (CD30, CD273/PDL2, and CD200). The cases harbor both FL-associated and PMBL-associated sequence variants, including 40% with mutations known to activate the JAK-STAT pathway. This frequency of mutations in JAK-STAT pathway genes is higher than that seen in typical FL/DLBCL, but perhaps lower than in classic PMBL (Blood 2019;134:802-13). PMBL also frequently has gains/amplifications of 9p24.1, which was not seen in our cohort. However, gains/amplification of REL/2p, which is seen in approximately 50% of PMBL, was identified in 60% of the tFLs. The 11q aberration identified in 1 case would be unusual for PMBL, and is instead more commonly associated with a subset of aggressive lymphomas with Burkitt-like features (Haematologica 2019;104:1822-9). Recently, lymphomas with similar blended features between DLBCL and PMBL, which were not arising in the setting of tFL, have been reported (Duns G, et al. Blood 2021). Our study extends the types of biological transformations, in addition to more classic DLBCL, that can be seen in FL. These tFLs with blended PMBL-DLBCL biology may have implications for therapeutic decision making including targeted therapies used in PMBL. Figure 1 Figure 1. Disclosures Rimsza: NanoString Technologies: Other: Fee-for-service contract. Steidl: Curis Inc.: Consultancy; Trillium Therapeutics: Research Funding; Bayer: Consultancy; Epizyme: Research Funding; Seattle Genetics: Consultancy; AbbVie: Consultancy; Bristol-Myers Squibb: Research Funding.

Introduction: Follicular lymphoma (FL) is an indolent disease that undergoes histological transformation (HT) to aggressive diffuse large B-cell lymphoma (DLBCL) in 8-15% of patients. FLs frequently share genetic features with DLBCL, especially those of the germinal center B-cell-like (GCB) cell-of-origin (COO) and the EZB/C3 genetic subgroup, and approximately 80% of transformed FL (tFL) are classified as GCB. Our current understanding of the genetics of FL and tFL is based on a variety of studies, most of which have sequenced tumors in small case numbers or using targeted approaches such that the potential role of non-coding mutations and aberrant somatic hypermutation (aSHM) in predicting HT have not previously been fully explored. Methods: Whole genome sequencing (WGS) data from 212 FL (including 24 from patients that subsequently underwent HT) and 241 de novo DLBCL were analyzed. Simple somatic mutations (SSMs) were called using an ensemble of somatic variant callers, while structural variants (SVs) were called with Manta and copy number variants (CNVs) with Battenberg and GISTIC. Fluorescence in situ hybridization with break-apart probes (BA-FISH) was used to identify MYC, BCL2, and BCL6 translocations, and with IGH /BCL2 dual-fusion probes (DF-FISH) for a subset of FLs. To compare the genetics of FL and DLBCL, 83 significantly mutated genes (SMGs) were identified with dNdS, MutSigCV, HotMaps, and OncoDriveFML, and non-silent mutations were tabulated for their presence in each genome. For 38 hypermutated regions, we used a region-specific threshold to binarize the data to aSHM/no aSHM. Recurrent missense mutations in FOXO1, MYD88L265P, CREBBP lysine acetyltransferase (KAT) domain, EZH2Y646, MEF2B, and STAT6 were tabulated separately from other mutations in these genes. Using only the FL tumors from patients with no evidence of subsequent transformation and all available de novo DLBCLs, we trained a random forest classifier to separate these two entities using this set of 129 features, including MYC and BCL6 translocations. To validate this classifier, we fit a linear model to the number of FL votes from each discovery case, utilizing the 65 features (including 19 aSHM features) that were adequately sequenced in a validation cohort of 127 tFL. Statistical tests were corrected for multiple comparisons where necessary. Results: This large cohort of FL and DLBCL genomes has enabled the curation of an extensive list of novel and established FL driver genes and the identification of distinguishing genetic features among SMGs and CNVs. Loci that are significantly enriched for mutations in FL vs. DLBCL include the CREBBP KAT domain (OR 11.5, P < 0.0001), RRAGC (OR 9.61, P < 0.001), and ATP6V1B2 (OR 11.17, P < 0.001). Deletions of ARID1A (OR 4.74, P < 0.1), PTEN (OR 3.65, P < 0.01), and TNFRSF14 (OR 3.31, P < 0.01) were among the CNVs significantly enriched in FL. Out of 156 FLs, 24 (15%) were negative for BCL2 translocations by BA-FISH, but 4 (17%) of these had BCL2 translocations detected from WGS data. All 4 of these cryptic events were confirmed using IGH /BCL2 DF-FISH. Using a threshold of 0.7, the linear model separated discovery FL cases into a more DLBCL-like subgroup, termed dFL (n = 107), and a genetically homogeneous subgroup enriched for the FL-associated features, which we describe as constrained FL (cFL, n = 105). This separation is supported by more mutations in dFL vs cFL across several aSHM loci, including the transcription start sites for BCL6, BCL7A, DTX1, and ZFP36L1 (Figure 1), consistent with reduced exposure to the germinal center reaction in cFL. Within the targeted capture validation cohort of tFL, 30 (24%) tumors were classified as cFL and 97 (76%) as dFL. The tFL cohort was significantly depleted for mutations in the CREBBP KAT domain (OR 0.59, P < 0.05), and were significantly less frequently classified as cFL (OR 0.30, P < 0.0001) compared to the discovery FLs. Conclusions: The distinction between cFL and dFL is strongly driven by CREBBP KAT domain mutations and different rates of aSHM genome wide. Given the known early clonal nature of CREBBP mutations in FL and its role in regulating germinal center cycling, we speculate that CREBBP KAT mutations may limit the exposure of FL to the dark zone, reducing the opportunity for aSHM and creating an evolutionary constraint that may limit the opportunity for HT. This classification may serve as a useful biomarker to identify FLs at higher risk of HT. Figure 1 Figure 1. Disclosures Coyle: Allakos, Inc.: Consultancy. Grande: Sage Bionetworks: Current Employment. Slack: Seagen: Consultancy, Honoraria. Steidl: Curis Inc.: Consultancy; Trillium Therapeutics: Research Funding; Epizyme: Research Funding; Bayer: Consultancy; Seattle Genetics: Consultancy; AbbVie: Consultancy; Bristol-Myers Squibb: Research Funding. Scott: Janssen: Consultancy, Research Funding; Abbvie: Consultancy; AstraZeneca: Consultancy; NanoString Technologies: Patents & Royalties: Patent describing measuring the proliferation signature in MCL using gene expression profiling.; Incyte: Consultancy; Rich/Genentech: Research Funding; Celgene: Consultancy; BC Cancer: Patents & Royalties: Patent describing assigning DLBCL COO by gene expression profiling--licensed to NanoString Technologies. Patent describing measuring the proliferation signature in MCL using gene expression profiling. . Morin: Epizyme: Patents & Royalties; Foundation for Burkitt Lymphoma Research: Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy.

Follicular lymphoma (FL) is an indolent lymphoma of mature B-cells but may transform to a more aggressive histology, most commonly diffuse large B cell lymphoma. Recurrent mutations associated with transformation have been identified; however, biological predictors to guide initial therapy have remained elusive. We hypothesized that clonal heterogeneity and patient-specific immune responses would contribute to variable clinical outcomes and that understanding the complexity of the entire tumor "ecosystem" would allow more individualized matching of patients with specific therapies. In prior ASH meetings, we presented preliminary analyses of B and T cell-focused phenotypic profiling of 155 newly diagnosed pre-treatment FL biopsy samples at single cell resolution by mass cytometry (CyTOF). These prior analyses unexpectedly revealed two distinct evolutionary trajectories which were independently reflected in both B and T cell compartments. One trajectory expectedly involved germinal center B cells (GCB); however, the other was more related to naïve/memory B-cells (NMB). Interestingly, cluster co-occurrence analysis suggested that the GCB and NMB trajectories were mutually exclusive of another and tended not to be found within the same tumor despite their high prevalences (χ 2 = 29.8, DF=1, p=4.8e-8; χ 2 test). Clustering analysis based on relative abundances of T cell subsets revealed 4 distinct immune patterns: Group 1 was characterized by naive T cells; Group 2 by T follicular helper (Tfh) cells; Group 3 by CD4+ regulatory T (Treg) and CD8 effector memory cells (CD8EM); and Group 4 by a diverse complement of naive, memory, and differentiated effector subsets. We report here further analyses, now incorporating DNA mutational and clinical outcome information. Tumors were parsed into 3 types based on the phenotype of the majority (>50%) of tumor cells present in the diagnostic biopsy: Type A tumors dominated by GCB cells (28% of samples), type B tumors dominated by NMB cells (18% of samples), and type nonA/nonB tumors dominated by neither GCB nor NMB cells (54% of samples). Type A tumors were significantly enriched for mutations in EZH2, TNFRSF14, and MEF2B, while no significant mutational associations were seen in type B and nonA/nonB tumors. Type B was significantly associated with increased risk of transformation, and when combined with a measure of intratumoral phenotypic diversity ("Entropy"), we found that type B tumors with high (above median) Entropy, representing 8.5% of all cases, exhibited a hazard ratio (HR) of 5.9 for transformation risk in comparison to all others combined (log-rank p We also investigated survival outcomes using a sub-cohort of 108 patients who had received bendamustine + rituximab (BR) as their primary therapy. Despite the association of type B tumors with transformation risk, patients with type nonA/nonB tumors exhibited the poorest outcomes as measured by disease-specific survival (DSS; 5yr survival 78% vs 98% for all others combined, log-rank p=0.0241). Combining type nonA/nonB with high Entropy defined 20% of patients with significantly shorter DSS (HR 5.3, log-rank p=0.0019). In multivariate analysis, type nonA/nonB and high risk FLIPI score were significant (p=0.038 and 0.035, respectively), while high Entropy trended with inferior DSS (HR 2.8, 95% CI 0.76-10; p=0.123). Taken together, these data support that CyTOF-defined phenotypic subtypes of FL and intratumoral phenotypic diversity identify clinically significant subgroups at initial diagnosis and compare favorably against FLIPI score in predicting both risk of transformation and inferior DSS. Figure 1 Figure 1. Disclosures Freeman: Incyte: Honoraria; Seattle Genetics: Honoraria; Sanofi: Honoraria, Speakers Bureau; Bristol Myers Squibb: Honoraria, Speakers Bureau; Amgen: Honoraria; Janssen: Honoraria, Speakers Bureau; Celgene: Honoraria; Teva: Research Funding; Abbvie: Honoraria; Roche: Research Funding. Sehn: Genmab: Consultancy; Novartis: Consultancy; Debiopharm: Consultancy. Savage: BMS: Consultancy, Honoraria, Other: Institutional clinical trial funding; Seattle Genetics: Consultancy, Honoraria; Astra-Zeneca: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Merck: Consultancy, Honoraria, Other: Institutional clinical trial funding; Takeda: Other: Institutional clinical trial funding; Roche: Research Funding; Servier: Consultancy, Honoraria; Beigene: Other: Institutional clinical trial funding; Genentech: Research Funding. Craig: Bayer: Consultancy. Scott: Abbvie: Consultancy; AstraZeneca: Consultancy; Incyte: Consultancy; Celgene: Consultancy; NanoString Technologies: Patents & Royalties: Patent describing measuring the proliferation signature in MCL using gene expression profiling.; BC Cancer: Patents & Royalties: Patent describing assigning DLBCL COO by gene expression profiling--licensed to NanoString Technologies. Patent describing measuring the proliferation signature in MCL using gene expression profiling. ; Rich/Genentech: Research Funding; Janssen: Consultancy, Research Funding. Steidl: Trillium Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; AbbVie: Consultancy; Seattle Genetics: Consultancy; Curis Inc.: Consultancy; Bayer: Consultancy; Epizyme: Research Funding.

Mutations in SKP1 and CUL1 (Zhang et. al. Oncol Lett 2018), which encode components of the SKP1-CUL1-F-BOX (SCF) ubiquitin E3-ligase complex, have previously been reported or characterized in AML. FBXO11, which encodes the substrate recognizing component, however, has not been studied in AML. We performed whole exome sequencing and RNA-seq on140 clinical AML samples and identified recurrent inactivating mutations in FBXO11. Of the components of the SCF FBXO11 complex, FBXO11 transcript expression is most significantly reduced in AML samples compared to normal. We show that loss of FBXO11 drives leukemogenesis through dysregulation of the novel target, LONP1, by reducing mitochondrial potential and promoting self-renewal. We found that UPS mutations co-occur with AML1-ETO (RUNX1-RUNX1T1) fusions and RAS mutations. Fbxo11 knockdown in mouse hematopoietic stem/progenitor cells (HSPC) cooperated with AML1-ETO to generate serially transplantable AML in mice. FBXO11 depletion in human cord-blood derived CD34+ cells (CD34+ CB), combined with AML1-ETO and a KRAS mutant, promoted stem cell maintenance and myeloid malignancy in a human xenotransplant model. Mass spectrometry analysis of FLAG-FBXO11 co-immunoprecipitating proteins in K562 cells identified mitochondrial protease, LONP1, as a top target. LONP1 protein expression did not vary with FBXO11 loss or overexpression, suggesting that LONP1 is not a degradation target of the SCF FBXO11complex. Knockdown of either FBXO11 or LONP1 resulted in myeloid bias in CD34+ CB in vitro, pointing to an activating role of FBXO11 on LONP1. Both FBXO11 and LONP1 depletion reduced mitochondrial membrane potential (MMP) in CD34+ CB and myeloid cell lines, aligning with the stemness phenotypes observed with FBXO11 depletion, as long-term hematopoietic stem cells (LT-HSCs) are characterized by low MMP (Mansell et. al. Cell Stem Cell 2021), and disruption of MMP promotes self-renewal in HSCs (Vannini et. al. Nat Commun 2016). As FBXO11 neddylates p53 to regulate transcription (Abida et. al. J. Biol. Chem 2007), we examined protein neddylation, and detected increased neddylation in immunoprecipitated LONP1 from FLAG-FBXO11-expressing K562 cells. As, neddylation regulates protein activation (Wu et. al. Nature 2005), our findings suggest that FBXO11 neddylation of LONP1 activates LONP1 to maintain mitochondrial function. Consequently, loss of FBXO11 function primes HSPC for self-renewal by reduction of MMP. To clarify the regulatory relationship between FBXO11 and LONP1, we performed RNA-seq on CD34+ CB cells expressing combinations of shRNAs targeting FBXO11 or LONP1, with overexpression of FLAG -FBXO11 or LONP1. Unsupervised clustering revealed that LONP1-overexpressing samples clustered with controls, suggesting that LONP1 requires modification by FBXO11 for functional effects. Using gene set enrichment analysis, we found that both FBXO11 and LONP1 depletion enriched for HSC and LSC (leukemic stem cell) gene sets. Knockdown of LONP1 reversed the effect of FLAG-FBXO11 overexpression, supporting a model of LONP1 being a downstream mediator of FBXO11 function. Both FBXO11 and LONP1 depletion enriched for a gene set composed of mitochondrial electron transport chain complex (ETC) genes, potentially reflecting a transcriptional response to loss of functional ETC activity, as suggested by accumulation of misfolded ETC proteins with knockdown of LONP1 (Ghosh et. al. Oncogene 2019). In this work, we demonstrate the leukemogenic effects of FBXO11 loss. We draw a novel connection between the UPS and the mitochondrial protease system with the identification of LONP1 as an FBXO11 target that regulates hematopoiesis. Disclosures No relevant conflicts of interest to declare.

Introduction: The recently developed DLBCL90 NanoString assay robustly distinguishes primary mediastinal large B-cell lymphoma (PMBCL) from diffuse large B-cell lymphoma (DLBCL), as well as cell-of-origin (COO) subtypes of DLBCL (ABC, GCB, unclassified) and cases with a Double-Hit (DHIT) signature (Ennishi D., JCO 2019). When this assay was applied to biopsies from 343 patients with de novo DLBCL uniformly treated with R-CHOP, nineteen of these cases had a molecular PMBCL signature (mPMBCL), despite the fact that they were diagnosed as DLBCL based on their morphology, immunophenotype and clinical features. Here, we aimed to comprehensively characterize the molecular and clinicopathologic features of these mPMBCL cases. Methods: Survival estimates were calculated using Kaplan-Meier analysis, using time to progression (TTP) and disease specific survival (DSS) as endpoints. We applied whole-exome sequencing, copy number analysis (SNP6.0) and RNAseq to identify somatic mutations, copy number aberrations and differentially expressed genes, respectively. FISH was applied to assess the presence of rearrangements affecting MYC, BCL2 and BCL6. We used data previously obtained within our centre from a PMBCL cohort (n=73) to compare mPMBCL with "bona fide" PMBCL (PMBCL) tumors (Mottok et al, Blood 2019). Results: Median age at diagnosis was significantly higher for mPMBCL compared to PMBCL (62 vs 37 years, p Comparison of the mutational landscape of mPMBCL to PMBCL demonstrated perturbations in the central hallmarks of PMBCL pathogenesis: JAK/STAT signaling, NF-ĸB pathway activation and immune evasion. Genomic aberrations affecting JAK-STAT signaling were shared between mPMBCL and PMBCL, with SNVs or indels affecting IL4R, STAT6 and SOCS1 found in 37%, 37%, and 89% of mPMBCL and 36%, 40% and 69% of PMBCL, respectively. Moreover, copy number analysis revealed JAK2 amplifications in 44% of mPMBCL (71% of PMBCL) and differential gene expression analysis showed increased levels of CD274 (PDL1), PDCD1LG2 (PDL2) and genes belonging to the JAK-STAT-signaling network in mPMBCL. In contrast, these genetic aberrations were rarely observed in a recent whole-exome sequencing study on 304 primary DLBCL tumors (Chapuy B., Nat.Med. 2018). Mutations were also observed in NF-ĸB pathways but the patterns of mutations were distinct between mPMBCL (BIRC3 and BTK) and PMBCL (NKBIE) suggesting convergent biology with alternative mechanisms of pathway dysregulation. Similarly, mPMBCL harbored different mutations (CD83) implicated in immune evasion compared with PMBCL (B2M). Finally, we compared the mutational landscape of mPMBCL with recently described genetically-defined subgroups of DLBCL. Interestingly, a large majority of mPMBCL harbored at least one of the mutations characteristic of "Cluster 4" (incl. CD83, HIST1H1E, SGK1), a subset of DLBCLs defined by Chapuy et al that predominantly includes GCB-DLBCLs. Conclusion: We have identified and characterized a subgroup of DLBCL that expresses the PMBCL gene expression signature. Similar to bona fide PMBCL, these tumors are characterized by genomic aberrations that affect JAK-STAT, NF-ĸB signaling and immune response. However, our data suggest that dysregulation of the latter two pathways is established through distinct evolutionary modes that are reflected in differential mutation patterns and anatomical and clinical presentations. Our findings provide potential novel therapeutic avenues for this subset of lymphoma. Disclosures Sarkozy: Takeda: Research Funding. Savage:BMS, Merck, Novartis, Verastem, Abbvie, Servier, and Seattle Genetics: Consultancy, Honoraria; Seattle Genetics, Inc.: Consultancy, Honoraria, Research Funding. Scott:Celgene: Consultancy; Roche/Genentech: Research Funding; 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; Juno Therapeutics: Consultancy; Tioma: Research Funding; Roche: Consultancy; Bayer: Consultancy; Seattle Genetics: Consultancy.

Introduction: Grey zone lymphoma (GZL), a B-cell lymphoma with features intermediate between large B-cell lymphoma (LBCL) and classical Hodgkin lymphoma (cHL), is a rare and poorly defined entity. To decipher its mutational landscape and discover new therapeutic targets, we performed exome sequencing of 31 GZL cases. Methods: GZL cases from the LYSA group (N=139) and BC Cancer (N=30) were centrally reviewed and classified as previously published (Sarkozy et al, Am J Surg Pathol 2019). Whole-exome sequencing was performed on 31 cases with available fresh frozen tissue, using laser micro-dissection (LMD, MMI technology) to enrich for tumor cells and obtain matching normal DNA from microenvironment cells. DNA was extracted (Agencourt® DNAdvance kit) and genomic libraries were constructed with the Ovation ultra-low kit (Nugen®). Exome capture was performed using Agilent SureSelectXT V6+UTR followed by paired-end sequencing (NextSeq®). Somatic nucleotide variants (SNVs) and indels were identified using VarScan, Strelka and Mutect. Parameters affecting the sensitivity and specificity of variant calling were optimized using 7 "gold standard" cases for which DNA from peripheral blood cells was additionally available. Possible oncogenic drivers were identified based on rate of recurrence, MutSigCV and literature review. Results: Among the 31 GZL cases, the median age was 41 y (14-83) with a sex ratio of 15M:16F; 21 cases had mediastinal involvement, including 15 within the thymic area; EBER in-situ hybridization (ISH) was positive in 8 cases. Seven (23%) cases were classified as group-0 (cHL morphology with 100% CD20 expression), 22 (71%) with an intermediate morphology as group-1 (N=9, cHL-like morphology) or group-2 (N=13, LBCL-like morphology) and 2 (6%) as group-3 (LBCL with 100% of CD30 expression). The mean coverage was 96X (42-203) for tumor samples. One case was excluded due to failure in the LMD process. Among the 30 cases, 6628 variants across 4826 genes were found, including 2903 coding mutations (325 indels and 2808 SNVs, mean of 104/sample, range: 15-678), 721 affecting the 5' UTR and 2774 the 3' UTR. A total of 152 genes were identified as being potential oncogenic drivers, with a mean of 11 mutated genes per case (range 2-36). The most recurrently mutated genes were SOCS1 (33%), B2M (23%), GNA13 (20%), LRRN3 (17%), and ZNF217, NCOR1, ITPKB, IRF2BP2, CSF2RB, and CSMD3 (13% each). The epigenetic SWI/SNF and transcription regulation pathway (including NCOR1/2, ARID1A, KMT2D, KMT2A) was affected in 73% of the cases, JAK/STAT in 70% and NF-kB in 19%. As assessed by CNVkit and GISTIC, the most recurrent gains/amplifications identified were in 9p24.1 (JAK2, CD274, PDCD2LG2; 69%) and 2p16.1 (REL, BCL11A; 62%), and losses in 11q14.3 (ATM; 48%) and 12q24.33 (NCOR2; 48%). Based on mutational signature analysis, individual base substitutions were linked to mutagenic processes, with the highest contributions associated with aging (29%) and defective DNA mismatch repair (27%); moreover, mutations attributable to AID/APOBEC activity (5%), were found to be significantly enriched in EBV- vs. EBV+ cases (p = 0.013). EBV+ cases had fewer total variants (mean 98 vs 258, p=0.08) and potential oncogenic variants (mean 7 vs 15, p=0.03) compared to EBV- cases. EBV+ cases also lacked mutations in the NF-kB pathway and MHC-class I components (B2M and HLA-B: 0% vs 43% in EBV-, p=0.06) but had mutations in STAT3, DHX58, ACTB and ATP13A4 (6/7 cases) not present in the 23 EBV- cases. LRRN3 and GNA13 mutations were significantly associated with thymic area involvement (40% vs 0%, p=0.01). Furthermore, fluorescence-ISH indicated that 20% (1/5) of EBV+ cases had a rearrangement in the CIITA locus (16p13.13) vs 53% (9/17) in EBV- cases. Patients with an intermediate morphology had more oncogenic variants than those in group 0 and 3 (mean of 15 vs 6 variants/case, p=0.01 affecting 12 vs 5 genes, p=0.004). Finally, NCOR1 (N=4) and NCOR2 (N=2) mutations were exclusively found in cases with intermediate morphology (23% vs 0% for those with group 0 or 3 morphology). Conclusion: These data suggest that GZL is a highly heterogenous disease harboring somatic driver events shared with PMBCL and HL. We also discovered novel gene mutations pointing to the importance of previously unrecognized pathways in the pathogenesis of GZL. The distinct mutational pattern in EBV+ GZL suggests divergent evolutionary trajectories. Disclosures Sarkozy: Takeda: Research Funding. Salles:Merck: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis, Servier, AbbVie, Karyopharm, Kite, MorphoSys: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Autolus: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Epizyme: Consultancy, Honoraria; BMS: Honoraria; Amgen: Honoraria, Other: Educational events; Roche, Janssen, Gilead, Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events. Savage:BMS, Merck, Novartis, Verastem, Abbvie, Servier, and Seattle Genetics: Consultancy, Honoraria; Seattle Genetics, Inc.: Consultancy, Honoraria, Research Funding. Scott:Celgene: Consultancy; Roche/Genentech: Research Funding; Janssen: Consultancy, Research Funding; NanoString: Patents & Royalties: Named inventor on a patent licensed to NanoSting [Institution], Research Funding. Steidl:Juno Therapeutics: Consultancy; Tioma: Research Funding; Roche: Consultancy; Bristol-Myers Squibb: Research Funding; Nanostring: Patents & Royalties: Filed patent on behalf of BC Cancer; Seattle Genetics: Consultancy; Bayer: Consultancy.

The Janus kinase-signal transducers and activators of transcription (JAK-STAT) pathway is an important and conserved pathway in lymphocytes which is activated by extracellular stimuli such as cytokines and growth factors. Aberrant activation of the JAK-STAT pathway is a hallmark of a variety of lymphomas which leads to increased proliferation/survival as well as immune evasion. Regarding the latter, it has been previously described that activation of the JAK-STAT signaling pathway can alter the secretome of lymphoma cells and the composition of the tumor microenvironment (TME). Specifically, our group reported PTPN1 loss-of-function as well as IL4R gain-of-function (p.I242N) mutations up-regulate the expression of the immune regulatory chemokine CCL17 through a STATs-dependent mechanism in primary mediastinal B cell lymphoma (PMBCL). Here, we assembled a cohort of 340 diffuse large B cell lymphoma (DLBCL) patients uniformly treated with R-CHOP to investigate JAK-STAT signaling mutations (targeted gene sequencing), copy number alteration (SNP arrays), gene expression (RNAseq) and TME composition (Cibersort, IHC). We confirmed the presence of mutations in SOCS1, STAT6 and 9p24 amplification with a frequency of 13.8%, 2.5%, 11.4%, respectively. Interestingly, we also identified the presence of somatic IL4R mutations in DLBCL, including the hotspot p.I242N mutation previously reported in PMBCL. Similarly to what was reported for other alterations in the JAK-STAT pathway, IL4R mutations were significantly enriched in GCB-DLBCL as compared to the ABC subtype, unclassified or double hit lymphomas with DLBCL morphology (p=0.045). Within the GCB group, patients carrying mutations in IL4R showed inferior disease-specific survival (p=0.029) and time to progression (p=0.023) after R-CHOP therapy. Mutational analysis revealed IL4R mutation being significantly concurrent together with mutations in ACTB, KLML6, MYC, STAT6, NLRC5, TNFAIP3 and mutually exclusive with EZH2 mutations (p In summary, our data suggest a common mechanism between PMBCL and DLBCL where aberrant JAK-STAT activation mediated by mutations in IL4R plays a significant role in altering chemokine expression profiles and TME changes. Disclosures Gascoyne: NanoString: Patents & Royalties: Named Inventor on a patent licensed to NanoString Technologies. Scott:Celgene: Consultancy, Honoraria; Roche: Research Funding; NanoString: Patents & Royalties: Named Inventor on a patent licensed to NanoString Technologies, Research Funding; Janssen: Research Funding. Steidl:Roche: Consultancy; Seattle Genetics: Consultancy; Bristol-Myers Squibb: Research Funding; Nanostring: Patents & Royalties: patent holding; Tioma: Research Funding; Juno Therapeutics: Consultancy.

Introduction: Among the tumor immune escape mechanisms described to date, alterations in the expression of major histocompatibility complex (MHC) molecules play a crucial role in the development of diffuse large B-cell lymphoma (DLBCL). Although the frequency of loss of MHC expression differs between ABC- and GCB-DLBCL cell of origin (COO) subtypes, distinct genetic alterations and molecular features that affect MHC expression and the composition of immune cells in the tumor microenvironment remain ill-defined. Here, we aimed to uncover the biologic and genomic basis underlying acquired loss of MHC expression. Method: We analyzed biopsies from 347 patients newly diagnosed with de novo DLBCL and uniformly treated with R-CHOP in British Columbia. We performed targeted resequencing, SNP6.0 array and RNAseq for genetic analyses. Immunohistochemical (IHC) staining of MHC-I and -II was performed on tissue microarrays (n=332). COO was assigned by the Lymph2Cx assay in 323 cases (183 GCB, 104 ABC and 36 unclassifiable). Immune cell composition was assessed by IHC, flow cytometry and gene expression profiling (GEP)-based deconvolution of cellular signatures. To experimentally confirm decreased MHC expression induced by EZH2 mutation, we measured surface MHC-I and -II expression on tumor B cells using EZH2Y641/BCL2 mouse model which was previously established (Beguelin et al, Cancer Cell 2013). We also treated human DLBCL cells harboring EZH2 mutation and wild type using EZH2 inhibitor (EPZ-6438), and evaluated their surface MHC-I and -II expression. Results: Loss of MHC-I and -II expression was observed in 43% and 28% of DLBCL cases, respectively. MHC-II loss of expression was significantly associated with the reduction of tumor-infiltrating lymphocytes (TILs), especially CD4 positive T-cells (FOXP3+ cells, PD-1+ cells, and CD4+ naïve and memory T-cells), and cytolytic activity (GZMB and PRF1 mRNA expression) in GCB-DLBCL (all; p We next performed GEP using RNAseq separately in each COO subtype. Interestingly, only four genes (HLA-DMA, DRA, DPA1 and CD74) were differentially expressed according to MHC-II expression (FDR Correlative genetic analysis revealed that, as expected, mutations of CIITA and RFXAP were detected more frequently in MHC-II-negative GCB-DLBCL (p=0.01 and 0.003, respectively). Strikingly, CD83 mutations, which elevate and stabilize MHC-II expression in centrocytes of the light zone (LZ), were significantly enriched in MHC-II positive GCB-DLBCL (p= 0.008), suggesting that these mutations affecting the antigen presentation machinery are selectively acquired in GCB-DLBCL tumors to further reduce and increase the surface MHC-II expression. Genetic analysis also highlighted that EZH2 mutations were most significantly enriched in MHC-II-negative as well as MHC-I-negative GCB-DLBCL cases (both, p Conclusion: Our findings provide important implications for understanding the cancer biology underlying acquired loss of MHC expression. The restoration of MHC expression by EZH2 inhibitors suggests a novel approach of epigenetically enhancing tumor recognition and eradication in combination with immune therapies. Disclosures Sehn: Abbvie: Consultancy, Honoraria; Roche/Genentech: Consultancy, Honoraria; Morphosys: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria; Lundbeck: Consultancy, Honoraria; TG Therapeutics: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Merck: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria. Connors:Roche Canada: Research Funding; Takeda: Research Funding; Merck: Research Funding; F Hoffmann-La Roche: Research Funding; Cephalon: Research Funding; Seattle Genetics: Honoraria, Research Funding; Amgen: Research Funding; Bayer Healthcare: Research Funding; Bristol Myers-Squibb: Research Funding; Lilly: Research Funding; NanoString Technologies: Patents & Royalties: Named Inventor on a patent licensed to NanoString Technologies, Research Funding; Janssen: Research Funding; Genentech: Research Funding. Gascoyne:NanoString: Patents & Royalties: Named Inventor on a patent licensed to NanoString Technologies. Scott:Roche: Research Funding; Janssen: Research Funding; NanoString: Patents & Royalties: Named Inventor on a patent licensed to NanoString Technologies, Research Funding; Celgene: Consultancy, Honoraria. Steidl:Juno Therapeutics: Consultancy; Roche: Consultancy; Seattle Genetics: Consultancy; Nanostring: Patents & Royalties: patent holding; Bristol-Myers Squibb: Research Funding; Tioma: Research Funding.

Abstract 265 In Hodgkin Lymphoma (HL), the Hodgkin Reed-Sternberg (HRS) cells are a minority of large mono- or multi-nucleated B cells characterized by a loss of B cell phenotype, constitutive NF-kB activation, a disturbed cell cycle and anti-apoptotic features. In this study we investigated the role of deregulated miRNA expression in the pathogenesis of HL. MiRNA in situ hybridization (ISH) in HL tissue was performed to determine expression of miRNAs previously reported to be highly abundant in HL cell lines, in HRS cells. Next we identified the miRNA-targetome of two HL cell lines by immunoprecipitation of RISC in untransfected and transfected cell lines. miRNA ISH confirmed expression of miR-17-5p, miR-24, miR-106a, miR-146a, miR-150, miR-155, miR-181b and miR-210 in HRS cells. Ago2-immunoprecipitation followed by microarray analysis of the co-immunoprecipitated mRNA revealed that the miRNA-targetome of HL comprises of about 2,500 genes. Inhibition of the anti-miR-17 seed family revealed that about 500 of these genes are regulated by miRNAs of the miR-17 seed family. Gene ontology (GO) analysis for the total miRNA-targetome of HL showed a significant enrichment of genes involved in the regulation of cell cycle, apoptosis, immune system development and NF-kB cascade. The miRNA-targetome of HL contained several genes known to be mutated in HRS cells, including A20, FAS, NFKB1A, NFKB1E, PERP and SOCS1. Also, using previously reported gene expression data, we defined a set of genes downregulated in HL cell lines (L428 and L1236) compared to germinal center B cells (GCB) and compared them to the miRNA-targetome of the same cell lines. This resulted in the identification of 149 genes in L428 and 183 genes in L1236 that were subjected to miRNA mediated repression. Unexpectedly, only a few of all the reported inactivated genes in HRS cells that might contribute to loss of B cell phenotype (MYBL1 and CXCR4) were found to be regulated by miRNAs in HL. In conclusion, we confirmed the expression of miRNAs in the HRS cells of HL tissue and identified miRNA repressed genes in HL. Our data indicated that aberrant miRNA expression contributes to the deregulation of apoptosis, cell cycle, and NF-kB pathways but not loss of B cell phenotype in HL. Disclosures: No relevant conflicts of interest to declare.

MiRNAs are small regulatory RNAs which control gene expression at the post-transcriptional level. Tumor cells of Hodgkin lymphoma (HL), the so-called Hodgkin Reed-Sternberg (HRS) cells, originate from defective germinal center B cells. HRS cells are characterized by their loss of B cell phenotype, large multi-nucleated cell size, a disturbed cell cycle and resistance to undergo apoptosis. The aim of our study is to investigate the role of deregulated miRNA expression to the pathogenesis of HL. To identify genes which are regulated by miRNAs in a high throughput manner, an approach called Ribonucleoprotein ImmunoPrecipitation – microarray (RIP-CHIP) was applied. As a first step, the AGO2 protein, which is part of the RISC complex, is immunoprecipitated (IP) with an AGO2 specific antibody. RNA isolation of the IP fraction followed by microarray analysis thus leads to the identification of miRNA targets from the whole transcriptome. With this approach, 1255 genes were found to be commonly regulated by miRNAs in both L1236 and L428 HL cell lines. Genes known to be absent or down regulated in HRS cells, like CDKN1A, CDKN1B, and PRDM1, were included in this gene list. Gene ontology analysis of these candidate miRNA target genes using Database for Annotation, Visualization and Integrated Discovery (DAVID) revealed a significant enrichment in KEGG pathways termed p53 signaling pathway and cell cycle. TargetScan prediction and seed sequence search at the 3′UTRs of these genes both indicated that about half of these genes were targets of the highly abundant miRNAs found in Hodgkin lymphoma cell lines. 10 randomly selected target genes were analyzed using luciferase reporter assays. For all genes, targeting by the predicted miRNA was confirmed using specific antisense Locked Nucleic Acids (LNA) inhibitors. In conclusion, we demonstrated an approach for large scale identification of endogenous miRNA targets without prior manipulation of the cells. HL specific target genes that may contribute to the characteristic phenotype of HRS cells and to the malignant transformation of germinal center B cells were identified.