7063 Background: Genetic subtypes of diffuse large B-cell lymphoma (DLBCL) capture biological differences between tumors that influence the response to immunochemotherapy (Schmitz et al., NEJM 2018). However, nearly 40% of DLBCL cases remain unclassified. The addition of gene expression signatures can accelerate classification and inform therapeutic intervention. Methods: We generated single-cell RNA sequencing of 103 DLBCL patient biopsies from Weill Cornell Medicine, New York Presbyterian Hospital, and the National Institutes of Health. We also utilized bulk genomic data from a discovery cohort (n=311, Ennishi et al., J Clin Oncol 2019) and a validation cohort (n=574, Schmitz et al., NEJM 2018). Results: Single cell sequencing allowed us to isolate the malignant B cells and develop genetic subtype signatures. The MCD signature was associated with poor overall survival (p<10 -6 ), as was the BN2 signature within ABC tumors (p<10 -3 ). When applied to unclassified tumors, the subtype signatures identified characteristic genetic alterations including SLC1A5 mutations in MCD (p<10 -5 ), UBE2A mutations in BN2 (p<10 -13 ), C10orf12 truncations and copy number loss in EZB (p<10 -6 ), and SGK1 mutations in ST2 (p<10 -7 ). Moreover, we discovered that most DLBCL tumors (80%) contained two or more genetic subclones (median 2, range 1-5) based on DNA copy number differences. The genetic subclones had distinct phenotypes based on expression of six recurrent gene expression meta-signatures, herein termed themes. The germinal center (GC) B cell, memory B cell, plasma cell, and pan-B cell themes reflect B cell differentiation whereas two other themes – cell cycle and cell growth – reflect proliferative and metabolic states that are independent of the differentiation states. Surprisingly, 23% of DLBCL (24/103) harbored genetic subclones expressing B cell differentiation themes that distinguished them from other malignant cells in the same tumor. The GC B cell theme was associated with a favorable response to R-CHOP chemotherapy (p<0.02), as expected, while the cell growth theme (but not the cell cycle theme) was associated with adverse survival (p<0.02). Conclusions: Our study revealed that genetic subtypes have distinct gene expression signatures. We further demonstrated a role for tumor subclones in generating intra-tumoral biological diversity. We developed signatures of inter and intra-tumoral heterogeneity that are associated with overall survival.

Genetic and gene expression subtypes of diffuse large B cell lymphoma (DLBCL) have been defined using bulk tumor analysis. To explore their biology, we derived single-cell RNA and ATAC sequencing data from 103 DLBCL biopsies and identified malignant B cells by their non-diploid DNA copy number profiles. Using malignant B cell gene expression, we developed and validated signatures of each DLBCL genetic subtype, revealing their distinctive characters. Most biopsies had genetic subclones, defined by distinct patterns of aneuploidy, that were distinguished by expression of biological themes reflecting B cell differentiation state, cell proliferation, and cell growth. This analysis revealed REL amplification as a mechanism to block terminal memory B cell differentiation. The genetic subtype signatures and biological themes varied independently, had distinctive transcription factor networks, and were associated with survival following chemotherapy. This single-cell resource illuminates intra- and inter-tumoral biological variation, facilitating studies of DLBCL pathogenesis and therapeutic response.

Anaplastic large cell lymphomas (ALCLs) are CD30+ T-cell lymphomas that share pathologic features but differ in presentation, outcome, and genetics. Current classification incorporates clinical presentation and ALK status, but inadequately addresses molecular heterogeneity and therapeutic vulnerabilities. We studied 689 ALCLs in the Lymphoma/Leukemia Molecular Profiling Project and performed expert consensus review, genetic subtyping (ALK, DUSP22, TP63, and triple-negative), and immunohistochemistry for phospho-STAT3Tyr705. RNAseq with unsupervised gene expression profiling in a sub-cohort (N=393) identified two main molecular types of ALCL that could be predicted with 91% accuracy based on the presence (Type I) or absence (Type II) of phospho-STAT3Y705 expression (P<0.0001). Type I ALCLs included ALK+ ALCL and a subset of triple-negative ALCLs (TN-I); Type II ALCLs included tumors with DUSP22 and/or TP63 rearrangements and the remaining triple-negative ALCLs (TN-II). Type I ALCLs were enriched for JAK-STAT3 (FDR<0.0001), whereas Type II ALCLs were enriched for non-tyrosine kinase pathways, particularly epigenetic regulators such as EZH2 (FDR<0.0001). EZH2 and H3K27me3 were overexpressed by immunohistochemistry (P<0.0001). Prognosis in systemic ALCL was favorable for DUSP22-rearranged ALCL (5-year OS, 95%; N=49) and ALK+ ALCL (88%; N=101), intermediate for triple-negative ALCL (TN-I, 52% and TN-II, 37%; N=92), and poor for TP63-rearranged ALCL (0%; P<0.0001; N=15). We introduce an integrated molecular classification that preserves currently diagnosed ALCL entities but identifies four molecularly distinct ALK− ALCL subtypes (DUSP22-rearranged, TP63-rearranged, TN-I, and TN-II). This classification can be easily implemented on paraffin tissue in routine practice or clinical trials and stratifies ALCL into diagnostically, prognostically, biologically, and potentially therapeutically relevant subtypes.

Abstract Diffuse large B-cell lymphoma (DLBCL) is a biologically heterogeneous disease. Two genomic classification systems, LymphGen and DLBclass, are capable of reproducibly classifying single tumors into subtypes with prognostic relevance in the context of standard-of-care R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) chemoimmunotherapy. Preliminary data from subgroup analyses of clinical trials suggest that the distinct biological features are targetable with drugs that exploit subtype-specific vulnerabilities, and large clinical trials are being designed to test this hypothesis. Although whole-exome sequencing (WES) remains the gold standard for each of these classification systems, smaller targeted sequencing panels reduce costs associated with sequencing, data storage, and processing. Here, we describe the design and validation of a targeted sequencing panel (LySeqST) that captures the genomic features required specifically for LymphGen classification. We perform in silico theoretical and real-world validation vs WES data and demonstrate that LySeqST can be used to accurately classify DLBCL tumors using both LymphGen and DLBclass. In an unselected population-based cohort, we determine the real-world proportions and validate the prognostic relevance of LymphGen subtypes, confirming that only tumors expressing the dark zone gene expression signature are consistently associated with inferior outcomes. Our results support the use of LySeqST for accurate genomic classification of DLBCL.

Imprinted genes are epigenetically regulated in normal tissues to follow monoallelic expression according to the parent of origin of each allele. Some of these patterns are dysregulated in cancer. We developed a novel computational multi-omic pipeline to evaluate monoallelic and biallelic expression patterns based on matched RNA-seq expression data, whole-exome sequencing information, and copy number data. We analyzed allelic expression of the entire genes, individual isoforms, and each exon of 59,283 autosomal protein-coding and ncRNA genes, with a focus on 94 genes previously reported to be imprinted. We analyzed 108 cell lines from 9 different tumor histologies using molecular data from the DepMap Portal for the Cancer Cell Line Encyclopedia. Allelic expression patterns of imprinted genes and isoforms in tumor cells were variable. We also identified additional genes and isoforms with predominantly monoallelic expression due to a variety of potential mechanisms. We provide a novel public dataset of transcriptome-wide allelic expression patterns in cell lines from diverse tumor categories, which can serve as a resource for future cancer studies. We examined associations of in vitro cell line response to antitumor agents and repurposed drugs with allelic patterns and overall levels of isoform expression of imprinted genes and of additional genes with predominantly monoallelic expression. Drug response was associated with isoform expression patterns of multiple imprinted genes including CPA4, DGCR6, DNMT1, GNAS, GRB10, H19, NAA60, OSBPL5, PHACTR2, and ZFAT, predominantly monoallelically expressed MAP2K5 and BCLAF1, and additional predominantly monoallelically expressed genes. Multiple associations may be related to mechanisms of drug activity, including associations between the response to the DNA damaging agents and allelic expression of ZFAT, CDC27, and BCLAF1 isoforms, and the response to inhibitors of multiple signaling pathways with expression patterns of GNAS isoforms. Tumor cells have a range of monoallelic and biallelic expression patterns in both imprinted and non-imprinted genes and are likely affected by the complex interplay among changes in allelic expression, sequence variants, copy number changes, and expression changes of biologically important genes. Multiple isoform-specific patterns of allelic expression were associated with drug response, indicating complex mechanisms of cancer chemoresistance.

ABSTRACT:Although follicular lymphoma (FL) typically follows an indolent course, patients with FL who experience early events, such as transformation or progression, have increased risk of death related to lymphoma. The FL24Cx is an algorithm based on a 45-target gene expression profiling (GEP) assay, which was developed and trained using 265 formalin-fixed, paraffin-embedded tissue samples on a reliable platform to predict, at the time of diagnosis, whether a patient will experience an event within 24 months. The modeling also confirmed and relied upon previously reported synergy between immune response (IR) gene expression signatures IR1 and IR2. Once locked, the 5-factor logistic regression FL24Cx model was independently validated in a retrospectively assessed cohort of 232 patients from 2 immunochemotherapy-treated arms of SWOG Cancer Research Network S0016 phase 3 clinical trial, in which it assigned 169 patients to the low-risk group with 29 events before 24 months (17.2%) and 63 patients to the high-risk group with 24 events before 24 months (38.1%). The relative risk of an event within 24 months after registration among patients who were classified into the high-risk group relative to patients who were classified into the low-risk group was 2.2 (95% confidence interval, 1.41 to 3.51). An up-front GEP biomarker, such as the FL24Cx, rigorously validated in a clinical laboratory and with a clinically relevant turnaround time, could identify and steer enrollment of patients at high risk for early events in clinical trials, thus enabling timely interpretation of such trials and increasing the pace of innovation.

Abstract: Molecular characterization of high-grade B-cell lymphoma, not otherwise specified (HGBCL-NOS), is hindered by its rarity, evolving definition, and poor diagnostic reproducibility. To address this challenge, we analyzed 92 HGBCL-NOS tumors collected across Lymphoma/Leukemia Molecular Profiling Project sites. Leveraging comparison cohorts of diffuse large B-cell lymphoma, NOS (DLBCL-NOS) and Burkitt lymphoma (BL), and molecular frameworks described in these entities, our analysis revealed a heterogenous molecular landscape, reminiscent of DLBCL-NOS but with an enrichment of BL features. By cell-of-origin classification, 59% were germinal center B-cell–like (GCB), and 25% were activated B-cell–like (ABC). LymphGen, a genetic classifier for DLBCL-NOS, assigned a genetic subtype to 34% of HGBCL-NOS. Although classification rate was lower than in DLBCL-NOS (66%), assigned subtypes spanned the spectrum of LymphGen classes, including 31% of ABCs classified as MCD. Features differentiating HGBCL-NOS from DLBCL-NOS included MYC rearrangement (47% vs 6%); dark zone signature (DZsig) expression (45% vs 7%); and more frequent mutation of ID3, MYC, CCND3, and TP53, all common to BL. A genetic classifier that differentiates DLBCL-NOS from BL classified 53% of DZsig+ tumors as BL-like, and those classified as DLBCL-like were frequently BCL2-rearranged. Among DZsig− GCB tumors, 95% were DLBCL-like. Centralized pathology review reclassified almost half of tumors as DLBCL-NOS but did not identify a more homogenous HGBCL-NOS population, with no difference in features between confirmed and reclassified tumors. In conclusion, molecular testing enables a subset of HGBCL-NOS to be assigned to established categories. Based on rarity and diagnostic challenges, broader inclusion of HGBCL-NOS should be considered in biomarker-driven DLBCL trials.

Background: Large B-cell lymphoma (LBCL) is characterized by genetic heterogeneity that confers a differential response to therapy. Pre-clinical models and clinical studies of BTK inhibitors (BTKi) in relapsed LBCL suggest preferential activity in ABC DLBCL (Wilson et al. Nat Med 2015). Further, ibrutinib with R-CHOP as frontline therapy is highly active in MCD and N1 genetic subtypes (Wilson et al. Cancer Cell 2021). Acalabrutinib (acala) is a BTKi with activity in LBCL but the full spectrum of untreated tumors that are BTKi-responsive remains unresolved. We designed a response-adapted study of acala as a window prior to frontline LBCL chemotherapy to investigate the molecular profile of BTKi-responsive tumors [NCT04002947]. Methods: Untreated LBCL (including transformed) pts were eligible if age ≥18, ≥stage II, PS ≤2, and adequate organ function. Pts with PMBL, unmeasurable lesions, or CNS disease were excluded. Pts first received acala 100mg twice daily x 14d in a window. All pts then received DA-EPOCH-R or R-CHOP; pts with ≥25% reduction by CT after the window continued acala 100mg BID on D1-10 of each cycle. Tumors were analyzed and molecularly classified by COO, LymphGen, and DZ signature. PET scans were analyzed by 2 radiologists blinded to outcomes. Plasma collected in Streck tubes at baseline, end of C2, at EOT, and during surveillance was analyzed by PhasED-Seq. The primary endpoint was the response (≥25%) rate of acala within LBCL subtypes. Secondary endpoints included safety and PFS/OS within LBCL subtypes. Results: Of 110 pts screened, 99 enrolled and initiated acala. Median age was 60 (range 26-85) including 25% ≥70y. 60% were male and racial/ethnic groups included White (49%), Black (22%), Hispanic (17%), Asian (10%), and Native American (1%). 47% had IPI score ≥3 and 4% pts had HIV. Pathologic subtypes included 45 (45%) non-GCB DLBCL, 44 (44%) GCB DLBCL, 7 (7%) HGBL with MYC and BCL2, and 3 (3%) T-cell/histiocyte-rich LBCL. Eleven (11%) pts had transformed lymphoma. 98 pts were evaluable for acala response: 49 (50%) pts responded and 49 (50%) had no response. In non-responding pts, 47 (96%) received DA-EPOCH-R and 2 (4%) received R-CHOP. In responding pts, 27 (55%) received R-CHOP + acala while 22 (45%) received DA-EPOCH-R + acala. Acala responses occurred across pathologic subtypes including 20 (43%) GCB DLBCL, 8 (53%) ABC DLBCL, and 5 (83%) unclassified (UC). Both evaluable pts with THRLBCL had dramatic responses to acala. Of 52 pts with GCB/UC DLBCL, 22 (50%) with DZsig- tumors responded versus 2 (25%) with DZsig+. Acala showed responses in all LymphGen subtypes including 7 (100%) MCD/N1, 3 (60%) ST2, 9 (60%) EZB, 1 (50%) A53, 2 (33%) EZB-MYC, 6 (33%) BN2, and 15 (54%) Other. The toxicity of acala + R-chemo was mostly hematologic: G3/G4 neutropenia was seen in 8%/63% cycles of DA-EPOCH-R + acala and 7%/16% of cycles of R-CHOP + acala. G3/G4 thrombocytopenia was seen in 24%/17% of cycles of DA-EPOCH-R + acala and 7%/3% cycles of R-CHOP + acala. ≥G3 non-hematologic toxicities with acala + R-chemo included infection (22%), fatigue (6%), and hypotension (6%). No opportunistic infections occurred and 2 (4%) pts who received acala + R-chemo had atrial fibrillation. After a median follow-up of 39 months, the 2-year PFS/OS of all pts was 84.8% (76-91) and 87.8% (79-93), respectively. No survival difference was observed between acala responders and non-responders with 2-year PFS of 89.1% (76-95) vs 82.7% (68-91)(p=0.62) and 2-year OS of 90.7% (77-96) vs 86.8% (73-94)(p=0.59). By COO, the 2-yr PFS for GCB (N=46) was 93.3% (81-98), ABC (N=15) was 86.2% (55-96), and UC (N=7) was 83.3% (27-98)(p=0.29). Interestingly, pts with GCB tumors that were BTK-responsive had a 2-year PFS of 100% compared to 88.1% (68-96) in pts with GCB tumors that were BTK-resistant (p=0.12). Differences in the tumor microenvironment were not observed using deconvolution approaches, but in vitro experiments identified GCB models that showed decreased NF-kB expression after acala treatment. 2-year PFS for pts with a negative vs positive EOT PET scan was 92% (82-97) compared to 68% (44-83)(p=0.02). Conclusions: Acala was universally active in MCD/N1 but also had clinical activity across COO and LymphGen genetic subtypes; In vitro experiments suggested a cell intrinsic survival role for BTK in GCB DLBCL. The toxicity profile of acala + R-chemo was safe in pts of all ages. Prognostic utility of interim and EOT MRD will be presented.

Introduction: Diffuse large B-cell lymphoma (DLBCL) is stratified into genetic subtypes (MCD, BN2, A53, N1, EZB, ST2) that differ in their gene expression profiles, oncogenic mechanisms, and response to therapy. Using paired single cell RNA (scRNA) and ATAC (scATAC) sequencing in DLBCL tumors, we previously identified gene expression themes reflecting B cell differentiation, cell growth, and cell cycle that distinguished intratumoral genetic subclones (Wang B, ASH, 2024). Here, we present a global analysis of transcription factor (TF) binding and activity in normal B cells and DLBCL tumors that revealed epigenetic heterogeneity among the DLBCL genetic subtypes, which underpins their divergent therapeutic responses. Methods: Paired scRNA and scATAC sequencing was performed on 102 DLBCL cases (504,444 cells) and 3 tonsils (12,227 cells). Gene expression and genetic subtypes were determined from matched bulk samples by RNA and whole exome sequencing. Computational analysis was performed using R/python and custom bioinformatic pipelines. Results: By linking TF activators (+/+) and repressors (-/+) to target gene expression using SCENIC+ (Bravo Gonzalez-Blas C, Nat Methods, 2023), we identified gene regulatory networks (GRNs) composed of enhancer-driven Regulons (eRegulons). In tonsillar B cell subpopulations, we identified 173 eRegulons that linked TF binding to 9,456 genomic regions and 3,535 target genes. A subset of these eRegulons were differentially active (p<0.05) in germinal center (GC) B cells (FOXO1, MEF2B, EBF1, PAX5, TCF3), plasma cells (PC; IRF4, XBP1, PRDM1) and memory B cells (KLF2, STAT1, ETV6). Importantly, cell lineage analysis traced the activity of these eRegulons along 3 differentiation trajectories stemming from naïve B cells towards either GC dark zone, PC, or memory B cells. Next, we used TF binding to define the epigenetic landscape of the DLBCL genetic subtypes, which could be distinguished from each other using subtype-specific gene expression signatures. Chromatin binding by TFs that regulate PC differentiation (IRF4, POU2F2, TCF4) correlated with the MCD, BN2 and A53 gene expression signatures as well as with gene expression themes reflecting PC differentiation, cell cycle, and cell growth. Binding by another group of TFs (FOXO1, MYBL1, STAT6, PAX5) was associated with the EZB signature and the GC B cell gene expression theme. Binding by BCL6 was anticorrelated with signatures of the N1 subtype and memory differentiation, suggesting that BCL6 antagonizes memory B cell differentiation and the generation of N1 DLBCL. To define GRNs in DLBCL genetic subtypes and genetic subclones, we used SCENIC+ to infer 289 eRegulons, comprised of 12,016 TF binding regions and 4,723 target genes. By integrating the eRegulon RNA and ATAC scores using multiomics factor analysis (Argelaguet R, Genome Biol, 2020), we identified major axes of variation that discriminated both DLBCL subtypes and normal B cell populations. The EZB and ST2 subtypes were significantly associated (p<0.05) with eRegulons that typify normal GC B cells (MEF2B, MEF2C, IRF8, FOXO1). Within these subtypes, subclones with REL amplification had significantly greater activity of a REL +/+ eRegulon than those with wild type REL (p<0.001). The MCD, A53 and BN2 subtypes were enriched (p<0.05) for the IRF4 +/+ eRegulon while MCD was additionally associated (p<0.05) with BATF, SPIB, XBP1 and PRDM1 eRegulons. A TBL1XR1 –/+ eRegulon was significantly associated with the N1 subtype (p<0.001), which is notable given that TBL1XR1 is a tumor suppressor that is frequently inactivated in N1. The subtype-associated eRegulons were also differentially active in normal B cell populations, with several MCD eRegulons active in PCs, N1 eRegulons active in memory B cells, and EZB eRegulons active in GC B cells. Accordingly, eRegulon scores correlated with the B cell differentiation themes across DLBCL subclones. Conclusions: By paired scRNA and scATAC sequencing, we identified GRNs present in normal and malignant B cells that highlight transcriptional states of DLBCL genetic subtypes which vary along three principal differentiation axes – GC B cell, memory B cell and PC. Our analysis illuminates the biological heterogeneity of DLBCL molecular subtypes and offers rationale targets for future therapeutic development.

Abstract Malignant cells undergo a broad array of epigenetic changes, including changes in imprinting patterns. In normal cells, imprinted genes have parent of origin-specific monoallelic expression, which is controlled via epigenetic mechanisms. Imprinted gene loci are often complex and frequently include multiple isoforms, which have different individual patterns of parent-of-origin monoallelic or biallelic expression in the normal tissues. Many imprinted genes promote cell proliferation and body growth, and their expression is important during embryonic and postnatal development. Dysregulation of imprinting in tumors has been suggested to contribute to growth and proliferation of cancer cells. Previously we reported that chemotherapy responses of cancer cell lines from a variety of tumors and of patient-derived acute myeloid leukemia samples were associated with copy number, expression, or DNA methylation of selected imprinted genes. In the current project, we examined allele-specific patterns of expression (monoallelic vs. biallelic) of imprinted genes and isoforms in tumors and studied their potential effect on response of cancer cells to drug treatment. We analyzed expression patterns at the whole gene, isoform, and exon levels of 59,283 autosomal protein-coding genes and ncRNA genes, with a special focus on 94 imprinted genes and their isoforms. We developed a computational pipeline to evaluate monoallelic and biallelic expression patterns of each gene in cancer cell lines and in tumor samples based on available matched RNA-seq expression data, whole exome sequencing information, and copy number data. Our initial analysis included 108 cell lines from the Cancer Cell Line Encyclopedia (CCLE), which had been derived from 9 pediatric and adult tumor histologies. We observed variation of allelic expression patterns of imprinted genes and their isoforms in tumor cell lines, including differences across and within cancer histologies. We also observed predominantly monoallelic expression of multiple additional genes. Some of them (PRIM2, BCLAF1, MAP2K3, and SEC22B) had been previously reported as potentially imprinted. Monoallelic expression of other genes identified in our analysis (e.g., GRK2, CBX4, and additional genes) was likely caused by molecular mechanisms other than imprinting. Allelic expression patterns and overall expression levels of isoforms of multiple imprinted and non-imprinted monoallelically expressed genes (e.g., CPA4, MAP2K3, and other genes) were associated with in vitro drug response. We also report our ongoing validation of allelic expression patterns of imprinted and non-imprinted genes, isoforms, and exons in primary bladder and breast tumors and in matched solid normal tissue samples using patient data from the Cancer Genome Atlas (TCGA). These results provide new knowledge about epigenetic dysregulation in cancer. Citation Format: Julia Krushkal, Travis L. Jensen, George Wright, Yingdong Zhao. Multi-omic analysis of allelic expression patterns of imprinted and non-imprinted genes in cancer and their association with drug response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 862.

ABSTRACT:Rearrangements that place the oncogenes MYC, BCL2, or BCL6 adjacent to superenhancers are common in mature B-cell lymphomas. Lymphomas with diffuse large B-cell lymphoma (DLBCL) or high-grade morphology with both MYC and BCL2 rearrangements are classified as high-grade B-cell lymphoma with MYC and BCL2 rearrangements ("double hit"; HGBCL-DH-BCL2) and are associated with aggressive disease and poor outcomes. Although it is established that MYC rearrangements involving immunoglobulin (IG) loci are associated with inferior outcomes relative to those involving other non-IG superenhancers, the frequency of and mechanisms driving IG vs non-IG MYC rearrangements have not been elucidated. Here, we used custom targeted capture and/or whole-genome sequencing to characterize oncogene rearrangements across 883 mature B-cell lymphomas including Burkitt lymphoma, follicular lymphoma, DLBCL, and HGBCL-DH-BCL2 tumors. We demonstrate that, although BCL2 rearrangement topology is consistent across entities, HGBCL-DH-BCL2 have distinct MYC rearrangement architecture relative to tumors with single MYC rearrangements or with both MYC and BCL6 rearrangements (HGBCL-DH-BCL6), including both a higher frequency of non-IG rearrangements and different architecture of MYC::IGH rearrangements. The distinct MYC rearrangement patterns in HGBCL-DH-BCL2 occur on the background of high levels of somatic hypermutation across MYC partner loci in HGBCL-DH-BCL2, creating more opportunity to form these rearrangements. Furthermore, because 1 IGH allele is already disrupted by the existing BCL2 rearrangement, the MYC rearrangement architecture in HGBCL-DH-BCL2 likely reflects selective pressure to preserve both BCL2 and B-cell receptor expression. These data provide new mechanistic explanations for the distinct patterns of MYC rearrangements observed across different lymphoma entities.

Purpose/Objective(s) Diffuse large B cell lymphoma (DLBCL) is the most common form of non-Hodgkin's lymphoma. Patients who receive standard of care treatment have variable responses and up to 40% relapse. Not much is known regarding differences within tumors, or intratumoral heterogeneity. Thus, our question is, what are the genotypes and phenotypes of DLBCL subclones? We hypothesize DLBCL tumors contain genetic subclones with phenotypic variation that reflects axes of B cell development. The aim is to determine the implication of tumor subclones in disease pathogenesis. Materials/Methods This study analyzed 101 DLBCL cases with paired single nuclei RNA (snRNA) and single nuclei ATAC (snATAC) sequencing, bulk whole exome and RNA sequencing, flow cytometry, and immunohistochemistry. The majority (75%) of tumors were treatment naive. Seurat 4.2.0 was used to process snRNA data. Genetic subclones were identified by snRNA-based copy number. ArchR was 1.0.3 was utilized for snATAC. Results The majority (85%) of tumors contained genetic subclones (mean 2, range 1-6). We identified six clusters of gene expression signatures, or themes, that characterized subclone diversity. Three themes (memory, plasma cell, and germinal center) recapitulated B cells blocked in differentiation and accounted for most of the heterogeneity between subclones (F test p = 6E-5). Two additional themes (cell cycle, metabolic) represented overall sample activity. Next, we utilized an independent discovery dataset (n = 560) to identify genetic alterations associated with each theme. Notably, we observed REL amplification is negatively associated with expression of the memory B cell theme in the discovery dataset (t test, p = 1E-11) and validated this in the single cell subclones (t test, p = 0.03). REL amplification is a highly recurrent alteration in the germinal center B cell subtype (GCB) DLBCL. In cell line models, we showed REL amplification restricted B cells to the germinal center and prevented memory B cell differentiation, thus driving cells to a malignant GCB phenotype. Conclusion This study is a comprehensive characterization of intratumoral heterogeneity. We identified genetic alterations that drive tumor subclones towards specific malignant phenotypes. This work will also provide a single cell resource to the DLBCL community.

Purpose: Polatuzumab Vedotin (Pola-V) is an antibody-drug conjugate directed to the B cell surface antigen CD79B. When combined with conventional immunochemotherapy, Pola-V improves outcomes in DLBCL overall; however, there is noted heterogeneity in response to Pola-V, with germinal center b-cell (GCB) DLBCL showing no added benefit to the addition of Pola-V compared to standard immunochemotherapy. We aimed to identify molecular determinants of sensitivity or resistance to Pola-V. We hypothesized that these might lead us to innovative strategies to improve on-target tumor killing by Pola-V, or to find novel biomarkers that predict drug resistance. Methods: We employed combined drug-sensitization and CD79B-sorted CRISPR-Cas9 screening to identify molecular determinants of sensitivity to CD79B-directed, tumor killing by Pola-V in 9 cell lines representing different molecular subtypes of DLBCL. Results: Our results reveal the striking impact of epitope glycosylation, specifically a2,6 sialylation, on the binding of Pola-V to CD79B and thereby its ability to kill tumor cells. Specifically, we identify the exact glycosylated residues on CD79A and CD79B which create a sialylated glycan shield around the Pola-V binding site, precluding binding to its target. We show how genetic, pharmacological and enzymatic approaches that remove terminal sialic acid residues from these N-linked glycans lead to enhanced tumor killing by Pola-V. We hypothesize and test multiple methods of targeting this pathway in order to enhance Pola-V killing both in vitro and in vivo. Finally, we reveal a previously unappreciated role for the ubiquitin ligase KLHL6 in regulating CD79B protein abundance and surface expression of the B cell antigen receptor (BCR), including how this pathway is used by physiological germinal center B cells and how it is corrupted to enhance BCR expression in GCB DLBCL. Conclusions: These findings unravel the molecular basis of response heterogeneity to Pola-V and identify approaches that might be deployed therapeutically to enhance the efficacy of CD79B-specific tumor killing. In addition, we identify how KLHL6 determines expression of the BCR in both physiological and malignant germinal center B cells, and how KLHL6 mutation may modulate sensitivity of GCB DLBCL tumors to Pola-V. Citation Format: Sean R Corcoran, Jaewoo Choi, Rachel E Fenner, Xin Yu, Sebastian Scheich, Galina Schevchenko, Evangelia K Papachristou, Vivian M Morris, Kamal Kishore, Clive S D'Santos, Stefania Pittaluga, George Wright, Jagan Muppidi, Daniel J Hodson, Louis M Staudt. Molecular determinants of sensitivity to Polatuzumab-Vedotin [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr B079.

Diffuse large B cell lymphoma (DLBCL) is an aggressive cancer that is profoundly heterogeneous, both molecularly and phenotypically, presenting a challenge for precision medicine. Inhibitors of Bruton tyrosine kinase (BTK) block B cell receptor (BCR)-dependent NF-κB signaling and are particularly effective in DLBCL with mutations in the BCR subunit CD79B and MYD88 (MCD DLBCL). MCD tumors are enriched for a multiprotein supercomplex, termed the My-T-BCR, that is nucleated by MYD88 L265P, TLR9 and the BCR, and serves as a central hub of NF-κB signaling. The integrity of the My-T-BCR complex is rapidly compromised following BTK inhibition, but the molecular mechanisms responsible for the dissolution of this molecular machine have not been elucidated. To investigate the underlying mechanisms regulating the My-T-BCR, we used genome wide CRISPR-Cas9 screens in MCD DLBCL cell line models treated with the BTK inhibitors (BTKi) and compared the results to screens with inhibitors of SYK, IKK, mTOR, and BRD4. We identified several drug resistance genes encoding known negative regulators of BCR, NF-κB, and PI3 kinase signaling that were recurrently inactivated by mutation and/or deletion in DLBCL biopsies. Unexpectedly, we identified multiple autophagy-related genes involved autophagosome formation ( ATG9A, ATG101, ATG13, RB1CC1 and ATG14) and autophagosome membrane expansion ( ATG2A, WIPI2, WDR45) that strongly counteracted the toxicity of BTKi (≥3 SD). Notably, these autophagy genes did not promote resistance to the mTOR inhibitors, which induces classical autophagy. To gain further insight, we generated BTKi-resistant cell lines deficient in ATG9A or ATG101 (ATG KO) and performed genome-wide CRISPR screens and RNA-seq with or without BTKi. In doing so, we observed 11 ATG genes that displayed epistatic interactions, no longer conferring BTKi resistance in ATG KO MCD cells (p≤0.05). We also observed the buffering of many NF-κB negative regulators (p≤0.001) and the increased sensitivity to loss of NF-κB positive regulators (p≤0.05). Furthermore, gene expression studies showed a marked decrease of BCR, MYD88 and NF-κB signatures in control BTKi-treated cells, whereas ATG KOs demonstrated a rescue of these same gene signatures and displayed higher levels of nuclear NF-κB localization upon BTKi treatment. MCD patients display the highest levels of NF-κB gene expression compared to other genetic subtypes. Interestingly, MCD patients also displayed the lowest gene expression profile for a subset of the ATG genes (p≤2.7x10 -6), suggesting that this pathway may be counter-selected during MCD pathogenesis. As autophagy promotes the lysosomal degradation of proteins, and disruption of autophagy promoted NF-κB signaling in MCD cell lines, we assessed global protein levels and localization of proteins to the My-T-BCR in ATG KO cells using mass spectrometry. Selective autophagy receptors TAX1BP1, NBR1 and p62 were significantly upregulated in ATG KOs and displayed significant enrichment of proximity to MYD88 L265Pin ATG KOs (p≤0.01), suggesting MYD88 L265P is targeted for degradation by selective autophagy. To test this, we engineered MCD cell lines with dual fluorescent autophagy reporters (GFP-RFP fusions) for TAX1BP1, NBR1, p62, or MYD88 L265P. Each reporter displayed an accumulation of GFP relative to RFP in ATG KOs or upon treatment with the autophagy blocking v-ATPase inhibitor bafilomycin. To identify genes that modulate selective autophagy of MYD88 L265P, we performed a CRISPR screen in MCD cells stably expressing a MYD88 L265P-RFP-GFP reporter. We observed deletion of the same epistatic interactors of ATG9A in BTKi survival screens also blocked MYD88 L265P autophagic degradation. Conversely, deletion of BTK, mTORC1-related genes and IRF4 were all among the top-ranked genes that promoted MYD88 L265P autophagic degradation. We validated these findings using chemical inhibitors of each gene alone or in combination and observed synergy for the promotion of MYD88 L265P autophagic degradation. Collectively, we identified a non-canonical form of selective autophagy that chronically degrades MYD88 L265P, is counter-selected in MCD tumors, and is promoted by BTK inhibitors. Our findings help to elucidate the exceptional benefit of BTK-targeted therapies in the MCD DLBCL subtype and offer a rationally designed combination therapy regimen to specifically degrade this mutant allele of MYD88.

Introduction Frontline therapy for pts with follicular lymphoma (FL) is not based on the molecular profile of the tumor. The PI3K pathway is central to FL biology, but the molecular profile of tumors most sensitive to PI3K inhibition (PI3Ki) is unknown. Copanlisib inhibits both PI3Kα and δ isoforms, and we hypothesized that most pts with treatment naïve FL will have PI3Ki-sensitive tumors and durable complete responses (CRs) may be achievable with short durations of targeted therapy. A gene expression profiling (GEP) predictor utilizes a combination of the expression of 45 selected informative genes and an additional 19 housekeeping genes to identify FL pts at high-risk for early progression within 24 months (Wright et al. ASH Annual Meeting2022). We also hypothesized that copanlisib would induce durable CRs in high-risk pts by the GEP assay. Here, we report a preliminary analysis of an ongoing “window of opportunity” study of copanlisib followed by response-adapted copanlisib and rituximab in treatment-naïve pts with FL (NCT03789240). Methods Pts with untreated grade 1-2, 3A FL, ≥stage 2 are eligible if systemic therapy is indicated: symptoms, progressive lymphadenopathy, or organ compromise. Prior radiation is permitted. Eligibility includes age ≥18 and adequate organ function unless due to lymphoma. HIV, CMV, Hep B or C, and autoimmune conditions are excluded. Pts first receive copanlisib 60mg on days 1, 8, and 15 of a 28-day “window of opportunity” to explore the activity of copanlisib. Following the window, pts receive 6 cycles of copanlisib 60mg on days 1, 8, and 15 of a 28-day cycle along with rituximab 375mg weekly x 4 then on day 1 of each cycle and response is assessed with FDG-PET and CT scans. Pts without response after C6 are taken off study and those with a partial response (PR) can continue for an additional 6 cycles and then stop therapy. Pts who achieve a CR after 6 cycles stop therapy. No maintenance is given. Supportive care includesPCP prophylaxis. The primary endpoint is the CR rate with secondary endpoints of safety, duration of CR, and PFS. Exploratory objectives include identification of a predictive signature of PI3Ki response and the response rate in high-risk pts identified by the GEP assay. Results Twenty-eight pts have enrolled. Median age was 56y (range, 24-80). Seventeen (61%) and 12 (43%) pts had high-risk FLIPI and FLIPI-2 scores ≥3, respectively; 6 (21%) pts had Grade 3A FL, and 17 (61%) pts met two or more GELF criteria. After copanlisib monotherapy in the window, 27 (96%) pts had tumor reductions by CT with a median change of -38% (-62% to +16%) (Figure 1). Among 22 pts who completed 6 cycles, 21 (96%) responded, including 9 (41%) pts with PR and 12 (55%) pts with CR. Of 9 pts with PR who received an additional 6 cycles of therapy, only 1 (11%) converted to a CR bringing the overall CR rate to 59% (13/22 pts). After a median follow-up of 25.8 months, the 2-year PFS was 43.2% (95% CI, 20.7-64.0%). The median duration of CR was 29.7 months (95% CI, 6.3 months - not estimable) with 8 (62%) CRs ongoing (Figure 2). Toxicity was evaluated in 28 pts across 220 cycles. Most common were rash (64%), mucositis (50%), and nausea/vomiting (50%), all G1-2 except 1 (4%) pt with G3 mucositis. The most common ≥G3 toxicities were neutropenia and infections in 5 (18%) pts each. ≥G3 neutropenia occurred in 10 (5%) cycles, responded to therapy interruption and/or growth factors, and did not require dose reduction. Two (8%) pts had copanlisib dose reduced, 1 (4%) each due to rash and mucositis. Therapy was prematurely discontinued in 5 pts: 3 due to COVID-19, 1 for hepatotoxicity that resolved, and 1 due to infusion reaction to rituximab. Nine of 24 (38%) pts were poor risk by the GEP assay. Complete responses were observed in 71%, 67%, and 57% of pts categorized as high-risk by FLIPI, FLIPI-2, and GEP assay, respectively. The CR rate was not affected by bulky disease (any LN >7cm; p=1.00), high-risk FLIPI (p=0.19), high-risk FLIPI-2 (p=0.67), poor-risk GEP (p=1.00), or metabolic tumor volume (p=0.33). Conclusion Nearly all pts with treatment naïve FL have PI3Ki-responsive tumors, and the combination of copanlisib with rituximab achieved a CR rate of 59% at the end of induction therapy. The median duration of CR is nearly 30 months, including ongoing remissions without maintenance. CRs were observed in pts deemed high-risk by the GEP assay and FLIPI score. The safety profile is excellent, with mostly G1-2 toxicities manageable with supportive care.

Background: Anaplastic large cell lymphomas (ALCLs) are CD30-positive T-cell lymphomas that share pathologic features but differ in clinical presentation, outcome, and molecular features. The World Health Organization (WHO) and International Consensus Classification (ICC) classify ALCLs by presence or absence of ALK rearrangements (R) and clinical presentation (systemic, cutaneous [c], or breast implant-associated [BIA]). ICC, but not WHO, recognizes DUSP22-R as defining a new genetic subtype of ALK- ALCL. The classifications otherwise do not reflect additional molecular heterogeneity in genetics (e.g., TP63-R) or therapeutic vulnerabilities (e.g., JAK-STAT3 pathway activation). Methods: ALCLs (N=689) underwent expert consensus review (WHO/ICC) through the Lymphoma/Leukemia Molecular Profiling Project (LLMPP). All cases also underwent genetic subtyping (ALK, DUSP22, TP63, and triple-negative [TN]) using fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC), as well as IHC for phospho-STAT3 Tyr705 (pSTAT3). RNAseq was performed and evaluable in 393 cases; the remaining cases had insufficient tissue, tumor content, RNA yield or quality, and/or sequencing data quality. Sequenced and non-sequenced sub-cohorts had similar demographics and subtype distribution. Results: Unsupervised gene expression profiling (GEP) identified 2 main molecular types of ALCL. Type I ALCLs predominantly included ALK+ ALCLs, BIA-ALCLs, and a subset of TN ALCLs (designated TN-I), whereas Type II ALCLs predominantly included ALCLs with DUSP22-R, TP63-R, or both (double-hit; DH), and the remaining TN ALCLs (TN-II). Type I ALCLs were strongly associated with pSTAT3 expression (74.2±26.4% positive malignant cells vs 9.9±22.7% for Type II; P<0.0001). An independently derived pSTAT3 staining threshold of 30% assigned Type I vs II with 91% accuracy. A third cluster of ALCLs, mostly cALCL, showed an epithelial GEP signature rather than a lymphoma signature; these cases were assigned to Types I or II based on pSTAT3 IHC. Distinct sub-signatures were identified for ALK+, DUSP22-R, TP63-R, and BIA ALCL (Fig. 1), but not ALK- ALCL or cALCL. Gene set enrichment analysis showed Type I ALCLs to be enriched for JAK-STAT3 signaling genes (normalized enrichment score [NES], 2.22; FDR<0.0001) and related pathways, such as TNFα-NFκB signaling (NES, 2.21; FDR<0.0001). In contrast, Type II ALCLs were enriched for cell cycle, DNA repair, epigenetic, and metabolic pathway genes, but not for major tyrosine kinase-mediated signaling pathway genes. Enriched epigenetic pathways included chromatin modifying enzymes (NES, -1.86; FDR=0.002) and histone methylation (NES, -1.71; FDR=0.002). EZH2 was the most overexpressed gene in Type II ALCLs (fold-change, 7.74; FDR=8.84×10 -306). At the protein level, EZH2 IHC H-scores were 275±45 in Type II and 168±70 in Type I ALCLs (P<0.0001); H3K27me3 H-scores were 170±81 and 76±63, respectively (P<0.001). The top metabolic gene set involved cholesterol biosynthesis (NES, -1.88; FDR=0.002). Overall survival (OS) data were available in 257 systemic ALCL patients (145 sequenced and 112 non-sequenced; cALCL and BIA-ALCL were excluded). Non-sequenced TN ALCLs were assigned to TN-I or TN-II using pSTAT3 IHC. The results supported earlier data indicating favorable prognosis of DUSP22-R ALCL (5 y OS, 95%) and ALK+ ALCL (87%), intermediate prognosis of TN ALCL (TN-I, 52% and TN-II, 38%; P=NS), and poor prognosis of TP63-R/DH ALCL (0%)(P<0.0001; Fig. 2). Conclusions: Two overarching molecular types of ALCL exist, predominantly associated with the presence (Type I) or absence (Type II) of the JAK-STAT3 signaling program. Distinct GEP signatures exist for ALK+ ALCL and BIA-ALCL (predominantly Type I), and DUSP22-R ALCL and TP63-R ALCL (predominantly Type II). TN ALCLs lacking ALK-R, DUSP22-R, and TP63-R can be stratified into TN-I and TN-II subtypes. pSTAT3 IHC has >90% accuracy as a surrogate for GEP-based subtyping. ALK- ALCL and cALCL cluster by molecular subtype rather than by defining GEP signatures. Type II ALCLs are enriched for targetable epigenetic and metabolic pathways, including EZH2/histone methylation and cholesterol biosynthesis. This molecular classification is diagnostically, prognostically, and potentially therapeutically relevant, and can be applied using FISH and IHC in routine practice and in the clinical trial setting.

Background: Foundational studies have revealed essential oncogenic pathways in DLBCL, triggering the development of drugs targeting distinct survival pathways in this malignancy. While many of these agents are active in DLBCL as monotherapy, they rarely induce deep responses or cure. Based on our identification of drug synergy in DLBCL models, we hypothesized that targeting multiple survival pathways concurrently could be curative in DLBCL. We developed a 5-drug combination regimen (ViPOR) that targets DLBCL survival sustained by constitutive B-cell receptor (BCR) signaling (ibrutinib, lenalidomide, prednisone) and by BCL2 (venetoclax), and also enlists the innate immune system using obinutuzumab. To maximize drug exposure and minimize toxicity, we administered all agents in non-continuous cycles for fixed duration in R/R DLBCL. Methods: R/R DLBCL pts with adequate organ function were eligible. In Ph I, pts were treated at 4 doses of venetoclax (200-800 mg) PO D2-14 to identify the MTD. An initial 12d venetoclax ramp-up was given in combination with fixed-dose ibrutinib 560 mg PO D1-14, prednisone 100 mg PO D1-7, obinutuzumab 1000 mg IV D1-2, and lenalidomide 15 mg PO D1-14. Ph II expansion cohorts of R/R GCB and non-GCB DLBCL were included at the MTD. Max 6C of ViPOR q21d were given without maintenance. TLS, G-CSF, and PCP prophylaxis were given to all pts. Baseline CT, PET, BM, and tumor biopsies were performed with CT after C1, 2, 4, and 6 and PET after C6. CT was then performed q3m x 1y, q4m x 1y, q6m x 1y, then q12m x 2y. Tumor genomics and ctDNA (clonoSEQ) were studied. Results: 50 DLBCL pts were enrolled (25 DLBCL NOS, 17 HGBCL-DH-BCL2, 3 HGBCL-DH-BCL6, and 5 THRLBCL). 52% and 48% were GCB and non-GCB subtype by IHC, respectively, with transformed lymphoma in 34%. Median age was 61y (range 29-77), with stage 3-4 disease in 92%, elevated LDH in 86%, >2 extranodal sites in 56%, and IPI >3 in 68% of pts. Median prior txs were 3 (range 1-9), with 40% post-CAR-T pts and 58% refractory. A single DLT of G3 intracranial hemorrhage occurred, and venetoclax 800 mg was identified as the MTD. Heme AEs were most common, with G3-4 neutropenia in 24%, thrombocytopenia in 23%, and anemia in 7% of cycles. Febrile neutropenia occurred in 3 (1%) cycles. The only G3-4 non-heme AE in >10% pts was hypokalemia (28%). G3 A.fib occurred in 3 pts, and G4 TLS occurred in 1 pt, which resolved. Other common any grade non-heme AEs (% pts) included diarrhea (68%), hypokalemia (67%), nausea (45%), rash (35%), and fatigue (33%). Dose reductions occurred in 17% of pts, and 8% discontinued tx due to AE. Of 48 evaluable pts (2 came off tx prior to restaging), ORR was 54% (26/48), and CR was 38% (18/48). Responses were observed across all molecular DLBCL subtypes, including a CR rate of 62% (8/13) in non-GCB DLBCL, 53% (8/15) in HGBCL-DH-BCL2, 25% (2/8) in other DLBCL, and a PR rate of 33% (4/12) in GCB DLBCL (non-DH) (Fig. 1A). CR rate was 20% (4/20) and 19% (5/27) in post-CAR-T and refractory pts, respectively. With a median FU of 40m, 72% of CRs are ongoing, with a 2-year PFS and OS of 34% and 36%, respectively. By histology, 2-year PFS was 47%, 38%, 38%, and 8% in HGBCL-DH-BCL2, non-GCB DLBCL, other DLBCL, and GCB DLBCL (non-DH), respectively (Fig. 1B). 2-year PFS was 30% and 21% in post-CAR-T and refractory pts, respectively. MRD was undetectable in 38% (16/42) of pts at end of therapy (EoT), and in 93% (14/15) of pts in PET CR at EoT. Elevated baseline ctDNA or detectable ctDNA during or at EoT were associated with significantly inferior PFS and OS, as were quantitative PET parameters (elevated baseline TMTV and TLG). Two genetic subtypes known to rely on BCR-dependent NF-kB signaling - MCD and N1 - had a significantly higher CR rate (5/6, 83%) than all other genetic subtypes (4/22, 18%; p=0.0066). Conclusions: This is the first study to show the feasibility and curative potential of multi-targeted therapy in R/R DLBCL. ViPOR was well tolerated across all ages in R/R DLBCL with rare febrile neutropenia. ViPOR was most effective in non-GCB DLBCL, as expected from its reliance on BCR signaling and BCL2. ViPOR was also highly active in HGBCL-DH-BCL2, possibly due to inhibition of MYC-driven apoptosis by BCL2 in this subtype. Durable remissions and likely cure were observed in non-GCB DLBCL (38%) and HGBCL-DH-BCL2 (47%), including pts relapsed after or refractory to CAR-T (30%). Multicenter Ph II testing is in development to confirm the activity of ViPOR in R/R non-GCB DLBCL and HGBCL-DH-BCL2.