Abstract: Venetoclax, the first approved BH3 mimetic targeting BCL2, demonstrates high response rate in chronic lymphocytic leukemia (CLL) but resistant cases are emerging. Aside from BCL2 mutations affecting venetoclax binding, multiple lines of mounting evidence suggest a role for non-mutational mechanisms underlying resistance to this drug. By applying both CRISPR-Cas9 knock-out and ORF overexpression screens in the lymphoma cell line OCI-Ly1, we previously reported the identification of MCL-1 overexpression and of the AMPK/PKA signaling axis in altering energy metabolism underlying venetoclax resistance (Guieze, ASH 2018). Here, we report further in-depth exploration of the impact of these findings, discovered through the analysis of lymphoid cell lines, and of specimens collected from CLL patients developing venetoclax resistance. The resistant lymphoma cell lines that we generated (OCI-Ly1 and SU-DHL4 cells) displayed increased oxidative phosphorylation (OXPHOS) compared to the parental lines, measured by Seahorse assay. We instead observed that venetoclax rapidly perturbs OXPHOS in sensitive cells. This process is dependent on mitochondrial outer membrane permeabilization, as this effect is abrogated in BAX/BAK1 double knockout (KO) cells. Targeting OXPHOS was shown to synergize with venetoclax in vitro and in vivo, as combination of venetoclax and oligomicin (an inhibitor of the ATP synthase, the complex V of the mitochondrial electron transport chain), was more effective than each drug alone in reducing tumor growth of a subcutaneous NSG xenograft model based on OCI-Ly1. Among the candidate markers driving resistance identified from the genome-wide screens, we focused on AMP pathway members (AMPK and PKA) and the ID3 transcriptional regulator, given that ID3 KO cells demonstrated similar transcriptomic changes than the resistant OCI-Ly1 cells. We found that PRKAR2B (encoding a PKA subunit), already highlighted in our ORF screen, was the top transcript overexpressed when knocking out ID3. To clarify how the dominant-negative transcription factor ID3 regulates PRKAR2B expression, we performed ATAC-seq of the ID3 OCI-Ly1 knockout (vs control) lines in order to determine differential signatures of chromatin accessibility and transcription factor engagement. We showed that ID3 repression leads to genome-wide increased accessibility associated with motifs of the lymphoid transcription factor TCF3. TCF3 has previously been shown to interact with ID3 and to be involved in the transcription of ADIPOQ, which was identified in the GOF screen. TCF3 binding sites were confirmed to be present within putative enhancer regions of PRKAR2B in a B cell context. We then investigated whether our findings could be validated in patient samples. By whole-exome sequencing of matched pretreatment and venetoclax-resistant CLL samples collected from 6 patients, we did not detect any recurrent somatic mutations associated with resistance. The resistant samples from three of 6 patients, however, harbored subclones with 1q amplification in a common region encompassing the MCL1 locus. We identified 4 additional CLL cases relapsing on venetoclax with leukemia samples collected before and after relapse. By immunohistochemical staining of 9 of 10 cases for which tissue was available, we detected increased MCL-1 expression at relapse in 6 of 9 cases (p = 0.026). We furthermore confirmed the involvement of AMPK signaling by detecting evidence of AMPK, ACC and p-ACC expression in 4 of 9 patients (all p = 0.0062). ID3 expression was decreased at matched relapse samples (p = 0.0001), supporting the presence of the resistance circuit we identified above. Taken together, our results identified the increased MCL-1 expression and PKA/AMPK activation as underlying mechanisms for venetoclax resistance. Our data support the implementation of combinatorial therapy with metabolic modulators to address venetoclax resistance. Disclosures Guièze: Abbvie: Honoraria; Roche: Honoraria; Janssen: Honoraria; Gilead: Honoraria. Thompson:AbbVie: Research Funding; Amgen: Consultancy, Research Funding; Pfizer: Research Funding; Pharmacyclics: Research Funding; Genentech: Consultancy, Honoraria; Gilead: Consultancy, Honoraria. Davids:AbbVie, Acerta Pharma, Adaptive, Biotechnologies, Astra-Zeneca, Genentech, Gilead Sciences, Janssen, Pharmacyclics, TG therapeutics: Membership on an entity's Board of Directors or advisory committees; Research to Practice: Honoraria; AbbVie, Astra-Zeneca, Genentech, Janssen, MEI, Pharmacyclics, Syros Pharmaceuticals, Verastem: Consultancy; Acerta Pharma, Ascentage Pharma, Genentech, MEI pharma, Pharmacyclics, Surface Oncology, TG Therapeutics, Verastem: Research Funding. Brown:AbbVie: Consultancy; Acerta Pharma: Consultancy; Loxo: Consultancy, Research Funding; BeiGene: Consultancy; Catapult Therapeutics: Consultancy; AstraZeneca: Consultancy; Novartis: Consultancy; Pfizer: Consultancy; Pharmacyclics: Consultancy; Sunesis: Consultancy; TG Therapeutics: Consultancy; Verastem: Consultancy, Research Funding; Sun Pharmaceuticals: Research Funding; Janssen: Honoraria; Teva: Honoraria; Morphosys: Other: Data safety monitoring board; Invectys: Other: Data safety monitoring board; Octapharma: Consultancy; Kite, a Gilead Company: Consultancy, Research Funding; Juno/Celgene: Consultancy; Dynamo Therapeutics: Consultancy; Genentech/Roche: Consultancy; Gilead: Consultancy, Research Funding. Wierda:Xencor: Research Funding; Cyclcel: Research Funding; Genentech: Research Funding; Pharmacyclics LLC: Research Funding; Gilead Sciences: Research Funding; KITE pharma: Research Funding; Oncternal Therapeutics Inc.: Research Funding; Sunesis: Research Funding; AbbVie: Research Funding; Janssen: Research Funding; Acerta Pharma Inc: Research Funding; GSK/Novartis: Research Funding; Miragen: Research Funding; Loxo Oncology Inc.: Research Funding; Juno Therapeutics: Research Funding. Letai:AbbVie, AstraZeneca, Novartis: Consultancy, Research Funding; Zeno Pharmaceuticals, Vivid Bioscience, Flash Therapeutics, Dialectic Therapeutics: Membership on an entity's Board of Directors or advisory committees, Other: Cofounder or Advisory Board member. Neuberg:Pharmacyclics: Research Funding; Madrigal Pharmaceuticals: Equity Ownership; Celgene: Research Funding. Mootha:Jansen Pharmaceuticals: Other: SAB, compensation; 5am Ventures: Other: SAB, compensation; Raze Therapeutics: Other: Founder, SAB, equity. Getz:MuTect, ABSOLTUE, MutSig and POLYSOLVER: Patents & Royalties: MuTect, ABSOLTUE, MutSig and POLYSOLVER; Pharmacyclics: Research Funding; IBM: Research Funding. Wu:Pharmacyclics: Research Funding; Neon Therapeutics: Other: Member, Advisory Board.

Abstract: Collective large-scale sequencing efforts have unexpectedly revealed the high frequency of mutations in the splicing factor genes (SF3B1, U2AF1, SRSF2, ZRSR2) in various solid and hematological cancers, suggesting the association of splicing dysregulation with tumorigenesis. Mutations in SF3B1 occur in 5-20% of patients with chronic lymphocytic leukemia (CLL) and are associated with poorer overall survival and chemotherapy resistance. These mutations are restricted to hotspots ( 〉 50% at K700E site) and strongly co-occur with ATM mutations (loss-of-function) and deletion of 11q (ATM minimal deleted region). Numerous studies including ours have demonstrated that somatic alterations in this gene cause RNA splicing dysregulation, however, how this splicing factor mutation alone and in combination with ATM deletion impacts cellular processes and contributes to CLL remains to be fully defined. To this end, we modeled the effects of these combined alterations by crossing mice with conditional knockout of Atm and mice with a conditional knock-in allele of SF3B1 mutation (Sf3b1-K700E). We achieved B cell-restricted expression of heterozygous Sf3b1 mutation and Atm deletion by breeding these mice with CD19-Cre homozygous transgenic mice. Conditional expression of heterozygous Sf3b1-K700E mutation in mouse B cells disrupts pre-mRNA splicing, alters B-cell development, and induces a state of cellular senescence. Combined with Atm deletion in B cells led to the overcoming of cellular senescence and the development of clonal CLL cells in elderly mice at low penetrance (6%). These malignant cells could be propagated by in vivo passaging, with detectable disease within 4 weeks following transfer, thus making this mouse line amenable to further drug discovery and biologic investigations. To fully understand the underlying mechanisms of how the combined alterations led to CLL, we performed integrated genome, transcriptome, and proteome analysis using mouse CLL (DM-CLL) cells and B cells with either Sf3b1 mutation or Atm deletion, or with double genetic lesions (DM). Whole-genome sequencing of paired DNA from B cells (or DM-CLL) and non-B cell tissue (kidney) revealed the somatic mutation rate in the CLL cells to be ~0.5 mutations/Mb. Few recurrent mutations were identified among the samples. However, copy number variation analysis of DM-CLL cells revealed recurrent amplifications of chromosomes 15 and 17. RNA-seq analysis revealed that these amplifications were associated with overexpression of 835 of 987 Chr15 and Chr17 genes detected in DM-CLL vs. DM cells. Of note, 146 genes were overexpressed in human CLLs with SF3B1 mutations (DFCI cohort), compared to normal B-cells (p 〈 0.05). Integrated transcriptome and proteome analysis of the DM-CLL cells showed coordinated dysregulation of multiple CLL-associated cellular processes with B-cell receptor (BCR) signaling as the most dramatically downregulated compared to DM cells. Since BCR signaling is a therapeutic target in CLL and has critical roles in B cell biology, we asked how SF3B1 mutation contributes to gene expression of BCR signaling. Through RNA-seq data analysis derived from two independent patient cohorts (DFCI and ICGC), we identified downregulation of BCR gene expression in SF3B1 mutant CLL cells. In line with this, human CLLs harboring SF3B1 mutations exhibit greater sensitivity to in vitro treatment with ibrutinib, and altered response kinetics in vivo to ibrutinib, per analysis of patients with SF3B1 mutations treated with ibrutinib. These studies together highlight a role of SF3B1 mutation in BCR signaling. In summary, we have generated a genetically-engineered murine model that recapitulates human CLL genetics, and presents an informative model to functionally dissect the effects of mutant SF3B1 in a B cell context. Starting from computation-based identification of recurrent co-occurring events in CLL, our study employs murine lines that express genetic alterations in an lineage-specific fashion, utilizes integrated genomics and proteomics approaches to dissect pathways that are fundamental to CLL phenotype, and more importantly, links the dysregulated pathways back to human CLL gene expression data and clinical trials to reveal novel mechanisms underlying therapeutic response. Disclosures Wiestner: Pharmacyclics LLC, an AbbVie Company: Research Funding. Wu:Neon Therapeutics: Equity Ownership.

Abstract: Activation and proliferation of chronic lymphocytic leukemia (CLL) cells depend on signals from the lymph node (LN) tumor microenvironment (TME). Separately, the genetic makeup of CLL has been closely linked to disease aggressiveness and its capacity to evolve under the selective pressures of treatment. Here, we investigated the intersection between the TME and molecular events in CLL pathogenesis. Whole exome and RNA sequencing (RNA-seq) were performed on CD19+ cells of paired peripheral blood (PB) and LN samples and matched germline DNA from 14 patients with treatment-naïve CLL. RNA-seq was also done on unsorted LN samples containing tumor and non-tumor cells from the same patients. A median of 27 (range 11-69) somatic single nucleotide variants (sSNVs) and 3 (0-10) insertions and deletions (sIndels) were detected per exome. All but one patient had copy number alterations (CNAs), most commonly del 11q and del 13q. Cancer cell fractions (CCFs) of sSNVs, sIndels, and CNAs were inferred from variant allele frequencies then clustered over the two anatomic compartments for each patient. Genetic compartmentalization (ΔCCF 〉 0.25, false discovery rate [FDR] 〈 0.1) was observed in 7 patients (50%), of whom 6 demonstrated subclonal expansion in LN. To understand factors contributing to spatial heterogeneity, we compared the tumor transcriptome based on the presence (shifted group) or absence (stable group) of an expanded subclone in LN. Most differentially expressed genes between PB and LN were shared by all patients and reflected the activation of CLL cells in the LN TME as previously shown. However, cell cycle genes (e.g. E2F2, CDC25A) were more upregulated (log2FC 〉 0.5, FDR 〈 0.05) in LN of the shifted group, while lymphocyte activation markers (e.g. CD83, CD69) were more upregulated in LN of the stable group. We hypothesized the latter finding could indicate immune-mediated control of clonal outgrowth. We therefore evaluated the expression of an 18-gene T-cell associated inflammatory signature in unsorted LN samples. This signature was originally developed as a predictive biomarker for response to immune checkpoint blockade in multiple cancer types. Unsupervised hierarchical clustering of signature genes revealed an inflamed TME in the stable group relative to the shifted group. In summary, genetic compartmentalization is a common phenomenon in CLL. Clonal equilibrium is maintained by a T-cell inflamed TME. When immune surveillance is inactivated, subclones with a competitive advantage may expand in response to support signals provided by the TME. An immunotherapy-based clinical study using checkpoint blockade to restrict clonal evolution is currently in progress (NCT03204188). This research was supported by the Intramural Research Program of the NIH, NHLBI. Disclosures Getz: Pharmacyclics: Research Funding; IBM: Research Funding; MuTect, ABSOLTUE, MutSig and POLYSOLVER: Patents & Royalties: MuTect, ABSOLTUE, MutSig and POLYSOLVER. Wu:Neon Therapeutics: Other: Member, Advisory Board; Pharmacyclics: Research Funding. Wiestner:Merck: Research Funding; Pharmayclics: Research Funding; Acerta: Research Funding; Nurix: Research Funding.

Abstract: The FDA-approval of potent targeted therapies has led to great changes in the therapeutic landscape of chronic lymphocytic leukemia (CLL). As a key example, venetoclax, a first-in-class BCL-2 inhibitor, leads to response in about 80% of patients with relapsed/refractory (R/R) CLL. Disease progression on venetoclax, however, has been increasingly observed, and better biologic understanding of resistance mechanisms to this agent is needed. To systematically discover the potential mechanisms of resistance to venetoclax, we performed both genome-scale loss- (LOF) and gain-of-function (GOF) genetic modifier screens in the BCL-2-driven OCI-Ly1 lymphoma cell line using CRISPR-Cas9 sgRNA and ORF libraries, respectively. Significant hits from both screens included the BCL-2 family: the LOF screen with pro-apoptotic genes (PMAIP1, BAX, BAK1, BCL-2L11) and the GOF screen with anti-apoptotic genes (BCL2L1, BCL2L2, BCL2, MCL1). In addition, the LOF screen uncovered genes in pathways relevant to lymphoid biology (i.e, NFKBIA) and lymphoid transcription factors and modulators (IKZF5, ID3, EP300, NFIA). The GOF screen also uncovered components of the energy-stress sensor PKA/AMPK signaling pathways (ADIPOQ, PRKAR2B, PRKAA2) and regulators of mitochondrial metabolism. In parallel, we performed an integrated transcriptome, whole proteome and functional characterization of an OCI-Ly1 cell line rendered resistant to venetoclax (OCI-Ly1-R) from the parental cell line (OCI-Ly1-S). RNA-seq and spectrometry-based proteomics revealed coordinated dysregulation of transcripts and proteins in the resistant line originating from genes critical to cellular metabolism, cell cycle, B-cell biology and autophagy. Of the transcripts and proteins significantly associated with the resistant cell line, only MCL-1 overlapped with the gene hits from the genome-scale screens. Treatment of the OCI-Ly-R cells with the MCL-1 inhibitor S63845 synergized with venetoclax. Given the dysregulation of proteins critical to metabolism in both the GOF screen and in OCI-Ly1-R cells, we also evaluated the role of metabolic reprogramming in venetoclax resistance. We first assessed mitochondrial respiration by measuring the oxygen consumption rate. Compared to OCI-Ly-S cells, OCI-Ly1-R cells demonstrated markedly higher respiration levels, suggesting a state of higher oxidative phosphorylation (OXPHOS). More directly, we measured oxygen consumption following venetoclax exposure. Consistent with impairment of OXPHOS by venetoclax, we observed both an immediate decrease in oxygen consumption and an immediate burst of glycolysis following venetoclax in the OCI-Ly1-S cells, but not in the OCI-Ly1-R cells. In line with these findings, the AMPK inhibitor dorsomorphin and mitochondrial electron transport chain (mETC) inhibitors synergized with venetoclax in OCI-Ly1-S cells. Transcriptome related to ID3 (identified as one of the LOF screen targets) was characterized in isogenic ID3-knockout OCI-Ly1 lines. It revealed PRKAR2B overexpression as a key effect, suggesting a role for ID3, and perhaps of other lymphoid transcription factors in regulating metabolic reprogramming associated with resistance. Indeed, exposure of ID3 knockout lines to mETC inhibitors overcame resistance to venetoclax. To determine if there is a genetic basis for the drug resistance seen in OCI-Ly1-R cells, we compared whole-exome sequencing (WES) results of DNA isolated from the OCI-Ly1-R and OCI-Ly1-S cell lines. A clear region was amplified on chromosome 1q23, which includes MCL1 and PRKAB2 (the regulatory subunit of AMPK). Similarly, a WES-based analysis of paired CLL DNA samples isolated from 6 R/R CLL patients just prior to venetoclax initiation and at time of progression on venetoclax was performed. We did not identify any non-silent somatic single nucleotide in BCL2 or its family members at baseline or at progression, despite marked clonal shifts in all patients. We confirmed the presence of the amp(1q23) as acquired at relapse after venetoclax in 3 out of 6 patients. Our study reveals that venetoclax resistance implicates changes not only for outer mitochondrial membrane (MCL-1 expression) but also for inner membrane (oxydative metabolism). Such mitochondrial reprogramming represents a new vulnerability that can potentially be exploited through combinatorial therapy with metabolic modulators to overcome resistance. Disclosures Guieze: abbvie: Honoraria; janssen: Honoraria; gilead: Honoraria. Thompson:Gilead Sciences: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Honoraria, Research Funding; Adaptive Biotechnologies: Research Funding; Pharmacyclics: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Honoraria, Membership on an entity's Board of Directors or advisory committees. Davids:Merck: Consultancy; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees; BMS: Research Funding; MEI Pharma: Consultancy, Research Funding; Verastem: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Consultancy; AbbVie, Inc: Consultancy, Membership on an entity's Board of Directors or advisory committees; Surface Oncology: Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees; Roche/Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; TG Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Brown:Sun Pharmaceutical Industries: Research Funding; Abbvie: Consultancy; Acerta / Astra-Zeneca: Membership on an entity's Board of Directors or advisory committees; Morphosys: Membership on an entity's Board of Directors or advisory committees; TG Therapeutics: Consultancy; Janssen: Consultancy; Sunesis: Consultancy; Roche/Genentech: Consultancy; Verastem: Consultancy, Research Funding; Boehringer: Consultancy; Loxo: Consultancy; Beigene: Membership on an entity's Board of Directors or advisory committees; Invectys: Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy; Gilead: Consultancy, Research Funding; Pharmacyclics: Consultancy; Genentech: Consultancy. Wierda:AbbVie, Inc: Research Funding; Genentech: Research Funding. Letai:AstraZeneca: Consultancy, Other: Lab research report; Novartis: Consultancy, Other: Lab research report; AbbVie: Consultancy, Other: Lab research report; Flash Therapeutics: Equity Ownership; Vivid Biosciences: Equity Ownership. Wu:Neon Therapeutics: Equity Ownership.

Abstract: Richter's syndrome (RS) arising from chronic lymphocytic leukemia (CLL) is a striking example of an aggressive malignant histology that emerges from indolent cancer. A major barrier to disease control in CLL, RS is associated with poor clinical outcomes and limited survival. The genetic basis of RS is poorly understood and its relationship to antecedent CLL remains incompletely characterized. Notable challenges to the genomic study of RS includes those of sample acquisition, the distinction between true tumor events rather than sequence artifacts in archival fixed tissue, and the limitations of available computational techniques for deconvoluting admixtures of CLL and RS DNA within the same biopsy specimen. To address these challenges and characterize the genetic profile of RS, we performed whole-exome sequencing (WES) on samples collected from 42 patients with RS of diffuse large B cell lymphoma (DLBCL) histology. For this genomic characterization, samples from 37 patients were analyzed as 'trios' (matched germline, CLL and RS tissue DNA) and those from 5 as 'duos' (matched CLL and RS DNA). CLL diagnosis preceeded RS diagnosis by a median of 60.6 months (range 0.1-234.5). The median number of prior CLL-directed therapies was 2 (range 0-10). 8 patients had no prior CLL-directed therapy, while 9 were exposed to novel agents. The median time from most proximal CLL sampling to RS was 2.7 months (range: 82.2 months pre- to 3.8 months post RS diagnosis). Critical analytic innovations applied to this dataset included addressing contamination of CLL DNA in the germline sample (through the tool DeTIN) and generating the ability to discriminate between clones arising from RS or from CLL, even while both histologies were commonly co-existing within originating biopsies (via the tool PhylogicNDT). From this discovery cohort of 42 cases, 36 (86%) revealed RS and CLL to be clonally-related based on WES analysis, with a distinct RS clone emerging from an existing CLL subclone. Of the 6 (14%) cases determined to be clonally unrelated by WES, 4 had been previously examined by IGHV sequencing; only 1 of 4 was categorized as clonally unrelated, likely due to CLL and RS admixture. RS displayed mutational signatures reflecting aging (CpG), canonical AID, and non-canonical AID processes. Through deconvoluting clonal composition using PhylogicNDT in related sample trios (n=31), we established several notable differences compared to antecedent CLL. First, RS clones presented higher rates of additional mutations than the ancestral CLL clones from which they developed (2.47 vs. 0.86 Mut/Mb, p & lt;0.0001). Second, the frequency of CLL-associated driver mutations in the RS clones was altered:TP53 mutation (n=21, 50%), NOTCH1 mutation (n=17, 40%) NFKBIE (n=5, 12%), EGR2 (n=6, 14%), XPO1 (n=5, 12%), and RPS15 (n=3, 7%). Third, the clonal transition to RS was marked by a diversity of additional driver mutations and particularly increased copy number variants (CNVs). RS biopsies had recurrent arm level events, including del(17p) in 44%, del(4p) in 27%, del(4q) in 27%, del(9p) in 22%, del(17q) in 22% and del(9q) in 20% (Q & lt;0.05, GISTIC). The top focal alterations in RS biopsies, as identified by tool GISTIC included (Q value & lt;= 0.05): amp(7q21.2) - CDK6,amp(8q24.3) - RECQL4, amp(13q31.3) - ERCC5, amp(19p13.3), amp(19q13.42), del(8p12), del(17p13.1) - TP53, del(13q14.3), del(7q35), and del(16q12.2). Finally, whole genome doubling was observed in 6 cases upon transition to RS. To further investigate RS and CLL clonal evolution at high resolution, we performed single-cell RNA-sequencing (10x Genomics), on biopsies at the time of RS diagnosis in 5 individuals with clonally related transformation. Data analysis and clustering was conducted using Seurat(v3) with doublet removal (DoubletFinder). We identified CNV in single-cell transcriptomes that matched the WES copy-number profiles of individual subclones of the RS and CLL populations and thus linked subclones identified by WES to single-cell expression clusters and states, revealing CLL, RS and intermediate evolutionary cell states. In conclusion, we identify that RS arises from CLL subclones through distinct mutational trajectories. Further molecular subclassification of RS, including genetic characterization of additional cases, and linking mutational data with clinical outcomes is ongoing and has potential to alter clinical classification and prognostication of RS. Disclosures Guieze: abbvie: Honoraria, Other: advisory board, travel funds; janssen cilag: Honoraria, Other: advisory board, travel funds; roche: Other: travle funds; gilead: Honoraria, Other: travel funds; astrazanecka: Honoraria, Other: advisory board. Leshchiner:PACT Pharma, Inc.: Consultancy. Tausch:Roche: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria, Research Funding; Janssen-Cilag: Consultancy, Honoraria, Research Funding. Davids:Genentech: Consultancy, Research Funding; Janssen: Consultancy; Gilead Sciences: Consultancy; Novartis: Consultancy, Research Funding; MEI Pharma: Consultancy, Research Funding; Surface Oncology: Research Funding; AbbVie: Consultancy; Adaptive Biotechnologies: Consultancy; Merck: Consultancy; Pharmacyclics: Consultancy, Research Funding; TG Therapeutics: Consultancy, Research Funding; Verastem: Consultancy, Research Funding; Syros Pharmaceuticals: Consultancy; Sunesis: Consultancy; Zentalis: Consultancy; AstraZeneca: Consultancy, Research Funding; Ascentage Pharma: Consultancy, Research Funding; Eli Lilly: Consultancy; Research to Practice: Honoraria; Celgene: Consultancy; BeiGene: Consultancy; Bristol Myers Squibb: Research Funding. Elagina:AbbVie: Current Employment. Jain:TG Therapeutics: Honoraria, Membership on an entity's Board of Directors or advisory committees; Servier: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Precision Bioscienes: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Incyte: Research Funding; Pfizer: Research Funding; AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Fate Therapeutics: Research Funding; Verastem: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Research Funding; Cellectis: Research Funding; BeiGene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Aprea Therapeutics: Research Funding; Genentech: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive Biotechnologies: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; ADC Therapeutics: Research Funding; AstraZeneca: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Kipps:Oncternal Therapeutics, Inc.: Other: Cirmtuzumab was developed by Thomas J. Kipps in the Thomas J. Kipps laboratory and licensed by the University of California to Oncternal Therapeutics, Inc., which provided stock options and research funding to the Thomas J. Kipps laboratory, Research Funding; Celgene: Honoraria, Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Genentech/Roche: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; VelosBio: Research Funding; Pharmacyclics/ AbbVie, Breast Cancer Research Foundation, MD Anderson Cancer Center, Oncternal Therapeutics, Inc., Specialized Center of Research (SCOR) - The Leukemia and Lymphoma Society (LLS), California Institute for Regenerative Medicine (CIRM): Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Ascerta/AstraZeneca, Celgene, Genentech/F. Hoffmann-La Roche, Gilead, Janssen, Loxo Oncology, Octernal Therapeutics, Pharmacyclics/AbbVie, TG Therapeutics, VelosBio, and Verastem: Membership on an entity's Board of Directors or advisory committees. Broséus:Novartis: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; AstraZeneca: Consultancy, Honoraria; Gilead: Honoraria. Kay:MEI Pharma: Research Funding; Cytomx: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta Pharma: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Juno Theraputics: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Rigel: Membership on an entity's Board of Directors or advisory committees; Agios Pharma: Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Membership on an entity's Board of Directors or advisory committees; Sunesis: Research Funding; Morpho-sys: Membership on an entity's Board of Directors or advisory committees. Purroy:AstraZenica: Current Employment. Utro:IBM: Current Employment. Rhrissorrakrai:IBM: Current Employment. Levovitz:IBM: Current Employment. Parikh:GlaxoSmithKline: Honoraria; Pharmacyclics: Honoraria, Research Funding; AstraZeneca: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; MorphoSys: Research Funding; TG Therapeutics: Research Funding; Merck: Research Funding; AbbVie: Honoraria, Research Funding; Ascentage Pharma: Research Funding; Genentech: Honoraria; Verastem Oncology: Honoraria. Brown:Abbvie, Acerta, AstraZeneca, Beigene, Invectys, Juno/Celgene, Kite, Morphosys, Novartis, Octapharma, Pharmacyclics, Sunesis, TG Therapeutics, Verastem: Consultancy; Gilead, Loxo, Sun, Verastem: Research Funding; Janssen, Teva: Speakers Bureau. Parida:IBM: Current Employment. Neuberg:Madrigak Pharmaceuticals: Current equity holder in publicly-traded company; Pharmacyclics: Research Funding; Celgene: Research Funding. Stilgenbauer:Novartis: Consultancy, Honoraria, Other, Research Funding; Mundipharma: Consultancy, Honoraria, Other, Research Funding; Janssen-Cilag: Consultancy, Honoraria, Other: travel support, Research Funding; Gilead: Consultancy, Honoraria, Other: travel support, Research Funding; GlaxoSmithKline: Consultancy, Honoraria, Other: travel support, Research Funding; Genentech: Consultancy, Honoraria, Other: travel support, Research Funding; Genzyme: Consultancy, Honoraria, Other: travel support, Research Funding; Pharmacyclics: Consultancy, Honoraria, Other, Research Funding; Boehringer-Ingelheim: Consultancy, Honoraria, Other: travel support, Research Funding; Celgene: Consultancy, Honoraria, Other: travel support, Research Funding; F. Hoffmann-LaRoche: Consultancy, Honoraria, Other: travel support, Research Funding; Amgen: Consultancy, Honoraria, Other: travel support, Research Funding; AbbVie: Consultancy, Honoraria, Other: travel support, Research Funding. Getz:Scorpion Therapeutics: Consultancy, Current equity holder in publicly-traded company, Other: Founder; IBM: Research Funding; Pharmacyclics: Research Funding; Broad Institute: Patents & Royalties: MuTect, ABSOLUTE, MutSig, MSMuTect, MSMutSig, POLYSOLVER and TensorQTL. Wu:Pharmacyclics: Research Funding; BionTech: Current equity holder in publicly-traded company.

Abstract: Despite advances in the treatment of chronic lymphocytic leukemia (CLL), the transformation of CLL to an aggressive lymphoma, or Richter's transformation (RT), remains a clinical challenge, as it responds poorly to standard therapies and shortens survival. Recent studies demonstrate that RT, but not underlying CLL, responds to PD-1 checkpoint blockade (CPB) with an overall response rate of 43-65%. Given the central role of T cells in anti-tumor immunity, we hypothesized that differences in T cell populations underlie response and resistance to CPB in RT. We focused on a discovery cohort of 6 patients with RT (4 responders, 2 non-responders) and 2 patients with relapsed/refractory CLL enrolled on a study in which patients were initiated with anti-PD1 therapy (nivolumab 3 mg/kg every 2 weeks), with subsequent concurrent ibrutinib (420 mg daily)(NCT 02420912). We examined a total of 15 serial study marrow specimens collected at treatment initiation and 3 month response evaluation, as well as 2 healthy marrow donors. To systematically discover the T cell populations and states associated with CPB response in RT, we performed single-cell RNA-sequencing (scRNA-seq, 10x Genomics) of non-lymphoma (CD5-CD19-) cells isolated by flow cytometry from marrow samples. A total of 60,727 T and NK cells were captured with average detection of 1001 genes/cell. Using the novel joint clustering approach Conos, 11 transcriptionally distinct clusters of lymphocytes were identified. We first contrasted baseline RT/CLL with normal marrow and observed differences across T cell populations, which we confirmed through the examination of publicly available marrow scRNA-seq data from 28 healthy donors. Compared to normal marrow, RT/CLL marrow was enriched for cytotoxic populations, including both CD8 effector/effector memory (E/EM) (p=0.001, t-test) and cytotoxic CD4 (p=0.001) T cells as well as for cells expressing multiple exhaustion markers, including PDCD1, LAG3 and TIGIT (p=0.001). In contrast, normal marrow contained increased T cells with a naïve-like phenotype (p=0.06). When we focused on the pre-treatment samples from RT patients, RT responders had a larger CD8 E/EM population (p=0.04) and fewer T regulatory cells (p=0.006, t-test) than RT non-responders. Using DESeq2 to compare clusters from all samples, we evaluated if there were differences in gene expression between RT responders and non-responders. CD8 E/EM T cells of RT non-responders showed increased expression of TOX, a recently uncovered master regulator of cell exhaustion (padj =0.00016), while this cell subtype in RT responders upregulated a contrasting program of activating transcription factors as well as the co-stimulatory gene CD226 (padj =0.04). As for CD4 T cells, RT responders revealed an enriched cytotoxic gene program compared to RT non-responders (padjPRF1 5.9 x 10-10, GZMH 6.0 x 10-6, NKG7 6.4 x 10-19). To investigate whether response to CPB therapy for RT was associated with changes in the T cell receptor (TCR) repertoire, and to obtain protein-level validation of transcriptional signatures, we performed single-cell TCR sequencing with paired gene and protein expression (10x Genomics) on pre- and post-therapy samples from a RT responder and a non-responder. Indeed, we confirmed our gene expression findings, including validation of cytotoxic CD4 T cells and the enrichment of CD226 protein in E/EM CD8 T cells in the RT responder. TCR clonal expansion was observed in the RT responder at baseline with persistence of enriched clonotypes following CPB, suggesting the presence of tumor-reactive T cell clones. In contrast, the RT non-responder displayed higher TCR diversity with enriched clonotypes showing increased exhaustion post-CPB (p & lt;0.001, Poisson rate test). Ongoing validation studies include characterizing the phenotypes of corresponding peripheral blood T cells and confirming our findings in an independent, larger cohort of RT patients using multiplex immunofluorescence and flow cytometry. In conclusion, we identified marrow T cell populations enriched in RT patients and described distinct T cell transcriptional programs that delineate RT responders from non-responders. We have thus discovered candidate gene biomarkers that may identify patients likely to respond to CPB therapies and uncovered a CD8 E/EM T cell population that is likely to underlie response to PD-1 CPB. Disclosures Getz: Pharmacyclics: Research Funding; IBM: Research Funding; MuTect, ABSOLTUE, MutSig and POLYSOLVER: Patents & Royalties: MuTect, ABSOLTUE, MutSig and POLYSOLVER. Neuberg:Celgene: Research Funding; Madrigal Pharmaceuticals: Equity Ownership; Pharmacyclics: Research Funding. Rodig:Bristol Myers Squib: Consultancy, Honoraria, Other: Travel Expenses, Speakers Bureau; Kite, a Gilead Company: Research Funding; Affirmed: Research Funding; Merck: Research Funding. Wierda:KITE pharma: Research Funding; Gilead Sciences: Research Funding; AbbVie: Research Funding; Acerta Pharma Inc: Research Funding; Genentech: Research Funding; GSK/Novartis: Research Funding; Pharmacyclics LLC: Research Funding; Sunesis: Research Funding; Miragen: Research Funding; Oncternal Therapeutics Inc.: Research Funding; Cyclcel: Research Funding; Loxo Oncology Inc.: Research Funding; Janssen: Research Funding; Xencor: Research Funding; Juno Therapeutics: Research Funding. Jain:AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Verastem: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Incyte: Research Funding; AstraZeneca: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Servier: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Cellectis: Research Funding; Janssen Pharmaceuticals, Inc.: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Pharmacyclics, an AbbVie company: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Precision Biosciences: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive Biotechnologies: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; ADC Therapeutics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Research Funding. Wu:Neon Therapeutics: Other: Member, Advisory Board; Pharmacyclics: Research Funding.

Abstract: In 2020, the COVID-19 pandemic followed a two-wave pattern in most countries. Hospital admission for COVID-19 in one wave or another could have affected mortality, especially among the older persons. The objective of this study was to evaluate whether the admission of older patients during the different waves, before SARS-CoV-2 vaccination was available, was associated with a different mortality. We compared the mortality rates of patients hospitalized during 2020 before (first wave) and after (second wave) July 7, 2020, included in the SEMI-COVID-19 Registry, a large, multicenter, retrospective cohort of patients admitted to 126 Spanish hospitals for COVID-19. A multivariate logistic regression analysis was performed to control for changes in either the patient or disease profile. As of December 26, 2022, 22,494 patients had been included (17,784 from the first wave and 4710 from the second one). Overall mortality was 20.4% in the first wave and 17.2% in the second wave (risk difference (RD) − 3.2%; 95% confidence interval (95% CI) − 4.4 to − 2.0). Only patients aged 70 and older (10,973 patients: 8571 in the first wave and 2386 in the second wave) had a significant reduction in mortality (RD − 7.6%; 95% CI − 9.7 to − 5.5) (unadjusted relative risk reduction: 21.6%). After adjusting for age, comorbidities, variables related to the severity of the disease, and treatment received, admission during the second wave remained a protective factor. In Spain, patients aged 70 years and older admitted during the second wave of the COVID-19 pandemic had a significantly lower risk of mortality, except in severely dependent persons in need of corticosteroid treatment. This effect is independent of patient characteristics, disease severity, or treatment received. This suggests a protective effect of a better standard of care, greater clinical expertise, or a lesser degree of healthcare system overload.