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The challenge of eradicating leukemia in patients with acute myelogenous leukemia (AML) after initial cytoreduction has motivated modern efforts to combine synergistic active modalities including immunotherapy. Recently, the ETCTN/CTEP 10026 study tested the combination of the DNA methyltransferase inhibitor decitabine together with the immune checkpoint inhibitor ipilimumab for AML/myelodysplastic syndrome (MDS) either after allogeneic hematopoietic stem cell transplantation (HSCT) or in the HSCT-naïve setting. Integrative transcriptome-based analysis of 304 961 individual marrow-infiltrating cells for 18 of 48 subjects treated on study revealed the strong association of response with a high baseline ratio of T to AML cells. Clinical responses were predominantly driven by decitabine-induced cytoreduction. Evidence of immune activation was only apparent after ipilimumab exposure, which altered CD4+ T-cell gene expression, in line with ongoing T-cell differentiation and increased frequency of marrow-infiltrating regulatory T cells. For post-HSCT samples, relapse could be attributed to insufficient clearing of malignant clones in progenitor cell populations. In contrast to AML/MDS bone marrow, the transcriptomes of leukemia cutis samples from patients with durable remission after ipilimumab monotherapy showed evidence of increased infiltration with antigen-experienced resident memory T cells and higher expression of CTLA-4 and FOXP3. Altogether, activity of combined decitabine and ipilimumab is impacted by cellular expression states within the microenvironmental niche of leukemic cells. The inadequate elimination of leukemic progenitors mandates urgent development of novel approaches for targeting these cell populations to generate long-lasting responses. This trial was registered at www.clinicaltrials.gov as #NCT02890329.

Relapsed myeloid disease after allogeneic stem cell transplantation (HSCT) remains largely incurable. We previously demonstrated the potent activity of immune checkpoint blockade in this clinical setting with ipilimumab or nivolumab. To define the molecular and cellular pathways by which CTLA-4 blockade with ipilimumab can reinvigorate an effective graft-versus-leukemia (GVL) response, we integrated transcriptomic analysis of leukemic biopsies with immunophenotypic profiling of matched peripheral blood samples collected from patients treated with ipilimumab following HSCT on the Experimental Therapeutics Clinical Trials Network 9204 trial. Response to ipilimumab was associated with transcriptomic evidence of increased local CD8+ T-cell infiltration and activation. Systemically, ipilimumab decreased naïve and increased memory T-cell populations and increased expression of markers of T-cell activation and costimulation such as PD-1, HLA-DR, and ICOS, irrespective of response. However, responding patients were characterized by higher turnover of T-cell receptor sequences in peripheral blood and showed increased expression of proinflammatory chemokines in plasma that was further amplified by ipilimumab. Altogether, these data highlight the compositional T-cell shifts and inflammatory pathways induced by ipilimumab both locally and systemically that associate with successful GVL outcomes. This trial was registered at www.clinicaltrials.gov as #NCT01822509.

Richter's syndrome (RS) represents one of the foremost challenges in CLL management, and its pathogenesis remains largely undefined. We recently leveraged CRISPR-Cas9 in vivo gene editing to develop mouse models of RS by engineering multiplexed loss-of-function lesions typical of CLL (Atm, Trp53, Chd2, Birc3, Mga, Samhd1) in early stem and progenitor cells [Lineage - Sca-1 + c-kit + (LSK)] from MDR-Cd19Cas9 donor mice. These animals express Cas9-GFP in a B-cell restricted fashion and the leukemogenic MDR lesion, which mimics del(13q) when the sgRNA-transduced LSK cells are transplanted in CD45.1 immunocompetent recipients. Through these methods, we observed not only development of CLL, but also transformation into RS, and even captured a stage where CLL and RS were co-existing in the same animal (CLL/RS). We hypothesized that the molecular events underlying RS development would be markedly distinct from those of CLL and performed transcriptome analysis of FACS-sorted CLL and/or RS cells (5 CLL, 4 CLL/RS, 10 RS) and normal B cell controls from 4 age-matched wild type MDR-Cd19Cas9 mice. We identified a unique transcriptional profile of RS (ANOVA, FDR We asked whether these oncogenic circuitries would be recapitulated in human RS. By correlating the differentially expressed genes in murine RS with those of 7 human RS cases (compared to matched CLL), we identified similar pathway dysregulations with >100 commonly altered genes including upregulated cell cycle regulators (CDK1, CCNA2) and downregulated signaling adapters (ITPKB, MAP3K9). To further dissect gene regulatory networks driving transformation in the mouse, we profiled one CLL and one RS case by single cell ATAC sequencing (scATAC-seq). Consistent with the RNA-seq profiles, we detected increased chromatin accessibility of MYC-family associated transcription factor motifs (MAX, MYCN), and reduced accessibility of the pro-inflammatory STAT2 motif in RS (-log10adjP>50). Functionally, decreased interferon gamma responses were confirmed by the reduced ability of RS cells to phosphorylate STAT1 and STAT3 at 5' and 15' after IFN-gamma stimulation, compared to CLL and normal B cells (Western Blot). To define the genetic landscape underlying these changes, we performed whole genome sequencing analysis, and identified loss of chr12 and chr16 as recurrent events in RS (6/8 cases) and CLL/RS (2/2), but not in CLL cases (0/5). Among the genes encoded by these chromosomes, we identified several epigenetic drivers (Dnmt3a, Crebbp, Setd3/4), MAP kinase family members (Map4k5, Mapk1), cytoskeletal regulators (Hcls1, Rhoj), and interferon family receptors (Ifnar1/2, Ifngr2), suggesting that broad epigenetic modifications together with loss of BCR and interferon signaling molecules represent key events of transforming disease. RS cases were also characterized by a significantly higher number of full chromosome amplifications or deletions (median=6; range: 2-9), as compared to CLL or CLL/RS (1; 0-5, P=0.0008), consistent with the high degree of genomic instability observed in human disease. Finally, we asked whether the observed changes would impact RS therapeutic vulnerabilities, and exposed 15 primary murine RS splenocyte samples to 20 drugs in vitro for 24 hours, followed by CellTiter-Glo assessment of cellular viability. We observed strong sensitivity to the BRD4 inhibitor JQ1 and the mTOR inhibitor everolimus (both reported to interfere with MYC signaling, P In conclusion, we define the evolutionary trajectories and therapeutic vulnerabilities of RS in a mouse model, with unique transcriptional, genetic, and epigenetic features, indicative of broad changes in MYC, IFN and BCR signaling pathways and remarkable similarities with human disease. In-depth analyses of BCR signaling and in vivo treatment studies are underway and will refine mechanistic insights into the biology of RS. Disclosures Davids: Surface Oncology: Research Funding; Eli Lilly and Company: Consultancy; Genentech: Consultancy, Research Funding; Takeda: Consultancy; MEI Pharma: Consultancy; Janssen: Consultancy; Verastem: Consultancy, Research Funding; Ascentage Pharma: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; TG Therapeutics: Consultancy, Research Funding; Astra-Zeneca: Consultancy, Research Funding; Merck: Consultancy; Adaptive Biotechnologies: Consultancy; Research to Practice: Consultancy; AbbVie: Consultancy; MEI Pharma: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Celgene: Consultancy; BeiGene: Consultancy. Letai: Dialectic Therapeutics: Other: equity holding member of the scientific advisory board; Flash Therapeutics: Other: equity holding member of the scientific advisory board; Zentalis Pharmaceuticals: Other: equity holding member of the scientific advisory board. Neuberg: Madrigal Pharmaceuticals: Other: Stock ownership; Pharmacyclics: Research Funding. Wu: Pharmacyclics: Research Funding; BioNTech: Current equity holder in publicly-traded company.

Reconstitution of donor hematopoiesis after allogeneic hematopoietic stem cell transplantation (HSCT) forms the basis for effective graft-versus-leukemia responses, but mixed chimerism is not an infrequent outcome. How the donor and host hematopoietic system interact under conditions of mixed chimerism remains incompletely understood. Multi-modal single cell sequencing platforms are increasingly available and provide information regarding cell identities and interactions at high resolution. However, the analysis of post-transplant immune reconstitution requires consistent distinguishing of donor- and recipient-derived cells, which for sparse single cell sequencing data until now has remained a challenge. Recently, mitochondrial DNA (mtDNA) mutations have been recognized for their potential as personal genetic barcodes that can be detected with mitochondrial single cell assay for transposase-accessible chromatin with sequencing (mtscATAC-seq). We hypothesized that individual-specific mtDNA mutations could provide a sensitive and robust approach for distinguishing donor- from recipient-derived cells, and therefore tested this approach on bone marrow (BM) samples from patients with relapsed acute myeloid leukemia (AML) post-HSCT. We employed ATAC with select cell surface antigen profiling by sequencing (ASAP-seq), which enables the detection of mtDNA mutations within distinct surface marker-defined cell populations alongside chromatin accessibility. We selected serial samples collected from the ETCTN 10026 study, which tested combined decitabine (days 1-5, every 4 weeks, start cycle 0) and ipilimumab (day 1, every 4 weeks, start cycle 1) in relapsed AML post-HSCT. We focused on 13 samples (study entry, on treatment and disease progression) from 3 patients: AML1012 (HSCT from a matched related donor [MRD]), and AML1010 and AML1026 (matched unrelated donor [MUD]-HSCT). In total, we obtained 33,943 ASAP-seq profiles, including 3,283 single T cells. While clustering using single cell chromatin profiles alone only allowed identification of either CD4 + or CD8 + T cells, integration with surface marker expression enabled more detailed annotations of 8 T cell subpopulations and NK cells. Further, phenotypically distinct subpopulations such as CD57 + CD4 + and CD8 + T cells shared highly similar chromatin profiles, and 11.1% of CD4 + and 33.7% of CD8 + T cells would have been mislabeled based on clustering of chromatin profiles alone. Thus, ASAP-seq identified T cell subsets with markedly improved accuracy and resolution than scATAC-seq alone. Upon evaluation of mtDNA mutations to discriminate donor- and recipient-derived single T cells, we found that this was unreliable for MRD-HSCT (AML1012), but highly robust in the setting of MUD-HSCT (AML1010, AML1026), consistent with maternal inheritance of mitochondrial genomes. For the latter two patients, we identified 48 donor- and 26 recipient-specific mtDNA mutations, all with high heteroplasmy (range 82 - 99%). Presence of donor- and recipient-derived mtDNA mutations was mutually exclusive, and recipient-specific mtDNA mutations were also detectable in AML cells. Clinical bulk and mtDNA mutation-based single T cell chimerisms were highly correlated (r = 0.97). AML1010 had sustained complete T cell chimerism (>97%) during study treatment. In AML1026, the mtDNA mutation-based T cell chimerism rose from 55% to 71% after 1 cycle of decitabine and then remained stable until disease progression 3 months later. This was associated with increased percentage of donor-derived CD4 + T cells (45% [study entry] vs. 71% [after 1 cycle of decitabine], p < 0.01), while donor-derived CD8 + T cells remained unchanged at 76%. Across all studied timepoints in AML1026, donor versus recipient skewing was also highest in CD4 + T cell subsets, with fewer naïve (20% vs. 31%, p < 0.01) but more donor-derived CD57 + CD4 + T cells (13% vs. 3%, p < 0.01). We demonstrate that mtDNA mutations can discriminate between donor- and recipient-derived single cells, enabling detection and in-depth characterization of chimeric immune cell dynamics after MUD HSCT. This approach will allow to systematically dissect conditions of mixed chimerism in the post-transplant setting with larger studies. Disclosures DeAngelo: Abbvie: Research Funding; Takeda: Consultancy; Servier: Consultancy; Pfizer: Consultancy; Novartis: Consultancy, Research Funding; Jazz: Consultancy; Incyte: Consultancy; Forty-Seven: Consultancy; Autolus: Consultancy; Amgen: Consultancy; Agios: Consultancy; Blueprint: Research Funding; Glycomimetrics: Research Funding. Neuberg: Madrigal Pharmaceuticals: Other: Stock ownership; Pharmacyclics: Research Funding. Sankaran: Cellarity: Consultancy; Forma: Consultancy; Novartis: Consultancy; Branch Biosciences: Consultancy; Ensoma: Consultancy. Soiffer: Jasper: Consultancy; Jazz Pharmaceuticals, USA: Consultancy; Precision Biosciences, USA: Consultancy; Juno Therapeutics, USA: Other: Data Safety Monitoring Board; Kiadis, Netherlands: Membership on an entity's Board of Directors or advisory committees; Rheos Therapeutics, USA: Consultancy; Gilead, USA: Other: Career Development Award Committee; NMPD - Be the Match, USA: Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy. Garcia: Genentech: Research Funding; Prelude: Research Funding; Pfizer: Research Funding; AstraZeneca: Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Astellas: Consultancy, Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Wu: Pharmacyclics: Research Funding; BioNTech: Current equity holder in publicly-traded company. OffLabel Disclosure: ipilimumab to modulate anti-leukemia immunity in the post-transplant and transplant-naive context

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 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.

Relapse after allogeneic hematopoietic stem cell transplantation (HSCT) remains an unmet medical need. The ETCTN 9204 study evaluated in 71 study subjects if immune checkpoint blockade with anti-CTLA-4 (Ipilimumab (Ipi), n = 43) or anti-PD-1 (Nivolumab (Nivo), n = 28) antibodies could stimulate graft-versus-leukemia (GvL) responses in this setting. We focused mainly on patients (pts) with relapsed AML/MDS, which constituted the majority of pts (n = 38; 54%). Ipi induced both long-term complete remissions (CR; n = 3) and transient CRs (TR; n = 3), while Nivo did not generate any CRs, but 4 patients demonstrated partial remissions (PR). To define the molecular features associated with response to Ipi, we performed bulk transcriptomic analyses of formalin-fixed paraffin-embedded biopsies of sites of AML/MDS involvement (n = 35) collected before and after Ipi treatment from 13 pts. Our analysis of matched pre- and post-Ipi samples of patients with CRs identified 50 differentially expressed genes. By gene ontology analysis, these were enriched for signatures of 'lymphocyte activation' and 'antigen-receptor signaling'. Principal component analysis using these genes separated post-Ipi CR samples as a distinct cluster, transcriptionally apart from pre-Ipi CR samples and from non-responder (NR, n = 15) pre and post-Ipi samples. Of note, post-Ipi CR samples were similar to both pre- and post-Ipi TR samples as well as samples from GvHD/toxicity biopsies (n = 9). Consistent with these findings, we detected increased CD8+ T cell abundance post-Ipi in CR but not NR samples with CIBERSORTx (pre vs post, median score 0.043 vs. 0.56, p < 0.01). Likewise, reconstruction of T cell receptor (TCR) CDR3 sequences using the tool TRUST showed an increase in TCR clonotypes per million reads post-Ipi in CR samples (pre vs post, median 0.33 vs. 1.65, p < 0.05). In sum, response to CTLA-4 blockade is characterized by transcriptional evidence of T cell infiltration and activation within the tumor microenvironment, with similar gene programs observed in the setting of GvHD. To determine if the changes within tissue sites following Ipi are also observed in peripheral blood (PB), we analyzed the immunophenotype and TCR repertoire of T cells from serially collected PB samples from pts with AML/MDS (n = 14) or non-myeloid malignancy (n = 6). In responders and non-responders, exposure to Ipi was associated with decreased naïve, increased effector memory, and increased expression of HLA-DR on central memory T cells (p < 0.05), consistent with T cell differentiation and activation. From 9 of 14 AML/MDS pts (CR = 4, NR = 5), bulk TCR sequencing before and after 1 cycle of Ipi yielded 572,017 PB TCR sequences. Only 776 clonotypes demonstrated significant change in frequency, and these TCRs were detected in greater proportion among responders (613/776 versus NR 163/776, p < 0.01). Thus, Ipi alters the differentiation states of circulating T cells irrespective of response and leads to higher TCR repertoire turnover in CR patients. Of the AML patients achieving PR following Nivo, we also observed transcriptional evidence of CD8+ T cell infiltration in one patient. This signature, however, was not detected in a second such patient. In a separate instance, we had the opportunity to dissect the molecular features of a partial response in a patient with JAK2V617F+ secondary AML following Nivo through single-cell RNA and ATAC-sequencing (scRNA-seq and scATAC-seq, 10x Genomics) of PB mononuclear cells collected serially across 6 timepoints. In total, we analyzed the transcriptomes and chromatin accessibility data from of 27,777 and 28,713 individual cells, respectively. At time of response, non-exhausted CD4+ T cells expanded while both exhausted CD8+ T cells and a malignant subpopulation with increased expression of PD-L1 and features of megakaryocytic differentiation preferentially contracted. The subsequent expansion of a PD-L1- malignant population at progression suggests that decreased leukemic PD-L1 expression was associated with relapse. Altogether, these data highlight the molecular and cellular features of successful reinvigoration of GvL using CTLA-4 blockade, from increased local T cell infiltration and activation in the leukemic microenvironment to peripheral T cell turnover. In addition, the selection of therapy-resistant subclones after PD-1 blockade underscores the need for further high-resolution studies of GvL responses. Disclosures Zeiser: Novartis: Honoraria; Incyte: Honoraria; Malinckrodt: Honoraria. Ritz:Rheos Medicines: Consultancy; LifeVault Bio: Consultancy; Infinity Pharmaceuticals: Consultancy; Falcon Therapeutics: Consultancy; Avrobio: Consultancy; Kite Pharma: Research Funding; Talaris Therapeutics: Consultancy; Equillium: Research Funding; Amgen: Research Funding; TScan Therapeutics: Consultancy. Neuberg:Madrigak Pharmaceuticals: Current equity holder in publicly-traded company; Celgene: Research Funding; Pharmacyclics: Research Funding. Soiffer:alexion: Consultancy; Gilead: Consultancy; Be the Match/ National Marrow Donor Program: Membership on an entity's Board of Directors or advisory committees; Rheos Therapeutics: Consultancy; Juno: Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy; Mana Therapeutics: Consultancy; Precision Bioscience: Consultancy; VOR Biopharma: Consultancy; Kiadis: Membership on an entity's Board of Directors or advisory committees; Cugene: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees. Liu:GV20 Oncotherapy: Consultancy, Membership on an entity's Board of Directors or advisory committees; 3DMed Care: Consultancy; Sanofi: Research Funding; Takeda: Research Funding. Davids:AbbVie: Consultancy; Gilead Sciences: Consultancy; Sunesis: Consultancy; BeiGene: Consultancy; AstraZeneca: Consultancy, Research Funding; Syros Pharmaceuticals: Consultancy; Research to Practice: Honoraria; Pharmacyclics: Consultancy, Research Funding; TG Therapeutics: Consultancy, Research Funding; Verastem: Consultancy, Research Funding; Adaptive Biotechnologies: Consultancy; Janssen: Consultancy; Surface Oncology: Research Funding; Novartis: Consultancy, Research Funding; MEI Pharma: Consultancy, Research Funding; Genentech: Consultancy, Research Funding; Eli Lilly: Consultancy; Zentalis: Consultancy; Celgene: Consultancy; Bristol Myers Squibb: Research Funding; Merck: Consultancy; Ascentage Pharma: Consultancy, Research Funding. Wu:Pharmacyclics: Research Funding; BionTech: Current equity holder in publicly-traded company. OffLabel Disclosure: Ipilimumab and Nivolumab were tested in the setting of relapsed hematological malignancies after allogeneic stem cell transplantation.

Although we have gained a wealth of knowledge from large-scale DNA sequencing studies across blood cancers, we still know little about the functional interplay of the discovered putative drivers in the generation of chronic lymphocytic leukemia (CLL) and its transformation into Richter's syndrome (RS). We have previously observed that CRISPR-Cas9 in vivo B-cell editing of common CLL loss-of-function (LOF) lesions (Atm, Trp53, Chd2, Birc3, Mga, Samhd1) can increase in vitro B cell fitness, but is not sufficient to sustain in vivo B cell survival after 12 months post-transplant. We therefore asked whether combinatorial introduction of mutations was required for CLL development. To this end, we generated transplant lines by in vitro engineering of early stem and progenitor cells (Lineage- Sca-1+ c-kit+ [LSK]) from MDR-/-Cd19-Cas9 donor mice (animals expressing Cas9-GFP in a B-cell restricted fashion and the leukemogenic homozygous MDR lesion, mimicking del(13q)) with pooled lentivirus expressing sgRNAs against the 6 genes of interest and the mCherry marker. Engineered LSKs were then re-transplanted into sub-lethally irradiated immune-competent CD45.1 or immune-deficient NSG recipients (n=35/strain). Parallel control cohorts of equal size were generated by transducing LSKs with a pool of 6 non-targeting sgRNAs. Disease development (B220+CD5+Igk+ cells) was assessed by flow cytometric analysis of bi-monthly peripheral bleeds, starting at 4 months post-transplant, and flow cytometry/IHC were utilized to classify tumors at euthanasia. Analysis of PCR-based targeted NGS of peripheral blood edited tumor cells (GFP+mCherry+) was performed utilizing CRISPResso software to assess presence of the 6 LOF mutations. We observed incidence of circulating CLL in 28/35 (80%) CD45.1 and 27/35 (77%) NSG mice, whereas only 5/35 (14%) CD45.1 and 4/35 (11.4%) NSG from the non-targeting control cohort developed CLL-like disease (P To determine the genetic composition of the 55 leukemias/lymphomas (n=22, 11 and 22, with patterns A, B and C), we interrogated the LOF mutational burden at euthanasia. We observed a median number of 4 LOF mutations (range:1-6), and a high overall frequency of Trp53 lesions (58%). The other 5 drivers were less prevalent (Mga: 26%; Chd2: 21%; Samhd1: 17%; Birc3 and Atm: 13%). Trp53 mutations were predominantly clonal (≥90% indels, P In conclusion, we demonstrate that combinatorial in vivo modeling of CLL-LOF mutations leads not only to CLL development, but also to RS, thus establishing a faithful framework for analysis of genetic and microenvironmental determinants of disease transformation. We are now interrogating genome-wide mutational patterns and clonal architecture of CLL vs. RS, while analyzing their microenvironmental composition. These novel models provide a unique platform to discern critical insights into RS pathogenesis and to discover RS-specific therapeutic vulnerabilities. Disclosures Clement: Edilytics: Current Employment, Current equity holder in private company. Wu:Pharmacyclics: Research Funding; BionTech: Current equity holder in publicly-traded company.

Amongst the novel putative drivers identified by large-scale sequencing studies of chronic lymphocytic leukemia (CLL) is the ribosomal protein RPS15. Mutated in 5.3% of CLL, it co-occurs with heterozygous TP53 alterations in 36% of RPS15-mutated samples. Mutation of this mediator of ribosome maturation and translation is associated with poor disease prognosis and enriched in cohorts with del(17p) and relapsed CLL, suggesting a role in disease progression and therapeutic resistance. However, the impact of RPS15 mutation on B cell function and CLL development, in the presence or absence of TP53 mutation, has yet to be characterized. To this end, we developed overexpression HG3 CLL cell lines modeling four common RPS15 mutations (G134R, H137Y, S138F, and S139F) and a conditional knock-in mouse model of the S138F mutation with and without heterozygous Trp53 deletion (generated by crossing Rps15 and Trp53 mutant mice with Cd19-Cre mice). To characterize the impact of RPS15 mutation on transcription, we performed RNA-sequencing on splenic B cells from 3-month-old Rps15WT, Rps15Het and Rps15Hom mice (3 per cohort). We identified 255 and 670 upregulated and 596 and 777 downregulated genes in the Rps15MT vs Rps15WT mice (Rps15Het and Rps15Hom, respectively; log2FC>0.5, p1, nominal p-value To evaluate whether RPS15 mutant proteins incorporate into ribosomes, we performed polysome profiling of the HG3 lines. All overexpressed RPS15-WT and MT proteins were observed to integrate into the small ribosomal subunit and mature ribosomes, potentially impacting translation. Next, ribosome profiling of HG3 RPS15-WT and S138F cells revealed 2,334 genes with differential translation efficiency (TE) between RPS15-S138F vs WT cells and 2,425 genes between RPS15-S138F vs WT in TP53 knock-out cells (log2FC>0.5, p To determine whether Rps15 mutation can drive CLL-like disease, we engineered 6 novel mouse lines with B cell restricted expression of alterations through crossing with CD19-Cre mice: Rps15WT, Rps15Het, and Rps15Hom mutant mice alone or co-expressing Trp53 deletion. We detected circulating CLL-like (B220+CD5+) cells in 5 of 30 (17%) Rps15Het mice by 20 months of age, but not in 30 age-matched Rps15WT mice. We also detected CLL-like cells in 6 of 30 (20%) Trp53+/- mice by 17 months, indicating that Trp53 deletion alone can induce CLL-like disease. Interestingly, we found CLL-like cells in 2 of 30 Rps15Het/Trp53+/- mice as early as 15 months of age. The cohorts of Rps15Hom and Rps15Hom/Trp53+/- mice, however, have been monitored for 18 months of age with no disease occurrences, indicating that a double dosage of Rps15 mutation may be detrimental to disease formation. Altogether, Rps15 heterozygous mutation can drive CLL development in mice, and our early data hint that co-mutation with Trp53 may shorten the latency of CLL-like disease. Overall, RPS15 mutant protein can incorporate into the ribosome and induce changes in mRNA translation, resulting in MYC activation predominantly in the context of TP53 loss. Our mouse studies indicate that mut-Rps15 drives CLL development, with a more aggressive disease course when combined with Trp53 deletion. Our results collectively suggest that RPS15 and TP53 co-mutation drives CLL development through translational dysregulation and MYC-mediated signaling. Disclosures Neuberg: Pharmacyclics: Research Funding; Celgene: Research Funding; Madrigak Pharmaceuticals: Current equity holder in publicly-traded company. Getz:Broad Institute: Patents & Royalties: MuTect, ABSOLUTE, MutSig, MSMuTect, MSMutSig, POLYSOLVER and TensorQTL; Pharmacyclics: Research Funding; IBM: Research Funding; Scorpion Therapeutics: Consultancy, Current equity holder in publicly-traded company, Other: Founder. Wu:BionTech: Current equity holder in publicly-traded company; Pharmacyclics: Research Funding.

A hotspot mutation within the DNA-binding domain of IKZF3 (IKZF3-L162R) has been identified as a putative driver in chronic lymphocytic leukemia (CLL); however, its functional effects are unknown. We recently confirmed its role as a CLL driver in a B cell-restricted conditional knock-in model. IKZF3 mutation altered mature B cell development and signaling capacity, and induced CLL-like disease in elderly mice (~40% penetrance). Moreover, we found IKZF3-L162R acts as a gain-of-function mutation, altering DNA binding specificity and target selection of IKZF3, and resulting in overexpression of multiple B-cell receptor (BCR) genes. Consistent with the murine data, RNA-sequencing analysis showed that human CLL cells with mut-IKZF3 [n=4] have an enhanced signature of BCR-signaling gene expression compared to WT-IKZF3 [n=6, all IGHV unmutated] (p While mutation in IKZF3 has a clear functional impact on a cardinal CLL-associated pathway, such as BCR signaling, we note that this driver occurs only at low frequency in patients (~3%). Because somatic mutation represents but one mechanism by which a driver can alter a cellular pathway, we examined whether aberrant expression of IKZF3 could also yield differences in BCR-signaling gene expression. We have observed expression of the IKZF3 gene to be variably dysregulated amongst CLL patients through re-analysis of transcriptomic data from two independent cohorts of human CLL (DFCI, Landau et al., 2014; ICGC, Ferreira et al., 2014). We thus examined IKZF3 expression and BCR-signaling gene expression, or the 'BCR score' (calculated as the mean expression of 75 BCR signaling-associate genes) in those cohorts (DFCI cohort, n=107; ICGC cohort, n=274). Strikingly, CLL cells with higher IKZF3 expression (defined as greater than median expression) had higher BCR scores than those with lower IKZF3 expression ( We previously reported that CLL cells with IKZF3 mutation appeared to increase in cancer cell fraction (CCF) with resistance to fludarabine-based chemotherapy (Landau Nature 2015). Instances of increase in mut-IKZF3 CCF upon treatment with the BCR-signaling inhibitor ibrutinib have been reported (Ahn ASH 2019). These studies together suggest an association of IKZF3 mutation with increased cellular survival following either chemotherapy or targeted treatment. To examine whether higher expression of IKZF3 was associated with altered sensitivity to ibrutinib, we performed scRNA-seq analysis (10x Genomics) of two previously treatment-naïve patients undergoing ibrutinib therapy (paired samples, baseline vs. Day 220). We analyzed an average of 11,080 cells per patient (2000 genes/cell). Of note, following ibrutinib treatment, remaining CLL cells expressed higher levels of IKZF3 transcript compared to pretreatment baseline (both p0.05), suggesting that cells with high expression of IKZF3 were selected by ibrutinib treatment. Moreover, we showed that ibrutinib treatment resulted in consistent upregulation of BCR-signaling genes (e.g., CD79B, LYN, GRB2, FOS, RAC1, PRKCB and NFKBIA) (n ranging between 362 to 1374 per experimental group, all p Altogether, these data imply that IKZF3 mutation or overexpression may influence upregulation of BCR-signaling genes and enhance cellular fitness even during treatment with BCR-signaling inhibitors. We highlight our observation that IKZF3 mutation appears to be phenocopied by elevated IKZF3 expression, and suggest that alterations in mRNA or protein level that mimic genetic mutations could be widespread in human cancers. Disclosures Kipps: 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; 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; 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; 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. Wu:BionTech: Current equity holder in publicly-traded company; Pharmacyclics: Research Funding.

Cancer's ability to evolve and adapt is a major challenge to therapeutic success. Fueling this evolution is vast tumor heterogeneity, with constituent clones varying in their genetics, epigenetics and response to therapy. As a field, however, we have yet to couple the genetic alterations present within individual clones to their transcriptional or functional outputs. Here, we applied a novel adaptation of clone tracing that integrates DNA barcoding with single-cell RNA sequencing (scRNA-seq) to HG3, a CLL cell line harboring del(13q) and no other known cancer drivers, to model in vitro responses to front-line chemotherapy with fludarabine and cyclophosphamide at clone-level resolution. To generate a high-diversity barcode library compatible with scRNA-seq, a random pool of 20 base pair DNA barcodes was introduced into the 3'UTR of a reporter gene in a lentiviral expression vector. This viral barcode library was transduced into HG3 cells (at MOI 0.1 to minimize multiple barcode-tagging of cells) and 1.2x106 barcoded cells were sorted and expanded to establish the parental barcoded HG3 population. We subsequently treated this barcoded population with an LD95 combined dose of fludarabine and mafosfamide (the in vitro analog of cyclophosphamide) in 8 parallel experiments. Cell barcodes were sequenced prior to treatment (TP1) and following outgrowth from treatment (TP2) for analysis of clonal composition. 10,000 cells each from TP1 and from 2 of 8 parallel replicates at TP2 were processed for scRNA-seq. We observed a massive decrease in viability across all 8 replicates, with regrowth occurring at 20 days post-treatment. Barcode analysis revealed a marked decrease in clonal diversity from TP1 to TP2 (11,827 to 2,622 ± 380, n=8; or ~78%), and clones that survived treatment did so consistently such that 94% of surviving cells in each replicate had a clonal identity that was present in all 8 replicates. Analysis of clonally-resolved transcriptional profiles revealed that clones consistently fell into one of two stable gene expression states (clusters) prior to treatment, with nominal intermixing between populations. Treatment predominantly selected for clones comprising the smaller of these two clusters (TP1-'high tolerance'), with only a minimal number of resistant clones originating from the larger cluster at TP1 (TP1-'low tolerance'). Pathway and gene set enrichment analysis of these two TP1 clusters demonstrated that TP1-high tolerance had a stark upregulation of common CLL signaling pathways (i.e. WNT and CXCR4, an inflammatory/migratory phenotype) and a reliance on chromatin modification pathways. TP1-low tolerance, on the other hand, exhibited upregulated type 2 antigen presentation and prostaglandin biosynthesis/metabolism which has a known role in driving inflammation and migration in adjacent cells (Wang et al, BMJ 2006). These gene expression states remained stable after treatment, but with the added upregulation of well-described mechanisms of resistance to cyclophosphamide, with TP1-high tolerance exhibiting upregulation of GSTP1, a glutathione S-transferase that is a main mediator of cyclophosphamide metabolism, and TP1-low tolerance exhibiting upregulation of members of the ALDH family thought to ameliorate toxicity from chemotherapy-induced ROS (Andersson et al, Acta Oncologica 1995). Through this work, we resolved the underlying clonal composition of a CLL cell line and observed that the constituent clones exhibit stable and discrete gene expression states that differentially respond to chemotherapy. We noted two different axes of resistance - a more successful avenue that relies on WNT and CXCR4 signaling as well as cyclophosphamide clearance for resistance, and a less-successful avenue that involves clearance of reactive oxygen species for survival. The intersection of these two critical CLL pathways in in vitro resistance to first-line CLL therapy is of particular interest given the FAT1 (WNT regulator) mutations and CXCR4 upregulation frequently seen in chemo-refractory CLL (Messina et al, Blood 2014; Burger et al, Blood 2006), and future efforts will assess the stability and interplay of these two pathways in patient samples collected upon relapse to fludarabine and cyclophosphamide. Further, our approach provides a template for the high-resolution study of tens of thousands of clones and their respective phenotypes in a mixed leukemic population. Disclosures Neuberg: Pharmacyclics: Research Funding; Madrigal Pharmaceuticals: Equity Ownership; Celgene: Research Funding. Wu:Pharmacyclics: Research Funding; Neon Therapeutics: Other: Member, Advisory Board.

Mouse models represent invaluable tools for the systematic evaluation of cancer drivers, yet models that address the impact of putative genetic drivers of chronic lymphocytic leukemia (CLL) on B cell development and function are largely lacking. To study recurrent loss-of-function (LOF) mutations observed in human CLL, we established a transplant model that can rapidly evaluate genetic lesions. First, we crossed mice carrying B-cell restricted Cre expression (Cd19-cre) with mice carrying conditional Cas9-GFP, to generate a strain expressing B cell-restricted Cas9 (Cd19-Cas9). Next, we optimized methods for in vitro engineering of early stem and progenitor cells (Lin- Sca-1+ c-kit+ [LSK]) from Cd19-Cas9 mice using lentivirus expressing sgRNAs (mCherry+)targeting Atm, Trp53, Chd2, Birc3, Mga, or Samhd1. We chose LSKs because of their high transducibility and long-term repopulating potential. Last, we transplanted the single sgRNA-expressing LSKs into sub-lethally irradiated CD45.1 recipient mice, and then confirmed presence of ~45-85% gene-edited sequences (>70% carrying frameshift mutations) in edited B cells (GFP+mCherry+) at 2 months post-transplant, by PCR-based targeted deep sequencing and CRISPResso software analysis. We also verified presence of gene alterations (and putative off-target lesions) at the single cell DNA level (targeted sequencing by Tapestri, Mission Bio). We first asked whether presence of the 6 LOFs could impact B cell developmental trajectories in marrow, spleen and peritoneum at 4 months post-transplant, a time point by which B cells are considered to achieve optimal host reconstitution (n=5/group, including a non-targeting control group). No marked changes were observed in mice with Atmindel, Trp53indel, Chd2indel, Birc3indel or Samhd1indel, as analyzed by flow cytometry. Of interest, however, Mgaindel mice were detected to have increased germinal center (B220+CD95+CD38-) and marginal zone (B220+CD21highCD23-) splenic B cells, and also showed increased B1a (CD5+ B220low CD23- CD43+) and decreased B1b (CD5- B220low CD23- CD43+) cells in the peritoneum (p The overall abundance of edited B cells in spleen and blood of each group was higher (overall median: 17.0%; 90%CI 6.7-58.8%) than the non-targeting control (8.4%; 90%CI 1.6-14.2%) at 4 months post-transplant (n=8/group, p To address this question, we analyzed the transcriptional profiles of edited B cell splenocytes (n=3/group), and compared them to their non-edited counterparts (GFP+mCherry- splenocytes from the same animal), identifying a total of ~3900 differentially expressed genes among the 6 groups (p0.37 for each of the 10 pairs of 5 groups), with the exception of Mgaindel, consistent with its unique phenotype, observed in developmental studies. Gene ontology analyses using Enrichr confirmed commonalities in pathway dysregulations across the 5 similar groups of mice (p In conclusion, we demonstrate that common LOFs typical of patients with CLL lead to increased cellular fitness in B-cell restricted mouse models, while dysregulating pro-survival pathways relevant to B cell development, CLL pathogenesis and more broadly to tumorigenesis. We are currently exploring phenotypic similarities and differences through tailored functional assays, while addressing the relative contribution of each alteration to CLL development in multiplexed edited mouse lines. Disclosures Wang: Mission Bio Inc.: Employment. Jacob:Mission Bio Inc.: Employment. Flynn:Mission Bio Inc.: Employment. Ruff:Mission Bio Inc.: Employment. Jones:Mission Bio Inc.: Employment. Neuberg:Pharmacyclics: Research Funding; Madrigal Pharmaceuticals: Equity Ownership; Celgene: Research Funding. Wu:Neon Therapeutics: Other: Member, Advisory Board; Pharmacyclics: Research Funding.

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 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.

The genetic changes occurring during natural progression and following therapy in CLL have recently been characterized. However, the role of co-existing immune cell populations during disease evolution has not been systematically evaluated. New single cell transcriptome sequencing (scRNA-seq) technologies provide a powerful approach for dissecting the composition and state of complex heterogeneous cell populations such as immune cells. We hypothesized that changes of specific immune features underlie the kinetics of progression of CLL. To this end, we selected a discovery set of CLL samples from 6 patients previously genetically characterized by bulk whole-exome sequencing (WES). Three patients were "slow-progressors" (median time to first treatment [TTFT]: 10.7 years (yrs), range: 7.7-12.2), while the other three were "fast-progressors" (median TTFT: 1.9 yrs, range: 1.3-2.4). We processed paired samples obtained close to the time of diagnosis (T1; median yrs from diagnosis: 2.54, range 0.6-4.2) and close to first treatment (T2; median yrs to TTFT: 0.22, range 0-5.9). Non-CD19+CD5+ cells were isolated from peripheral blood mononuclear cells by flow cytometry for scRNA-seq using the 10X Genomics Chromium Controller platform. Replicates were available in 8 of 12 samples, for a total of 20 specimens. Dimensionality reduction and clustering was then performed by a novel pipeline called MUDAN (multi-sample unified discriminant analysis). We used a mixed-effects model to identify trends in cell type-specific gene expression and proportions over time across patients. We observed changes in the composition of immune cells over time across these patients. In total, 57,069 cells were analyzed (median number of cells per sample: 4,394, range 774-8657) and the mean number of genes per cell was 906 (SD: 116.7). We identified a total of 13 immune cell types, consistent with diverse subsets of T and NK cells, myeloid cells, and hematopoietic stem cells. At T1, fast-progressors had a higher proportion of myeloid cells (dendritic cells, classical and non-classical monocytes, p Over time, we observed a broad upregulation of gene expression across all cell types in both fast and slow-progressors. Within the lymphoid compartment, we observed an upregulation of cell activation (CD3E, CD69, and GITR), chemotaxis (CCL3, CCL4, and XCL2), cytotoxicity (GZMK, GZMA, and NKG7) and pro-inflammatory (INFG, ISG15, and TNF) markers, especially in memory CD4+ T cells. In contrast, memory CD8+ T cells, which were marked by the inhibitory molecule KLRB1(CD161) in our cohort, showed the lowest increase in these gene signatures. TIGIT followed by LILRB2, CD160 and LAG3 were the most upregulated immune checkpoints across time, especially in memory CD4+ and naïve CD8+ T cells, and resting NK cells. LAG3 was revealed to be the only of these immune checkpoints associated with fast-progressors (p Altogether, these findings provide fresh insights of the evolving immune microenvironment during CLL progression. Despite differences in the immune composition at the time of diagnosis, fast and slow-progressors converged into an immune activation state, mostly dominated by CD4+ T cells, ineffective cytotoxic cells and poor immunogenic phagocytic cells that ultimately contributed to the progression of the disease. These results provide a rationale for new immunotherapeutic strategies in previously untreated CLL patients. Disclosures Kipps: Verastem: Membership on an entity's Board of Directors or advisory committees; F. Hoffmann-La Roche Ltd: Consultancy, Research Funding; Celgene: Consultancy; Pharmacyclics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: 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; Verastem: Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Consultancy, Honoraria, Research Funding; Genentech Inc: Consultancy, Research Funding. Wu:Neon Therapeutics: Equity Ownership.

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.

Donor lymphocyte infusion (DLI) is a potentially curative immune therapy for leukemic relapse after allogeneic hematopoietic stem cell transplant (allo-SCT). We previously reported that durable response to DLI for chronic myelogenous leukemia (CML) was associated with reversal of exhaustion of bone marrow-infiltrating T cells. Critical questions remain, however, regarding the exact cellular identities and transcriptional states of those T cell subtypes mediating exhaustion, anti-leukemia responses, and resistance to DLI. To map evolving phenotypic T cell states in situ at single cell resolution, we profiled viable cells isolated from cryopreserved bone marrow mononuclear cells (BMMCs) from a median of 3 timepoints (range: 2-6) before and after DLI from 12 patients with relapsed CML after T-cell depleted allo-SCT, using single cell RNA sequencing (scRNAseq, via the 10x Genomics Chromium platform). For reference, we also characterized a healthy donor marrow sample. Six of 12 patients were long-term responders to CD8-depleted DLI ("R's") and the remaining 6 were nonresponders ("NR's,"). In total, 381,462 cells derived from 43 unique patient-timepoints met our quality metrics, with a median of 2548 mRNA molecules/cell and 8735 cells/sample. By merging data across the cohort and removing batch effects (using the tool Biscuit), we curated a set of 62 distinct cell states, including subtypes of T, B, NK, monocytes, progenitors and CD34+ stem cells, whose identities were determined by both cell type and time point. We evaluated if response to DLI was associated with distinct T cell transcriptional phenotypes ("states"). We observed a marked increase in the number of T cell clusters in post-DLI samples (mean 41, range: 35-46) compared to matched pre-DLI samples, (mean 38, range: 34-41) after controlling for cell number (p-value We next compared global T cell dysfunction between R vs NR cases by summarizing scores for various dysfunction signatures across all T cells. We again observed increased T cell exhaustion signatures in R-pre T cells but also detected increased tolerance and anergy in NR-post T cells, suggesting multiple forms of T cell dysfunction in DLI resistance. We found that the clusters dominated by post-DLI R T cells were characterized by greater diversity of T helper subsets (Th1, Tfh, Th2, Th9, and Th22) and enrichment for exhaustion, type I and II IFN pathways, proinflammatory gene sets and CD8 T cell activation. Clusters dominated by NR T cells displayed increases in Th17 and Treg signatures, anergy and tolerance. Anergic cells were enriched for Treg signatures and did not share cluster membership with tolerant cells, which did not enrich for a specific subtype. Both types expressed only CD3D without CD8A or CD4, suggesting decreased antigen responsiveness. Single cell analysis of TCR repertoires and co-evolving leukemia cells will be updated at the meeting. Altogether, these data suggest that (1) pretreatment T cell phenotypic diversity may be important for DLI response; (2) that DLI increases such diversity differentially in responders than in nonresponders; and (3) even in the absence of clinical response, nonresponders undergo significant T cell phenotypic remodeling. Further studies will involve functional validation of dysfunctional T cell clusters and identification of therapeutic targets for reversing DLI resistance. Disclosures Soiffer: Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees. Wu:Neon Therapeutics: Equity Ownership.

Cancer cell phenotype is controlled by both genetic composition and gene expression. Recent large-scale cancer sequencing studies have revealed extensive intratumoral genetic heterogeneity and have demonstrated its potential impact on clonal evolution and clinical outcome. The most direct approach to uncovering the impact of genetic heterogeneity on cellular phenotype requires integration of genetic and transcriptomic profiles of single cells. Currently, however, RNA and DNA cannot be reliably isolated from the same cell. Here, we demonstrate the feasibility for linking single-cell somatic mutation data with cellular transcriptional heterogeneity through a targeted RNA-based approach. By leveraging a microfluidic platform (Fluidigm BioMarkTMHD system) to perform multiplexed targeted amplification of RNA derived from hundreds of single cells, we have generated a versatile approach for the integrated detection of somatic mutations in relation to specific gene transcripts. We focused on a series of chronic lymphocytic leukemia (CLL) B cells that were previously characterized by bulk whole-exome (WES) and RNA-sequencing (RNA-Seq). We developed 2 classes of assays. First, we generated multiplexed nested quantitative RT-PCR assays of 96 genes with known involvement in CLL biology. Second, to simultaneously detect patient-specific somatic mutations in the same cell, we devised multiplexed pre-amplification primers targeting transcribed regions containing somatic point mutations. These regions were then amplified using paired nested primers, for detection of the wild-type or mutant alleles. We focused on those somatic mutations with detectable expression in bulk CLL RNA (> 5 FPKM by RNA-seq). When applied to either artificial oligonucleotide templates or bulk patient cDNA, these paired wild-type and mutant allele detection assays reliably demonstrated consistent differences in DCT values of >6 cycles. In total, we designed expression assays for 96 genes and 46 mutation detection applied to 5 CLL samples (median of 9 assays/sample, range 6-13). We examined up to 384 single cells from each of 5 samples and from normal CD19+ B cells. Based on expression of housekeeping genes ACTB and B2M, we observed viable expression in 1951 of 2112 cells (92.4%). We could clearly discern that expression of the 96 genes was heterogeneous across 354 single CLL-B cells and could discriminate CLL from 174 normal B cells by principal component analysis. 32 out of 46 (70%) mutation detection assays successfully distinguished between wild-type and mutant alleles and the mutant allele was consistently observed in the originating CLL cells, but not in unrelated CLL or non-leukemic B cells. Our RNA-based estimates of allele frequency agreed with single-cell targeted DNA-based detection of somatic mutations conducted for 3 of 5 CLL samples as well as with frequencies estimated from bulk WES-based cancer cell fraction (CCF) measurements. We applied our integrated assay design to 2 CLL samples known to harbor mutations in the putative CLL driver SF3B1: Patient 1 with bulk CCF of 17% (G742D) and Patient 2 with 87% (K700E). Mutation of this critical spliceosome component broadly changes RNA splicing profiles although the functional impact of these alternative splice variants on CLL biology remains unknown. We generated multiplex assays for SF3B1 mutation detection and for expression of mutation-associated alternative splice variants. Consistent with the bulk-sequencing results, we detected 50 of 373 (13.4%) single CLL cells from Patient 1 with SF3B1 mutation. Moreover, the subset of cells with SF3B1 mutation demonstrated high expression of splice variants relative to wild-type cells (GCC2 and MAP3K7, p< 0.000001). This SF3B1 mutated subclone also displayed reduced expression of RNA splicing factors (BTAF1, DDX17, SNW1, SRSF3, U2SURP; all p Taken together, our study demonstrates the feasibility of linking genotype with gene expression at the RNA level. Furthermore, these analyses reveal the potential for single cell RNA-based analysis to directly uncover the effects of driver mutations on the leukemia cell phenotype. Disclosures Brown: Sanofi, Onyx, Vertex, Novartis, Boehringer, GSK, Roche/Genentech, Emergent, Morphosys, Celgene, Janssen, Pharmacyclics, Gilead: Consultancy.