Clonal and Single Cell Dynamics of Resistance to Graft-Versus-Leukemia (GvL) in Chronic Lymphocytic Leukemia (CLL)

Abstract Although the GvL effect is the curative basis for allogeneic hematopoietic stem cell transplantation, the key cellular and molecular mechanisms driving GvL sensitivity and resistance remain incompletely understood. Using genomic approaches, we systematically characterized the changes in cellular composition and state of CLL and non-CLL cells in two settings of effective GvL: reduced intensity conditioning regimens (RIC) and donor lymphocyte infusion (DLI). We identified 10 patients with CLL progression after RIC, 6 of whom had complete responses before relapse. To define the evolutionary trajectories of CLL cells after RIC, we generated paired whole-exome sequencing data from pre- and post-RIC CLL cells sorted from PBMCs. We used DNA from autologous CD4+ T cells for germline comparison and the algorithms MuTect2 and ABSOLUTE to identify somatic alterations with corresponding cancer cell fractions (CCFs). 5 of the 10 patients had clonal mutations in TP53 and/or SF3B1 pre-transplant. Mutation burden was higher at baseline than previously described for CLL (mean 29.7 vs 17.9 non-silent SNVs/exome, p<0.0001, Student's t-test) but not different from post-transplant. Neither mutations nor altered expression (based on RNA sequencing) of HLA class 1 or 2, or B2M were observed. 8 relapse pairs exhibited complex branched evolution involving CCF shifts of subclonal and clonal mutations whereas two relapse pairs showed CCF shifts only in subclonal mutations. Presence of clonal shifts associated with active immunity (off immune suppression or presence of chronic graft-vs-host disease; p=0.02, Fisher's exact test), longer time to relapse (>1 vs <1 year; p=0.02), and achievement of complete response (p=0.05). These data suggest that immune selective pressure by GvL can lead to gain of resistance capability, potentially facilitated by the replacement of dominant clones. We likewise saw diverse clonal trajectories in 2 index cases of DLI response followed by relapse, either 11 [branched evolution] or 1.5 [linear] years after DLI. To deeply examine co-evolution of CLL and immune cells during DLI-relapse, we performed single cell RNA sequencing of both cell types collected from 4 paired PBMC samples representing either pre- or post-(relapsed)-DLI time points. Using the inDrop platform, we profiled a median of 11,686 (range: 9,101-16,756) cells per sample with a median of 5,363 CD19+ CD5+ expressing CLL cells (range: 3,622-9,463). We first sought to define the transcriptional heterogeneity underlying CLL cells during DLI relapse. Data visualization using t-distributed stochastic neighbor embedding plots revealed broad transcriptional shifts in CLL clusters from pre- to post-DLI and also showed the complexity of transcriptional substructure to more closely relate to a patient's own genomic structure rather than a common CLL phenotype, in contrast to prior studies. DLI-relapsed CLL cells in both patients were marked by upregulation of CXCR4 and members of the RhoGTPase family, suggesting migration capacity and cytoskeletal remodeling to play a role in GvL escape. GO term enrichment analysis identified DLI sensitive CLL cells in these cases to associate with regulation of lipid and lipoprotein metabolism and interferon signaling. We then determined parallel changes in PBMC immune states over time, which were subtle and not related to time point. To determine if the leukemic microenvironment can differentially affect immune states, we profiled, in total, 32,777 single bone marrow mononuclear cells (BMMC) from pre-DLI, during DLI response, and post-DLI relapse for one patient. Unlike PBMCs, BMMC-derived T cells clustered preferentially by time point, then state of differentiation. DLI response induced a pronounced shift in all T cell states, reflected by upregulation of NFKB and PI3K-AKT signaling; a dysfunctional state marked by metallothionein family expression, recently discovered in murine single cell studies, was unique to the post-DLI relapse timepoint in this patient. Altogether, these data suggest that GvL selective pressure can shape genetic evolutionary trajectories; scRNA-seq analysis of the 2 informative DLI cases is consistent with the notion that the CLL microenvironment shapes immune states during GvL response and relapse. Ongoing studies will dissect the molecular pathways governing these trajectories to suggest therapeutic strategies for overcoming GvL resistance. Disclosures Brown: Boehringer: Consultancy; Sunesis: Consultancy; Morphosys: Membership on an entity's Board of Directors or advisory committees; Gilead: Consultancy, Research Funding; Invectys: Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy; Verastem: Consultancy, Research Funding; Celgene: Consultancy; Beigene: Membership on an entity's Board of Directors or advisory committees; Genentech: Consultancy; Loxo: Consultancy; TG Therapeutics: Consultancy; Sun Pharmaceutical Industries: Research Funding; Roche/Genentech: Consultancy; Acerta / Astra-Zeneca: Membership on an entity's Board of Directors or advisory committees; Abbvie: Consultancy; Pharmacyclics: Consultancy. Ho:Jazz Pharmaceuticals: Consultancy. Soiffer:Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees. Wu:Neon Therapeutics: Equity Ownership.

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Single-Cell Transcriptomic and Proteomic Diversity in Multiple Myeloma

Blood ◽

10.1182/blood-2019-131005 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 5531-5531

Author(s):

Reyka G Jayasinghe ◽

Yige Wu ◽

Ying Zhu ◽

Ruiyang Liu ◽

Mark A. Fiala ◽

...

Keyword(s):

Multiple Myeloma ◽

T Cells ◽

Single Cell ◽

Board Of Directors ◽

Rna Sequencing ◽

Research Funding ◽

Plasma Cells ◽

Malignant Cells ◽

Advisory Committees ◽

Equity Ownership

Multiple myeloma (MM) is a disease defined by clonal proliferation of abnormal plasma cells from B-cells. Improved treatments for MM have led to improving overall lifespan, but still remains incurable due to acquired resistance to therapy and tumor heterogeneity. Single-cell RNA sequencing studies (scRNA-seq) of MM patients have highlighted the significant inter-individual heterogeneity and subclonal architecture of the malignant plasma cell populations, emphasizing the importance of developing personalized therapies specific to a patients molecular pathogenesis. In this study, we have integrated scRNA-seq with single-cell proteomics (sc-Prot) for 10 plasma cells and CD4+ T cells to validate and prioritize driver events in malignant cells and evaluate the tumor microenvironment. This effort will be expanded to another 10 cases to further integrate scRNA-seq, snATAC-seq, whole exome sequencing and bulk RNA-sequencing on a fraction of the cells isolated from bone marrow. The remaining cells will be sorted using FACS to select for specific malignant and immune cells including 40 plasma cells, 15 CD4+ T and 15 CD8+ T cells. These sorted cells will be profiled with a scProt technology (BASIL nanoPOTS) to illuminate their cell-to-cell heterogeneity. In our pilot study comparing bulk and single-cell proteomic data of a single patient's plasma cells (CD138+) for 400 representative proteins, while a majority of expression signatures are concurrent between the two methods, some signaling pathways including translation and apoptotic cleavage are discordant. Our findings stress the importance of interrogating subpopulations of immune and malignant cells at the single-cell level to further refine the transcriptomic and proteomic heterogeneity of MM in a cell type specific manner. With the aid of single-cell technology, we have assessed the heterogeneity of malignant and immune cell types to evaluate transcriptomic and proteomic changes contributing to altering the interplay between the immune environment and tumor cells. Disclosures Fiala: Incyte: Research Funding. Rettig:WashU: Patents & Royalties: Patent Application 16/401,950. O'Neal:Wugen: Patents & Royalties: Patent Pending; WashU: Patents & Royalties: Patent Pending. DiPersio:WUGEN: Equity Ownership, Patents & Royalties, Research Funding; Macrogenics: Research Funding, Speakers Bureau; Cellworks Group, Inc.: Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy; Magenta Therapeutics: Equity Ownership; RiverVest Venture Partners Arch Oncology: Consultancy, Membership on an entity's Board of Directors or advisory committees; NeoImmune Tech: Research Funding; Karyopharm Therapeutics: Consultancy; Incyte: Consultancy, Research Funding; Amphivena Therapeutics: Consultancy, Research Funding; Bioline Rx: Research Funding, Speakers Bureau. Vij:Bristol-Myers Squibb: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Genentech: Honoraria; Janssen: Honoraria; Karyopharm: Honoraria; Sanofi: Honoraria; Takeda: Honoraria, Research Funding.

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Pre-Existing T Cell Subsets Determine Anti-PD1 Blockade Response in Richter's Transformation

Blood ◽

10.1182/blood-2020-138601 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 42-43

Author(s):

Prajish Iyer ◽

Lu Yang ◽

Zhi-Zhang Yang ◽

Charla R. Secreto ◽

Sutapa Sinha ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Single Cell ◽

Board Of Directors ◽

Peripheral Blood ◽

Research Funding ◽

Gene Signature ◽

T Cell Subsets ◽

Rna Seq ◽

Advisory Committees

Despite recent developments in the therapy of chronic lymphocytic leukemia (CLL), Richter's transformation (RT), an aggressive lymphoma, remains a clinical challenge. Immune checkpoint inhibitor (ICI) therapy has shown promise in selective lymphoma types, however, only 30-40% RT patients respond to anti-PD1 pembrolizumab; while the underlying CLL failed to respond and 10% CLL patients progress rapidly within 2 months of treatment. Studies indicate pre-existing T cells in tumor biopsies are associated with a greater anti-PD1 response, hence we hypothesized that pre-existing T cell subset characteristics and regulation in anti-PD1 responders differed from those who progressed in CLL. We used mass cytometry (CyTOF) to analyze T cell subsets isolated from peripheral blood mononuclear cells (PBMCs) from 19 patients with who received pembrolizumab as a single agent. PBMCs were obtained baseline(pre-therapy) and within 3 months of therapy initiation. Among this cohort, 3 patients had complete or partial response (responders), 2 patients had rapid disease progression (progressors) (Fig. A), and 14 had stable disease (non-responders) within the first 3 months of therapy. CyTOF analysis revealed that Treg subsets in responders as compared with progressors or non-responders (MFI -55 vs.30, p=0.001) at both baseline and post-therapy were increased (Fig. B). This quantitative analysis indicated an existing difference in Tregs and distinct molecular dynamic changes in response to pembrolizumab between responders and progressors. To delineate the T cell characteristics in progressors and responders, we performed single-cell RNA-seq (SC-RNA-seq; 10X Genomics platform) using T (CD3+) cells enriched from PBMCs derived from three patients (1 responder: RS2; 2 progressors: CLL14, CLL17) before and after treatment. A total of ~10000 cells were captured and an average of 1215 genes was detected per cell. Using a clustering approach (Seurat V3.1.5), we identified 7 T cell clusters based on transcriptional signature (Fig.C). Responders had a larger fraction of Tregs (Cluster 5) as compared with progressors (p=0.03, Fig. D), and these Tregs showed an IFN-related gene signature (Fig. E). To determine any changes in the cellular circuitry in Tregs between responders and progressors, we used FOXP3, CD25, and CD127 as markers for Tregs in our SC-RNA-seq data. We saw a greater expression of FOXP3, CD25, CD127, in RS2 in comparison to CLL17 and CLL14. Gene set enrichment analysis (GSEA) revealed the upregulation of genes involved in lymphocyte activation and FOXP3-regulated Treg development-related pathways in the responder's Tregs (Fig.F). Together, the greater expression of genes involved in Treg activation may reduce the suppressive functions of Tregs, which led to the response to anti-PD1 treatment seen in RS2 consistent with Tregs in melanoma. To delineate any state changes in T cells between progressors and responder, we performed trajectory analysis using Monocle (R package tool) and identified enrichment of MYC/TNF/IFNG gene signature in state 1 and an effector T signature in state 3 For RS2 after treatment (p=0.003), indicating pembrolizumab induced proliferative and functional T cell signatures in the responder only. Further, our single-cell results were supported by the T cell receptor (TCR beta) repertoire analysis (Adaptive Biotechnology). As an inverse measure of TCR diversity, productive TCR clonality in CLL14 and CLL17 samples was 0.638 and 0.408 at baseline, respectively. Fifty percent of all peripheral blood T cells were represented by one large TCR clone in CLL14(progressor) suggesting tumor related T-cell clone expansion. In contrast, RS2(responder) contained a profile of diverse T cell clones with a clonality of 0.027 (Fig. H). Pembrolizumab therapy did not change the clonality of the three patients during the treatment course (data not shown). In summary, we identified enriched Treg signatures delineating responders from progressors on pembrolizumab treatment, paradoxical to the current understanding of T cell subsets in solid tumors. However, these data are consistent with the recent observation that the presence of Tregs suggests a better prognosis in Hodgkin lymphoma, Follicular lymphoma, and other hematological malignancies. Figure 1 Disclosures Kay: Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Rigel: Membership on an entity's Board of Directors or advisory committees; Juno Theraputics: Membership on an entity's Board of Directors or advisory committees; Agios Pharma: Membership on an entity's Board of Directors or advisory committees; Cytomx: Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; 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; Sunesis: Research Funding; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding; MEI Pharma: Research Funding. Ansell:AI Therapeutics: Research Funding; Takeda: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Bristol Myers Squibb: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; ADC Therapeutics: Research Funding. Ding:Astra Zeneca: Research Funding; Abbvie: Research Funding; Octapharma: Membership on an entity's Board of Directors or advisory committees; MEI Pharma: Membership on an entity's Board of Directors or advisory committees; alexion: Membership on an entity's Board of Directors or advisory committees; Beigene: Membership on an entity's Board of Directors or advisory committees; DTRM: Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding. OffLabel Disclosure: pembrolizumab

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Single Cell RNA Sequencing Identifies a Crucial Role for ASXL1 in Neutrophil Development

Blood ◽

10.1182/blood-2019-125022 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 212-212

Author(s):

Theodore Braun ◽

Theresa Lusardi ◽

Trevor Enright ◽

Zachary Schonrock ◽

Cody Coblentz ◽

...

Keyword(s):

Clinical Trial ◽

Single Cell ◽

Board Of Directors ◽

Rna Sequencing ◽

Crucial Role ◽

Research Funding ◽

Advisory Committees ◽

Single Cell Rna Sequencing ◽

Equity Ownership ◽

Specific Granule

Single Cell RNA Sequencing Identifies a Crucial Role for ASXL1 in Neutrophil Development Additional sex combs-like 1 (ASXL1) is a polycomb-associated protein that is essential for normal hematopoiesis. ASXL1 is recurrently mutated across the spectrum of myeloid malignancies including myelodysplastic syndromes, myeloproliferative neoplasms and Acute Myeloid Leukemia. ASXL1 mutations are also found in the premalignant disorders clonal hematopoiesis of indeterminate potential and clonal cytopenias of indeterminate potential. In all cases, ASXL1 mutations are associated with more aggressive disease biology and resistance to treatment. Mutations in ASXL1 broadly dysregulate the hematopoietic system, opening chromatin at genes associated with differentiation and self-renewal, predisposing to malignant transformation. However, in spite of this, the specific role of ASXL1 at different phases of hematopoiesis remains unknown. Indeed, the development of therapeutic approaches for ASXL1-mutant malignancies will require a nuanced understanding of the role of ASXL1 in directing normal blood development to maximize on target effects and minimize toxicity. ASXL1 mutations are commonly identified in myeloid disorders with dysplasia. In the neutrophil lineage, morphologic dysplasia is associated with nuclear-cytoplasmic dyssynchrony, where neutrophils demonstrate differences in nuclear and cytoplasmic differentiation (i.e. hypolobated nuclei or hypogranular cytoplasm). Given its associated with dysplasia, we hypothesized that ASXL1 plays a fundamental role in neutrophil maturation. To investigate this, we performed single cell RNA sequencing (scRNA-seq) on lineage depleted bone marrow from MX-1 Cre/Asxl1FL/FL mice (Asxl1KO) or cre negative littermate controls (Asxl1WT). This analysis revealed a loss of multi-lineage differentiation potential in response to Asxl1 deletion with the most prominent effects noted in myeloid differentiation. Although the neutrophil-primed granulocyte-macrophage progenitors appeared relatively normal, a differentiation block was identified at the transition between promyelocytes and myelocytes. Specifically, Asxl1KO mice demonstrated a failure to normally upregulate specific granule constituents. Although key differentiation-associated transcription factors are present in the appropriate precursor populations, they appear to require normal Asxl1 function to effectively initiate transcription of specific granule genes. This is the first description of a crucial role for Asxl1 in terminal neutrophil differentiation. Furthermore, the failure to effectively upregulate specific granule genes in Asxl1 deficient mice may provide a mechanistic explanation for the dysplasia-associated hypogranular neutrophils present in dysplastic disorders with mutant ASXL1. Disclosures Druker: Vivid Biosciences: Membership on an entity's Board of Directors or advisory committees, Other: Stock options; Beat AML LLC: Other: Service on joint steering committee; GRAIL: Equity Ownership, Other: former member of Scientific Advisory Board; CureOne: Membership on an entity's Board of Directors or advisory committees; Beta Cat: Membership on an entity's Board of Directors or advisory committees, Other: Stock options; Monojul: Other: former consultant; ALLCRON: Membership on an entity's Board of Directors or advisory committees; Amgen: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Aptose Biosciences: Consultancy, Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Patient True Talk: Consultancy; The RUNX1 Research Program: Membership on an entity's Board of Directors or advisory committees; Novartis: Other: PI or co-investigator on clinical trial(s) funded via contract with OHSU., Patents & Royalties: Patent 6958335, Treatment of Gastrointestinal Stromal Tumors, exclusively licensed to Novartis, Research Funding; Pfizer: Other: PI or co-investigator on clinical trial(s) funded via contract with OHSU., Research Funding; Merck & Co: Patents & Royalties: Dana-Farber Cancer Institute license #2063, Monoclonal antiphosphotyrosine antibody 4G10, exclusive commercial license to Merck & Co; Dana-Farber Cancer Institute (antibody royalty): Patents & Royalties: #2524, antibody royalty; OHSU (licensing fees): Patents & Royalties: #2573, Constructs and cell lines harboring various mutations in TNK2 and PTPN11, licensing fees ; Cepheid: Consultancy, Honoraria; Burroughs Wellcome Fund: Membership on an entity's Board of Directors or advisory committees; Blueprint Medicines: Consultancy, Equity Ownership, Membership on an entity's Board of Directors or advisory committees; ICON: Other: Scientific Founder of Molecular MD, which was acquired by ICON in Feb. 2019; Gilead Sciences: Other: former member of Scientific Advisory Board; Celgene: Consultancy; Pfizer: Research Funding; Aileron Therapeutics: #2573, Constructs and cell lines harboring various mutations in TNK2 and PTPN11, licensing fees , Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Patents & Royalties, Research Funding; Bristol-Myers Squibb: Other: PI or co-investigator on clinical trial(s) funded via contract with OHSU., Research Funding.

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Single-Cell Analysis of the Classical Hodgkin Lymphoma Immune Environment Reveals a Clonally-Expanded CD8+ T Cell Population with a Cytotoxic Phenotype

Blood ◽

10.1182/blood-2020-137171 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 40-41

Author(s):

Jovian Yu ◽

Xiufen Chen ◽

James Godfrey ◽

Girish Venkataraman ◽

Sonali M. Smith ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Single Cell ◽

Board Of Directors ◽

Cd8 T Cells ◽

Research Funding ◽

Immune Cell ◽

Clonal Expansion ◽

Advisory Committees ◽

Cell Clusters

Introduction: Classical Hodgkin lymphoma (cHL) is characterized by a robust and complex immune cell infiltrate and the rare presence of malignant Hodgkin-Reed-Sternberg (HRS) cells. At the genetic level, HRS cells recurrently acquire alterations that lead to defective antigen presentation (β2 microglobulin mutations) and mediate T cell dysfunction (PD-L1 copy gains/amplifications) in order to subvert host immune surveillance. The clinical relevance of PD-L1 protein over-expression in cHL is clear, as response rates to PD-1 blockade therapy are extremely high among patients with relapsed/refractory (r/r) disease. Despite its remarkable efficacy, the cells that mediate response to anti-PD-1 therapy in cHL remain undefined. Recent analyses have highlighted a possible role for CD4+ T cells in mediating the clinical activity of anti-PD-1 therapy in cHL. CD4+ T cells significantly outnumber CD8+ T cells in cHL lesions and are more frequently juxtaposed to HRS cells in situ. Furthermore, HLA class II expression on HRS cells predicted higher complete response rates to PD-1 blockade therapy in r/r cHL patients. However, a candidate T cell population capable of specific reactivity to antigens expressed by HRS cells has yet to be identified. This information is critical as such T cells might be functionally reinvigorated to mediate HRS cell elimination following PD-1 blockade therapy. In order to address this key knowledge gap, we analyzed data at single cell (sc) resolution using paired RNA and T cell receptor (TCR) sequencing in 9 diagnostic cHL and 5 reactive lymph node (RLN) specimens. Methods: Sequencing was performed using the 10x Genomics Chromium Single Cell 5' Gene Expression and V(D)J workflows. B-cell depletion of each sample was achieved using CD19 microbeads and negative selection to enrich T cell populations. Reads were analyzed and aligned with CellRanger (v3.1.0) and Seurat (v3.2.0) was used to conduct clustering by a shared nearest neighbor (SNN) graph on scRNA data. TCR sequencing data was integrated using scRepertoire (v1.0.0). Results: A detailed map of the immune cell states in cHL was created using scRNA-seq (10X) data on 79,085 cells from 9 cHL (52,602 cells) and 5 RLN samples (26,484 cells) expressing a total of 21,421 genes (mean 5649 cells/sample; mean 2849 mRNA reads/cell). Dimensionality reduction and unsupervised graph-based clustering revealed 21 distinct cell type and activation state clusters, including T cells, NK cells, macrophages, and dendritic cells (Fig 1A-B). A cluster identifying HRS cells was not observed, consistent with a recently published report. Ten T cell clusters were identified (47,573 cells), including naive- and memory-like T cells, effector/cytotoxic CD8+ T cells, regulatory T cells, and T follicular helper cells. Unexpectedly, a putative exhausted T cell cluster was not clearly observed. The relative contributions of cHL and RLNs cases to these clusters are shown in Fig 1C. Paired TCR sequencing was available for 23,943 cells. Overall TCR diversity was lower among cHL samples compared to RLN specimens (Fig 1D). In cHL samples, modest clonal expansion within regulatory T cell and memory CD4+ T cell clusters was observed, but the most striking clonal expansion occurred among cells assigned to effector/cytotoxic CD8+ T cell clusters - a finding not observed in most RLN specimens (Fig 1E). Clonally-expanded effector/cytotoxic CD8+ T cells displayed high expression of granzymes (GZMA, GZMH, GZMK), cytokines (TNF, IFNG) and chemokines (CCL4/CCL5), and modest expression of exhaustion markers (PDCD1, ENTPD1, HAVCR2, ITGAE), contrasting with data from single-cell analyses of solid tumors. Clonal expansion of effector/cytotoxic CD8+ T cells was particularly robust in EBV-positive cHLs, likely due to recognition of viral-derived epitopes displayed on HRS cells (Fig 1F). Phenotypic and functional validation of key immune cell clusters in cHL specimens using spectral cytometry is underway and will be reported at the meeting. Conclusions: For the first time, our data have unveiled the nature of the T cell repertoire in cHL at single cell resolution. Our results reveal a recurrent pattern of clonal expansion within effector CD8+ cells, which may be the HRS antigen-specific T cells that mediate response to PD-1 blockade. This hypothesis requires confirmation through similar analyses of pre- and on-treatment biopsies of cHL patients receiving anti-PD-1 therapy. Disclosures Godfrey: Gilead: Research Funding; Merck: Research Funding; Verastem: Research Funding. Venkataraman:EUSA Pharma: Speakers Bureau. Smith:Janssen: Consultancy; BMS: Consultancy; TG Therapeutics: Consultancy, Research Funding; Genentech/Roche: Consultancy, Other: Support of parent study and funding of editorial support, Research Funding; Karyopharm: Consultancy, Research Funding; FortySeven: Research Funding; Pharmacyclics: Research Funding; Acerta: Research Funding; Celgene: Consultancy, Research Funding. Kline:Kite/Gilead: Speakers Bureau; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees; Merck: Research Funding; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Verastem: Membership on an entity's Board of Directors or advisory committees, Research Funding.

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Characterization of T-Cell Exhaustion in Rapid Progressing Multiple Myeloma Using Cross Center Scrna-Seq Study

Blood ◽

10.1182/blood-2021-153863 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 401-401

Author(s):

William Pilcher ◽

Beena E Thomas ◽

Swati S Bhasin ◽

Reyka G Jayasinghe ◽

Adeeb H Rahman ◽

...

Keyword(s):

Multiple Myeloma ◽

T Cells ◽

T Cell ◽

Single Cell ◽

Board Of Directors ◽

Research Funding ◽

Surface Marker ◽

Cell Cluster ◽

Advisory Committees ◽

Surface Marker Expression

Abstract Introduction: Multiple myeloma (MM) is a complex hematological malignancy with the heterogenous immune bone marrow (BM) environment contributing to tumor growth, drug resistance, and immune escape. T-Cells play a critical role in the clearance of malignant plasma cells from the tumor environment. However, T-Cells in multiple myeloma demonstrate impaired cytotoxicity, proliferation, and cytokine production due to the activation of immune inhibitory receptors from ligands produced by the myeloma cells. In this study, we investigate the behavior of T-Cells in MM patients by using single-cell RNA-Seq (scRNA-Seq) to compare the transcriptomic profiles of BM T-Cells of patients with rapid progressing (FP; PFS < 18mo) and non-progressing (NP; PFS > 4yrs) disease. Methods: Newly diagnosed MM patients (n=18) from the Multiple Myeloma Research Foundation (MMRF) CoMMpass study (NCT01454297) were identified as either rapid progressors or non-progressors based on their progression free survival since diagnosis. To capture transcriptomic data, scRNA-Seq was performed on 48 aliquots of frozen CD138-negative BM cells at three medical centers/universities (Beth Israel Deaconess Medical Center, Boston, Washington University in St. Louis, and Mount Sinai School of Medicine, NYC). Samples were collected at diagnosis prior to treatment. Surface marker expression for 29 proteins was captured for at least one sample per patient using CITE-Seq. After integration and batch correction, clustering was performed to identify cells of T or NK lineage. Uniform Manifold Approximation and Projection (UMAP) and differential expression were used to identify T-Lymphoid subtypes, and differences in NP and FP samples. Results: In this study, single cell transcriptomic profiles were identified for ~102,207 cells from 48 samples of 18 MM patients. 40,328 T (CD3+) and NK (CD3-, NKG7+) cells were isolated, and subclustered for further analysis (Fig 1A). Using differentially expressed markers for each cluster, the T-Lymphoid subset was refined into seven subtypes, consisting of various CD4+ T-Cells, CD8+ T-Cells, and NK cells (Fig 1B). The CD8+ cells were divided into three distinct phenotypes, namely a GZMK-, GZMB- CD8+ T-Cell cluster, a GZMK+ CD8+ Exhausted T-Cell cluster enriched in TIGIT and multiple chemokines (CCL3, CCL4, XCL2), and a GZMB+ NkT cluster enriched in cytolytic markers (PRF1, GNLY, NKG7) (Fig 1C). Differential expression between NP and FP samples in this CD8+ subset showed enrichment of the NkT cytotoxic markers in NP samples, while FP samples were enriched in the CD8+ Exhausted chemokine markers (Fig 1D). Furthermore, the proportion of CD8+ Exhausted T-Cells was enriched in FP samples (p.val < 0.05) (Fig 1E). Exhaustion markers were measured through both RNA and surface marker levels. In RNA, TIGIT was uniquely associated with the FP-enriched CD8+ Exhausted T-Cell cluster, and CD160 was uniquely expressed in FP samples (Fig 1F). CITE-Seq surface marker expression confirms enrichment of both TIGIT and PD1 in the CD8+ Exhausted T-Cell cluster, and along with more exhaustion in FP samples (p.val < 0.01). Conclusion: In this study, we have identified significant differences in T-Cell activity in patients with non-progressing and rapid-progressing multiple myeloma. T-Cells in rapid progressing patients appear to be in a suppressed state, with low cytolytic activity and enriched exhaustion markers. This GZMK+ T-Cell population shows strong similarities with an aging-associated subtype of effector memory T-Cells found to be enriched in older populations (Mogilenko et al, Immunity 54, 2021). These findings will be further validated in an expanded study, consisting both of a larger number of samples, and multiple samples at different timepoints from the same patient. Figure 1 Figure 1. Disclosures Jayasinghe: MMRF: Consultancy; WUGEN: Consultancy. Vij: BMS: Research Funding; Takeda: Honoraria, Research Funding; Sanofi: Honoraria, Research Funding; BMS: Honoraria; GSK: Honoraria; Oncopeptides: Honoraria; Karyopharm: Honoraria; CareDx: Honoraria; Legend: Honoraria; Biegene: Honoraria; Adaptive: Honoraria; Harpoon: Honoraria. Kumar: Carsgen: Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Beigene: Consultancy; Bluebird Bio: Consultancy; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Tenebio: Research Funding; Oncopeptides: Consultancy; Antengene: Consultancy, Honoraria; Roche-Genentech: Consultancy, Research Funding; Merck: Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Amgen: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Avigan: Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Research Funding; Kite Pharma: Consultancy, Research Funding; Juno: Membership on an entity's Board of Directors or advisory committees; Partner Tx: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Aviv MedTech Ltd: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Legend Biotech: Membership on an entity's Board of Directors or advisory committees; Chugai: Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy; Parexcel: Consultancy; Takeda: Consultancy; Sanofi: Consultancy.

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Comprehensive Genetic Interrogation of Circulating Multiple Myeloma Cells at Single Cell Resolution

Blood ◽

10.1182/blood.v128.22.800.800 ◽

2016 ◽

Vol 128 (22) ◽

pp. 800-800

Author(s):

Jens G Lohr ◽

Sora Kim ◽

Joshua Gould ◽

Birgit Knoechel ◽

Yotam Drier ◽

...

Keyword(s):

Single Cell ◽

Board Of Directors ◽

Rna Sequencing ◽

Research Funding ◽

Single Cells ◽

Advisory Committees ◽

Single Cell Rna Sequencing ◽

Genomic Characterization ◽

Whole Transcriptome

Abstract Continuous genomic evolution has been a major limitation to curative treatment of multiple myeloma (MM). Frequent monitoring of the genetic heterogeneity in MM from blood, rather than serial bone marrow (BM) biopsies, would therefore be desirable. We hypothesized that genomic characterization of circulating MM cells (CMMCs) recapitulates the genetics of MM in BM biopsies, enables MM classification, and is feasible in the majority of MM patients with active disease. Methods: To test these hypotheses, we developed a method to enrich, purify and isolate single CMMCs with a sensitivity of at least 1:10(5). We then performed DNA- and RNA-sequencing of single CMMCs and compared them to single BM-derived MM cells. We determined CMMC numbers in 24 randomly selected MM patient samples and compared them to numbers of circulating MM cells obtained by flow cytometry. We performed single-cell whole genome amplification of single cells from 10 MM patients, and targeted sequencing of the 35 most recurrently mutated loci in MM. A total of 568 single primary cells representing CMMCs, BM MM cells, CD19+ B lymphocytes, CD45+CD138- WBC from these patients were subjected to DNA-sequencing. By processing 80 single cells from four MM cell lines with known mutations we determined the mean sensitivity of mutation detection in single cells to be 93 ± 9%. In addition to DNA-sequencing we also isolated 57 single MM cells from the BM and peripheral blood of two MM patients and performed whole transcriptome single cell RNA-sequencing. Results: In 24 randomly selected MM patient samples we detected >12 CMMCs per 1ml of blood in all 24 patients. In comparison, by flow cytometry, we detected ≥10 CMMCs per 10(5) white blood cells in 10/24 cases (42%), ≥1 CMMC but ≤ 10 CMMCs in 13/24 cases (54%), and < 1 CTCs in 1/24 patients (4%). Mutational analysis of 35 recurrently mutated loci in 335 high quality single MM cells from the blood and BM of 10 patients, including one MGUS patient, revealed the presence of a total of 12 mutations (in KRAS, NRAS, BRAF, IRF4 and TP53). All targeted mutations that were detected by clinical-grade genotyping of bulk BM were also detected in single cell analysis of CMMCs. While in most patients, the fraction of mutated single cells was similar between blood and BM, in three patients, the proportion of MM cells harboring TP53 R273C, BRAF G469A and NRAS G13D mutations was significantly higher in the blood than in the BM, suggesting a different clonal composition. We developed an analytical model to predict whether a genetic locus underwent loss of heterozygosity, using the distribution of known allelic fractions of previously described mutations in MM cell lines as a benchmark. In two patients who simultaneously harbored two mutations, we predicted a BRAF G469E and a KRAS G12C mutation to be heterozygous, whereas the loci harboring a TP53 R273C and a TP53 R280T mutation were predicted to be associated with LOH with high statistical confidence. Whole transcriptome single cell RNA-sequencing of 57 MM cells from the BM and peripheral blood of two patients showed >3,700 transcripts per cell. Single-cell RNA-sequencing allowed for a clear distinction between normal plasma cells and MM cells, either based on analysis of CD45, CD27, and CD56 alone, or by unsupervised hierarchical clustering of detected transcripts in single cells. In addition, single cell CMMC expression analysis could be used to infer the existence of key MM chromosomal translocations. For example, CCND1 and CCND3 were highly upregulated in single MM cells from the blood and BM of two patients, whose MM was found by FISH analysis to harbor a t(11;14) and a t(6;14) translocation, respectively. Conclusion: We demonstrate that extensive genomic characterization of MM is feasible from very small numbers of CMMCs with single cell resolution. Interrogation of single CMMCs faithfully reproduces the pattern of somatic mutations present in MM in the BM, identifies actionable oncogenes, and reveals if somatic mutated loci underwent loss of heterozygosity. Single CMMCs also reveal mutations that are not detectable in the BM either by single cell sequencing or clinical grade bulk sequencing. Single cell RNA-sequencing of CMMCs provides robust transcriptomic profiling, allowing for class-differentiation and inference of translocations in MM patients. Disclosures Raje: Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Merck: Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy, Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Research Funding; Eli Lilly: Research Funding.

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Ibrutinib-Based Therapy Improves Anti-Tumor T Cell Killing Function Allowing Effective Pairing with Anti-PD-L1 Immunotherapy Compared to Traditional FCR Chemoimmunotherapy; Implications for Therapy and Correlative Immune Functional Data from the Phase III E1912 Trial

Blood ◽

10.1182/blood-2018-99-118333 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 236-236 ◽

Cited By ~ 2

Author(s):

Despoina Papazoglou ◽

Connie E. Lesnick ◽

Victoria Wang ◽

Neil E. Kay ◽

Tait D. Shanafelt ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

B Cells ◽

Board Of Directors ◽

Research Funding ◽

Phase Iii ◽

Advisory Committees ◽

Time Points ◽

Killing Function ◽

Time Point

Abstract The targeted therapy ibrutinib inhibits B cell receptor signaling (BTK inhibitor) and has yielded high response rates and durable remissions in patients with chronic lymphocytic leukemia (CLL). However, it is widely believed that the addition of immune therapies to targeted drugs will be required to activate anti-tumor immunity and work towards curative therapy. Identifying effective combinations of targeted drugs and/or standard chemotherapy with immunotherapy is a priority research area and particularly relevant for CLL, as patients' T cells have been shown to exhibit profound tolerance/exhaustion and notably, no activity was reported in a recent trial of anti-PD-1 immunotherapy for relapsed disease. Ibrutinib has shown beneficial immunomodulatory activity in CLL by inhibiting IL-2-inducible T cell kinase (ITK) as well BTK that is associated with increased effector CD4+and CD8+ T cell numbers and decreased expression of inhibitory checkpoint receptors such as PD-1 on patient T cells. Here we have performed comparative immune bioassays from a randomized phase III trial comparing ibrutinib-based therapy to traditional FCR chemoimmunotherapy to assess the effects of treatments on anti-tumor T cell function. Viable peripheral blood mononuclear cell samples were collected serially (baseline, 6 months and 12 months) from CLL patients on the randomized phase III E1912 trial of ibrutinib and rituximab versus FCR for previously untreated disease to allow longitudinal batched immune analysis. Cytotoxicity assays revealed that highly purified CD3+ T cells from the FCR treated patients at 6 and 12-month time-points did not change their activated killing function against autologous baseline CD19+ CLL tumor B cells (acting as target antigen-presenting cells pulsed with superantigen, sAg) compared to pre-treatment/baseline exhausted T cells (n=22). In contrast, patients treated with ibrutinib-based therapy had a significant increase in activated anti-tumor T cell killing function (P<.01, n=22) at both 6-month (66% increase) and 12-month (89% increase) time-points. Flow cytometric analysis of circulating immune subsets revealed that the percentage of PD-1 and PD-L1 positive cells among CD8+ and CD4+ T cells (particularly effector compartments) were reduced with ibrutinib-based therapy, whereas only a partial reduction was detected following FCR treatment. However, patients' T cells from both treatment arms responded normally to T cell receptor engagement by upregulating these checkpoint molecules. This led us to explore ex vivo treatment of highly purified CD3+ T cells and CD19+ CLL B cells from both treatment arms with anti-PD-L1 or anti-PD-1 immunotherapy prior to cytotoxicity assays. Our functional data revealed that the T cells from both FCR time-points (6 and 12-months) were not sensitive to either anti-PD-L1 (n=14) or anti-PD-1 (n=14) treatment. In contrast, ibrutinib-based treatment sensitized anti-tumor T function (23% increase in killing) following anti-PD-L1 treatment (n=14) at the 6-month time-point only (P<.01) but not with anti-PD-1. To investigate the mechanism underlying these effector function differences, we compared the ability of highly purified CD3+ T cells from each treatment arm (n=45) time-point to form F-actin immunological synapses with baseline autologous CLL tumor B cells. Quantitative confocal image analysis revealed that ibrutinib-based therapy significantly (P<.01) enhanced polarization of F-actin, tyrosine-phosphorylated proteins and granzyme B at immune synapses with tumor cells at both 6 and 12-month time-points, whereas FCR treated patient T cells failed to mobilize these lytic synapse molecules. Importantly, our assays have revealed that T cells from both FCR treatment time-points formed "non-polarized" immune synapses with tumor cells, in keeping with cytotoxic dysfunction and insensitivity to additional checkpoint immunotherapy. In contrast, our functional correlative bioassays have revealed that ibrutinib-based therapy can reactivate exhausted cytolytic T cell function and suggest to us, a potential therapeutic window for anti-PD-L1 immunotherapy at the earlier 6-month time-point. We believe this data supports the concept of incorporating functional bioassays to immune-monitoring assays associated to clinical trials that should aid knowledge-led design of future combination immunotherapy. Disclosures Kay: Janssen: Membership on an entity's Board of Directors or advisory committees; Agios Pharm: Membership on an entity's Board of Directors or advisory committees; Acerta: Research Funding; Cytomx Therapeutics: Membership on an entity's Board of Directors or advisory committees; Infinity Pharm: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding. Shanafelt:Pharmacyclics: Research Funding; Genentech: Research Funding; GlaxoSmithKline: Research Funding; Jansen: Research Funding. Ramsay:Celgene Corporation: Research Funding; Roche Glycart AG: Research Funding; MedImmune: Research Funding.

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Single Cell Deconvolution of Myeloblasts Reveals Depletion of HSCs and Expansion of Inflammatory Granulocyte-Monocyte Progenitors (GMPs) Associated with Adverse Outcomes in Chronic Myelomonocytic Leukemia (CMML)

Blood ◽

10.1182/blood-2021-151348 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 319-319

Author(s):

Abhishek Dhawan ◽

Meghan Ferrall-Fairbanks ◽

Brian Johnson ◽

Hannah Newman ◽

Virginia Volpe ◽

...

Keyword(s):

Flow Cytometry ◽

Single Cell ◽

Disease Progression ◽

Board Of Directors ◽

Rna Sequencing ◽

Research Funding ◽

Adverse Outcomes ◽

Advisory Committees ◽

Myeloid Neoplasms ◽

Cluster 2

Abstract Myeloblasts are associated with adverse outcomes and define transformation to acute myeloid leukemia in all chronic myeloid neoplasms. Myeloblasts represent hematopoietic stem and progenitor cells (HSPCs) that express CD34, but are never resolved into stem and progenitor subpopulations during clinical evaluation. Therefore, how expansion of myeloblasts reshapes the HSPC compartment and its impact on clinical outcomes remains undefined. To address this important feature of disease progression, we transcriptionally and immunophenotypically mapped CD34 + HSPCs at single cell resolution for 66 samples from 45 patients with CMML. Single cell-RNA sequencing was performed on 137,578 CD34 + enriched HSPCs from 39 CMML samples and integrated with 63,672 publicly available CD34 + normal HSPCs (Fig A). We overlaid each CMML sample on a pseudotime projection of differentiation trajectories from normal samples to establish sample-specific aberrancies in HSPC states. This mapping classified samples into HSPC-biased groups of monocyte (mono)-bias, megakaryocyte erythroid (ME)-bias, and normal-like, respectively enriched for GMP, MEP, and HSC transcriptional signatures (Fig B). These groups were associated with distinct clinical genomic characteristics and were congruent with patient-specific bulk sequencing. For example, ME biased cases had statistically higher hemoglobin and mono-bias cases were associated with adverse survival, inflammatory clinical correlates, and RAS pathway mutations (Fig C). Importantly, we identified significant depletion of HSC across CMML that was most pronounced in the mono-bias group. This was validated by flow cytometry in 26 CD34 + enriched samples, which showed HSC numbers decreased as myeloblasts expanded and disease progressed (Fig D,E). The mono-biased group strongly correlated to the fraction of cells that were transcriptionally enriched for cytokine receptor (CR) signaling (cluster 2, Fig F). These cluster 2 cells constituted a subset of GMPs that could be identified by CD120b expression based on COMET analysis (Fig F), were depleted after therapy in sequential samples, and were associated with high CTNNB1 and low IRF8 expression, suggesting that they are self-renewing GMPs as previously reported in murine models (Herault Nature 2017). To validate the clinical relevance of CR signaling in HSPCs, we established a CR high-parameter flow cytometry panel by prioritizing CRs from primary CMML CD34 + RNA-sequencing data and quantified their expression using PE-conjugated antibodies to screen CR expression and density. This led to a 30-parameter panel that accounted for CR co-expression, spectral overlap, enabled us to both map CRs on HSCs, CMPs, MEPs, and GMPs, and calculate the CR Shannon diversity in 26 CMML and 5 normal controls (Fig G). Patients with CD120b + GMPs had inferior survival, were associated with higher-risk, proliferative disease, and higher CR diversity (Fig H). Further, increased CR diversity was associated with inferior survival across all HSPC compartments. Given the expansion of GMPs in mono-biased patients, we hypothesized that prior periods of stress-induced hematopoiesis (SIH) could contribute to the development of this adverse HSPC differentiation trajectory during disease progression. We modeled SIH by performing BMT experiments with NRAS Q61R/WT bone marrow cells and controls as RAS mutations were associated with a mono-bias state. These experiments identified a depletion of HSC and expansion of CD120b + GMPs compared to controls recapitulating the HSPC compartment in human mono-biased cases (Fig I,J). We modeled the impact of SIH in human CMML by chronically treating RAS mutated CMML PDX models with LPS or vehicle and similarly observed HSC depletion and CD120b + GMP expansion in LPS-treated mice (Fig K,L). Our data suggests that HSC depletion is a characteristic of myeloblast expansion during disease progression. Further, even in a disease with homogenous hematopoietic output (monocytosis), progenitor expansion of HSPCs can occur in three distinct skewed states. The mono-biased state is associated with poor outcomes and can be recapitulated by modeling SIH in CMML. PDX studies are ongoing to validate these results and the effects of SIH on survival. Deconvolution of HSPCs at single cell resolution of other myeloid neoplasms and strategies to mitigate triggers of SIH to prevent the mono-biased state should be explored. Figure 1 Figure 1. Disclosures Komrokji: Acceleron: Consultancy; AbbVie: Consultancy; Taiho Oncology: Membership on an entity's Board of Directors or advisory committees; PharmaEssentia: Membership on an entity's Board of Directors or advisory committees; Geron: Consultancy; Jazz: Consultancy, Speakers Bureau; BMSCelgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Sallman: Intellia: Membership on an entity's Board of Directors or advisory committees; Agios: Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Syndax: Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Kite: Membership on an entity's Board of Directors or advisory committees; Shattuck Labs: Membership on an entity's Board of Directors or advisory committees; Magenta: Consultancy; Takeda: Consultancy; Aprea: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees; Incyte: Speakers Bureau. Bejar: Gilead: Consultancy, Honoraria; Takeda: Research Funding; Aptose Biosciences, Inc.: Current Employment, Current equity holder in publicly-traded company; Silence Therapeutics: Consultancy; Astex: Consultancy; Epizyme: Consultancy, Honoraria; BMS: Consultancy, Research Funding. Padron: BMS: Research Funding; Incyte: Research Funding; Kura: Research Funding; Blueprint: Honoraria; Taiho: Honoraria; Stemline: Honoraria.

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Distinct Evolutionary Patterns in Chronic Lymphocytic Leukemia (CLL) during Resistance to Graft-Versus-Leukemia (GvL)

Blood ◽

10.1182/blood-2019-129520 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 516-516

Author(s):

Pavan Bachireddy ◽

Christina Ennis ◽

Vinhkhang N Nguyen ◽

Nikolas Barkas ◽

Sachet Shukla ◽

...

Keyword(s):

Stem Cell ◽

Single Cell ◽

Board Of Directors ◽

Research Funding ◽

Clonal Evolution ◽

Epigenetic Mechanism ◽

Patient Specific ◽

Advisory Committees ◽

Hla Genes ◽

Evolutionary Trajectories

The factors mediating GvL resistance following allogeneic stem cell transplant (SCT) in lymphoid malignancies remain incompletely characterized. Because cell-intrinsic features shape chemotherapeutic relapse, we hypothesized that they also shape GvL outcomes by influencing evolutionary trajectories of CLL relapse after reduced intensity conditioning SCT (RIC). We identified 9 heavily pre-treated patients (pts) (range: 1-5 therapies, median: 3) with various times to CLL relapse after RIC (range: 83-1825 days), of which 8 had at least partial responses before relapse. To define evolutionary trajectories, we generated paired whole-exome and RNA sequencing data from purified CLL cells pre/post-RIC, using MuTect2 and ABSOLUTE algorithms to identify somatic alterations (SAs) and corresponding cancer cell fractions (CCFs). 5 pts had clonal SAs in TP53 and/or SF3B1 pre-SCT, and no single SA was specific to post-RIC. Furthermore, we found no SAs nor altered expression of HLA class I/II or b2M in either baseline or post-RIC samples. However, we found 6 relapse pairs to exhibit complex branched evolution involving CCF shifts of at least 0.2 in subclonal and clonal SAs whereas 3 pairs showed genomic stability. Clonal evolution was associated with longer time to relapse (Wilcoxon, p=0.02; median 798 versus 304 days) as well as complete response (p=0.05), suggesting that GvL immune escape may be facilitated by clonal evolution. To determine the phenotypic consequences of clonal evolution, we examined single cell transcriptomes using scRNAseq from paired pre/post-RIC CLL cells from 2 pts with early (304, 442 days; "ERs") and 2 pts with late (1801, 1825 days; "LRs") relapses after RIC. Using the inDrop platform, we profiled a median of 3560 CLL cells/pt (range: 2254-5278). Clustering using Seurat revealed marked transcriptional stability after RIC in ERs whereas dramatic shifts in gene expression programs were observed in LRs. Single cell trajectory analysis using Monocle identified ordered biological processes through which LRs, but not ERs, progressed. Branched expression analysis revealed multiple patient specific pathways defining LRs, including within chromatin regulators (EBF1, BANK1), oncogenic pathways (AFF3, DENND4A) and ribosomal biosynthesis (EEF1G, NACA). Thus, genetic evolution in LRs results in distinct phenotypic consequences. To directly link SAs with transcriptional outcomes, we interrogated scRNAseq data for known SAs identified by WES. In one LR, loss of a CLL cancer driver (RPS15mut) was observed in two of three post-RIC transcriptional clusters, either through deletion of chr.19p (where RPS15 resides) or reversion to the wildtype allele (implying loss of heterozygosity). In addition, genomic and transcriptional loss of HLA genes were detectable in pre-RIC clusters that failed to expand at relapse in both LRs, suggesting that pre-existing HLA loss does not provide a selective advantage for CLL relapse after RIC, consistent with our bulk analyses. These data highlight how scRNAseq can delineate genetic selection pressures within subpopulations of a single patient. To investigate whether epigenetic dysregulation underlies these genetic changes, we measured locally disordered methylation (LDM), a known epigenetic mechanism of CLL genetic variability. Genome-wide methylome profiles revealed increases in LDM in LRs compared to ERs for various genomic regions (Kruskal-Wallis (KW), p<0.05 for promoters, genes, distal regulatory modules); no increases in LDM were observed in an independent cohort of late CLL relapse after chemotherapy alone (n=7; time between samples: 496-1511 days). Moreover, we controlled for time between samples by calculating the rate of change in LDM and still found significant differences only during LR after RIC (versus ER or late relapse after chemotherapy; KW, p<10-13). Finally, genes with increased LDM were enriched for multiple stem cell gene sets (q<0.01), implicating a common stem-like state in LRs. Altogether, these data highlight important features of GvL resistance in CLL: 1) GvL selective pressure, shown by LRs, can shape evolutionary trajectories through genotypic alterations that directly exert phenotypic consequences; 2) alterations in HLA genes have less influence in CLL than in myeloid malignancies; and 3) GvL immune editing may select for epigenetic variability that facilitates evasion through stem-like states. Disclosures Brown: Octapharma: Consultancy; Novartis: Consultancy; Loxo: Consultancy, Research Funding; Kite: Consultancy, Research Funding; Janssen: Honoraria; Invectys: Other: other; Gilead: Consultancy, Research Funding; Genentech/Roche: Consultancy; Dynamo Therapeutics: Consultancy; Catapult Therapeutics: Consultancy; BeiGene: Consultancy; AstraZeneca: Consultancy; Acerta Pharma: Consultancy; Morphosys: Other: Data safety monitoring boards ; Sun Pharmaceuticals, Inc: Research Funding; Sun: Research Funding; Verastem: Consultancy, Research Funding; TG Therapeutics: Consultancy; Teva: Honoraria; Sunesis: Consultancy; Pharmacyclics: Consultancy; Pfizer: Consultancy. Getz:MuTect, ABSOLTUE, MutSig and POLYSOLVER: Patents & Royalties: MuTect, ABSOLTUE, MutSig and POLYSOLVER; IBM: Research Funding; Pharmacyclics: Research Funding. Ho:Jazz Pharmaceuticals: Consultancy; Jazz Pharmaceuticals: Research Funding; Omeros Corporation: Membership on an entity's Board of Directors or advisory committees. Neuberg:Celgene: Research Funding; Pharmacyclics: Research Funding; Madrigal Pharmaceuticals: Equity Ownership. Soiffer:Gilead, Mana therapeutic, Cugene, Jazz: Consultancy; Jazz: Consultancy; Kiadis: Other: supervisory board; Mana therapeutic: Consultancy; Cugene: Consultancy; Juno, kiadis: Membership on an entity's Board of Directors or advisory committees, Other: DSMB. Ritz:TScan Therapeutics: Consultancy; Equillium: Research Funding; Merck: Research Funding; Kite Pharma: Research Funding; Aleta Biotherapeutics: Consultancy; Celgene: Consultancy; Avrobio: Consultancy; LifeVault Bio: Consultancy; Draper Labs: Consultancy; Talaris Therapeutics: Consultancy. Wu:Neon Therapeutics: Other: Member, Advisory Board; Pharmacyclics: Research Funding.

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Site to Site Comparison of Follicular Lymphoma Biopsies By Single Cell RNA Sequencing

Blood ◽

10.1182/blood-2019-129445 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 297-297 ◽

Cited By ~ 4

Author(s):

Sarah Haebe ◽

Tanaya Shree ◽

Anuja Sathe ◽

Grady Day ◽

HoJoon Lee ◽

...

Keyword(s):

T Cells ◽

B Cells ◽

B Cell ◽

Single Cell ◽

Board Of Directors ◽

Rna Sequencing ◽

Peripheral Blood ◽

Advisory Committees ◽

Blood Samples ◽

Single Cell Rna Sequencing

Follicular lymphoma (FL) originates from a single B cell that has rearranged one copy of its BCL2 gene on chromosome 18 to the Ig locus on chromosome 14 and in addition has acquired a mutation in a histone modifying gene such as CREBBP or KMTD2. By the time the disease is diagnosed the progeny of this original cell harbors additional mutations and is usually found at multiple lymphoid sites throughout the body. At each of these sites the malignant cells are accompanied by a rich network of follicular dendritic cells, T cells and other immune cells. This tumor microenvironment (TME) is clearly an important feature of the biology of FL and can impact the clinical behavior of the disease (Dave et al., NEJM, 2004). It remains unknown whether tumor clonal heterogeneity and the composition of the TME differ between various lymphoma sites within the same patient. Single cell RNA sequencing facilitates a detailed and unbiased view of both the tumor clone and the complex TME. To profile the TME and explore FL tumor evolution, we obtained fine needle aspirates (FNAs) at 2 different sites in the body and peripheral blood specimens all on the same day and subjected these samples to single cell RNA sequencing and immune repertoire analysis. These biopsies were taken prior to therapy from patients entering immunotherapy clinical trials (NCT02927964, NCT03410901). Single cell RNA sequencing of FNA and blood samples was performed using the 10X Genomics platform to an average targeted depth of 50,000 reads/cell. We have prepared sequencing libraries from 15 tumor FNA and peripheral blood samples from 5 patients thus far. Typically, 3,000-10,000 cells have been sequenced per sample, with excellent sequencing quality metrics. By applying Uniform Manifold Approximation and Projection (UMAP), a dimensionality reduction algorithm, we found the TME of these FL patients to be richly populated by many phenotypically discrete non-malignant cells, including many subpopulations of T cells, B-cells, myeloid cells, NK cells and dendritic cells. Evaluating the combined dataset containing all tumor samples for all 5 patients, we found that malignant B cells from different patients clearly clustered apart from each other, a feature not dependent on immunoglobulin clonality or HLA type. Each patient's tumor population contained 3-5 distinct subpopulations, presumably a result of multiclonal tumor evolution. Nonetheless, we were able to define several malignant B-cell sub-phenotypes common to all patients. Intriguingly, compared to malignant B cells, infiltrating non-malignant B cells showed higher MHC I expression, activation markers, and an enrichment in interferon-induced genes. Of note, we could also detect circulating tumor cells in peripheral blood samples of several patients, and these exhibited a distinct gene expression profile compared to their counterparts within lymph nodes. Analysis of the diverse T cell subpopulations within tumors revealed distinct functional states. For example, in regulatory and T follicular helper cells, we identified activated clusters (CD27, BATF, TNFRSF4) and putative resting clusters (SELL, KLF2, IL7R), while effector T cells resided in separate cytotoxic (GZMA, GZMB, GNLY) and exhausted (TIGIT, CXCL13, LAG3) clusters. Tumor B cell gene expression and composition of the TME from site to site within the same patient were similar in some cases and remarkably divergent in others. For example, we detected a significant upregulation of interferon signaling pathways in the tumor B cells and an enrichment of effector T cells in only one of the two sites within one patient. Analysis of B cell and T cell antigen receptor sequences to evaluate tumor subclonality and TCR clonotype diversity are ongoing. To the best of our knowledge, this is the first study to compare different sites of FL in the same patients at the single cell level. Our analyses characterize inter- and intra-patient heterogeneity in malignant and immune cell subsets and provide a baseline for eventual comparison of alterations occurring over time as these patients receive experimental immunotherapy interventions. Disclosures Levy: XCella: Membership on an entity's Board of Directors or advisory committees; Immunocore: Membership on an entity's Board of Directors or advisory committees; Walking Fish: Membership on an entity's Board of Directors or advisory committees; Five Prime: Membership on an entity's Board of Directors or advisory committees; Corvus: Membership on an entity's Board of Directors or advisory committees; Quadriga: Membership on an entity's Board of Directors or advisory committees; BeiGene: Membership on an entity's Board of Directors or advisory committees; GigaGen: Membership on an entity's Board of Directors or advisory committees; Teneobio: Membership on an entity's Board of Directors or advisory committees; Sutro: Membership on an entity's Board of Directors or advisory committees; Checkmate: Membership on an entity's Board of Directors or advisory committees; Nurix: Membership on an entity's Board of Directors or advisory committees; Dragonfly: Membership on an entity's Board of Directors or advisory committees; Innate Pharma: Membership on an entity's Board of Directors or advisory committees; Abpro: Membership on an entity's Board of Directors or advisory committees; Apexigen: Membership on an entity's Board of Directors or advisory committees; Nohla: Membership on an entity's Board of Directors or advisory committees; Spotlight: Membership on an entity's Board of Directors or advisory committees; 47 Inc: Membership on an entity's Board of Directors or advisory committees.

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