scholarly journals Single Cell Transcriptomic Evolution and Resistance Mechanisms of BTK and BCL-2 Inhibition in Mantle Cell Lymphoma

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 33-34
Author(s):  
Vivian Changying Jiang ◽  
Shaojun Zhang ◽  
Junwei Lian ◽  
Yuanxin Wang ◽  
Rongjia Zhang ◽  
...  
Keyword(s):  
Single Cell ◽  
Disease Progression ◽  
Rna Sequencing ◽  
Research Funding ◽  
Clonal Evolution ◽  
Underlying Mechanism ◽  
Therapeutic Resistance ◽  
Immune Microenvironment ◽  
Tumor Immune Microenvironment ◽  
Single Cell Rna Sequencing

Introduction: Mantle cell lymphoma (MCL) is a rare and aggressive subtype of B-cell non-Hodgkin's lymphoma with high risk of relapse after frontline therapies. Ibrutinib and venetoclax are two efficacious therapies for refractory/relapsed MCL patients. However, resistance to these therapies occurs frequently and is an urgent unmet clinical need. To understand the underlying mechanism of how intra- and inter-tumor heterogeneity (ITH) and its immune microenvironment contributes to therapeutic resistance, we performed a state-of-art single cell RNA sequencing on longitudinal samples from ibrutinib and venetoclax dual-resistant MCL patients with side-by-side comparison to ibrutinib-sensitive patients in our discovery cohort. To support our novel findings, patient samples from multiple validation cohorts were collected and analyzed via various approaches. Methods: Patient specimens from our discovery cohort that included ibrutinib-sensitive and ibrutinib-venetoclax dual-resistant MCL patients were collected longitudinally and subject to single cell RNA sequencing using 10x genomics. Integrative computational analysis was conducted to uncover the ITH and tumor immune microenvironment at single cell resolution and the underlying mechanism of therapeutic resistance and clonal evolution. To validate the novel findings, additional cohorts of patient samples were collected and subject to bulk RNA sequencing, whole exome sequencing, and multi-color flow cytometry analysis. An orthotopic PDX model was established from one of the ibrutinib-venetoclax dual-resistant MCL patients and was used to validate the novel findings as well as to test the potential therapies in vivo to overcome resistance. Results: To understand the underlying mechanism of heterogeneity and therapeutic relapse, we carried out sequential single cell RNA sequencing on 21 specimens (18,794 cells in total) collected from ibrutinib-sensitive and ibrutinib-venetoclax dual-resistant MCL patients along the course of ibrutinib and/or venetoclax treatments. Integrative computational analysis revealed a high degree of ITH with distinct profiles of cellular and molecular transcriptome. We revealed 15 top cancer hallmarks associated with disease progression and therapeutic resistance, albeit with remarkable clinical, pathological, and genetic-based inter-patient heterogeneity. We observed appearance and clearance of multiple subpopulations in patient blood samples, which likely interprets the clinical ibrutinib-induced lymphocytosis phenomenon at single-cell resolution and disease-progression-associated clonal evolution, which were further validated. Our analysis revealed reprogramming of the tumor microenvironment and tumor immune evasion. Moreover, we revealed multiple actionable targets to help overcome therapeutic resistance as tailored anti-MCL strategies. We found that the 17q gain strongly correlated with this dual resistance and thus targeting survivin located at 17q by YM155 significantly inhibited tumor growth and prolonged mouse survival in the ibrutinib-venetoclax dual-resistant PDX model. Conclusions: This study is the first to describe the mechanisms underlying dual resistance to ibrutinib and venetoclax at the single cell level. We not only identified various pathways underlying this resistance, but also characterized the evolutionary dynamics by using a longitudinal sampling strategy to uncover the underlying mechanisms. We found that the 17q gain highly correlates with ibrutinib-venetoclax dual resistance and showed that inhibition of survivin, located at 17q, overcame this dual resistance. These data provide evidence that 17q gain may be the driving force of disease progression and therapeutic resistance. Moreover, for the first time in MCL, we characterized changes in tumor immune microenvironment and identified a T-cell exhaustion signature correlated with the dual resistance. These changes to the tumor microenvironment strongly suggest the role of immune resistance in mediating dual resistance to ibrutinib and venetoclax in MCL. Disclosures Wang: Lu Daopei Medical Group: Honoraria; Beijing Medical Award Foundation: Honoraria; OncLive: Honoraria; Molecular Templates: Research Funding; Verastem: Research Funding; Dava Oncology: Honoraria; Guidepoint Global: Consultancy; Nobel Insights: Consultancy; Oncternal: Consultancy, Research Funding; InnoCare: Consultancy; Acerta Pharma: Research Funding; VelosBio: Research Funding; BioInvent: Research Funding; Juno: Consultancy, Research Funding; Kite Pharma: Consultancy, Other: Travel, accommodation, expenses, Research Funding; Pulse Biosciences: Consultancy; Loxo Oncology: Consultancy, Research Funding; Targeted Oncology: Honoraria; OMI: Honoraria, Other: Travel, accommodation, expenses; Celgene: Consultancy, Other: Travel, accommodation, expenses, Research Funding; AstraZeneca: Consultancy, Honoraria, Other: Travel, accommodation, expenses, Research Funding; Janssen: Consultancy, Honoraria, Other: Travel, accommodation, expenses, Research Funding; MoreHealth: Consultancy; Pharmacyclics: Consultancy, Honoraria, Other: Travel, accommodation, expenses, Research Funding.

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

Blood ◽  
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.

scholarly journals Single-cell RNA sequencing reveals compromised immune microenvironment in precursor stages of multiple myeloma

Nature Cancer ◽  
2020 ◽  
Vol 1 (5) ◽  
pp. 493-506 ◽  
Author(s):  
Oksana Zavidij ◽  
Nicholas J. Haradhvala ◽  
Tarek H. Mouhieddine ◽  
Romanos Sklavenitis-Pistofidis ◽  
Songjie Cai ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Single Cell ◽  
Rna Sequencing ◽  
Immune Microenvironment ◽  
Single Cell Rna Sequencing

scholarly journals Abstract 139: Single-cell RNA sequencing reveals compromised immune microenvironment in precursor stages of multiple myeloma

2019 ◽  
Author(s):  
Nicholas J. Haradhvala ◽  
Oksana Zavidij ◽  
Tarek H. Mouhieddine ◽  
Romanos Sklavenitis-Pistofidis ◽  
Jihye Park ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Single Cell ◽  
Rna Sequencing ◽  
Immune Microenvironment ◽  
Single Cell Rna Sequencing

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

Blood ◽  
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.

scholarly journals Single-cell RNA sequencing reveals compromised immune microenvironment in precursor stages of multiple myeloma

2019 ◽  
Vol 19 (10) ◽  
pp. e27
Author(s):  
Oksana Zavidij ◽  
Nicholas J. Haradhvala ◽  
Tarek Mouhieddine ◽  
Romanos Sklavenitis-Pistofidis ◽  
Michael P. Agius ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Single Cell ◽  
Rna Sequencing ◽  
Immune Microenvironment ◽  
Single Cell Rna Sequencing

Single cell RNA sequencing of AML initiating cells reveals RNA-based evolution during disease progression

Leukemia ◽  
2021 ◽  
Author(s):  
L. C. Stetson ◽  
Dheepa Balasubramanian ◽  
Susan Pereira Ribeiro ◽  
Tammy Stefan ◽  
Kalpana Gupta ◽  
...  
Keyword(s):  
Single Cell ◽  
Disease Progression ◽  
Rna Sequencing ◽  
Single Cell Rna Sequencing

scholarly journals Single-cell RNA sequencing reveals markers of disease progression in primary cutaneous T-cell lymphoma

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Katharina Rindler ◽  
Constanze Jonak ◽  
Natalia Alkon ◽  
Felix M. Thaler ◽  
Harald Kurz ◽  
...  
Keyword(s):  
T Cell ◽  
Single Cell ◽  
Disease Progression ◽  
Rna Sequencing ◽  
Cell Lymphoma ◽  
Early Stage ◽  
T Cell Lymphoma ◽  
Advanced Stage ◽  
Cutaneous T Cell Lymphoma ◽  
Single Cell Rna Sequencing

Abstract Background In early-stage mycosis fungoides (MF), the most common primary cutaneous T-cell lymphoma, limited skin involvement with patches and plaques is associated with a favorable prognosis. Nevertheless, approximately 20–30% of cases progress to tumors or erythroderma, resulting in poor outcome. At present, factors contributing to this switch from indolent to aggressive disease are only insufficiently understood. Methods In patients with advanced-stage MF, we compared patches with longstanding history to newly developed plaques and tumors by using single-cell RNA sequencing, and compared results with early-stage MF as well as nonlesional MF and healthy control skin. Results Despite considerable inter-individual variability, lesion progression was uniformly associated with downregulation of the tissue residency markers CXCR4 and CD69, the heat shock protein HSPA1A, the tumor suppressors and immunoregulatory mediators ZFP36 and TXNIP, and the interleukin 7 receptor (IL7R) within the malignant clone, but not in benign T cells. This phenomenon was not only found in conventional TCR-αβ MF, but also in a case of TCR-γδ MF, suggesting a common mechanism across MF subtypes. Conversely, malignant cells in clinically unaffected skin from MF patients showed upregulation of these markers. Conclusions Our data reveal a specific panel of biomarkers that might be used for monitoring MF disease progression. Altered expression of these genes may underlie the switch in clinical phenotype observed in advanced-stage MF.

scholarly journals Comprehensive Single-Cell RNA-Sequencing Mapping of Primary Acute Myeloid Leukemias and Profiling of NPM1-Mutated Cells

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 995-995
Author(s):  
Vincent-Philippe Lavallee ◽  
Elham Azizi ◽  
Vaidotas Kiseliovas ◽  
Ignas Masilionis ◽  
Linas Mazutis ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Research Funding ◽  
Single Cells ◽  
Cell Types ◽  
Wild Type ◽  
Sequencing Data ◽  
Single Cell Rna Sequencing ◽  
Equity Ownership ◽  
Acute Myeloid

Abstract Introduction: Acute myeloid leukemia (AML) evolution is a multistep process in which cells evolve from hematopoietic stem and progenitor cells (HSPCs) that acquire genetic anomalies, such as chromosomal rearrangements and mutations, which define distinct subgroups. Mutations in Nucleophosmin 1 (NPM1), which occur in ~30% patients, are the most frequent subgroup-defining mutations in AML and appear to be a late driver event in this disease. Bulk RNA-sequencing studies have identified differentially expressed genes between AML subgroups, but they are uninformative of the composition of cell types populating each sample. Large scale Single-cell RNA sequencing (scRNA-seq) technologies now enable a detailed characterization of intra tumoral heterogeneity, and could help to better understand the stepwise evolution from normal to malignant cells. Methods: Twelve primary human AML specimens from MSKCC and Quebec Leukemia Cell Bank, including 8 with NPM1 mutations, were included in this cohort. Cells were subjected to scRNA-seq using 10X Genomics Chromium Single Cell 3' protocols and libraries were sequenced on Illumina HiSeq or NovaSeq platforms. FASTQ files were processed using SEQC pipeline (Azizi E et al, Cell 2018), resulting in a carefully filtered count matrix of > 100,000 single cells (4877 to 11532 cells per sample). Results: Using euclidean distance metrics and t-Distributed Stochastic Neighbor Embedding (t-SNE) visualization, we explored the phenotypic overlap between samples and showed that leukemia cells from different patients were mostly dissimilar, suggesting inter-sample heterogeneity. However, samples with similar morphology and similar NPM1 mutational status were phenotypically closer (Fig A), as anticipated from bulk RNA-sequencing data (TCGA, NEJM 2013). We partitioned cells into distinct clusters using Phenograph (Levine J et al, Cell 2015) (Fig B) and measured the diversity of samples per cluster using Shannon's entropy metric, revealing that mature cell types (B/plasma cells, T/NK and erythroid cells, Fig C), presumably excluded from the tumor bulk, are transcriptionally similar across samples. Most notably, the next most diverse cluster (C36), comprising 438 cells from 11/12 samples, contains cells with a HSPC-like phenotype, as suggested by i) highest correlation of the centroid of this cluster with HSC1 (lin-/CD133+/CD34dim) population from sorted bulk RNA-sequencing data (Novershtern N et al, Cell 2011), and ii) marked GSEA enrichment for stem cell signatures (top enrichment: Jaatinen_hematopoeitic_stem_cell_up, NES = 9.04, FDR q-val = 0). To study the extent to which NPM1 or other mutations drive heterogeneity in leukemia populations, we interrogated 3'-derived single-cell sequences for all recurrent mutations in AML and found that NPM1 gene has unique features (e.g. relatively high single-cell expression and 3' localization) that allow specific identification of mutations in 5 to 34% of cells per mutated sample. To control for the high frequency of false negatives caused by dropouts in scRNA-seq data, we normalized the abundance of mutated vs wild-type cells to provide an estimation of mutation frequency in different cell types (Fig D). As expected, NPM1 mutations were rare in B and T/NK lymphoid cells (also observed using RT-qPCR in sorted populations by Dvorakova D et al, Leuk Lymphoma 2013) and were found in the majority of leukemia and myeloid cells. Interestingly, these mutations were detected at various frequencies in erythroid cells, suggesting that NPM1 mutations are acquired in cells with different lineage commitment in different patients. Most notably, the HSPC-like cluster C36 also contained a subpopulation of cells that have acquired NPM1 mutations and are transcriptionally different from wild-type cells. Conclusion: This study presents a first comprehensive single-cell map of primary AML, and the first 3'-based interrogation of mutations in single cells. It led to the identification phenotypically distinct cells presenting a HSPC-like expression profile which were sub-clonally harboring NPM1 mutations, providing the means to identify deregulated genes in these important leukemia subpopulations. Figure Figure. Disclosures Levine: Epizyme: Patents & Royalties; Celgene: Consultancy, Research Funding; Janssen: Consultancy, Honoraria; Isoplexis: Equity Ownership; C4 Therapeutics: Equity Ownership; Prelude: Research Funding; Gilead: Honoraria; Imago: Equity Ownership; Novartis: Consultancy; Roche: Consultancy, Research Funding; Loxo: Consultancy, Equity Ownership; Qiagen: Equity Ownership, Membership on an entity's Board of Directors or advisory committees.

scholarly journals 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 ◽  
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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