High Throughput Single-Cell Simultaneous Genotyping and Chromatin Accessibility Reveals Genotype to Phenotype Relationship in Human Myeloproliferation

Abstract In hematopoiesis, changes in chromatin accessibility define priming and commitment of hematopoietic precursors towards cellular fates. In turn, somatic mutations in hematopoietic stem and progenitor cells (HSPCs) drive the onset and progression of myeloid disorders, such as myeloproliferative neoplasms (MPNs), and reshape differentiation topologies. To chart how somatic mutations disrupt the epigenetic landscape in human clonal outgrowths, we developed Genotyping of Targeted loci with Chromatin Accessibility (GoT-ChA), linking genotypes to chromatin accessibility across thousands of single cells. Crucially, GoT-ChA captures genotypes directly from genomic DNA (Fig. 1a), and thus independently of the genomic location or expression of the target. We tested GoT-ChA via cell line mixing studies targeting either TP53 R248Q (Fig. 1b), or JAK2 V617F (Fig. 1c), assigning cell line identity solely based on chromatin accessibility. Notably, GoT-ChA resulted in genotyping of 54% of cells with 96.9% accuracy for TP53 R248Q and 60% of cells with 99.7% accuracy for JAK2 V617F. These data show the transformative advantage of targeting DNA directly, as prior high-throughput droplet methods to target the lowly expressed JAK2 via cDNA resulted in genotyping of only ~7% of cells (Nam et al, Nature, 2019). Next, we applied GoT-ChA to CD34 + cells from JAK2 V617F-mutant myelofibrosis (MF) samples (Fig. 1d). We clustered cells based on chromatin profiles, revealing the expected cell populations in hematopoiesis (Fig. 1d-e), and then projected genotyping status onto the differentiation map (Fig. 1f). In further validation of genotyping accuracy, copy number inference showed a sample that contained a partial deletion of chromosome 20 (Fig. 1g) concordant with our genotyping. Furthermore, GoT-ChA can be integrated with recent protocols to allow for high mitochondrial genome coverage (Lareau et al, Nature Biotechnology, 2020). We observed mitochondrial mutations that were highly concordant with JAK2 V617F (Fig. 1h), allowing genotyping of >85% of cells. Within MPN samples, wildtype (WT) and mutated (MUT) cells were intermingled across the differentiation topology. Nonetheless, we observed an increase in the mutant fraction within erythroid progenitors (EP; Fig. 1i). Moreover, pseudo-temporal ordering of chromatin accessibility revealed that the mutant cell fraction increased along erythroid or megakaryocyte differentiation in untreated MPN (Fig 1j), in line with clinical phenotypes. Chromatin accessibility profiles can provide clues to the underlying regulatory network through transcription factor (TF) motif accessibility. Uniquely, GoT-ChA enables de novo differential motif accessibility, directly comparing WT and MUT cells co-existing within the same bone marrow. Mutant HSPCs showed increased motif accessibility (FDR < 0.05) for TFs associated with erythropoiesis (Fig. 1k), suggestive of increased erythroid priming. Within EP clusters, we observed increased motif accessibility of STAT5A and STAT5B, downstream targets of JAK2 (Fig. 1l-m). These data demonstrated a cell-type specific effect of the JAK2 V617F mutation. Ruxolitinib is a frontline JAK1/2 inhibitor for MF. Despite improvements in quality of life, ruxolitinib does not clearly target the MPN clone or prevent progression of disease. In ruxolitinib-treated patients the MUT cell fraction was uniformly distributed along the differentiation (Fig.1i-j), demonstrating an abrogation of the fitness advantage of JAK2 V617F in committed progenitors, but not in HSPCs. Consistently, STAT5A motif accessibility remained increased in MUT cells at intermediate stages of erythroid maturation but decreased to similar levels as WT cells at later stages (Fig. 1n-o). Overall, GoT-ChA radically expands the single-cell multi-omics toolkit and obviates limiting dependencies on target gene transcription, allowing high throughput somatic genotype-to-phenotype mapping. Applied to JAK2 V617F-mutated MPN, GoT-ChA uncovered a cell-type specific fitness advantage with erythroid commitment, that was reversed upon JAK2 inhibitor treatment. The reshaping of the differentiation topography traced back to differential transcription factor activity driving uncommitted vs. committed JAK2 V617F progenitors. Thus, single-cell multi-omics with GoT-ChA enables to chart the epigenetic underpinnings of hematopoietic clonal outgrowth. Figure 1 Figure 1. Disclosures Mimitou: Immunai: Current Employment. Hoffman: Protagonist Therapeutics, Inc.: Consultancy; Kartos Therapeutics, Inc.: Research Funding; Novartis: Other: Data Safety Monitoring Board, Research Funding; AbbVie Inc.: Other: Data Safety Monitoring Board, Research Funding. Abdel-Wahab: Prelude Therapeutics: Consultancy; LOXO Oncology: Consultancy, Research Funding; Merck: Consultancy; Foundation Medicine Inc: Consultancy; H3B Biomedicine: Consultancy, Research Funding; Lilly: Consultancy; AIChemy: Current holder of stock options in a privately-held company, Membership on an entity's Board of Directors or advisory committees; Envisagenics Inc.: Current holder of stock options in a privately-held company, Membership on an entity's Board of Directors or advisory committees. Smibert: Immunai: Current Employment.

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A Comprehensive Analysis of Single-Cell Chromatin Accessibility and Gene Expression Identifies Intra-Tumor Heterogeneity and Molecular Treatment Responses in Relapsed/Refractory Multiple Myeloma

Blood ◽

10.1182/blood-2019-130051 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 575-575

Author(s):

Alexandra M Poos ◽

Jan-Philipp Mallm ◽

Stephan M Tirier ◽

Nicola Casiraghi ◽

Hana Susak ◽

...

Keyword(s):

Gene Expression ◽

Single Cell ◽

Board Of Directors ◽

Research Funding ◽

Tumor Heterogeneity ◽

Mek Inhibitor ◽

Chromatin Accessibility ◽

University Research ◽

Sample Processing ◽

Advisory Committees

Introduction: Multiple myeloma (MM) is a heterogeneous malignancy of clonal plasma cells that accumulate in the bone marrow (BM). Despite new treatment approaches, in most patients resistant subclones are selected by therapy, resulting in the development of refractory disease. While the subclonal architecture in newly diagnosed patients has been investigated in great detail, intra-tumor heterogeneity in relapsed/refractory (RR) MM is poorly characterized. Recent technological and computational advances provide the opportunity to systematically analyze tumor samples at single-cell (sc) level with high accuracy and througput. Here, we present a pilot study for an integrative analysis of sc Assay for Transposase-Accessible Chromatin with high-throughput sequencing (scATAC-seq) and scRNA-seq with the aim to comprehensively study the regulatory landscape, gene expression, and evolution of individual subclones in RRMM patients. Methods: We have included 20 RRMM patients with longitudinally collected paired BM samples. scATAC- and scRNA-seq data were generated using the 10X Genomics platform. Pre-processing of the sc-seq data was performed with the CellRanger software (reference genome GRCh38). For downstream analyses the R-packages Seurat and Signac (Satija Lab) as well as Cicero (Trapnell Lab) were used. For all patients bulk whole genome sequencing (WGS) data was available, which we used for confirmatory studies of intra-tumor heterogeneity. Results: A comprehensive study at the sc level requires extensive quality controls (QC). All scATAC-seq files passed the QC, including the detected number of cells, number of fragments in peaks or the ratio of mononucleosomal to nucleosome-free fragments. Yet, unsupervised clustering of the differentially accessible regions resulted in two main clusters, strongly associated with sample processing time. Delay of sample processing by 1-2 days, e.g. due to shipment from participating centers, resulted in global change of chromatin accessibility with more than 10,000 regions showing differences compared to directly processed samples. The corresponding scRNA-seq files also consistently failed QC, including detectable genes per cell and the percentage of mitochondrial RNA. We excluded these samples from the study. Analysing scATAC-seq data, we observed distinct clusters before and after treatment of RRMM, indicating clonal adaptation or selection in all samples. Treatment with carfilzomib resulted in highly increased co-accessibility and >100 genes were differentially accessible upon treatment. These genes are related to the activation of immune cells (including T-, and B-cells), cell-cell adhesion, apoptosis and signaling pathways (e.g. NFκB) and include several chaperone proteins (e.g. HSPH1) which were upregulated in the scRNA-seq data upon proteasome inhibition. The power of our comprehensive approach for detection of individual subclones and their evolution is exemplarily illustrated in a patient who was treated with a MEK inhibitor and achieved complete remission. This patient showed two main clusters in the scATAC-seq data before treatment, suggesting presence of two subclones. Using copy number profiles based on WGS and scRNA-seq data and performing a trajectory analysis based on scATAC-seq data, we could confirm two different subclones. At relapse, a seemingly independent dominant clone emerged. Upon comprehensive integration of the datasets, one of the initial subclones could be identified as the precursor of this dominant clone. We observed increased accessibility for 108 regions (e.g. JUND, HSPA5, EGR1, FOSB, ETS1, FOXP2) upon MEK inhibition. The most significant differentially accessible region in this clone and its precursor included the gene coding for krüppel-like factor 2 (KLF2). scRNA-seq data showed overexpression of KLF2 in the MEK-inhibitor resistant clone, confirming KLF2 scATAC-seq data. KLF2 has been reported to play an essential role together with KDM3A and IRF1 for MM cell survival and adhesion to stromal cells in the BM. Conclusions: Our data strongly suggest to use only immediately processed samples for single cell technologies. Integrating scATAC- and scRNA-seq together with bulk WGS data showed that detection of individual clones and longitudinal changes in the activity of cis-regulatory regions and gene expression is feasible and informative in RRMM. Disclosures Goldschmidt: John-Hopkins University: Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; John-Hopkins University: Research Funding; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Mundipharma: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; MSD: Research Funding; Molecular Partners: Research Funding; Dietmar-Hopp-Stiftung: Research Funding; Janssen: Consultancy, Research Funding; Chugai: Honoraria, Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive Biotechnology: Membership on an entity's Board of Directors or advisory committees.

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Single-Cell Multi-Omics Defines the Cell-Type Specific Impact of SF3B1 Splicing Factor Mutations on Hematopoietic Differentiation in Human Clonal Hematopoiesis and Myelodysplastic Syndromes

Blood ◽

10.1182/blood-2021-147529 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 145-145

Author(s):

Federico Gaiti ◽

Allegra Hawkins ◽

Paulina Chamely ◽

Ariel Swett ◽

Xiaoguang Dai ◽

...

Keyword(s):

Single Cell ◽

Research Funding ◽

Mrna Translation ◽

Splicing Factor ◽

Cell Type ◽

Advisory Committees ◽

Oxford Nanopore ◽

Cell Type Specific ◽

The Impact ◽

Oxford Nanopore Technologies

Abstract Splicing factor mutations are recurrent genetic alterations in blood disorders, highlighting the importance of alternative splicing regulation in hematopoiesis. Specifically, mutations in splicing factor 3B subunit 1 (SF3B1) are implicated in the pathogenesis of myelodysplastic syndromes (MDS) and linked to a high-risk of leukemic transformation in clonal hematopoiesis (CH). SF3B1 mutations are associated with aberrant RNA splicing, leading to increased cryptic 3' splice site (ss) usage and MDS with ring sideroblasts phenotype. The study of mutant SF3B1-driven splicing aberrations in humans has been hampered by the inability to distinguish mutant and wildtype single cells in patient samples and the inadequate coverage of short-read sequencing over splice junctions. To overcome these limitations, we developed GoT-Splice by integrating Genotyping of Transcriptomes (GoT; Nam et al. 2019) with Nanopore long-read single-cell transcriptome profiling and CITE-seq (Fig. A). This allowed for the simultaneous single-cell profiling of protein and gene expression, somatic mutation status, and alternative splicing. Our method selectively enriched full-length sequencing reads with the accurate structure, enabling the capture of higher number of junctions per cell and greater coverage uniformity vs. short-read sequencing (10x Genomics; Fig. B, C). We applied GoT-Splice to CD34+ bone marrow progenitor cells from MDS (n = 15,436 cells across 3 patients; VAF: [0.38-0.4]) to study how SF3B1 mutations corrupt human hematopoiesis (Fig. D). High-resolution mapping of SF3B1 mutvs. SF3B1 wt hematopoietic progenitors revealed an increasing fitness advantage of SF3B1 mut cells towards the megakaryocytic-erythroid lineage, resulting in an expansion of SF3B1 muterythroid progenitor (EP) cells (Fig. E, F). Accordingly, SF3B1 mutEP cells displayed higher protein expression of erythroid lineage markers, CD71 and CD36, vs. SF3B1 wt cells (Fig. G). In these SF3B1 mutEP cells, we identified up-regulation of genes involved in regulation of cell cycle and checkpoint controls (e.g., CCNE1, TP53), and mRNA translation (eIFs gene family; Fig. H). Next, while SF3B1 mut cells showed the expected increase of cryptic 3' splicing vs. SF3B1 wt cells (Fig. I), they exhibited distinct cryptic 3' ss usage as a function of hematopoietic progenitor cell identity, displaying stage-specific aberrant splicing during erythroid maturation (Fig. J). In less differentiated EP cells, we observed mis-splicing of genes involved in iron homeostasis, such as the hypoxia-inducible factor HIF1A, and key regulators of erythroid cell growth, such as SEPT2. At later stages, we observed mis-splicing of BAX, a pro-apoptotic member of the Bcl-2 gene family and transcriptional target of p53, and erythroid-specific genes (e.g., PPOX). We further predicted 54% of the aberrantly spliced mRNAs to introduce premature stop codons, promoting RNA degradation through nonsense-mediated decay (NMD). In line with this notion, we observed a significant decrease in expression of NMD-inducing genes in SF3B1 mut vs . SF3B1 wtEP cells (Fig. K). Lastly, splicing factor mutations observed in CH subjects provide an opportunity to interrogate the downstream impact of SF3B1 mutations prior to development of disease. Like MDS, by applying GoT-splice to CD34+ progenitor cells from SF3B1 mut CH subjects (n = 9,007 cells across 2 subjects; VAF: [0.15-0.22]; Fig. L), we revealed increased mutant cell frequency in EP cells (Fig. M) with concomitant increased expression of genes involved in mRNA translation (Fig. N), consistent with SF3B1 mutation causing mis-splicing injury to translational machinery and ineffective erythropoiesis. Notably, CH patients already exhibited cell-type specific cryptic 3' ss usage in SF3B1 mut cells (Fig. O). In summary, we developed a novel multi-omics single-cell toolkit to examine the impact of splicing factor mutations on cellular fitness directly in human samples. With this approach, we showed that, while SF3B1 mutations arise in uncommitted HSCs, their effect on fitness increases with differentiation into committed EPs, in line with the mutant SF3B1-driven dyserythropoiesis phenotype. We revealed that SF3B1 mutations exert cell-type specific mis-splicing that leads to abnormal erythropoiesis. Finally, we demonstrated that the impact of SF3B1 mutations on EP cells begins before disease onset, as observed in CH subjects. Figure 1 Figure 1. Disclosures Dai: Oxford Nanopore Technologies: Current Employment. Beaulaurier: Oxford Nanopore Technologies: Current Employment. Drong: Oxford Nanopore Technologies: Current Employment. Hickey: Oxford Nanopore Technologies: Current Employment. Juul: Oxford Nanopore Technologies: Current Employment. Wiseman: Astex: Research Funding; Novartis: Consultancy; Bristol Myers Squibb: Consultancy; Takeda: Consultancy; StemLine: Consultancy. Harrington: Oxford Nanopore Technologies: Current Employment. Ghobrial: AbbVie, Adaptive, Aptitude Health, BMS, Cellectar, Curio Science, Genetch, Janssen, Janssen Central American and Caribbean, Karyopharm, Medscape, Oncopeptides, Sanofi, Takeda, The Binding Site, GNS, GSK: Consultancy. Abdel-Wahab: H3B Biomedicine: Consultancy, Research Funding; Foundation Medicine Inc: Consultancy; Merck: Consultancy; Prelude Therapeutics: Consultancy; LOXO Oncology: Consultancy, Research Funding; Lilly: Consultancy; AIChemy: Current holder of stock options in a privately-held company, Membership on an entity's Board of Directors or advisory committees; Envisagenics Inc.: Current holder of stock options in a privately-held company, Membership on an entity's Board of Directors or advisory committees.

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High-throughput single-cell chromatin accessibility CRISPR screens enable unbiased identification of regulatory networks in cancer

Nature Communications ◽

10.1038/s41467-021-23213-w ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Sarah E. Pierce ◽

Jeffrey M. Granja ◽

William J. Greenleaf

Keyword(s):

Transcription Factor ◽

Single Cell ◽

Cancer Cells ◽

High Throughput ◽

Regulatory Networks ◽

Temporal Dynamics ◽

Chromatin Accessibility ◽

Regulatory Regions ◽

Factor Binding ◽

Genome Wide

AbstractChromatin accessibility profiling can identify putative regulatory regions genome wide; however, pooled single-cell methods for assessing the effects of regulatory perturbations on accessibility are limited. Here, we report a modified droplet-based single-cell ATAC-seq protocol for perturbing and evaluating dynamic single-cell epigenetic states. This method (Spear-ATAC) enables simultaneous read-out of chromatin accessibility profiles and integrated sgRNA spacer sequences from thousands of individual cells at once. Spear-ATAC profiling of 104,592 cells representing 414 sgRNA knock-down populations reveals the temporal dynamics of epigenetic responses to regulatory perturbations in cancer cells and the associations between transcription factor binding profiles.

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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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High-Throughput Immunofluorescence and Electron Tomography to Characterize Centrosomal Aberrations in Plasma Cell Neoplasia

Blood ◽

10.1182/blood-2019-130713 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 3077-3077

Author(s):

Tobias Dittrich ◽

Martin Schorb ◽

Isabella Haberbosch ◽

Elena Bausch ◽

Mandy Börmel ◽

...

Keyword(s):

Board Of Directors ◽

Cancer Patients ◽

Genomic Instability ◽

Cell Lines ◽

Plasma Cell ◽

High Throughput ◽

Research Funding ◽

Electron Tomography ◽

Automated Analysis ◽

Advisory Committees

Introduction Genomic instability is the basic prerequisite for a Darwinian-type evolution of neoplasia and as such represents a fundamental hallmark of cancer. Centrosomal aberrations have been identified as potent drivers of genomic instability (Cosenza et al., Cell Reports 2017; Krämer et al., Leukemia 2003). The current standard to investigate centrosomal aberrations in cancer patients is immunofluorescence (IF) staining. Although this method is fast and easily scalable, its diagnostic significance is controversially discussed. Moreover, ultrastructural analysis of centrosomes in cancer patients is required to gain a mechanistical understanding of the relationship between genomic instability and centrosomal aberrations. To address this, we combined semi-automated analysis of immunofluorescence (IF) images with high-throughput electron tomography (ET) of different cell lines and subentities of primary plasma cell neoplasia, which serve as surrogate for clonal evolution. Methods CD138+ plasma cells were isolated from bone marrow aspirates of consenting patients with plasma cell neoplasia. Each sample was split to be subsequently processed for IF and ET. The IF workflow included (1) chemical fixation, (2) staining for nuclei, cells, centrin and pericentrin, (3) semi-automated acquisition of >1000 cells, (4) semi-automated analysis of IF data using the software Konstanz Information Miner (KNIME) (Berthold et al., GfKL 2007). The ET workflow included (1) chemical fixation (2) agarose embedding, (3) dehydration and epoxy resin embedding, (4) serial sectioning at 200 nm, (5) semi-automated screening for centrioles with transmission electron microscopy (TEM) (Schorb et al., Nature Methods 2019), (6) semi-automated acquisition of previously identified centriole regions with serial section ET. Results So far, four patients with relapsed refractory myeloma as well as two cell lines (U2OS-PLK4, RPMI.8226) have been screened with TEM. No centrosomal amplification was apparent by IF in any of these patients. Within 5598 cells, 205 centrosomes have been detected. A total of 659 electron tomograms were performed on 141 regions of interest that were distributed on average over five sections. One patient with highly refractory multiple myeloma (resistance to eight prior therapies) showed over-elongated and partially fragmented centrioles (Figure), similar to recently reported findings in tumor cell lines (Marteil et al., Nature Communications 2018). Six out of 10 mother centrioles in this patient were longer than 500 nm, which is supposed to be the physiological length. The dimensions (mean [range]) of mother (decorated with appendages) and daughter centrioles in this patient were: length 919 nm [406 nm - 2620 nm] and 422 nm [367 nm - 476 nm]; diameter 221 nm [99 nm - 470 nm] and 236 nm [178 nm - 450 nm]. Moreover, the mother centrioles showed multiple sets of appendages (mean [range]: 5.9 [2 - 13]), while one set of appendages would be physiological. This is an ongoing study and additional results are expected by the date of presentation. Conclusions We present a semi-automated methodological setup that combines high-throughput IF and cutting-edge ET to study centrosomal aberrations. To our knowledge, this is the first study that systematically analyzes the centrosomal phenotype of cancer patients at the ultrastructural level. Our preliminary IF results suggest that supernumerary centrosomes in plasma cell neoplasia might be less common than previously reported. Moreover, we for the first time describe and characterize over-elongated centrioles in myeloma patients, reminiscent of previous findings in tumor cell lines. With increasing numbers of patients, we will be also able to correlate results from IF and ET to address the current uncertainty with respect to IF screens for centrosomal aberrations. Better insight into centrosomal aberrations will likely increase our understanding on karyotype evolution in plasma cell neoplasia and possibly facilitate the development of novel targeted therapies. Figure Disclosures Goldschmidt: John-Hopkins University: Research Funding; John-Hopkins University: Research Funding; MSD: Research Funding; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Dietmar-Hopp-Stiftung: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive Biotechnology: Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Research Funding; Molecular Partners: Research Funding; Janssen: Consultancy, Research Funding; Mundipharma: Research Funding; Chugai: Honoraria, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Müller-Tidow:MSD: Membership on an entity's Board of Directors or advisory committees. Schönland:Medac: Other: Travel Grant; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding. Krämer:Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Research Funding; Daiichi-Sankyo: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bayer: Research Funding.

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Dynamic Epigenetic Landscapes Define Multiple Myeloma Progression and Drug Resistance

Blood ◽

10.1182/blood-2020-142872 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 32-33

Author(s):

Rafael Renatino-Canevarolo ◽

Mark B. Meads ◽

Maria Silva ◽

Praneeth Reddy Sudalagunta ◽

Christopher Cubitt ◽

...

Keyword(s):

Gene Expression ◽

Drug Resistance ◽

Disease Progression ◽

Board Of Directors ◽

Research Funding ◽

Chromatin Accessibility ◽

Refractory Disease ◽

Advisory Committees ◽

Cytogenetic Abnormalities ◽

Genome Wide

Multiple myeloma (MM) is an incurable cancer of bone marrow-resident plasma cells, which evolves from a premalignant state, MGUS, to a form of active disease characterized by an initial response to therapy, followed by cycles of therapeutic successes and failures, culminating in a fatal multi-drug resistant cancer. The molecular mechanisms leading to disease progression and refractory disease in MM remain poorly understood. To address this question, we have generated a new database, consisting of 1,123 MM biopsies from patients treated at the H. Lee Moffitt Cancer Center. These samples ranged from MGUS to late relapsed/refractory (LR) disease, and were comprehensively characterized genetically (844 RNAseq, 870 WES, 7 scRNAseq), epigenetically (10 single-cell chromatin accessibility, scATAC-seq) and phenotypically (537 samples assessed for ex vivo drug resistance). Mutational analysis identified putative driver genes (e.g. NRAS, KRAS) among the highest frequent mutations, as well as a steady increase in mutational load across progression from MGUS to LR samples. However, with the exception of KRAS, these genes did not reach statistical significance according to FISHER's exact test between different disease stages, suggesting that no single mutation is necessary or sufficient to drive MM progression or refractory disease, but rather a common "driver" biology is critical. Pathway analysis of differentially expressed genes identified cell adhesion, inflammatory cytokines and hematopoietic cell identify as under-expressed in active MM vs. MGUS, while cell cycle, metabolism, DNA repair, protein/RNA synthesis and degradation were over-expressed in LR. Using an unsupervised systems biology approach, we reconstructed a gene expression map to identify transcriptomic reprogramming events associated with disease progression and evolution of drug resistance. At an epigenetic regulatory level, these genes were enriched for histone modifications (e.g. H3k27me3 and H3k27ac). Furthermore, scATAC-seq confirmed genome-wide alterations in chromatin accessibility across MM progression, involving shifts in chromatin accessibility of the binding motifs of epigenetic regulator complexes, known to mediate formation of 3D structures (CTCF/YY1) of super enhancers (SE) and cell identity reprograming (POU5F1/SOX2). Additionally, we have identified SE-regulated genes under- (EBF1, RB1, SPI1, KLF6) and over-expressed (PRDM1, IRF4) in MM progression, as well as over-expressed in LR (RFX5, YY1, NBN, CTCF, BCOR). We have found a correlation between cytogenetic abnormalities and mutations with differential gene expression observed in MM progression, suggesting groups of genetic events with equivalent transcriptomic effect: e.g. NRAS, KRAS, DIS3 and del13q are associated with transcriptomic changes observed during MGUS/SMOL=>active MM transition (Figure 1). Taken together, our preliminary data suggests that multiple independent combinations of genetic and epigenetic events (e.g. mutations, cytogenetics, SE dysregulation) alter the balance of master epigenetic regulatory circuitry, leading to genome-wide transcriptional reprogramming, facilitating disease progression and emergence of drug resistance. Figure 1: Topology of transcriptional regulation in MM depicts 16,738 genes whose expression is increased (red) or decreased (green) in presence of genetic abnormality. Differential expression associated with (A) hotspot mutations and (B) cytogenetic abnormalities confirms equivalence of expected pairs (e.g. NRAS and KRAS, BRAF and RAF1), but also proposes novel transcriptomic dysregulation effect of clinically relevant cytogenetic abnormalities, with yet uncharacterized molecular role in MM. Figure 1 Disclosures Kulkarni: M2GEN: Current Employment. Zhang:M2GEN: Current Employment. Hampton:M2GEN: Current Employment. Shain:GlaxoSmithKline: Speakers Bureau; Amgen: Speakers Bureau; Karyopharm: Research Funding, Speakers Bureau; AbbVie: Research Funding; Takeda: Honoraria, Speakers Bureau; Sanofi/Genzyme: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Honoraria, Speakers Bureau; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Adaptive: Consultancy, Honoraria; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Siqueira Silva:AbbVie: Research Funding; Karyopharm: Research Funding; NIH/NCI: Research Funding.

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Clonotype-Immunophenotype Relationships in TET2 and IDH-Mutant Myeloid Transformation

Blood ◽

10.1182/blood-2021-151819 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 373-373

Author(s):

Linde A. Miles ◽

Robert L. Bowman ◽

Nicole Delgaudio ◽

Troy Robinson ◽

Martin P. Carroll ◽

...

Keyword(s):

Dna Sequencing ◽

Single Cell ◽

Board Of Directors ◽

Research Funding ◽

Expression Patterns ◽

Clonal Expansion ◽

Mutant Mice ◽

Triple Mutant ◽

Advisory Committees ◽

Disease Evolution

Abstract Large scale molecular profiling studies in AML patients have suggested that stepwise acquisition of somatic mutations is crucial in driving leukemic development. High variant allele frequency (VAF) mutations in epigenetic modifier genes, such as TET2 and IDH1/2, are thought to occur early in AML pathogenesis while oncogenic mutations with typically lower VAF mutations, including FLT3 and NRAS, are suggested to occur late in disease evolution. While bulk DNA sequencing has catalogued co-mutations found in individual AMLs, it cannot unveil the heterogeneity and composition of clones that makes up the disease. Elucidating the architecture and clone-specific molecular profiles at the single cell resolution will be key to understanding how sequential and/or parallel mutation acquisition drives myeloid transformation. To assess the clonal architecture of AML, we previously performed single cell DNA sequencing (scDNA seq) in 146 patients with myeloid malignancies. We have further identified specific mutational combinations driving clonal expansion in TET2- or IDH1/2- mutant AML samples. These studies suggest TET2 and IDH1/2 can cooperate to promote clonal expansion with DNMT3A and NPM1 (Figure 1A). However, TET2 or IDH1/2 mutant clones that acquired KRAS mutations underwent minimal clonal expansion, suggesting mutant-pair specific fitness alterations (Figure 1B). To further identify how co-mutational pairing impacted clonal fitness and differentiation, we integrated the scDNA platform with immunophenotypic profiling of 45 cell surface markers and analyzed new TET2- and IDH1/2- mutant AML samples (Figure 1C). We identified clone-specific differences in lineage markers depending on co-mutational partners. NPM1 co-mutant clones were enriched for more primitive markers (CD33), whereas NRAS co-mutant clones possessed high expression of myeloid differentiation markers (CD14/CD11b), suggestive of clone-specific fitness landscapes across hematopoietic differentiation. We also identified divergent clonotype-immunophenotype patterns in TET2- and IDH2-mutant clones harboring NPM1/RAS mutations, suggesting that initiating mutations may prime mutant clones for very different evolutionary trajectories as they acquire similar mutations in leukemogenesis (Figure 1D). To deterministically delineate the relationship between clonal evolution and myeloid transformation, we generated Cre-inducible single (Tet2 -/-), double (Tet2 -/-/Nras G12Dand Tet2 -/-/Npm1 cA/wt), and triple (Tet2 -/-/Npm1 cA/wt/Nras G12D) mutant mice and evaluated differences in chimerism, immunophenotype, and survival. We observed a shortened survival for double and triple mutant mice, compared to Tet2 -/- only mice (Figure 1E). As previously reported, Tet2 -/-/Nras G12D mice developed a CMML-like phenotype. Critically, the addition of Npm1 resulted in a more rapid disease onset and transformation to AML (Figure 1F). Moreover, triple mutant WBM transplanted to form a fully penetrant disease into secondary recipients, while double mutant Tet2 -/-/Nras G12D WBM failed to form disease within 3 months of transplant, suggesting a difference in the cell population responsible for disease propagation. Immunophenotypic alterations were evident with Tet2 -/-/ Nras G12D displaying an increase in Mac1 +Gr1 + cells compared to Tet2 -/-/Npm1 cA/wt/Nras G12D mice which possessed increased Mac1 +Gr1 - cells and expansion of lineage negative cells (Figure 1G). These findings align with the clonotype specific expression patterns observed in clinical specimen and suggest that myeloid transformation and maturation biases are influenced by specific mutational combinations. Figure 1 Figure 1. Disclosures Miles: Mission Bio: Honoraria, Speakers Bureau. Bowman: Mission Bio: Honoraria, Speakers Bureau. Carroll: Janssen Pharmaceutical: Consultancy; Incyte Pharmaceuticals: Research Funding. Levine: Astellas: Consultancy; Janssen: Consultancy; Auron: Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria; QIAGEN: Membership on an entity's Board of Directors or advisory committees; Mission Bio: Membership on an entity's Board of Directors or advisory committees; Isoplexis: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Incyte: Consultancy; Imago: Membership on an entity's Board of Directors or advisory committees; Roche: Honoraria, Research Funding; Prelude: Membership on an entity's Board of Directors or advisory committees; Ajax: Membership on an entity's Board of Directors or advisory committees; Zentalis: Membership on an entity's Board of Directors or advisory committees; Gilead: Honoraria; C4 Therapeutics: Membership on an entity's Board of Directors or advisory committees; Lilly: Honoraria; Morphosys: Consultancy.

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B Cell Receptor Signaling Drives APOBEC3 Expression Via Direct Enhancer Regulation in Chronic Lymphocytic Leukemia B Cells

Blood ◽

10.1182/blood-2021-153214 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 3313-3313

Author(s):

Zhiquan Wang ◽

Huihuang Yan ◽

Justin C. Boysen ◽

Charla R. Secreto ◽

Esteban Braggio ◽

...

Keyword(s):

B Cells ◽

Board Of Directors ◽

Research Funding ◽

Chromatin Accessibility ◽

S Phase ◽

Advisory Committees ◽

Bcr Signaling ◽

Before And After ◽

One Year ◽

Apobec3 Expression

Abstract Introduction: CLL is the most common leukemia in the U.S. and characterized by constitutively activated BCR signaling pathway, which has a crucial role both in normal B cell development and B cell malignancies. The biological events controlled by BCR signaling in CLL are not fully understood. Active BCR signaling is mediated through activation of the downstream kinase Bruton tyrosine kinase (BTK), which has become a key therapeutic target to inhibit BCR signaling for the treatment of B cell malignancies. We reasoned that blood samples from CLL patients before and after Bruton's tyrosine kinase inhibitors (BTKi) treatment would provide a valuable resource in the study of BCR modulation of epigenetic machinery in leukemic B cells. Methods: We obtained blood samples from CLL patients before and after BTKi ibrutinib treatment and used them to study BCR signaling regulated genes (n = 8 patients, after one-year of continuous ibrutinib treatment). Gene expression profile of CLL B cells from patients before and after one-year ibrutinib treatment was analyzed by mRNA-seq seq. Genome wide Histone H3K4me1, H3K27ac, and H3K4me3 profile was determined by CUT&tag. Chromatin accessibility was determined by ATAC-seq. Putative enhancers were deleted by CRISPR-Cas9. Results: Notably BTKi treatment led to the reduction of expression in genes associated with single strand DNA deamination (Fig. 1A) The BTKi regulated genes involved in this process mainly contains the APOBEC3 family genes (APOBEC3C, APOBEC3D APOBEC3F, APOBEC3G, APOBEC3H), and their expression levels showed a consistent reduction in CLL B cells from ibrutinib treated patients (Fig. 1B). We then confirmed the reduction of APOBEC3 levels by western blot in CLL B cells from four patients before and after one-year of continuous ibrutinib treatment (Fig. 1C). We hypothesized that BCR signaling regulates APOBEC3 expression by modifying the local chromatin around the APOBEC3 gene cluster and performed CUT&Tag to map the histone marks including H3K4me1, H3K4me3, H3K27ac and ATAC-seq. This approach permitted us to examine the chromatin accessibility of the leukemic cells from CLL patients before and then after one-year of continuous ibrutinib treatment. We found that BTKi treatment caused reductions of H3K4me1, H3K27ac, and chromatin accessibility at these regions in ibrutinib treated patients ( 7 of the 8 samples tested), however, there was no change of the promoter marker H3K4me3 (Fig. 1D), which indicated that BTKi treatment leads to APOBEC3 genes expression change via the regulation of their enhancer regulation (APOBEC3 enhancers, AEs). Based on the enrichment of H3K4me1, H3K27ac and chromatin accessibility, AE regions of the ibrutinib native samples contain three active enhancer modules, we designated these modules as AE1, AE2, and AE3 (Fig. 1D). To assess the functional activity of these enhancers on the expression of APOBEC3 genes, we investigated the consequence of deletion of each one of these AEs in the MEC1 cell line by CRISPR-Cas9. PCR analysis showed very robust deletion of AE1, AE2, and AE3 (Fig. 1E). Both deletion of AE1 or AE2 reduced the expression of APOBEC3 genes, while AE3 deletion suppressed the expression of APBEC3C, APOBEC3D, APOBEC3F and APOBEC3G, but not APOBEC3H, which is in closest proximity to AE3 (Fig. 1F, G). Together, we identified the BCR signaling dependent enhancers that regulate APOBEC3 expression. Since APOBEC3 deaminates ssDNA, we reasoned that APOBEC3 in CLL B cells may also contribute to replication stress and DNA instability. We found that MEC1 cells have a high level of spontaneous DNA damage in the S phase cells (Fig. 1H). which is associated with replication stress. However, AE2 deleted MEC cells showed decreased γH2Ax in the S phase cells (Fig. 1H). Edu/PI assay showed that MEC1 cells had a fraction of S phase cells with low Edu incorporation during S phase, also indicating DNA replication stress (Fig. 1I); however, AE2 deletion greatly increased Edu incorporation (Fig. 1I). Taken together, these data suggest that increased expression of APOBEC3 may be involved in DNA replication stress and drives genomic instability in malignant B cells. Conclusion: We demonstrate a novel mechanism for BTKi suppression of APOBEC3 expression via direct enhancer regulation in CLL B cells, implicating BCR signaling as a potential regulator of leukemic genomic instability. Figure 1 Figure 1. Disclosures Parikh: Pharmacyclics, MorphoSys, Janssen, AstraZeneca, TG Therapeutics, Bristol Myers Squibb, Merck, AbbVie, and Ascentage Pharma: Research Funding; Pharmacyclics, AstraZeneca, Genentech, Gilead, GlaxoSmithKline, Verastem Oncology, and AbbVie: Membership on an entity's Board of Directors or advisory committees. Kay: AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Genentech: Research Funding; Agios 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; Sunesis: Research Funding; Juno Therapeutics: Membership on an entity's Board of Directors or advisory committees; Targeted Oncology: Membership on an entity's Board of Directors or advisory committees; Rigel: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; MEI Pharma: Research Funding; Behring: Membership on an entity's Board of Directors or advisory committees; Acerta Pharma: Research Funding; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; TG Therapeutics: Research Funding; Tolero Pharmaceuticals: Research Funding; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; CytomX Therapeutics: Membership on an entity's Board of Directors or advisory committees.

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Patient Reported Financial Toxicity in Acute Leukemia

Blood ◽

10.1182/blood-2018-99-119163 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 4796-4796 ◽

Cited By ~ 1

Author(s):

Thomas G. Knight ◽

Myra Robinson ◽

Michael R. Grunwald ◽

Lauren M. Bohannon ◽

Erin Blackwell ◽

...

Keyword(s):

Acute Leukemia ◽

Board Of Directors ◽

Research Funding ◽

Safety Monitoring ◽

Data Safety Monitoring Board ◽

Financial Toxicity ◽

Advisory Committees ◽

Data Safety ◽

Safety Monitoring Board ◽

Data Safety Monitoring

Abstract Background: Financial Toxicity (FT) is increasingly recognized as a major contributor to morbidity and mortality in a variety of cancers. Treatment of acute leukemia is associated with heavy healthcare utilization and high costs. The purpose of this study was to define rates, risk factors, and mortality implications for FT in patients with acute leukemia using patient reported data. Methods: All patients seen at the Levine Cancer Institute, a tertiary hospital-based leukemia practice, were surveyed prior to each visit over a six-month period. All patients were aged ≥18 years and were diagnosed with acute myeloid leukemia (AML) or acute lymphoblastic leukemia (ALL). The survey consisted of the PROMIS Global-10 measure and two questions from the COST measure. FT was defined as scoring 4 or less (maximum: 10) in agreement with the COST questions: "I know that I have enough money in savings, retirement, or assets to cover the costs of my treatment" and "I am satisfied with my current financial situation." Demographic data and disease characteristics were abstracted from the medical record. Model selection was carried out using logistic regression to identify factors impacting the incidence of financial toxicity. Correlation of numerical financial toxicity scores with PROMIS scores and with mortality data was assessed using linear regression. Results: Of the 106 patients, 58 (54%) met the definition of exhibiting FT. The factors associated with incidence of FT included: age, race, and insurance type. The odds of FT in those patients <65 years of age were 2.7 times the odds of FT in those ≥65, adjusting for race, insurance, and time since first treatment (95% CI: 0.884 - 8.438, p = .081). The odds of FT in African American patients were 4.3 times the odds of FT in Caucasian patients, adjusting for age, insurance, and time since first treatment (CI: 0.408 - 44.824, p = .150). The odds of FT in patients with Medicaid insurance were 14.2 times the odds of FT in patients with commercial insurance, adjusting for age, race, and time since first treatment (CI: 1.658 - 121.862, p = .106). Gender, distance from the hospital, type of acute leukemia, history of blood/marrow transplant, and history of relapsed disease were not found to be significant. There was a significant correlation for both the PROMIS global physical (p < .001) and mental (p < .001) scores with the FT score. Lower FT score (higher degree of FT) was associated with lower mental and physical scores. There was no statistically significant difference in survival between patients with FT scores >4 compared to patients with FT scores <=4; however, there was a trend toward decreased survival in those with lower FT scores (Figures 1 and 2). Conclusions: Patients with acute leukemia represent an extremely vulnerable population for financial toxicity with rates of distress even higher than other reported malignancies. Urgent interventions are indicated in this population. Disclosures Grunwald: Medtronic: Equity Ownership; Cardinal Health: Consultancy, Membership on an entity's Board of Directors or advisory committees; Genentech: Research Funding; Merck: Consultancy, Membership on an entity's Board of Directors or advisory committees; Forma Therapeutics: Research Funding; Janssen: Research Funding; Incyte Corporation: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Alexion: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees; Ariad: Consultancy, Membership on an entity's Board of Directors or advisory committees; Agios: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees. Avalos:Juno: Membership on an entity's Board of Directors or advisory committees. Symanowski:Five Prime Therapeutics: Other: Data Safety Monitoring Board ; Boston Biomedical: Other: Data Safety Monitoring Board ; Eli Lily & Co: Other: Data Safety Monitoring Board; Immatics: Other: Data Safety Monitoring Board.

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Exploiting marker genes for robust classification and characterization of single-cell chromatin accessibility

10.1101/2021.04.01.438068 ◽

2021 ◽

Author(s):

Risa Karakida Kawaguchi ◽

Ziqi Tang ◽

Stephan Fischer ◽

Rohit Tripathy ◽

Peter K. Koo ◽

...

Keyword(s):

Single Cell ◽

Marker Gene ◽

Cell Types ◽

Chromatin Accessibility ◽

Marker Genes ◽

Cell Type ◽

Gene Sets ◽

Typing Methods ◽

Cell Type Specific ◽

Cell Typing

Background: Single-cell Assay for Transposase Accessible Chromatin using sequencing (scATAC-seq) measures genome-wide chromatin accessibility for the discovery of cell-type specific regulatory networks. ScATAC-seq combined with single-cell RNA sequencing (scRNA-seq) offers important avenues for ongoing research, such as novel cell-type specific activation of enhancer and transcription factor binding sites as well as chromatin changes specific to cell states. On the other hand, scATAC-seq data is known to be challenging to interpret due to its high number of zeros as well as the heterogeneity derived from different protocols. Because of the stochastic lack of marker gene activities, cell type identification by scATAC-seq remains difficult even at a cluster level. Results: In this study, we exploit reference knowledge obtained from external scATAC-seq or scRNA-seq datasets to define existing cell types and uncover the genomic regions which drive cell-type specific gene regulation. To investigate the robustness of existing cell-typing methods, we collected 7 scATAC-seq datasets targeting mouse brain for a meta-analytic comparison of neuronal cell-type annotation, including a reference atlas generated by the BRAIN Initiative Cell Census Network (BICCN). By comparing the area under the receiver operating characteristics curves (AUROCs) for the three major cell types (inhibitory, excitatory, and non-neuronal cells), cell-typing performance by single markers is found to be highly variable even for known marker genes due to study-specific biases. However, the signal aggregation of a large and redundant marker gene set, optimized via multiple scRNA-seq data, achieves the highest cell-typing performances among 5 existing marker gene sets, from the individual cell to cluster level. That gene set also shows a high consistency with the cluster-specific genes from inhibitory subtypes in two well-annotated datasets, suggesting applicability to rare cell types. Next, we demonstrate a comprehensive assessment of scATAC-seq cell typing using exhaustive combinations of the marker gene sets with supervised learning methods including machine learning classifiers and joint clustering methods. Our results show that the combinations using robust marker gene sets systematically ranked at the top, not only with model based prediction using a large reference data but also with a simple summation of expression strengths across markers. To demonstrate the utility of this robust cell typing approach, we trained a deep neural network to predict chromatin accessibility in each subtype using only DNA sequence. Through model interpretation methods, we identify key motifs enriched about robust gene sets for each neuronal subtype. Conclusions: Through the meta-analytic evaluation of scATAC-seq cell-typing methods, we develop a novel method set to exploit the BICCN reference atlas. Our study strongly supports the value of robust marker gene selection as a feature selection tool and cross-dataset comparison between scATAC-seq datasets to improve alignment of scATAC-seq to known biology. With this novel, high quality epigenetic data, genomic analysis of regulatory regions can reveal sequence motifs that drive cell type-specific regulatory programs.

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