ARID1A Controls a Novel Transcriptional Network Regulating FAS in Follicular Lymphoma

Abstract Follicular lymphoma (FL) is a clinically and genetically heterogeneous disease. Somatic gene mutations contribute to the heterogeneous clinical course of FL. ARID1A, which encodes for a subunit of the SWI/SNF chromatin remodeling complex, is among the most commonly mutated genes in FL (up to 15% of cases). These mutations are mostly disruptive and are predicted to result in protein haplodeficiency. While we have previously shown that ARID1A mutations are predictive of treatment outcome (Pastore, 2015), the underlying biology of ARID1A loss in FL is unclear. A functional genome-wide in vitro screen showed that ARID1A loss rescued a number of cancer cell lines from FAS-L induced apoptosis (Luo, 2008). FAS-L induced apoptosis plays a critical role in normal B-cell development and homeostasis. Thus, FAS/FAS-L deficiency could contribute to FL development and disease biology. Therefore, we studied the role of ARID1A loss in FAS expression and regulation. We first tested FAS-L induced apoptosis in established lymphoma cell lines that harbor the FL-hallmark translocation t(14;18)[BCL2/IGH] plus ARID1A mutations (Karpas422, WSU-FSCCL) or no ARID1A mutations (OCI-Ly1, OCI-Ly8, SU-DHL16). ARID1A mutant (mut) cells were indeed markedly less sensitive to FAS-L (300 ng/mL/24 hrs) compared to ARID1A wild type (WT) cells (98% vs 52% mean viability by Annexin-V). FAS receptor expression on mutant cells was reduced by almost half compared to WT cells by FACS analysis (N=3, P=0.0004). To test if reduced FAS expression was directly linked to ARID1A loss, we generated single-cell derived clones (from OCI-Ly1 and OCI-Ly8) with either heterozygous (het) loss or complete knock-out (KO) of ARID1A by CRISPR/Cas9. ARID1A loss was validated by Sanger sequencing and Western blot. We consistently observed significantly reduced FAS-L induced apoptosis in het and KO clones (exemplary shown for OCI-Ly8 in Fig A). Remarkably, re-expressed of ARID1A in het cells (het+ARID1A) rescued sensitivity to FAS-L induced apoptosis (Fig A). We confirmed reduced FAS expression on mutant clones by FACS, while re-expression of ARID1A rescued its expression (Fig B). Furthermore, FAS mRNA expression was significantly reduced by qPCR in mut vs WT clones (N=4, P<0.05), while FAS mRNA levels were rescued to WT levels in het+ARID1A cells. To understand the molecular mechanism that links ARID1A loss and reduced FAS expression, we performed ATAC sequencing (Seq) and RNA Seq on 15 single-cell derived clones (9 mut and 6 WT from OCI-Ly1 and OCI-Ly8). RNA Seq confirmed significantly lower ARID1A and FAS mRNA levels (adj p<0.001 each) in the mut clones. We first hypothesized that ARID1A loss could directly affect chromatin accessibility at the FAS promoter. However, we did not observe different chromatin accessibility at the FAS promoter. Next, we searched our data for all known FAS-regulating transcription factors (TFs) (https://dorothea.opentargets.io/#/), but could not identify candidates that were both differentially accessible and differentially expressed. Finally, we searched our data for transcriptional networks, i.e. hubs of all recognized FAS-regulating TFs and their known and predicted interacting partners (https://string-db.org/). Through this, we identified RUNX3, a predicted Co-TF of ETS1, to be both less accessible ("closed chromatin") and less expressed upon ARID1A loss (Fig C), suggesting a novel ARID1A-dependent FAS-regulatory network. To functionally validate our model, we first confirmed reduced RUNX3 expression in ARID1A mutant clones by qPCR and Western blot, and showed that ETS1 levels were unaffected by ARID1A loss. Then, we stably overexpressed RUNX3 in ARID1A mutant clones by lentiviral transduction and could indeed show rescue of FAS surface levels by FACS (Fig D). Lastly, we wanted to validate our findings in primary patients samples. We quantified FAS expression in FL biopsies with known ARID1A mutation status by nCounter gene expression profiling (GEP; N=51, 12 mut vs 39 WT) and quantitative multispectral imaging (QMI; N=44, 10 mut vs 34 WT) (Fig E). Both approaches showed significantly reduced FAS expression in ARID1A mutant FL (P<0.05 for GEP, P<0.0001 for QMI; Fig E). In summary, we show that ARID1A loss is directly linked to reduced FAS expression via a novel RUNX3/ETS1 transcriptional network, potentially opening avenues for therapeutic targeting of this clinically relevant perturbation. Figure 1 Figure 1. Disclosures Subklewe: Pfizer: Consultancy, Speakers Bureau; Takeda: Speakers Bureau; Klinikum der Universität München: Current Employment; Janssen: Consultancy; Seattle Genetics: Consultancy, Research Funding; Roche: Research Funding; Novartis: Consultancy, Research Funding, Speakers Bureau; MorphoSys: Research Funding; Miltenyi: Research Funding; Gilead: Consultancy, Research Funding, Speakers Bureau; Amgen: Consultancy, Research Funding, Speakers Bureau; BMS/Celgene: Consultancy, Research Funding, Speakers Bureau. von Bergwelt: Kite/Gilead: Honoraria, Research Funding, Speakers Bureau; Roche: Honoraria, Research Funding, Speakers Bureau; Novartis: Honoraria, Research Funding, Speakers Bureau; Astellas: Honoraria, Research Funding, Speakers Bureau; Miltenyi: Honoraria, Research Funding, Speakers Bureau; BMS: Honoraria, Research Funding, Speakers Bureau; Mologen: Honoraria, Research Funding, Speakers Bureau; MSD Sharpe & Dohme: Honoraria, Research Funding, Speakers Bureau. Weigert: Janssen: Speakers Bureau; Epizyme: Membership on an entity's Board of Directors or advisory committees; Roche: Research Funding.

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Investigation of the Mechanism of Idelalisib Resistance in the Follicular Lymphoma WSU-Fsccl Cell Line

Blood ◽

10.1182/blood.v126.23.2482.2482 ◽

2015 ◽

Vol 126 (23) ◽

pp. 2482-2482 ◽

Cited By ~ 2

Author(s):

Rick Sorensen ◽

Sarah Meadows ◽

Anella Yahiaoui ◽

Li Li ◽

Peng Yue ◽

...

Keyword(s):

Western Blot ◽

Growth Inhibition ◽

Follicular Lymphoma ◽

Single Cell ◽

Cell Line ◽

Wnt Pathway ◽

Parental Line ◽

Rna Seq ◽

Resistance Mutations ◽

Cell Clones

Abstract Idelalisib (Zydelig®), a first-in-class, selective, oral inhibitor of PI3Kd, is approved in the US and EU for the treatment of patients with follicular lymphoma (FL) who have received at least 2 prior systemic therapies based on the outcome of a phase 2 clinical trial demonstrating an ORR of 54% (Gopal AK, et al. ASH 2014, Abstract 1708; Zydelig® SmPC, Mar 2015). Complete responses are rare (6%) and patients ultimately relapse leading to an urgent need to understand mechanisms of resistance (MOR) to idelalisib. We report here the MOR identified from 3 sets of the transformed FL cell line WSU-FSCCL which were made resistant to idelalisib by continuous in vitro exposure. Methods: Idelalisib resistance was established by continuous passaging of a clonal isolate of WSU-FSCCL in the presence of 1 μM idelalisib. Growth inhibition to idelalisib or other inhibitors was performed using CellTiter Glo viability assay (Promega) at 96 h. Clonal isolates of idelalisib sensitive (FSCCLS) and idelalisib resistant (FSCCLR) cell lines were generated through two rounds of single cell limiting dilution. Characterization of mutations and gene expression in FSCCLS and FSCCLR clones was done by whole exome sequencing (WES, GENEWIZ) and RNA-Seq (Expression Analysis), respectively. Whole cell lysates were analyzed by Simple Western using Peggy Sue (Protein Simple) or SDS-PAGE and Western blot. Results: WSU-FSCCL were highly sensitive to idelalisib and the pan-PI3K inhibitor GDC-0941 with an EC50 of 140 and 180 nM, respectively, indicating that cell viability is driven by PI3Kd, while profiling of BTK inhibitors showed continued lack of activity. FSCCLR showed a loss of sensitivity to idelalisib (1 μM) with a maximal growth inhibition of 16% vs. 85% for parental line (FSCCLS). WES analysisrevealed PIK3CA resistance mutations in 3 independently generated sets of FSCCLR single cell clones, while no PIK3CD, PIK3CB, or PIK3CG resistance mutations were observed. PIK3CA was mutated at N345K (11/11 clones), P539R (3/3 clones) and E970K (3/3 clones). PI3K isoform profiling showed no alterations in expression of any of the four p110 isoforms. Idelalisib activity on PIK3CA mutant clone viability was dramatically shifted (EC50 >5 μM). The sensitivity of PIK3CA mutant FSCCLR to the PI3Kα- specific inhibitor BYL719 was not increased compared to FSCCLS (EC50 > 1.5 μM).Interestingly the combination of idelalisib treatment with BYL719 (0.5 μM) restored the sensitivity of FSCCLR to a concentration in the range of parental cells (EC50 = 0.066 μM, Figure 1). A second set of FSCCLR clones (set 2) were PI3KCA WT and had a 2.7-fold upregulation of PTEN. A survey of compensatory pathway activation revealed upregulation of Src family kinase (SFK) phosphorylation (p-SFK Y416) and specifically of p-Hck Y411 and p-Lyn Y396. SFK phosphorylation was sensitive to treatment with the SFK inhibitor dasatinib. Set 2 FSCCLR were slightly less sensitive to dasatinib (EC50 = 0.058 μM) compared to FSCCLS (EC50 = 0.034 μM). Interestingly, addition of 30 nM dasatinib (EC25 in FSCCLS) to FSCCLR increased the sensitivity of set 2 FSCCLR to idelalisib (EC50 = 0.95 μM) (Figure 2). FSCCLR clones were more resistant to the Syk inhibitor entospletinib (ENTO) (EC50 > 10 μM) as compared to FSCCLS (EC50 = 0.18 μM). Profiling of idelalisib activity on set 2 FSCCLR clones showed resistance to idelalisib as expected (EC50 > 10, μM); the addition of entospletinib at a clinically relevant concentration (0.68 μM), resulted in greater sensitivity than use of either single agent alone (EC50 = 2.27 μM ) (Figure 3). RNA-Seq analysis of the FSCCLR PIK3CA WT single cell clones additionally revealed that a subset of clones (set 3) upregulated a set of WNT pathway genes. Western blot analysis of set 3 FSCCLR showed upregulation of downstream markers of the canonical WNT pathway, including LEF1/TCF, c-Jun, β-catenin, c-Myc and p-GSK3β. Conclusions: Mechanisms of idelalisib resistance in the follicular lymphoma WSU-FSCCL cell line were independent of alterations in p110d but included the likely gain of function mutations in the PIK3CA gene and activation of SFK and WNT pathways. The sensitivity to idelalisib in the resistant clones could be re-established by the combination of idelalisib with inhibitors of compensatory pathways: BYL719 in PIK3CA mutant clones and dasatinib or entospletinib in SFK activated clones. Disclosures Sorensen: Gilead Sciences: Employment, Other: Share holder. Meadows:Gilead Sciences: Employment, Other: Share holder. Yahiaoui:Gilead Sciences: Employment, Other: Share holder. Li:Gilead Sciences: Employment, Other: Share holder. Yue:Gilead Sciences: Employment, Other: Share holder. Kashishian:Gilead Sciences: Employment, Other: Share holder. Queva:Gilead Sciences: Other: Share holder. Tannheimer:Gilead Sciences: Employment, Other: Share holder.

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Massively Parallel Single Cell RNA-Seq of Primary Lymphomas Reveals Distinct Cellular Lineages and Diverse, Intratumoral Transcriptional States

Blood ◽

10.1182/blood.v128.22.1090.1090 ◽

2016 ◽

Vol 128 (22) ◽

pp. 1090-1090

Author(s):

Noemi Andor ◽

Erin Simonds ◽

Jiamin Chen ◽

Susan Grimes ◽

Christina Wood ◽

...

Keyword(s):

B Cells ◽

Follicular Lymphoma ◽

B Cell ◽

Single Cell ◽

Mhc Class Ii ◽

Research Funding ◽

Immune Cell ◽

Single Cells ◽

Transcriptional Networks ◽

Rna Seq

Abstract Follicular lymphoma (FL) is a generally incurable B-cell malignancy which has the potential to transform into highly aggressive lymphomas. Genomic studies indicate it is often a small subpopulation rather than the dominant population in the FL that gives rise to the more aggressive subtype.To resolve the underlying transcriptional networks of follicular B-cell lymphomas at single molecule and cell resolution, we leveraged droplet-based barcoding technology for highly parallel single cell RNA-Seq. We analyzed the transcriptomes from tens of thousands of cells derived from five primary FL tumors (average > 5,000 cells/sample). Simultaneously, we conducted multi-dimensional flow cell sorting to validate our characterizing of cellular lineages and critical expressed proteins. For each tumor, we identified multiple cellular subpopulations, matching known hematopoietic lineages. Despite some common features, such as MYC and BCLoverexpression, distinct transcriptional patterns and regulatory programs were evident among the different tumors. Within each tumor, subpopulations of malignant cell transcripts were compared to matched normal B-cells (Figure 1). Transcriptome analysis of >13,500 B-cells across 5 samples reveals sample-specific and joint clusters of B-cells. Each dot represents the t-SNE projection of a single cell's transcriptome profile. Single cells are colored according to sample origin (control PBMC samples 1 & 2; follicular lymphoma samples 1, 2 & 3). Normal B-cells within follicular lymphoma samples cluster together with PBMC derived B-cells. Malignant B-cells cluster according to sample origin, except for the cycling tumor cells (upper left cell cluster). Malignant B-cells were characterized by expression of restricted immunoglobulin light chain type (either kappa or lambda), BCL2 expression, and CD20 expression. We show evidence for the coexistence of small, malignant subpopulations alongside the dominant FL population in the majority of tumors. These smaller subpopulations harbored several transcriptional changes that were absent from the dominant population, including upregulation of MHC class II expression, downregulation of β-2-microglobulin, and exclusive expression of chemokines (CCL22 and CCL17), that would have resulted in alteration in antigen presentation and of the T cell immune system. In addition, we characterize the transcriptomes of the infiltrating immune cell populations that are characteristic of this disease. Our findings provide an unprecedented resolution of distinct immune lineages as seen by transcriptionally characterized cellular diversity. Figure 1 Assignment of 13.5K B-cells to normal and malignant phenotypes. Figure 1. Assignment of 13.5K B-cells to normal and malignant phenotypes. Disclosures Levy: Kite Pharma: Consultancy; Five Prime Therapeutics: Consultancy; Innate Pharma: Consultancy; Beigene: Consultancy; Corvus: Consultancy; Dynavax: Research Funding; Pharmacyclics: 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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SAT-298 Integrative Single-Cell Transcriptomic and Epigenomic Landscape of Mouse Anterior Pituitary Cell Types

Journal of the Endocrine Society ◽

10.1210/jendso/bvaa046.593 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

Author(s):

Frederique Murielle Ruf-Zamojski ◽

Michel A Zamojski ◽

German Nudelman ◽

Yongchao Ge ◽

Natalia Mendelev ◽

...

Keyword(s):

Single Cell ◽

Cell Line ◽

Anterior Pituitary ◽

Cell Types ◽

Chromatin Accessibility ◽

Pituitary Cell ◽

Integrated Analysis ◽

Pituitary Cells ◽

Rna Seq ◽

Cell Type

Abstract The pituitary gland is a critical regulator of the neuroendocrine system. To further our understanding of the classification, cellular heterogeneity, and regulatory landscape of pituitary cell types, we performed and computationally integrated single cell (SC)/single nucleus (SN) resolution experiments capturing RNA expression, chromatin accessibility, and DNA methylation state from mouse dissociated whole pituitaries. Both SC and SN transcriptome analysis and promoter accessibility identified the five classical hormone-producing cell types (somatotropes, gonadotropes (GT), lactotropes, thyrotropes, and corticotropes). GT cells distinctively expressed transcripts for Cga, Fshb, Lhb, Nr5a1, and Gnrhr in SC RNA-seq and SN RNA-seq. This was matched in SN ATAC-seq with GTs specifically showing open chromatin at the promoter regions for the same genes. Similarly, the other classically defined anterior pituitary cells displayed transcript expression and chromatin accessibility patterns characteristic of their own cell type. This integrated analysis identified additional cell-types, such as a stem cell cluster expressing transcripts for Sox2, Sox9, Mia, and Rbpms, and a broadly accessible chromatin state. In addition, we performed bulk ATAC-seq in the LβT2b gonadotrope-like cell line. While the FSHB promoter region was closed in the cell line, we identified a region upstream of Fshb that became accessible by the synergistic actions of GnRH and activin A, and that corresponded to a conserved region identified by a polycystic ovary syndrome (PCOS) single nucleotide polymorphism (SNP). Although this locus appears closed in deep sequencing bulk ATAC-seq of dissociated mouse pituitary cells, SN ATAC-seq of the same preparation showed that this site was specifically open in mouse GT, but closed in 14 other pituitary cell type clusters. This discrepancy highlighted the detection limit of a bulk ATAC-seq experiment in a subpopulation, as GT represented ~5% of this dissociated anterior pituitary sample. These results identified this locus as a candidate for explaining the dual dependence of Fshb expression on GnRH and activin/TGFβ signaling, and potential new evidence for upstream regulation of Fshb. The pituitary epigenetic landscape provides a resource for improved cell type identification and for the investigation of the regulatory mechanisms driving cell-to-cell heterogeneity. Additional authors not listed due to abstract submission restrictions: N. Seenarine, M. Amper, N. Jain (ISMMS).

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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 landscape of nuclear configuration and gene expression during stem cell differentiation and X inactivation

Genome Biology ◽

10.1186/s13059-021-02432-w ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Giancarlo Bonora ◽

Vijay Ramani ◽

Ritambhara Singh ◽

He Fang ◽

Dana L. Jackson ◽

...

Keyword(s):

Gene Expression ◽

Single Cell ◽

Nuclear Structure ◽

Embryonic Stem ◽

Stem Cell Differentiation ◽

Chromatin Accessibility ◽

X Inactivation ◽

Rna Seq ◽

X Chromosomes ◽

Allele Specific

Abstract Background Mammalian development is associated with extensive changes in gene expression, chromatin accessibility, and nuclear structure. Here, we follow such changes associated with mouse embryonic stem cell differentiation and X inactivation by integrating, for the first time, allele-specific data from these three modalities obtained by high-throughput single-cell RNA-seq, ATAC-seq, and Hi-C. Results Allele-specific contact decay profiles obtained by single-cell Hi-C clearly show that the inactive X chromosome has a unique profile in differentiated cells that have undergone X inactivation. Loss of this inactive X-specific structure at mitosis is followed by its reappearance during the cell cycle, suggesting a “bookmark” mechanism. Differentiation of embryonic stem cells to follow the onset of X inactivation is associated with changes in contact decay profiles that occur in parallel on both the X chromosomes and autosomes. Single-cell RNA-seq and ATAC-seq show evidence of a delay in female versus male cells, due to the presence of two active X chromosomes at early stages of differentiation. The onset of the inactive X-specific structure in single cells occurs later than gene silencing, consistent with the idea that chromatin compaction is a late event of X inactivation. Single-cell Hi-C highlights evidence of discrete changes in nuclear structure characterized by the acquisition of very long-range contacts throughout the nucleus. Novel computational approaches allow for the effective alignment of single-cell gene expression, chromatin accessibility, and 3D chromosome structure. Conclusions Based on trajectory analyses, three distinct nuclear structure states are detected reflecting discrete and profound simultaneous changes not only to the structure of the X chromosomes, but also to that of autosomes during differentiation. Our study reveals that long-range structural changes to chromosomes appear as discrete events, unlike progressive changes in gene expression and chromatin accessibility.

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Intrapatient Complex Transcriptional Responses to Conventional Chemotherapy in Relapsed Acute Myeloid Leukemia Revealed By Single Cell RNA-Seq Analysis

Blood ◽

10.1182/blood-2021-153848 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 1179-1179

Author(s):

Hideaki Mizuno ◽

Akira Honda ◽

Mineo Kurokawa

Keyword(s):

Single Cell ◽

Signaling Pathway ◽

Myeloid Leukemia ◽

Research Funding ◽

Chemotherapy Resistance ◽

Rna Seq ◽

Conventional Chemotherapy ◽

Chugai Pharmaceutical ◽

Dna Mutation ◽

Otsuka Pharmaceutical

Abstract Resistance to anthracycline and cytarabine based conventional chemotherapy often occurs and results in extremely poor prognosis in patients with acute myeloid leukemia (AML). Although chemotherapy resistance is the most critical clinical problem, the mechanisms by which AML confers resistance to conventional chemotherapy are not yet fully understood. In this study, we investigated the key mechanisms of chemotherapy resistance through single cell RNA-sequencing analysis using paired bone marrow AML cells longitudinally collected from two AML-MRC patients at diagnosis and relapse after anthracycline-based chemotherapy. AML blasts were sorted by CD45/SSC gating and subjected to single cell RNA-seq analysis. Single cell RNA-seq was performed using 10x Genomics' Chromium System. Mean estimated number of cells per sample was 3.403 (2,731-4,200) and median detected genes per cell ranged 3,030 to 3,918 among four samples. Data collected from paired samples were combined in following analysis. Transcriptome based clustering following UMAP dimensionality reduction distinguished 5 and 9 cluster groups in each paired sample. Chemotherapy sensitive cluster groups dominant at diagnosis and chemotherapy resistant cluster groups dominant at relapse were clearly divided. In each paired sample, a few AML cells at diagnosis were allocated to chemotherapy resistant cluster groups. This suggested that transcriptionally identifiable less frequent cells resistant to chemotherapy existed at diagnosis and may expand during and/or after chemotherapy maintaining its transcriptional features. Next, to determine whether these transcriptional features are correlated with DNA mutation profiles, we labeled DNA mutation status to each cell and compared frequencies of mutation. As far as we detected, AML recurrent mutations such as DNMT3A R882C and TP53 missense mutation were not related to chemotherapy resistant cluster groups, although this method was relatively limited by the nature of RNA-seq-based mutation detection. Then we sought to determine transcriptional features of resistant clones. Gene set enrichment analysis identified some gene groups such as E2F signaling pathway, MYC signaling pathway, hedgehog signaling pathway and TNFA signaling pathway as transcriptional signatures related to emergence after chemotherapy. Analysis of known hematopoietic differentiation gene signatures showed distinct differentiation profiles in each cluster groups, whereas resistant cluster groups were not necessarily related to hematopoietic stem cell signatures. Intrapatient variations of transcriptional signatures among the resistant cluster groups were detected, which indicated that accurate detection of transcriptional features related to chemotherapy resistance may be difficult by using bulk RNA-seq method. As for other cluster groups which were not dominant both at diagnosis and relapse, these cluster groups hardly changed its frequencies between at diagnosis and relapse, which suggested less proliferative leukemia cells persisted during chemotherapy and have various transcriptional features although whether these persisting cells contribute to relapse was unclear. Since enriched transcriptional signatures in resistant cluster groups were not consistent between the two patients, further analysis using samples collected from more patients would be needed to determine common critical chemotherapy resistant transcriptional signature. In conclusion, our analysis suggested that a transcriptionally identifiable small fraction of cells showing gene signatures related to chemotherapy resistance at diagnosis may expand during chemotherapy and revealed intrapatient transcriptional complexity of response to chemotherapy, which cannot be uncovered by bulk RNA-sequencing. Disclosures Honda: Takeda Pharmaceutical: Other: Lecture fee; Otsuka Pharmaceutical: Other: Lecture fee; Chugai Pharmaceutical: Other: Lecture fee; Ono Pharmaceutical: Other: Lecture fee; Jansen Pharmaceutical: Other: Lecture fee; Nippon Shinyaku: Other: Lecture fee. Kurokawa: MSD K.K.: Research Funding, Speakers Bureau; Kyowa Hakko Kirin Co., Ltd.: Research Funding, Speakers Bureau; Daiichi Sankyo Company.: Research Funding, Speakers Bureau; Astellas Pharma Inc.: Research Funding, Speakers Bureau; Pfizer Japan Inc.: Research Funding, Speakers Bureau; Nippon Shinyaku Co., Ltd.: Research Funding, Speakers Bureau; Sumitomo Dainippon Pharma Co., Ltd.: Research Funding, Speakers Bureau; Otsuka Pharmaceutical Co., Ltd.: Research Funding, Speakers Bureau; Eisai Co., Ltd.: Research Funding, Speakers Bureau; ONO PHARMACEUTICAL CO., LTD.: Research Funding, Speakers Bureau; Teijin Limited: Research Funding, Speakers Bureau; Takeda Pharmaceutical Company Limited.: Research Funding, Speakers Bureau; Chugai Pharmaceutical Company: Research Funding, Speakers Bureau; AbbVie GK: Research Funding, Speakers Bureau.

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Uncoupling p53 from an Embryonic Regulome Exhausts Quiescent CML Stem Cells through Inhibition of a HIF1alpha Molecular Program

Blood ◽

10.1182/blood-2021-150372 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 1541-1541

Author(s):

Mary T Scott ◽

Wei Liu ◽

Rebecca Mitchell ◽

Cassie Clarke ◽

Hassan Almasoudi ◽

...

Keyword(s):

Stem Cells ◽

Single Cell ◽

Research Funding ◽

Embryonic Stem ◽

Rna Seq ◽

Combination Drug ◽

Human Cd34 ◽

Molecular Features ◽

Cd34 Cells

Abstract Although it has been recognized for many years that cancer stem cells and embryonic stem cells (ESC) share molecular features, identifying ways to exploit this therapeutically has proved challenging. To date, these shared features have not been examined in the leukemic stem cells (LSC) found in patients with chronic myeloid leukemia (CML). By integrating known ES regulatory circuitry with transcriptomics datasets, including deep single-cell RNA-seq profiling of 15,670 LSC from five patients with CML, we identified a core ESC regulome in the LSC containing 1243 genes. The significant majority of this regulome (1102 genes) was up-regulated in cycling LSC, whilst quiescent LSC showed up-regulation of a characteristic set of 101 genes, unique to cells with high ESC identity and with regulatory circuitry enriched for c-Myc and Nanog modules. Membership of the ESC regulome included the TP53 gene which was transcriptionally repressed and detected at a lower frequency in quiescent LSC compared to cycling ones (11.8% vs 43.6%). We also demonstrated that tyrosine kinase inhibitors (TKI) repress the ESC regulome and TP53 expression in LSC, suggesting that the regulome safeguards against high levels of TP53 expression, thus promoting survival of quiescent LSC in the presence of TKI. We hypothesized that overcoming the influence of the regulome on TP53 expression would provide an opportunity to eradicate quiescent LSC. To this end, we used an MDM2 inhibitor (MDM2i), RG7388 (idasanutlin) or RG7112, to stabilize the p53 protein, examining its potential in combination with nilotinib (NIL) to eradicate CML LSC in vitro and in vivo, with RG7388 being the most optimized and furthest in development. The combination of NIL plus MDM2i in vitro was more effective at targeted LSC from primary patient samples than NIL treatment alone, as evidenced by reduced CFC and LTC-IC outputs (p<0.05, 0.01 respectively). Intriguingly, the combination of NIL plus MDM2i did not result in significant reductions in the number of LSC compared to NIL only, when we quantified them at the end of drug treatments in pre-clinical mouse models. Instead, we observed a functional decline of the LSC as evidenced by diminished engraftment potential in 2 o recipient mice (p<0.05; SCLtTA x BCR-ABL1 transgenic model) or diminished colony-plating potential (p<0.05). This was followed by near complete depletion of the LSC population (p<0.05) 28 days after cessation of combination drug treatment (patient-derived xenografts/PDX in immunocompromised mice). In order to understand the molecular events underpinning these drug effects on LSC, we performed RNA-seq analysis of drug-treated CD34 + cells in vitro (bulk cells), or of human CD34 + cells obtained from PDX (single cell RNA-seq). CD34 + cells treated with NIL plus MDM2i in vitro showed evidence of increased p53 stabilization and activation of p53 target genes, and this was accompanied by repression of the ESC regulome beyond that normally observed with NIL only. Similarly, in PDX we observed increased repression of the ESC regulome in human CD34 + cells exposed to the combination of NIL plus MDM2i that included repression of HIF1alpha and a signature of genes required for cellular adaptations to hypoxia, and growth factor-mediated resistance to TKI therapy. Further, single cell analysis of differentiated human CD45 + cells from our PDX model, provided compelling evidence that acquisition of this repressive signature in the LSC, through combined NIL plus MDM2i treatment, re-wires them towards a basophilic fate, consistent with functional exhaustion of the LSC compartment. In conclusion, we have identified an ESC regulome in CML LSC and demonstrate that a combination of a TKI plus an MDM2i leads to p53 upregulation which antagonizes this regulome, providing a highly effective strategy to target near complete loss of functional LSC in pre-clinical models. Our study has revealed a new therapeutic paradigm to examine in other cancer stem cell populations that utilize ESC regulatory programs. Disclosures Higgins: Roche/Genentech: Current Employment, Current equity holder in publicly-traded company. Copland: Astellas: Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau; Pfizer: Honoraria, Speakers Bureau; Incyte: Honoraria, Research Funding, Speakers Bureau; Cyclacel Ltd: Research Funding; Jazz: Honoraria, Speakers Bureau.

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Role of Signal Transducing Adaptor Protein-1 (STAP-1) in Chronic Myelogenous Leukemia Stem Cells

Blood ◽

10.1182/blood-2018-99-113725 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 4245-4245

Author(s):

Jun Toda ◽

Michiko Ichii ◽

Hirohiko Shibayama ◽

Hideaki Saito ◽

Yuichi Kitai ◽

...

Keyword(s):

Stem Cells ◽

Research Funding ◽

Myelogenous Leukemia ◽

Z Score ◽

Rna Seq ◽

Interacting Protein ◽

Hematopoietic Stem ◽

Flow Cytometric ◽

Apoptotic Genes ◽

Induced Apoptosis

Abstract Chronic myelogenous leukemia (CML) is a clonal myeloproliferative disorder caused by hematopoietic stem cells expressing the BCR-ABL fusion oncoprotein, which constitutively activates multiple signal transduction pathways such as mitogen-activated protein kinase, phosphatidylinositol 3-kinase/Akt, and Janus kinase/signal transducer and activator of transcription (JAK/STAT). Although tyrosine kinase inhibitor (TKI) therapy results in dramatic clinical success, studies have shown that TKIs are unable to eradicate leukemic stem cells (LSCs). Several key signaling molecules and pathways have been proposed to regulate the survival of CML LSCs in the presence of TKI; however, the details remain unclear. It is necessary to elucidate the mechanisms that maintain LSCs to better understand the pathogenesis of CML and develop new treatment approaches. The family of signal-transducing adaptor proteins (STAPs), which includes STAP-1 and STAP-2, has been implicated in various intracellular signaling pathways. In 2003, we cloned STAP-2 as a c-fms interacting protein and reported that STAP-2 binds to BCR-ABL and enhances activity, leading to the activation of downstream molecules such as ERK, STAT5, BCL-xL, and BCL2. STAP-1 was cloned as a c-kit interacting protein from a hematopoietic stem cell library, but it is unknown whether STAP-1 plays a role in CML. Given the structural homology between STAP-1 and STAP-2 and the hematopoietic expression of STAP-1, we hypothesized that STAP-1 might contribute to the leukemogenesis of CML. A STAP-1-deficient (KO) CML mouse model was developed. To generate this model, lineage (Lin)− Sca-1+ c-Kithigh (LSK) fraction isolated from bone marrow (BM) cells was infected with a retrovirus carrying BCR-ABL1 and GFP and subsequently transplanted into congeneric recipients. STAP-1 KO CML mice showed significantly longer survival than WT CML mice and displayed less severe splenomegaly and lung hemorrhages compared with WT mice. In recipient BM, absolute numbers of STAP-1 KO LSCs (GFP+ LSK cells) were significantly lower than WT LSCs. In the colony-forming assay, STAP-1 KO LSCs generated fewer colonies compared to WT LSCs. Using flow cytometric analysis, we found that STAP-1 KO LSCs had a higher apoptotic rate than WT LSCs. These findings suggest that the suppression of apoptosis induced by STAP-1 mediates longer survival of LSCs. To further understand the effects of STAP-1, we performed a gene expression analysis using RNA-sequence (RNA-seq) and compared WT and STAP-1 KO CML LSCs. When canonical pathways were analyzed with Ingenuity Pathway Analysis, various pathways associated with inflammatory cytokines were observed to be regulated in STAP-1 KO CML LSCs. Changes in mRNA expression, including that of SOS1, SOS2, FOXO3, FASLG, NFKB2, and BCL-xL, indicated that the PTEN signaling pathway, known to play a tumor suppressive role in CML, was significantly activated by STAP-1 KO (p=1.096E-3, activation Z-score=2.611). The pathway related to JAK/STAT signaling was also affected (p=2.04E-5, activation Z-score=-3.286). Downstream genes in the JAK/STAT signaling pathway, such as STAT5B and BCL-xL, were downregulated more than 2-fold in STAP-1 KO LSCs, suggesting that the deletion of STAP-1 inhibits the expression of STAT5-targeted anti-apoptotic protein and induced apoptosis of CML LSCs. To confirm the results of the RNA-seq experiment, an intracellular flow cytometric assay with CML Lin− cells was conducted. The frequency of cells positive for phosphorylated STAT5 was reduced for STAP-1 KO compared with that for WT. Quantitative PCR with CML LSCs confirmed the downregulation of BCL2 and BCL-xL, which are STAT5-targeted anti-apoptotic genes, in STAP-1 KO CML LSCs. In conclusion, we show that STAP-1 plays a crucial role in the maintenance of CML LSCs using a murine model of CML. STAP-1 deficiency results in the reduction of phosphorylated STAT5, downregulation of anti-apoptotic genes BCL-2 and BCL-xL, and induced apoptosis of CML LSCs. These findings suggest that STAP-1 and related signaling pathways could be potential therapeutic targets for CML LSCs. Disclosures Ichii: Celgene K.K.: Speakers Bureau; Kowa Pharmaceutical Co.,LTD.: Speakers Bureau; Novartis Pharma K.K.: Speakers Bureau. Shibayama:Fujimoto Pharmaceutical: Honoraria, Research Funding; Takeda Pharmaceutical Co.,LTD.: Honoraria, Research Funding; Celgene K.K.: Honoraria, Research Funding; Jansen Pharmaceutical K.K: Honoraria; Ono Pharmaceutical Co.,LTD: Honoraria, Research Funding; Novartis Pharma K.K.: Honoraria, Research Funding; Mundipharma K.K.: Honoraria, Research Funding; Bristol-Meyer Squibb K.K: Honoraria, Research Funding. Oritani:Novartis Pharma: Speakers Bureau. Kanakura:Alexion Pharmaceuticals, Inc.: Consultancy, Honoraria, Research Funding.

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Single Cell RNA Sequencing and V(D)J Profiling of T-Cell Large Granular Lymphocytosis

Blood ◽

10.1182/blood-2018-99-115166 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 2404-2404

Author(s):

Shouguo Gao ◽

Zhijie Wu ◽

Carrie Diamond ◽

Bradley Arnold ◽

Valentina Giudice ◽

...

Keyword(s):

Gene Expression ◽

T Cell ◽

Single Cell ◽

Research Funding ◽

Clonal Expansion ◽

Rna Seq ◽

Healthy Donors ◽

Tcr Repertoire ◽

Before And After ◽

Repertoire Diversity

Abstract Introduction . T-cell large granular lymphocytosis (T-LGL) is a low grade lymphoproliferative disorder, often clinically manifest as bone marrow failure. Treatment with immunosuppressive therapies is effective, but the dominant clone may persist even in responding patients. The pathogenesis of T-LGL has not been fully elucidated. In this study, we performed single cell RNA sequencing (sc-RNA seq) and V(D)J profiling to discern clonotypes and gene expression patterns of T lymphocytes from T-LGL patients who were sampled before and after treatment. Methods. Blood was obtained from patients participating in a phase 2 protocol of alemtuzumab as second line therapy (NCT00345345; Dumitriu B et al, Lancet Haematol 2016). Leukapheresis was performed in 13 patients (M/F 7/6; median age 51 years, range 26-85) before and after 3-6 months alemtuzumab administration and in 7 age-matched healthy donors. Cryopreserved blood was enriched for T cells with the EasySep Human T cell Isolation Kit (Stem cell). sc-RNA seq was performed on the 10XGenomics Chromium Single Cell V(D)J + 5' Gene Expression platform, and sequencing obtained on the HiSeq3000 Platform. Barcode assignment, alignment, unique molecular index counting and T cell receptor sequence assembly were performed using Cell Ranger 2.1.1. Results. Four hundred fifty thousand cells from 13 patients and 107,000 cells from 7 healthy donors were profiled. We measured productive TCR chains (which fully span the V and J regions, with a recognizable start codon in the V region and lacking a stop codon in the V-J region, thus potentially generating a protein). We detected at least one productive TCR α-chain in 50%, one productive TCR β-chain in 69% and paired productive αβ-chains in 47% of all cells. There was loss of TCR repertoire diversity in patients which was quantified by Simpson's diversity index; most patients showed oligoclonal or, less frequently, monoclonal expansion of the TCR repertoire (Fig. A). Regardless of clinical response, alemtuzumab treatment did not correct the low TCR repertoire diversity. TCR repertoires can be classified as "public", when they express identical TCR sequences across multiple individuals, or "private", when each individual displays distinct TCR clonotypes. No TCRA or TCRB CDR3 homology among patients was observed: most TCR clonotypes appeared to be private. Our data suggests that T-LGL is etiologically heterogenous disease, consistent with T cell expansion in response to a variety antigens, in diverse HLA contexts, or randomly. Despite differences of TCR among patients and healthy donors, and the presence of large clones in patients, distribution of TCR diversity followed the power law distribution in healthy donors and patients (Fig. B, showing the negative linear relationship between logarithmic expression of clone frequency and clone size). The observed distribution is consistent with a somatic evolution model, in which cell fitness depends on cellular receptor response to specific antigens and stimulation of cells by cytokine and other signals from the environment; fitted clones have higher birth-death ratios and thus expand (Desponds J et al, PNAS 2016). CD4 and CD8 T cells can be virtually separated by imputation from their transcriptomes (Fig. C). Comparison of gene expression between patients and healthy donors showed dysregulation of genes involved in pathways related to the immune response and cell apoptosis, consistent with a pathophysiology of T cell clonal expansion. We used diffusion mapping, which localizes datapoints to their eigen components in low-dimesional space, to characterize sources contributing to the gene expression phenotype: the first component was mainly from T cell activation and the second was associated with TCR expression. In LGL the T cell transcriptome appeared to be shaped by both lineage development and TCR rearrangement. Conclusion. We describe at the single cell level T clonal expansion profiles in T-LGL, pre- and post-treatment. Single cell analysis allows accurate recovery of paired α and β chains in the same cell and demonstrates a continuum of cell lineage differentiation. We found a range of differences in transcriptome and TCR repertoires across patients. Transcriptome data, coupled with detailed TCR-based lineage information, provides a rich resource for understanding of the pathology of T-LGL and has implications for prognosis, treatment, and monitoring in the clinic. Figure. Figure. Disclosures Young: GlaxoSmithKline: Research Funding; CRADA with Novartis: Research Funding; National Institute of Health: Research Funding.

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