scholarly journals Comprehensive Activation Profiling of the Tabelecleucel Library, an Off-the-Shelf, Allogeneic EBV-Specific T-Cell Therapy

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 2809-2809
Author(s):  
Joseph M Benoun ◽  
Fiona J Ruiz ◽  
Kate Widmann ◽  
Tiffany Jehng ◽  
Tassja Spindler ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
T Cell ◽  
Manufacturing Process ◽  
Clustering Algorithm ◽  
Expression Patterns ◽  
Healthy Donors ◽  
Tcr Repertoire ◽  
T Cell Clonality ◽  
Cell Clonality

Abstract Background: Tabelecleucel (Tab-cel) is an investigational, off-the-shelf, allogenic Epstein-Barr virus (EBV)-specific T-cell immunotherapy. Tab-cel has shown clinical activity in patients with EBV + post-transplant lymphoproliferative disease (PTLD). Previously we have shown that the process for generating tab-cel from healthy donors results in a net amplification of EBV-target responsive T-cell clonality, and that upon activation, tab-cel demonstrates polyfunctionality associated with the secretion of effector and chemoattractive cytokines. Objective: We aim to comprehensively profile tab-cel through immunophenotype, TCR repertoire by analyzing overall repertoire overlap across lots, and TCR sequence homology (GLIPH 2.0 algorithm), cytokine polyfunctionality (PF), and differential gene expression patterns (GEP) between resting and TCR-MHC-driven EBV antigen stimulation states to replicate intrinsic effector responses associated with EBV + disease engagement. Methods: Immunophenotyping was performed using targeted FACS activation profiling (CD25/CD69), and 40-plex CyTOF. PF response and cytokine profiles were evaluated using the IsoLight single-cell PF strength assay. TCR repertoires were assessed using TCRβ immunoSEQ, and the GLIPH 2.0 algorithm was utilized to cluster TCRs that are predicted to bind the same MHC-restricted peptide antigen. GEP were evaluated using a custom Nanostring panel consisting of 333 T-cell lineage gene targets. Results: Baseline control activation levels of 7.9±1.3% increased specifically to 54.3±3.7% post-activation with EBV + targets (Figure 1A). Baseline PF was 0.54±0.14%, and upon EBV-specific activation, product cells demonstrated an average PF of 12.1±1.5%, demonstrating a 22.7-fold average increase (Figure 1B).The cytokine profile for activated tab-cel lots is primarily comprised of effector and chemoattractive cytokines including IFNγ and MIP1β. Baseline TCR repertoires of the initial donor peripheral T-cells are highly diverse; however, the tab-cel manufacturing process effectively amplified and enriched for EBV-specific TCRs that correspond back to a starting frequency of 2.6±0.58% of the initial donor TCR repertoire (Figure 1C). Notably, cross comparison of tab-cel-enriched TCRs against publicly available databases (VDJdb, McPas-TCR) identified previously curated EBV-specific TCRβ sequences as a component of the expanded repertoire. Additionally, using the GLIPH 2.0 clustering algorithm we were able to identify previously unannotated TCR sequences that clustered with known EBV-specific TCRβ sequences. The tab-cel post-activation GEP revealed associations with T-cell activation and polyfunctionality. The CD4/CD8 composition of a subset of tab-cel lots was analyzed: the average CD4:CD8 ratio of 0.25, with an average of CD8+ T-cells comprising 73% of the product. An extended immunophenotyping by CyTOF is currently being completed and will be reported at the time of presentation. Conclusions: In this expanded analysis we again demonstrate that the process for generating tab-cel from healthy donors enriches for known EBV-specific clones and results in a net amplification of EBV-target responsive T-cell clonality. Additionally, utilization of the GLIPH 2.0 clustering algorithm has led to the identification of novel putative EBV-specific TCR sequences that are enriched through the tab-cel manufacturing process. Upon activation, tab-cel exhibits a robust multifactorial activation signaling and demonstrates PF associated with secretion of effector and chemoattractive cytokines. Gene expression profiling of activated tab-cel lots highlights a conserved activation gene signature that is associated with post-activation PF. Lastly, these above analyses are being leveraged to perform correlation studies of immunophenotyped to post-activation PF, TCR repertoire characteristics, and GEP. These data support that the process for generating tab-cel from healthy donor PBMCs leads to the enrichment for EBV-specific T-cell clones that are capable of becoming activated upon stimulation with consistent final product characteristics. Figure 1 Figure 1. Disclosures Benoun: Atara Biotherapeutics: Current Employment. Ruiz: Atara Biotherapeutics: Current Employment. Widmann: Atara Biotherapeutics: Current Employment. Jehng: Atara Biotherapeutics: Current Employment. Spindler: Atara Biotherapeutics: Current Employment. Abraham: Atara Biotherapeutics: Current Employment. Minne: Atara Biotherapeutics: Consultancy. Tracy: Atara Biotherapeutics: Current Employment. Munson: Atara Biotherapeutics: Current Employment. Thota: Atara Biotherapeutics: Current Employment. Wang: Atara Biotherapeutics: Current Employment. Chuan: Atara Biotherapeutics: Current Employment. Yedwabnick: Atara Biotherapeutics: Current Employment. Dubovsky: Atara Biotherapeutics: Current Employment.

Assessment of T-Cell Receptor Repertoire and Clonal Expansion in Peripheral T-Cell Lymphoma Using RNA-Seq Data

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 1451-1451
Author(s):  
Chao Wang ◽  
Qiang Gong ◽  
Weiwei Zhang ◽  
Javeed Iqbal ◽  
Yang Hu ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
T Cell Receptor ◽  
Cell Lymphoma ◽  
Cell Receptor ◽  
T Cell Lymphoma ◽  
Rna Seq ◽  
Tcr Repertoire ◽  
T Cell Clonality ◽  
Cell Clonality

Abstract Introduction: Diversity of the T-cell receptor (TCR) repertoire reflects the initial V(D)J recombination events as shaped by selection by self and foreign antigens. Next generation sequencing is a powerful method for profiling the TCR repertoire, including sequences encoding complementarity-determining region 3 (CDR3). Peripheral T-cell lymphoma (PTCL) is a group of malignancies that originate from mature T-cells. T-cell clonality of PTCL is routinely evaluated with a PCR-based method to detect TCR gamma and less frequently beta chain rearrangements using genomic DNA. However, there are limitations with this approach, chief among which is the lack of sequence information. To date, the TCR repertoire of different subtypes of PTCL remains poorly defined. Objective: The purpose of this study was to determine the utility of RNA-seq for assessing T-cell clonality and analyzing the TCR usage in PTCL samples. Methods: We analyzed RNA-seq data from 30 angioimmunoblastic T-cell lymphoma (AITL), 23 Anaplastic large cell lymphoma (ALCL), 10 PTCL-NOS, and 17 NKCL. Data from naïve T cells, TFH cells, and T-effector cells (CD4+ CD45RA− TCRβ+ PD-1lo CXCR5lo PSGL-1hi) were obtained from publicly available resources. Referenced TCR and immunoglobulin transcripts according to the International ImMunoGeneTics Information System (IMGT) database were quantified by Kallisto software. We divided the pattern of Vβ (T-cell receptor beta variable region) into three categories: monoclonal (mono- or bi-allelic), oligoclonal (3-4 dominant clones), and polyclonal. CDR3 sequences were extracted by MiXCR program. PCR of the gamma chain using genomic DNA was utilized to validate the clonality of selected cases. Single nucleotide variants (SNVs) were called from aligned RNA-seq data using Samtools and VarScan 2 programs. Results: Analysis of RNA-seq data identified preferential usage of TCR-Vβ, Dβ (diversity region), and Jβ (joining region), length diversity of CDR3, and usage of nontemplated bases. Dominant clones could be identified by transcriptome sequencing in most cases of AITL (21/30), ALCL (14/23), and PTCL-NOS (7/10). Median CDR3 length is 42 nucleotides (nt) in normal T cells, 41 nt in ALCL, 48 nt in PTCL-NOS, and 44 nt in AITL. In 30 AITL samples, 20 showed monoclonal Vβ with a single peak, and 9 showed polyclonal Vβ. One case had two dominant clones with different CDR3, only one of which was in frame, implying biallelic rearrangements. As many as 3511 clones supported by at least four reads could be detected in polyclonal cases. In monoclonal cases, the dominant clone varied between 11.8% and 92.8% of TCR with Vβ rearrangements. TRBV 20-1, which is the most commonly used segment in normal T cells, is also frequently used in the dominant clones in AITL. The monoclonal AITL cases showed mutation of TET2, RHOA, DNMT3A or IDH2 whereas most of the polyclonal cases were negative or had low VAF mutation suggesting low or absent of tumor infiltrate in the specimen sequenced. There is no obvious correlation of any of the mutations with Vβ usage. Clonal B cell expansion was noted in some AITL samples. The occurrence of a preferential TRBV9 expansion in PTCL-NOS was striking. More than half of ALCL samples (14/23) showed expression of clonal Vβ, but 3/14 dominant clones were out-of-frame. γ chain expression was very low in cells expressing TCRαβ, but both expression levels and clonality were higher in TCRγδ expressing tumors. NKCL did not express significant levels of TCR Vβ or Vγ genes. Discussion/Interpretation: Transcriptome sequencing is a useful tool for understanding the TCR repertoire in T cell lymphoma and for detecting clonality for diagnosis. Clonal, often out-of-frame, Vβ transcripts are detectable in most ALCL cases and preferential TRBV9 usage is found in PTCL-NOS. Disclosures No relevant conflicts of interest to declare.

scholarly journals Unique Gene Expression Patterns in Human T-cell Lines Generated from Multiple Sclerosis Patients by Stimulation with a Synthetic MOG Peptide

2005 ◽  
Vol 12 (3) ◽  
pp. 203-209 ◽  
Author(s):  
Mathilda Mandel ◽  
Michael Gurevich ◽  
Gad Lavie ◽  
Irun R. Cohen ◽  
Anat Achiron
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
T Cell ◽  
Cell Lines ◽  
Healthy Subjects ◽  
Expression Patterns ◽  
Gene Expression Pattern ◽  
Gene Expression Patterns ◽  
T Cell Lines ◽  
Myelin Antigens

Multiple sclerosis (MS) is an autoimmune disease where T-cells activated against myelin antigens are involved in myelin destruction. Yet, healthy subjects also harbor T-cells responsive to myelin antigens, suggesting that MS patient-derived autoimmune T-cells might bear functional differences from T-cells derived from healthy individuals. We addressed this issue by analyzing gene expression patterns of myelin oligodendrocytic glycoprotein (MOG) responsive T-cell lines generated from MS patients and healthy subjects. We identified 150 transcripts that were differentially expressed between MS patients and healthy controls. The most informative 43 genes exhibited >1.5-fold change in expression level. Eighteen genes were up-regulated including BCL2, lifeguard, IGFBP3 and VEGF. Twenty five genes were down-regulated, including apoptotic activators like TNF and heat shock protein genes. This gene expression pattern was unique to MOG specific T-cell lines and was not expressed in T-cell lines reactive to tetanus toxin (TTX). Our results indicate that activation in MS that promotes T-cell survival and expansion, has its own state and that the unique gene expression pattern that characterize autoreactive T-cells in MS represent a constellation of factors in which the chronicity, timing and accumulation of damage make the difference between health and disease.

Impact of Lenalidomide on Gene Expression Profiles of Malignant and Immune Cells in Patients with Chronic Lymphocytic Leukemia

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 976-976 ◽  
Author(s):  
John C. Riches ◽  
Ajanthah Sangaralingam ◽  
Shahryar Kiaii ◽  
Tracy Chaplin ◽  
Demet Cekdemir ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
T Cell ◽  
B Cells ◽  
Family Member ◽  
Cell Function ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Lymphocytic Leukemia ◽  
Healthy Donors

Abstract Abstract 976 Lenalidomide has recently been demonstrated to have significant activity in chronic lymphocytic leukemia (CLL). Its mechanism of action in this disease is not well understood, but it is thought to act primarily by enhancing anti-tumor immunity and reducing production of pro-tumoral factors in the CLL microenvironment. We have previously demonstrated alterations in the expression of cytoskeletal genes in T-cells from patients with CLL and have subsequently shown that these changes translate into a deficit in T-cell function, due to impaired actin polymerization resulting in defective immunological synapse formation. Treatment of both autologous T-cells and CLL cells with lenalidomide was necessary to repair this defect, suggesting that this may be a key component of this agent's activity in CLL. Therefore we examined the effect of lenalidomide on the global gene expression profiles of isolated B-cells and T-cell subsets from CLL patients and healthy donors. Peripheral blood mononuclear cells from patients with untreated CLL or healthy donors were cultured in the presence of 1 μM lenalidomide or vehicle control for 48 hours. The lymphocyte subsets were isolated, followed by RNA extraction and gene expression profiling using the Affymetrix HGU133Plus2.0 platform. Lenalidomide treatment had similar effects on gene expression in T-cells from both patients with CLL and healthy donors. The most prominent changes in expression were of genes involved in cytoskeletal signaling including a 20-fold increase in WASF1 (Wiskott Aldrich Syndrome protein family, member 1), and greater than 2-fold increases in the expression of Rac-family member RHOC, (Ras homolog gene family, member C), actin binding proteins CORO1B (Coronin 1B), PARVA (Parvin alpha), and the Rho guanine nucleotide exchange factors (GEFs), ARHGEF5 and ARHGEF7. We also observed changes in genes regulating integrin signaling including PXN (Paxilin) and FAK (Focal adhesion kinase), and a shift towards Th1 differentiation with upregulation of TNF, IL-12R, and IL-18R. In addition, we noted increased expression of the transcription factors IKZF1, IKZF4 and IRF4, genes involved in the Ikaros pathways that are essential for hematopoiesis and control of lymphoid proliferation. These changes in gene expression provide further evidence that an important mechanism of action of lenalidomide is the upregulation of the actin cytoskeletal network including Rho-GTPases and integrin activation signaling, and are consistent with our previous observations concerning the functional repair of T-cells in CLL. Initial analysis of the effect of lenalidomide on the gene expression profiles of the CLL B-cells showed similar changes to those previously described in vivo from CLL patients receiving single agent lenalidomide in a clinical trial (Chen et al. JCO 2010). In our system, lenalidomide treatment resulted in a greater than 2-fold upregulation of 189 genes, and a greater than 2-fold downregulation of 85 genes in CLL B-cells. We observed increased expression of several genes belonging to the TNF superfamily including TNF-α, OX40L, and APRIL, and the receptors DR5, DCR2, and OX40. Many of these are known to mediate apoptosis signaling, and we also observed increased expression of pro-apoptotic genes such as FAS, BID (BH3 interacting domain death agonist), HRK (Harakiri), and CFLAR (CASP8 and FADD-like apoptosis regulator), and cell cycle regulators CDKN1A and CDKN1C (Cyclin-dependent kinase inhibitors 1A and 1C). Lenalidomide also upregulated expression of several genes of known importance in the CLL microenvironment, including the chemokines CCL3 and CCL4, CD40, CD274 (PD-L1), CD279 (PD-1), and adhesion molecules LFA3 and ICAM1. The effect of lenalidomide on the gene expression profiles of normal B-cells was less marked, with greater than 2-fold upregulation of 51 genes and downregulation of 12 genes. However, we did observe that lenalidomide treatment induced upregulation of genes involved in cytoskeletal pathways such as RND1 (Rho family GTPase 1), RHOQ (Ras homolog gene family, member Q), and MYO1B (myosin 1B). In conclusion, investigation of the effect of lenalidomide on gene expression profiling in CLL suggests that the drug acts both to enhance T-cell function, and to render the CLL cells more susceptible to immune cell mediated killing. Disclosures: Gribben: Roche: Honoraria; Celgene: Honoraria; GSK: Honoraria; Mundipharma: Honoraria; Gilead: Honoraria; Pharmacyclics: Honoraria.

Immunomodulatory Effects and Adaptive Immune Response to Daratumumab in Multiple Myeloma

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 3037-3037 ◽  
Author(s):  
Jakub Krejcik ◽  
Tineke Casneuf ◽  
Inger Nijhof ◽  
Bie Verbist ◽  
Jaime Bald ◽  
...  
Keyword(s):  
Immune Response ◽  
T Cells ◽  
T Cell ◽  
Research Funding ◽  
Immune Cell ◽  
Adaptive Immune Response ◽  
Advisory Committees ◽  
Adaptive Immune ◽  
T Cell Clonality ◽  
Cell Clonality

Abstract Introduction: Daratumumab (DARA) is a novel human monoclonal antibody that targets CD38, a protein that is highly expressed on multiple myeloma (MM) cells. DARA acts through multiple immune effector-mediated mechanisms, including complement-dependent cytotoxicity, antibody-dependent cell-mediated cytotoxicity, and antibody-dependent cellular phagocytosis. In two clinical studies (NCT00574288 [GEN501] and NCT01985126 [Sirius]) of DARA monotherapy in patients with relapsed and refractory MM, overall response rates were 36% and 29%, respectively. CD38 is highly expressed in myeloma cells but also expressed in lymphocytes and other immune cell populations. Therefore, the effects of DARA on immune cell populations and adaptive immune response pathways were investigated. Methods: The patient population investigated included treated subjects with MM that were relapsed after or were refractory to ≥2 prior therapies (GEN501) or had received ≥3 prior therapies, including a proteasome inhibitor (PI) and an immunomodulatory drug (IMiD), or were refractory to both a PI and an IMiD (Sirius). Patients assessed in this analysis were treated with 16 mg/kg DARA. When both studies were combined, median age (range) was 64 (31-84) years and median time from diagnosis was 5.12 (0.77-23.77) years. Seventy-six percent of patients had received >3 prior therapies and 91% were refractory to their last treatment. Clinical response was evaluated using IMWG consensus recommendations. Peripheral blood (PB) samples and bone marrow (BM) biopsies/aspirates were taken at prespecified time points and immunophenotyped by flow cytometry to enumerate various T-cell sub-types. T-cell clonality was measured by TCR sequencing. Antiviral T-cell response and regulatory T-cell (Treg) activity were analysed by functional in vitro assays. T-cell subpopulation counts were modelled over time with linear mixed modelling. Two group comparisons were performed using non-parametric Wilcoxon rank sum tests. Results: Data from 148 patients receiving 16 mg/kg DARA in GEN501 (n = 42) and Sirius (n = 106) were analyzed for changes in immune response. In PB, robust mean increases in CD3+ (44%), CD4+ (32%) and CD8+ (62%) T-cell counts per 100 days were seen with DARA treatment. However, responding evaluable patients (n = 45) showed significantly greater increases from baseline than nonresponders (n = 93) in CD3+ (P = 0.00012), CD4+ (P = 0.00031), and CD8+ (P = 0.00018) T cells. In BM aspirates the number of CD3+, CD4+, and CD8+ T-cells increased during treatment compared to baseline (the median percent increases were 19.95%, 5.66%, and 26.99% [n = 58]). Additionally, CD8+: CD4+ T-cell ratios significantly increased compared to baseline in both PB (P = 0.00017), and BM (P = 0.00016). T cell clonality, assessed by TCR sequencing, increased after DARA treatment compared with pretreatment (P = 0.049), with greater sums of absolute expansion in the repertoire (P = 0.037), as well as greater maximum expansion of a single clone (P = 0.048) in responders compared to nonresponders. Increased antiviral T-cell responses were observed post-DARA treatment, particularly in responders. Interestingly, a novel subpopulation of regulatory T cells was identified that expressed high levels of CD38. These cells comprised ~10% of all Tregs and were depleted by one DARA infusion. In ex vivo analyses, CD38+ Tregs appeared to be highly immune suppressive compared to CD38-Tregs. Conclusions: Robust T cell increases, increased CD8+: CD4+ ratios, increased antiviral responses, and increased T cell clonality were all observed after DARA treatment in a heavily pretreated, relapsed, and refractory patient population not expected to have strong immune responses. Improved clinical responses were associated with changes in these parameters. In addition, a sub-population of regulatory T cells expressing high CD38 levels was determined to be extremely immune suppressive and sensitive to DARA treatment. These data suggest a previously unknown immune modulatory role of DARA that may contribute to its efficacy, and a potential role for CD38 immune targeted therapies. We postulate that there are several distinct and complementary mechanisms that contribute to DARA's efficacy including increased antigen presentation through phagocytosis, targeting of immune suppressive Tregs, and increased adaptive immune responses. JK and TC contributed equally to this work. Disclosures Casneuf: Janssen: Employment. Verbist:Janssen: Employment. Bald:Janssen: Employment. Plesner:Genmab: Membership on an entity's Board of Directors or advisory committees; Roche and Novartis: Research Funding; Janssen and Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding. Liu:Janssen: Employment. van de Donk:Janssen Pharmaceuticals: Research Funding; Amgen: Research Funding; Celgene: Research Funding. Weiss:Janssen and Onclave: Research Funding; Janssen and Millennium: Consultancy. Ahmadi:Janssen: Employment. Lokhorst:Genmab: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Amgen: Honoraria. Mutis:Janssen: Research Funding; Genmab: Research Funding.

scholarly journals TCRβ Sequencing Reveals Spatial and Temporal Evolution of Clonal CD4 T cell Responses in a Breach of Tolerance Model of Inflammatory Arthritis

2020 ◽  
Author(s):  
Shaima Al-Khabouri ◽  
Robert A. Benson ◽  
Catriona T. Prendergast ◽  
Joshua I. Gray ◽  
Thomas D Otto ◽  
...  
Keyword(s):  
T Cell ◽  
Inflammatory Arthritis ◽  
Late Phase ◽  
Cd4 T Cell ◽  
Early Disease ◽  
Cell Responses ◽  
Cell Clones ◽  
Tcr Repertoire ◽  
T Cell Clonality ◽  
Cell Clonality

ABSTRACTObjectivesDevelopment of effective tolerogenic therapies for Rheumatoid Arthritis (RA) relies on understanding the evolution of articular antigen specific CD4 T cell responses. TCR clonality of the endogenous CD4 T cell infiltrate in early inflammatory arthritis was assessed to monitor the evolution of the TCR repertoire in the inflamed joint and its associated popliteal lymph node (pLN).MethodsMouse models of antigen-induced breach of self-tolerance and chronic polyarthritis were used to recapitulate the early and late phases of RA reported in patients. The infiltrating endogenous, antigen experienced CD4 T cells in inflamed joints and pLNs were analysed using flow cytometry and TCRβ sequencing.ResultsTCR repertoires from pLNs displayed increased clonality and diversity with disease progression, while inflamed joints maintain similar TCR repertoire clonality and diversity with time. Repertoires from late phase pLNs accumulated clones with a diverse range TRBV genes, while inflamed joints at both phases contain clones expressing similar TRBV genes. Repertoires from pLNs and joints at the late phase displayed reduced CDR3β sequence overlap compared to the early disease phase, however correlation analysis revealed the most abundant clones in pLNs accumulate in the joint at the later phase.ConclusionsCD4 T cell clonality broadens and evolves with progression of inflammatory arthritis and is reflected in pLNs before potentially being mirrored in the joint. These observations imply that antigen specific tolerogenic therapies for RA will be more easily developed and more effective at earlier phases of the disease, when CD4 T cell clonality is least diverse.KEY MESSAGESSelective accumulation of CD4 T cell clones has been observed in arthritic joints of RA patients, indicating the presence of antigen driven accumulation of CD4 T cells in these patients.These antigen specific T cell clones are thought to be pathogenic and thus are targets for tolerogenic therapy.This study suggests that CD4 TCR clonality is restricted at the early phases of disease and broadens with disease progression. Moreover, changes in CD4 TCR clonality are first reflected in joint draining lymph nodes before being mirrored in the inflamed joint.Thus tolerogenic therapies will be more effective when CD4 TCR clonality is restricted i.e. at early disease stages.Changes in CD4 TCR clonality in the joint draining lymph node can also be a biomarker for disease state.

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

Blood ◽  
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.

The correlation between tumor microenvironment and the clonality of the T-cell repertoire in lung cancer and colorectal cancer.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e14524-e14524
Author(s):  
Hua Cao ◽  
Jingxian Duan ◽  
Shunda Jiang ◽  
Tianhao Mu ◽  
Ruilian Xu
Keyword(s):  
Colorectal Cancer ◽  
Lung Cancer ◽  
T Cells ◽  
T Cell ◽  
Tumor Microenvironment ◽  
Clonal Expansion ◽  
T Helper ◽  
T Cell Clonality ◽  
Cell Clonality ◽  
Cell Clonal Expansion

e14524 Background: The tumor microenvironment has been shown to affect the responsiveness of immunotherapy. Effective anti-tumor immune response requires the activation and expansion of specific antigen-reactive T cell clones. It was reported that increased T cell clonality was associated with improved response to immunotherapy. However, what type of tumor microenvironment facilitates T cell clonal expansion remained controversial. The study aims to investigate the correlation between tumor microenvironment and the clonality of the T cell repertoire in lung cancer and colorectal cancer. Methods: 4 lung cancer patients and 4 colorectal cancer patients were enrolled in this study. Tumor tissues and peripheral blood samples were collected for RNA sequencing and T cell receptor CDR3 sequencing. The infiltration levels of 28 immune cells were estimated based on the mRNA expression of the genetic markers. The T cell clonality was defined as 1-Peilou’s evenness. Data were presented as mean± S.E.M. Results: The mean T cell clone counts in the blood samples of the 8 patients were 25676±4782 (ranging from 10259 to 45016), and the mean clonality of the TCR repertoires was 0.20±0.02 (ranging from 0.11 to 0.27). The clonality of T cells in colorectal cancer patients was similar to that of the lung cancer patients (0.22±0.02 versus 0.18±0.03, p = 0.31), showing comparable potentials of antigenic responses. The tumor infiltration of regulatory T cells, type 17 T helper cells, CD56bright natural killer cells, and natural killer cells varied greatly among patients, the coefficient of variation of those cells were 54.61%, 54.61%, 54.43%, and 55.62% respectively. In contrast, the coefficient of variation of monocytes was 23.34%, displaying a relatively even distribution among patients. The Pearson’s correlation coefficient was calculated to show the correlation between T cell clonality and the infiltration level of all 28 types of immune cells. Notably, only the infiltration of type 17 T helper cells significantly associated with T cell clonality, the positive correlation gave an R square value of 0.68 (r = 0.82, 95% confidence interval of 0.04-0.98, p = 0.04). The infiltration levels of CD4+ T cells, CD8+ T cells, regulatory T cells, type 1 and type 2 T cells, and gamma delta T cells were not affected by T cell clonal expansion. The expression of B cells, dendritic cells, macrophages, natural killer cells, and monocytes did not correlate with T cell clonal expansion. However, the abundance of neutrophils appears to positively correlate with T cell clonality (p = 0.09). Conclusions: The clonal expansion was significantly associated with the infiltration of type 17 T helper cells but not other subtypes of T cells, showing that the type 17 T helper cells are crucial to the antigenic responses in lung cancer and colorectal cancer. A neutrophil enriched tumor microenvironment may facilitate T cell clonal expansion.

Gene Expression Patterns Associated With Tumor-infiltrating CD4+  and CD8+ T Cells in Invasive Breast Carcinomas 

2020 ◽  
Author(s):  
Zhanwei Wang ◽  
Xi Yang ◽  
Jiamin Xu ◽  
Yuefen Pan ◽  
Junjun Shen ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
T Cell ◽  
Cd8 T Cells ◽  
Expression Patterns ◽  
Cd8 T Cell ◽  
Cd4 T Cell ◽  
Gene Expression Patterns ◽  
Cerna Network ◽  
Immune Score

Abstract Objective: This study investigated the gene expression patterns associated with tumor-infiltrating CD4+ and CD8+ T cells in invasive breast carcinomas.Methods: The gene expression data and corresponding clinical phenotype data from the Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) were downloaded. The stromal and immune score were calculated using ESTIMATE. The differentially expressed genes (DEGs) with a high vs. low stromal score and a high vs. low immune score were screened and then functionally enriched. The tumor-infiltrating immune cells were investigated using the Cibersort algorithm, and the CD4+ and CD8+ T cell-related genes were identified using a Spearman correlation test of infiltrating abundance with the DEGs. Moreover, the miRNA-mRNA pairs and lncRNA-miRNA pairs were predicted to construct the competing endogenous RNAs (ceRNA) network. Kaplan-Meier (K-M) survival curves were also plotted.Results: In total, 478 DEGs with a high vs. low stromal score and 796 DEGs with a high vs. low immune score were identified. In addition, 39 CD4+ T cell-related genes and 78 CD8+ T cell-related genes were identified; of these, 14 genes were significantly associated with the prognosis of BRCA patients. Moreover, for CD4+ T cell-related genes, the chr22-38_28785274-29006793.1-–miR-34a/c-5p–CAPN6 axis was identified from the ceRNA network, whereas the chr22-38_28785274-29006793.1–miR-494-3p–SLC9A7 axis was identified for CD8+ T cell-related genes.Conclusions: The chr22-38_28785274-29006793.1-–miR-34a/c-5p–CAPN6 axis and the chr22-38_28785274-29006793.1–miR-494-3p–SLC9A7 axis might regulate cellular activities associated with CD4+ and CD8+ T cell infiltration, respectively, in BRCA.

scholarly journals Single-Cell RNA Sequencing Unveils the Hallmarks of Populations at Different Stages of HTLV-1 Infection

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 3323-3323
Author(s):  
Yan Huang ◽  
Peifang Jiang ◽  
Jiazheng Li ◽  
Yanxin Chen ◽  
Zhengjun Wu ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
T Cell ◽  
Single Cell ◽  
Cd4 T Cells ◽  
Treg Cells ◽  
Cd4 T Cell ◽  
Expression Level ◽  
Normal People ◽  
Healthy Donors

Abstract Background Adult T-cell leukemia-lymphoma (ATL) is an aggressive mature T-cell neoplasm caused by human T -cell leukemia virus type 1 (HTLV-1). Up to 5% of infected individuals develop to ATL. HTLV-1 preferentially infects CD4 + T cells, and stimulates cell proliferation and prevents cell death by apoptosis. The viral oncogene-encoded proteins, Tax and HBZ, play important roles in viral infection and cell immortalization. However, the host factor of developing from carrier to patient is not clear. Results To characterize the heterogeneity of ATL patients, we performed single-cell RNA-sequencing (10x Genomics) analysis on single cell suspensions isolated from PBMCs of nine samples, including three ATL patients, three HTLV-1 asymptomatic carriers as well as three healthy donors (HD). We acquired 82977 high-quality cells with a median of 1718 genes detected per cell. Unsupervised clustering using Seurat followed by visualization in t-Stochastic Neighbor Embedding (t-SNE) identified 29 distinct cell clusters (Figure 1A). The single cell profiling of ATL patients were significantly different from that of carriers and healthy donors, while the latter two had little difference (Figure 1B). Based on singleR packages and marker genes of each cluster, 4 major cell populations (T cells, NK cells, B cells and myeloid cells) and other rare cell types were annotated, such as erythrocyte cluster and eosinophils cluster. We observed an enrichment of CD4 + T cell from patients in 4 cluster (Figure 1C), which proportion of cells was higher than that of carriers and healthy donors. According to cell type annotation, cells from cluster 11 were CD4 + CD25 + Foxp3 + Treg cells. Based on the increasing proportion of cluster 11 in healthy people, carriers and patients, without significant statistical differences, we assumed that Foxp3 + Treg cells were involved in the evolution of ATL tumor cells. That was identical with published literatures. To investigate the differences between tumor and normal CD4 + T cell, the gene expression was compared among 7 clusters of CD4 + T cell from three groups. Using a threshold of p value < 0.05 and | fold change| >2. Through integrated analysis, we identified 26 commonly upregulated genes (gene expression level: patients > carriers > HD) and 9 downregulated genes (gene expression level: patients < carriers < HD. To further analyze the biological function of the common DEGs, gene ontology (GO) analysis showed that these genes could be mainly categorized into plasma membrane and protein binding. Subsequently, we validated the mRNA expression level of upregulated common DEGs among three groups by qRT-PCR. The isolated CD4 + T cell using CD4 microbeads of a total of 6 patients, 3 carriers and 9 normal specimens were included. The result showed that the mRNA expression levels of gene CADM1 and RGS13 in patients were higher than those in carriers and healthy donors, although there was no statistical difference between patients and carriers, and the expression levels of carriers tended to be higher than those in normal people (Figure 1D and E). Previously, CADM1 has been revealed to be highly expressed in HTLV-1-infected CD4 + T cells. Our study confirmed this result by single-cell profiling. RGS13, a member of the regulators of G protein signaling (RGS) family, participates in cellular communication. The role of RGS13 in ATL needs to be investigated. Conclusions This study is the first time to analyze the single-cell RNA level of ATL patients, HTLV-1 virus carriers and normal people. The peripheral blood cell composition of the patient is significantly different from that of the carriers and healthy donors, while it is similar between carriers and normal people. CD4 + T cells are the main cell population of patients. The proportion of CD4 + CD25 + Foxp3 + Treg cells increased gradually in healthy people, carriers and patients. DEGs analysis showed that CADM1 and RGS13 were highly expressed in CD4 + T cells of patients, followed by carriers, validated by 18 clinical samples. However, the molecular mechanism of RGS13 in the process from HTLV-1 infection to ATL needs to be further studied. Figure 1 Figure 1. Disclosures Hu: Astellas Pharma, Inc.: Research Funding.

scholarly journals Selective Cell State in the Clonally Expanded T-Cell Compartment of Vκ*MYC Mice Responding to Treatment with Checkpoint Inhibitors

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 1581-1581
Author(s):  
Danielle C Croucher ◽  
Laura M Richards ◽  
Zhihua Li ◽  
Ellen nong Wei ◽  
Xian Fang Huang ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
T Cell ◽  
Mouse Model ◽  
Single Cell ◽  
Research Funding ◽  
Genetically Engineered ◽  
Cell State ◽  
Genetically Engineered Mouse Model ◽  
Tcr Repertoire

Abstract Introduction: Immune checkpoint receptor (ICR) blockade has emerged as an effective anti-tumour modality, but only in a subset of cancer patients. Moreover, in Multiple myeloma (MM), single-agent activity has not been observed, highlighting the need to better understand the mechanism of action of this class of drugs. We recently showed that combinatorial ICR blockade using αLAG3 and αPD-1 delays disease progression and improves survival in the transplantable Vκ*MYC model of MM (Croucher et al. ASH 2018). However, despite this being a controlled study with genetically-homogeneous tumours, anti-tumour immune responses were heterogeneous, with only a subset of mice demonstrating a delay in tumour progression (17/29 mice, response rate = 58.6%). Thus, using this model, we set out to define mechanisms underlying variability in response to ICR blockade. Methods: We established a cohort of mice by engrafting 5-week-old C57BL/6 mice with Vκ12598 cells via tail vein injection. Treatment with αLAG3/αPD-1 or Ig-control was initiated 1-week post-engraftment and bone marrow (BM) samples were collected 3 weeks after the start of treatment. Following FACS-enrichment of T cells and plasma cells (PCs), single cell suspensions were subjected to matched single-cell gene expression (5' scRNA-seq) and T cell receptor (TCR)/B cell receptor (BCR) profiling (10x Genomics). Results: Samples were selected for profiling based on response to treatment, with responders (n=4) defined by significantly lower disease burden compared to non-responders (n=3) and control-treated mice (n=5), as measured by serum M-protein and %PCs in BM/spleen at sacrifice. Unsupervised clustering of scRNA-seq data from PCs (n=3,318 cells) identified no gene expression or BCR repertoire differences between control and treated, or between responder and non-responder samples, supporting that variability in response was not related to malignant Vκ12598 cells themselves. Across all samples, a statistically significant difference was not detected between the total number of unique TCR sequences (clonotypes) comparing control-treated (351-2369), non-responders (1185-2327) and responders (1378-1698), with no overlapping TCR sequences between top clonotypes. Evaluation of TCR repertoire diversity revealed that αLAG3/αPD-1 treatment induces clonal T cell expansion in control versus treated mice, but this was not significantly different between responders and non-responders. Analysis of paired scRNA-seq data (n=21,520 cells) revealed that expanded T cells from αLAG3/αPD-1-treated mice occupy a different cell state in responder vs. non-responder mice. We speculate that underlying differences in the TCR repertoire may dictate the downstream phenotype of expanded, anti-tumour T cells in mice treated with combinatorial αLAG3/αPD-1. Tumour control following treatment was associated with clonal expansion of T cells expressing genes related to cytoxicity and activation (Ccl5, Ifng, Fasl, Gzmb), whereas tumour progression was associated with clonal expansion of proliferative T cells (Cdkn3, Birc5, Ccna2, Aurka, Mki67). Although T cell proliferation is typically a phenotype ascribed to effector T cells, recent studies have similarly observed this proliferative cell state in dysfunctional T cells within melanoma tumours. Moreover, emerging evidence supports suppression of T cell proliferation by CDK4/6 inhibitors as a means to augment anti-tumour activity of ICR-based therapy. Thus, studies exploring whether reversal of the observed proliferative T cell state can restore response to αLAG3/αPD-1 treatment in non-responding Vκ12598 mice are ongoing and will be reported. Conclusions: ICR inhibitors demonstrate significant activity in some cancers, however many patients fail to respond and a similarly promising level of efficacy has not been achieved in MM. Studies aimed at unraveling the mechanisms of response and resistance to ICR inhibitors are therefore needed to improve the utility of this class of drugs for all patients. Our approach of using paired single-cell gene expression and TCR repertoire profiling has enabled identification of molecular cell states specifically in expanded T cells of responder vs. non-responder mice. In turn, our work nominates novel mechanisms that may be used as potential biomarkers for anti-tumour immune responses as well as potential targets to augment responses to ICR blockade therapy. Disclosures Chesi: Abcuro: Patents & Royalties: Genetically engineered mouse model of myeloma; Novartis: Consultancy, Patents & Royalties: human CRBN transgenic mouse; Pfizer: Consultancy; Pi Therapeutics: Patents & Royalties: Genetically engineered mouse model of myeloma; Palleon Pharmaceuticals: Patents & Royalties: Genetically engineered mouse model of myeloma. Bergsagel: GSK: Consultancy, Honoraria; Genetech: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Oncopeptides: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Patents & Royalties: human CRBN mouse; Pfizer: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Sebag: Janssen: Research Funding; Bristol Myers-Squibb: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria; Karyopharm Therapeutics: Consultancy, Honoraria. Trudel: BMS/Celgene: Consultancy, Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; GlaxoSmithKline: Consultancy, Honoraria, Research Funding; Roche: Consultancy; Sanofi: Honoraria; Pfizer: Honoraria, Research Funding; Genentech: Research Funding.

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