scholarly journals Single-cell analyses identify circulating anti-tumor CD8 T cells and markers for their enrichment

2020 ◽  
Author(s):  
Kristen E. Pauken ◽  
Osmaan Shahid ◽  
Kaitlyn A. Lagattuta ◽  
Kelly M. Mahuron ◽  
Jacob M. Luber ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Therapeutic Potential ◽  
Cell Receptor ◽  
Cell Responses ◽  
Cell Clones ◽  
Single Cell Rna Sequencing ◽  
Melanoma Patients

AbstractThe ability to monitor anti-tumor CD8+ T cell responses in the blood has tremendous therapeutic potential. Here, we used paired single-cell RNA sequencing and T cell receptor (TCR) sequencing to detect and characterize “tumor matching” (TM) CD8+ T cells in the blood of mice with MC38 tumors and melanoma patients using the TCR as a molecular barcode. TM cells showed increased activation compared to non-matching T cells in blood, and appeared less exhausted than matching counterparts in tumor. Importantly, PD-1, which has been used to identify putative circulating anti-tumor CD8+ T cells, showed poor sensitivity for identifying TM cells. By leveraging the transcriptome we identified candidate cell surface marker panels for TM cells in mice and melanoma patients, and validated NKG2D, CD39, and CX3CR1 in mice. These data demonstrate that the TCR can be used to identify tumor-relevant populations for comprehensive characterization, reveal unique transcriptional properties of TM cells, and develop marker panels for tracking and analysis of these cells.SummaryUsing single-cell RNA-sequencing coupled with TCR sequencing, we detected CD8+ T cell clones shared between blood and tumor in mice and melanoma patients, characterized these matching clones in blood and tumor, and identified potential biomarkers for their isolation in blood.

scholarly journals Single-Cell RNA Sequencing Reveals Tissue Compartment-Specific Plasticity of Mycosis Fungoides Tumor Cells

2021 ◽  
Vol 12 ◽  
Author(s):  
Katharina Rindler ◽  
Wolfgang M. Bauer ◽  
Constanze Jonak ◽  
Matthias Wielscher ◽  
Lisa E. Shaw ◽  
...  
Keyword(s):  
T Cells ◽  
Lymph Node ◽  
T Cell ◽  
Single Cell ◽  
Tumor Cells ◽  
Rna Sequencing ◽  
Mycosis Fungoides ◽  
Cell Receptor ◽  
Skin Tumor ◽  
Single Cell Rna Sequencing

Mycosis fungoides (MF) is the most common primary cutaneous T-cell lymphoma. While initially restricted to the skin, malignant cells can appear in blood, bone marrow and secondary lymphoid organs in later disease stages. However, only little is known about phenotypic and functional properties of malignant T cells in relationship to tissue environments over the course of disease progression. We thus profiled the tumor micromilieu in skin, blood and lymph node in a patient with advanced MF using single-cell RNA sequencing combined with V-D-J T-cell receptor sequencing. In skin, we identified clonally expanded T-cells with characteristic features of tissue-resident memory T-cells (TRM, CD69+CD27-NR4A1+RGS1+AHR+). In blood and lymph node, the malignant clones displayed a transcriptional program reminiscent of a more central memory-like phenotype (KLF2+TCF7+S1PR1+SELL+CCR7+), while retaining tissue-homing receptors (CLA, CCR10). The skin tumor microenvironment contained potentially tumor-permissive myeloid cells producing regulatory (IDO1) and Th2-associated mediators (CCL13, CCL17, CCL22). Given their expression of PVR, TNFRSF14 and CD80/CD86, they might be under direct control by TIGIT+CTLA4+CSF2+TNFSF14+ tumor cells. In sum, this study highlights the adaptive phenotypic and functional plasticity of MF tumor cell clones. Thus, the TRM-like phenotype enables long-term skin residence of MF cells. Their switch to a TCM-like phenotype with persistent skin homing molecule expression in the circulation might explain the multi-focal nature of MF.

scholarly journals Early precursors and molecular determinants of tissue-resident memory CD8+ T lymphocytes revealed by single-cell RNA sequencing

2020 ◽  
Vol 5 (47) ◽  
pp. eaaz6894 ◽  
Author(s):  
Nadia S. Kurd ◽  
Zhaoren He ◽  
Tiani L. Louis ◽  
J. Justin Milner ◽  
Kyla D. Omilusik ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Expression Patterns ◽  
Microbial Infection ◽  
Cell Responses ◽  
Molecular Determinants ◽  
Single Cell Rna Sequencing ◽  
Potent Protection

During an immune response to microbial infection, CD8+ T cells give rise to distinct classes of cellular progeny that coordinately mediate clearance of the pathogen and provide long-lasting protection against reinfection, including a subset of noncirculating tissue-resident memory (TRM) cells that mediate potent protection within nonlymphoid tissues. Here, we used single-cell RNA sequencing to examine the gene expression patterns of individual CD8+ T cells in the spleen and small intestine intraepithelial lymphocyte (siIEL) compartment throughout the course of their differentiation in response to viral infection. These analyses revealed previously unknown transcriptional heterogeneity within the siIEL CD8+ T cell population at several stages of differentiation, representing functionally distinct TRM cell subsets and a subset of TRM cell precursors within the tissue early in infection. Together, these findings may inform strategies to optimize CD8+ T cell responses to protect against microbial infection and cancer.

scholarly journals Microenvironmental correlates of immune checkpoint inhibitor response in human melanoma brain metastases revealed by T cell receptor and single-cell RNA sequencing

2021 ◽  
Author(s):  
Christopher A Alvarez-Breckenridge ◽  
Samuel C Markson ◽  
Jackson H Stocking ◽  
Naema Nayyar ◽  
Matthew Lastrapes ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Brain Metastases ◽  
Single Cell ◽  
Rna Sequencing ◽  
T Cell Receptor ◽  
Immune Checkpoint ◽  
Cell Receptor ◽  
Mesenchymal Transition ◽  
Single Cell Rna Sequencing

Melanoma-derived brain metastases (MBM) represent an unmet clinical need due to central nervous system (CNS) progression as a frequent, end-stage site of disease. Immune checkpoint inhibition (ICI) represents a clinical opportunity against MBM; however, the MBM tumor microenvironment (TME) has not been fully elucidated in the context of ICI. To dissect unique MBM-TME elements and correlates of MBM-ICI response, we collected 32 fresh MBM and performed single cell RNA sequencing of the MBM-TME and T cell receptor clonotyping on T cells from MBM and matched blood and extracranial lesions. We observed myeloid phenotypic heterogeneity, most notably multiple distinct neutrophil states including an IL-8 expressing population that correlated with malignant cell epithelial-to-mesenchymal transition. Additionally, we observe significant relationships between intracranial T cell phenotypes and the distribution of T cell clonotypes intracranially and peripherally. We found that the phenotype, clonotype, and overall number of MBM-infiltrating T cells were associated with response to ICI, suggesting that ICI-responsive MBMs interact with peripheral blood in a manner similar to extracranial lesions. These data demonstrate unique features of the MBM-TME, which may represent potential targets to improve clinical outcomes for patients with MBM.

scholarly journals Single-cell RNA sequencing reveals ex vivo signatures of SARS-CoV-2-reactive T cells through ‘reverse phenotyping’

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
David S. Fischer ◽  
Meshal Ansari ◽  
Karolin I. Wagner ◽  
Sebastian Jarosch ◽  
Yiqi Huang ◽  
...  
Keyword(s):  
T Cells ◽  
Single Cell ◽  
Rna Sequencing ◽  
Ex Vivo ◽  
Severe Disease ◽  
Human Leukocyte ◽  
Cell Receptor ◽  
Single Cell Rna Sequencing

AbstractThe in vivo phenotypic profile of T cells reactive to severe acute respiratory syndrome (SARS)-CoV-2 antigens remains poorly understood. Conventional methods to detect antigen-reactive T cells require in vitro antigenic re-stimulation or highly individualized peptide-human leukocyte antigen (pHLA) multimers. Here, we use single-cell RNA sequencing to identify and profile SARS-CoV-2-reactive T cells from Coronavirus Disease 2019 (COVID-19) patients. To do so, we induce transcriptional shifts by antigenic stimulation in vitro and take advantage of natural T cell receptor (TCR) sequences of clonally expanded T cells as barcodes for ‘reverse phenotyping’. This allows identification of SARS-CoV-2-reactive TCRs and reveals phenotypic effects introduced by antigen-specific stimulation. We characterize transcriptional signatures of currently and previously activated SARS-CoV-2-reactive T cells, and show correspondence with phenotypes of T cells from the respiratory tract of patients with severe disease in the presence or absence of virus in independent cohorts. Reverse phenotyping is a powerful tool to provide an integrated insight into cellular states of SARS-CoV-2-reactive T cells across tissues and activation states.

scholarly journals Heterogeneity of T Cells in Atherosclerosis Defined by Single-Cell RNA-Sequencing and Cytometry by Time of Flight

2020 ◽  
Author(s):  
Holger Winkels ◽  
Dennis Wolf
Keyword(s):  
T Cells ◽  
T Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
T Regulatory Cells ◽  
Foam Cell ◽  
Regulatory Cells ◽  
T Helper ◽  
Antigen Specificity ◽  
Single Cell Rna Sequencing

The infiltration and accumulation of pro- and anti-inflammatory leukocytes within the intimal layer of the arterial wall is a hallmark of developing and progressing atherosclerosis. While traditionally perceived as macrophage- and foam cell-dominated disease, it is now established that atherosclerosis is a partial autoimmune disease that involves the recognition of peptides from ApoB (apolipoprotein B), the core protein of LDL (low-density lipoprotein) cholesterol particles, by CD4 + T-helper cells and autoantibodies against LDL and ApoB. Autoimmunity in the atherosclerotic plaque has long been understood as a pathogenic T-helper type-1 driven response with proinflammatory cytokine secretion. Recent developments in high-parametric cell immunophenotyping by mass cytometry, single-cell RNA-sequencing, and in tools exploring antigen-specificity have established the existence of several unforeseen layers of T cell diversity with mixed T H 1 and T regulatory cells transcriptional programs and unpredicted fates. These findings suggest that pathogenic ApoB-reactive T cells evolve from atheroprotective and immunosuppressive CD4 + T regulatory cells that lose their protective properties over time. Here, we discuss T cell heterogeneity in atherosclerosis with a focus on plasticity, antigen-specificity, exhaustion, maturation, tissue residency, and its potential use in clinical prediction.

scholarly journals OMIC-11. SINGLE CELL RNA SEQUENCING FROM THE CSF OF SUBJECTS WITH H3K27M+ DIPG/DMG TREATED WITH GD2 CAR T-CELLULAR THERAPY

2021 ◽  
Vol 23 (Supplement_1) ◽  
pp. i39-i39
Author(s):  
Aaron Mochizuki ◽  
Sneha Ramakrishna ◽  
Zina Good ◽  
Shabnum Patel ◽  
Harshini Chinnasamy ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Cell Product ◽  
Myeloid Suppressor Cells ◽  
Car T Cells ◽  
Car T Cell ◽  
Car T ◽  
Single Cell Rna Sequencing

Abstract Introduction We are conducting a Phase I clinical trial utilizing chimeric antigen receptor (CAR) T-cells targeting GD2 (NCT04196413) for H3K27M-mutant diffuse intrinsic pontine glioma (DIPG) and spinal cord diffuse midline glioma (DMG). Cerebrospinal fluid (CSF) is collected for correlative studies at the time of routine intracranial pressure monitoring via Ommaya catheter. Here we present single cell RNA-sequencing results from the first 3 subjects. Methods Single cell RNA-sequencing was performed utilizing 10X Genomics on cells isolated from CSF at various time points before and after CAR T-cell administration and on the CAR T-cell product. Output was aligned with Cell Ranger and analyzed in R. Results As detailed in the Majzner et al. abstract presented at this meeting, three of four subjects treated at dose-level one exhibited clear radiographic and/or clinical benefit. We have to date completed single cell RNA-sequencing for three of these four subjects (two with benefit, one without). After filtering out low-quality signals and doublets, 89,604 cells across 3 subjects were analyzed. Of these, 4,122 cells represent cells isolated from CSF and 85,482 cells represent CAR T-cell product. Two subjects who demonstrated clear clinical and radiographic improvement exhibited fewer S100A8+S100A9+ myeloid suppressor-cells and CD25+FOXP3+ regulatory T-cells in the CSF pre-infusion compared to the subject who did not derive a therapeutic response. In one subject with DIPG who demonstrated improvement, polyclonal CAR T-cells detectable in CSF at Day +14 demonstrated enrichment of CD8A, GZMA, GNLY and PDCD1 compared to the pre-infusion CAR T-cells by trajectory analysis, suggesting differentiation toward a cytotoxic phenotype; the same subject exhibited increasing numbers of S100A8+S100A9+ myeloid cells and CX3CR1+P2RY12+ microglia over time. Further analyses will be presented as data become available. Conclusions The presence of immunosuppressive myeloid populations, detectable in CSF, may correlate to clinical response in CAR T cell therapy for DIPG/DMG.

scholarly journals Re-investigation of classic T cell subsets and identification of novel cell subpopulations by single-cell RNA sequencing

2021 ◽  
Author(s):  
Xuefei Wang ◽  
Xiangru Shen ◽  
Shan Chen ◽  
Hongyi Liu ◽  
Ni Hong ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Cell Surface ◽  
Single Cell ◽  
Rna Sequencing ◽  
T Cell Activation ◽  
Expression Profiles ◽  
T Cell Subsets ◽  
Cell Subpopulation ◽  
Single Cell Rna Sequencing

AbstractClassic T cell subsets are defined by a small set of cell surface markers, while single cell RNA sequencing (scRNA-seq) clusters cells using genome-wide gene expression profiles. The relationship between scRNA-seq Clustered-Populations (scCPops) and cell surface marker-defined classic T cell subsets remain unclear. Here, we interrogated 6 bead-enriched T cell subsets with 62,235 single cell transcriptomes and re-grouped them into 9 scCPops. Bead-enriched CD4 Naïve and CD8 Naïve were mainly clustered into their scCPop counterparts, while cells from the other T cell subsets were assigned to multiple scCPops including mucosal-associated invariant T cells and natural killer T cells. The multiple T cell subsets that form a single scCPop exhibited similar expression pattern, but not vice versa, indicating scCPops are much homogeneous cell populations with similar cell states. Interestingly, we discovered and named IFNhi T, a new T cell subpopulation that highly expressed Interferon Signaling Associated Genes (ISAGs). We further enriched IFNhi T by FACS sorting of BST2 for scRNA-seq analyses. IFNhi T cluster disappeared on tSNE plot after removing ISAGs, while IFNhi T cluster showed up by tSNE analyses of ISAGs alone, indicating ISAGs are the major contributor of IFNhi T cluster. BST2+ T cells and BST2− T cells showing different efficiencies of T cell activation indicates high level of ISAGs may contribute to quick immune responses.

scholarly journals Targeted reconstruction of T cell receptor sequence from single cell RNA-sequencing links CDR3 length to T cell differentiation state

2016 ◽  
Author(s):  
Shaked Afik ◽  
Kathleen B. Yates ◽  
Kevin Bi ◽  
Samuel Darko ◽  
Jernej Godec ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Cell Response ◽  
T Cell Response ◽  
Effector Memory ◽  
Cell State ◽  
Tcr Repertoire ◽  
Single Cell Rna Sequencing

ABSTRACTThe T cell compartment must contain diversity in both TCR repertoire and cell state to provide effective immunity against pathogens1,2. However, it remains unclear how differences in the TCR contribute to heterogeneity in T cell state at the single cell level because most analysis of the TCR repertoire has, to date, aggregated information from populations of cells. Single cell RNA-sequencing (scRNA-seq) can allow simultaneous measurement of TCR sequence and global transcriptional profile from single cells. However, current protocols to directly sequence the TCR require the use of long sequencing reads, increasing the cost and decreasing the number of cells that can be feasibly analyzed. Here we present a tool that can efficiently extract TCR sequence information from standard, short-read scRNA-seq libraries of T cells: TCR Reconstruction Algorithm for Paired-End Single cell (TRAPeS). We apply it to investigate heterogeneity in the CD8+T cell response in humans and mice, and show that it is accurate and more sensitive than previous approaches3,4. We applied TRAPeS to single cell RNA-seq of CD8+T cells specific for a single epitope from Yellow Fever Virus5. We show that the recently-described "naive-like" memory population of YFV-specific CD8+T cells have significantly longer CDR3 regions and greater divergence from germline sequence than do effector-memory phenotype CD8+T cells specific for YFV. This suggests that TCR usage contributes to heterogeneity in the differentiation state of the CD8+T cell response to YFV. TRAPeS is publicly available, and can be readily used to investigate the relationship between the TCR repertoire and cellular phenotype.

scholarly journals OP0003 AUTOREACTIVE CD4+ T CELLS AND THEIR TCR REPERTOIRE IN PR3-ANCA ASSOCIATED VASCULITIS

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1.3-1
Author(s):  
R. Kumar ◽  
N. Yoosuf ◽  
A. Bartoletti ◽  
A. Avik ◽  
B. Raposo ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Single Cell ◽  
Cd4 T Cells ◽  
Cell Receptor ◽  
Cd4 T Cell ◽  
Proteinase 3 ◽  
Anca Associated Vasculitis ◽  
Cell Clones ◽  
Tcr Repertoire

Background:ANCA-associated vasculitis (AAV) with proteinase 3 (PR3) ANCA is genetically associated with HLA-DP [1], is often relapsing in nature, and has a predisposition for kidneys, lungs and ear-nose-throat involvement [2]. Despite the presence of PR3+ANCA, indicating CD4+T-cell help in the disease, the knowledge about autoreactive CD4+T cells is scarce. Activated T cells have been shown at site of inflammation [3] and involvement of proinflammatory cytokines in circulation is also reported [4, 5].Objectives:Identification of autoreactive T cells may help to identify the drivers of the immune responses and chronicity. We therefore aimed to investigate PR3-specific CD4+T-cell responses in peripheral blood of AAV patients with a focus on both phenotype and T-cell receptor (TCR) repertoires.Methods:The study included sixty-six patients: 26 with active PR3 autoantibody+ AAV, 21 with inactive but PR3+ AAV and 19 with inactive PR3- AAV. In-vitro cultures with PR3 protein were established to assess antigen-specific cytokine responses in a 3-color fluorospot assay. Deep immunophenotyping was performed by flow cytometry. Antigen-responsive CD4+ T cells were isolated and single cell TCRαβ sequences were generated and analyzed from PR3+ AAV patients (n=5) using a previously published protocol [6].Results:PBMCs from AAV patients demonstrated an HLA-DP associated cytokine responses to PR3 stimulation including IFN-γ and IL-10, but not IL-17A. This T-cell autoreactivity was found to be confined to a highly differentiated CD4+ T cell population characterized by perforin and GPR56 expression, implicating a cytotoxic feature of the response. Active disease involved a reduction in expression of several markers associated with cytotoxicity amongst the CD4+GPR56+ T cells. Their frequency was also negatively associated with the doses of prednisolone. A similar phenotype was shared with T cells activated by human cytomegalovirus (HCMV) peptides in the same patient cohort. Single cell sequencing of paired alpha beta T-cell receptors (TCRs) revealed different patterns of gene usage between PR3 and HCMV reactive T cells. Moreover, we could identify shared (public) PR3-reactive T-cell clones between different HLA-DPB1*04:01+ patients.Conclusion:PR3 is an autoantigen which provokes ANCA responses in AAV patients. Our study identified PR3-reactive CD4+ T cells at the level of their phenotype and TCR repertoire. The autoreactive CD4+ T cells, present in both active and inactive disease, implicate chronic antigen exposure and the persistence of long-lived T-cell clones. The presence of public autoreactive clones between HLA-DPB1*04:01+ patients suggests an active role for these cells in pathogenesis of AAV and validates the link with predisposed genotype.References:[1]Lyons PA, Rayner TF, Trivedi S, Holle JU, Watts RA, Jayne DR, et al. Genetically distinct subsets within ANCA-associated vasculitis. New England Journal of Medicine. 2012; 367(3):214-223.[2]Kumar Sharma R, Lövström B, Gunnarsson I, Malmström V. Proteinase 3 autoreactivity in Anti-Neutrophil Cytoplasmic Antibody-associated vasculitis–immunological versus clinical features. Scandinavian Journal of Immunology. 2020:e12958.[3]Wilde B, Thewissen M, Damoiseaux J, van Paassen P, Witzke O, Tervaert JWCJAr, et al. T cells in ANCA-associated vasculitis: what can we learn from lesional versus circulating T cells? 2010; 12(1):204.[4]Hoffmann JC, Patschan D, Dihazi H, Müller C, Schwarze K, Henze E, et al. Cytokine profiling in anti neutrophil cytoplasmic antibody-associated vasculitis: a cross-sectional cohort study. Rheumatology international. 2019; 39(11):1907-1917.[5]Berti A, Warner R, Johnson K, Cornec D, Schroeder D, Kabat B, et al. Circulating Cytokine Profiles and ANCA Specificity in Patients with ANCA-Associated Vasculitis. Arthritis & rheumatology (Hoboken, NJ). 2018; 70(7):1114.[6]Han A, Glanville J, Hansmann L, Davis MM. Linking T-cell receptor sequence to functional phenotype at the single-cell level. Nature biotechnology. 2014; 32(7):684-692.Disclosure of Interests:None declared

scholarly journals Chicken peripheral blood lymphocyte response to ALV-J infection assessed by single-cell RNA sequencing

2021 ◽  
Author(s):  
Manman Dai ◽  
Min Feng ◽  
Ziwei Li ◽  
Weisan Chen ◽  
Ming Liao
Keyword(s):  
T Cells ◽  
T Cell ◽  
Viral Infection ◽  
Single Cell ◽  
Rna Sequencing ◽  
Peripheral Blood ◽  
Cell Populations ◽  
Control Group ◽  
Marker Genes ◽  
Single Cell Rna Sequencing

ABSTRACTChicken peripheral blood lymphocytes (PBLs) exhibit wide-ranging cell types, but current understanding of their subclasses, immune cell classification, and function is limited and incomplete. Previously, we found that viremia caused by avian leukosis virus subgroup J (ALV‐J) was eliminated by 21 days post infection (DPI), accompanied by increased CD8+ T cell ratio in PBLs and low antibody levels. Here we performed single-cell RNA sequencing (scRNA-seq) of PBLs in ALV-J infected and control chickens at 21 DPI to determine chicken PBL subsets and their specific molecular and cellular characteristics, before and after viral infection. Eight cell clusters and their potential marker genes were identified in chicken PBLs. T cell populations (clusters 6 and 7) had the strongest response to ALV-J infection at 21 DPI, based on detection of the largest number of differentially expressed genes (DEGs). T cell populations of clusters 6 and 7 could be further divided into four subsets: activated CD4+ T cells (cluster A0), Th1-like cells (cluster A2), Th2-like cells (cluster A1), and cytotoxic CD8+ T cells. Hallmark genes for each T cell subset response to viral infection were initially identified. Furthermore, pseudotime analysis results suggested that chicken CD4+ T cells could potentially differentiate into Th1-like and Th2-like cells. Moreover, ALV-J infection probably induced CD4+ T cell differentiation into Th1-like cells in which the most immune related DEGs were detected. With respect to the control group, ALV-J infection also had an obvious impact on PBL cell composition. B cells showed inconspicuous response and their numbers decreased in PBLs of the ALV-J infected chickens at 21 DPI. Percentages of cytotoxic Th1-like cells and CD8+ T cells were increased in the T cell population of PBLs from ALV-J infected chicken, which were potentially key mitigating factors against ALV-J infection. More importantly, our results provided a rich resource of gene expression profiles of chicken PBL subsets for a systems-level understanding of their function in homeostatic condition as well as in response to viral infection.

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