Single-cell Multiomics Reveals Clonal T-cell Expansions and Exhaustion in Blastic Plasmacytoid Dendritic Cell Neoplasm

AbstractThe immune system represents a major barrier to cancer progression, driving the evolution of immunoregulatory interactions between malignant cells and T-cells in the tumor environment. Blastic plasmacytoid dendritic cell neoplasms (BPDCN), a rare acute leukemia with plasmacytoid dendritic cell (pDC) differentiation, provides a unique opportunity to study these interactions. pDCs are key producers of interferon alpha (IFNA) that play an important role in T-cell activation at the interface between the innate and adaptive immune system. To assess how uncontrolled proliferation of malignant BPDCN cells affects the tumor environment, we catalog immune cell heterogeneity in the bone marrow (BM) of five healthy controls and five BPDCN patients by analyzing 52,803 single-cell transcriptomes, including 18,779 T-cells. We test computational techniques for robust cell type classification and find that T-cells in BPDCN patients consistently upregulate interferon alpha (IFNA) response and downregulate tumor necrosis factor alpha (TNFA) pathways. Integrating transcriptional data with T-cell receptor sequencing via shared barcodes reveals significant T-cell exhaustion in BPDCN that is positively correlated with T-cell clonotype expansion. By highlighting new mechanisms of T-cell exhaustion and immune evasion in BPDCN, our results demonstrate the value of single-cell multiomics to understand immune cell interactions in the tumor environment.

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CTIM-29. CRUCIAL APPLICATION OF SINGLE CELL GENE EXPRESSION FOR MONITORING CHANGES IN GLIOBLASTOMA PATIENTS WITH SUSTAINED RADIOGRAPHIC RESPONSE TO CMV pp65-LAMP RNA-PULSED DENDRITIC CELL-BASED VACCINES

Neuro-Oncology ◽

10.1093/neuonc/noaa215.163 ◽

2020 ◽

Vol 22 (Supplement_2) ◽

pp. ii39-ii39

Author(s):

Oleg Yegorov ◽

Changlin Yang ◽

Anjelika Dechkovskaia ◽

Maryam Rahman ◽

Ashley Ghiaseddin ◽

...

Keyword(s):

Gene Expression ◽

T Cells ◽

T Cell ◽

Dendritic Cell ◽

Single Cell ◽

Immune Cell ◽

Nkt Cells ◽

Durable Response ◽

Radiographic Response ◽

Dc Vaccines

Abstract BACKGROUND The application of single cell sequencing as a novel immune monitoring platform can be used to identify the molecular mechanisms of immune response to dendritic cell- based vaccines, trace the cell types and states involved, and uncover novel biomarkers for immunotherapy. We applied single-cell RNA Seq analysis of longitudinal peripheral blood mononuclear cells (PBMCs) in patients with newly-diagnosed GBM enrolled on the ATTAC II clinical trial (FDA IND BB-16530; Clinicaltrials.gov # NCT02465268) who experienced a sustained radiographic response to autologous CMV pp65-LAMP RNA-pulsed DC vaccines plus GM-CSF and tetanus-diphtheria booster administered during adjuvant cycles of dose-intensified temozolomide. METHODS We constructed 5’ gene expression libraries and T cell receptor enriched libraries for 10x Genomics single-cell 5’ and VDJ sequencing, generated from PBMCs collected prior to and during patient immunization using dendritic cells loaded with messenger ribonucleic acid encoding the human cytomegalovirus (CMV) matrix protein pp65 conjugated with the lysosomal associated membrane protein (LAMP) sequence. RESULTS Overall, we sequenced a total of 189,808 single-cell transcriptomes from 5 patients. We leveraged these transcriptome-wide features to distinguish 15 peripheral immune cell subtypes in tested PBMCs. Analysis revealed dynamic changes in immune cell subsets over the course of first three vaccines, including increases in cytotoxic CD8 T cells, CD4 T cells, and NK cell subsets. Increased markers of T cell activation were observed during vaccination. Surprisingly, we observed a very high-level frequency of natural killer T (NKT) cells in the patient with a complete durable response compared to other patients. After three DC vaccines, the level of NKT cells in PBMC of this patient increased up to 10%. CONCLUSIONS These results emphasize the importance of subset specific profiling to achieve higher resolution in monitoring immune responses compared with bulk expression profiling in patients receiving immunotherapeutic treatment.

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An Atlas of Immune Cell Exhaustion in HIV-Infected Individuals Revealed by Single-Cell Transcriptomics

10.1101/678763 ◽

2019 ◽

Cited By ~ 2

Author(s):

Shaobo Wang ◽

Qiong Zhang ◽

Hui Hui ◽

Kriti Agrawal ◽

Maile Ann Young Karris ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Hiv Infection ◽

Single Cell ◽

Cd8 T Cells ◽

Chronic Infection ◽

Cell Function ◽

Immune Cell ◽

Gene Signatures ◽

Cell Exhaustion

Chronic infection with human immunodeficiency virus (HIV) can cause progressive loss of immune cell function, or exhaustion, which impairs control of virus replication. However, little is known about the development and maintenance, as well as heterogeneity of immune cell exhaustion. Here, we investigated the effects of HIV infection on immune cell exhaustion at the transcriptomic level by analyzing single-cell RNA sequencing of peripheral blood mononuclear cells from two healthy subjects (15,121 cells) and six HIV-infected donors (28,610 cells). We identified nine immune cell clusters and eight T cell subclusters according to their unique gene expression programs; three of these (exhausted CD4+ and CD8+ T cells and interferon-responsive CD8+ T cells) were detected only in samples from HIV-infected donors. An inhibitory receptor KLRG1 was identified in the exhausted T cell populations and further characterized in HIV infected individuals. We identified a novel HIV-1 specific exhausted CD8+ T cell population expressing KLRG1, TIGIT, and T-betdimEomeshi markers. Ex-vivo antibody blockade of KLRG1 restored the function of HIV-specific exhausted CD8+ T cells demonstrating the contribution of KLRG1+ population to T cell exhaustion and providing a novel target for developing immunotherapy to treat HIV chronic infection. Analysis of gene signatures also revealed impairment of B cell and NK cell function in HIV-infected donors. These data provide a comprehensive analysis of gene signatures associated with immune cell exhaustion during HIV infection, which could be useful in understanding exhaustion mechanisms and developing new cure therapies.

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A Single-Cell Transcriptional Analysis of Tumour Cells and the Immune Microenvironment during Disease Evolution in a Transgenic Mouse Model of Myeloma

Blood ◽

10.1182/blood-2018-99-118691 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 56-56 ◽

Cited By ~ 1

Author(s):

Danielle C Croucher ◽

Marta Chesi ◽

Zhihua Li ◽

Victoria Marie Garbitt ◽

Meaghen E Sharik ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Single Cell ◽

Board Of Directors ◽

Cd8 T Cells ◽

Immune Checkpoint ◽

Immune Cell ◽

Advisory Committees ◽

Disease Evolution ◽

Cell Exhaustion

Abstract Introduction: Multiple Myeloma (MM) is consistently preceded by pre-malignant asymptomatic monoclonal gammopathies (AMG). To date, our understanding of the pathogenesis of progression to MM remains incomplete. Genetic analyses of AMG cells compared to MM-derived plasma cells (PCs) have found few differences, suggesting that progression may be mediated in part by tumour-extrinsic mechanisms. To comprehensively examine the cellular and molecular complexities of MM pathogenesis, we performed an unbiased single cell RNA-sequencing (scRNA-seq) analysis of tumour cells as well as immune cells from the tumour microenvironment (TME) derived from transgenic mice transitioning from AMG to MM. Methods: We employed the Vk*MYC immune-competent mouse model of MM (C57BL/6/KaLwRij), which is a clinically and biologically faithful model of untreated disease that similarly progresses from AMG to MM with age. We established an age-based cohort of Vk*MYC mice to recapitulate a range of MM disease stages, generated single-cell suspensions from flushed bone marrow and subjected these cells to scRNA-seq profiling (10x Genomics). Results: Across 12 samples profiled to date, our scRNA-seq dataset contains 82,853 high-quality cells, expressing 17,922 genes. We employed dimensionality reduction and unsupervised graph-based clustering to visualize and group transcriptionally-similar cell populations, which revealed 42 clusters. Expression of known marker genes and computed correlation scores with bulk gene expression reference datasets enabled annotation of cell types, revealing both malignant cells and non-malignant immune cell populations. We first focused on single cell T/NK profiles in our data given the emerging utility of immune checkpoint inhibitors that target these populations. Although we did not observe numerical differences in the proportion of CD8+ T cells across disease stages, analysis of immune checkpoint receptor genes revealed increased expression of Pdcd1 (PD-1) and Lag3 in CD8+ T cells from mice with disease. Co-expression of LAG3 and PD-1 proteins was also confirmed using a Vk*MYC transplantable model, with a positive correlation between disease burden (%CD138+/B220- cells) and %PD1+LAG3+ CD8+ T cells by flow cytometry. Consistent with reports of PD-1 and LAG3 co-expression on non-functional exhausted T cells, CD8+ T cells from diseased mice demonstrated elevated T cell exhaustion scores in our scRNA-seq dataset. These observations suggest that T cell exhaustion may be mediated by multiple immune checkpoint receptors during disease evolution. Although combinatorial treatment with PD-1 and LAG3 antibodies failed to induce tumour regression in mice with established disease, the addition of cyclophosphamide (Cy) to these antibodies resulted in marked improvement in survival of the mice compared to Cy alone, presumably by promoting immunogenic cell death. Studies exploring the combination of LAG3 and PD-1 antibodies as a strategy to inhibit transition from AMG to MM in the Vk*MYC mice are ongoing and will be reported. We also performed subclustering analysis of 5,228 Sdc1+ (CD138) PCs in our scRNA-seq dataset revealing 11 distinct clusters, with evidence of inter- and intra-tumoural heterogeneity across all Vk*MYC mice. Differential gene expression analysis revealed a non-malignant PC (nPC) cluster as supported by lower Myc transgene and Ccnd2 expression. Moreover, this cluster was predominantly comprised of cells from age-matched control mice or mice with earlier disease. Single-cell chromosomal copy number analysis revealed loss of Chr5 in the majority of tumour cells from MM mice, but not in the nPC cluster. Loss of Chr5 was observed in tumor subclones from all AMG mice suggesting that it is an early and potentially unifying event in Vk*MYC mice during disease progression. Further, the data support the establishment of intratumoural heterogeneity early in disease evolution. Conclusions: Our approach of using scRNA-seq to characterize the pathogenesis of disease evolution in MM has enabled simultaneous measurement of intratumoural heterogeneity and immune cell phenotypes in the TME. In turn, this has provided insights into mechanisms that may contribute to transition from AMG to MM, including induction of T cell exhaustion and loss of mouse Chr5. Ongoing and future work aims to evaluate whether these mechanisms can be exploited therapeutically in pre-malignant AMG. Disclosures Sebag: Amgen Canada: Membership on an entity's Board of Directors or advisory committees; Janssen Inc.: Membership on an entity's Board of Directors or advisory committees; Celgene Canada: Membership on an entity's Board of Directors or advisory committees; Takeda Canada: Membership on an entity's Board of Directors or advisory committees. Pugh:Prosigna: Honoraria; N/A: Patents & Royalties: Hybrid-capture sequencing for determining immune cell clonality; N/A: Patents & Royalties: Combined hybrid-capture DNA sequencing for disease detection; Boehringer Ingelheim: Research Funding; Chrysalis Biomedical Advisors: Honoraria; Merck: Honoraria; DynaCare: Consultancy.

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540 Transcriptionally defined immune landscape in human gliomas

Journal for ImmunoTherapy of Cancer ◽

10.1136/jitc-2020-sitc2020.0540 ◽

2020 ◽

Vol 8 (Suppl 3) ◽

pp. A576-A576

Author(s):

Pravesh Gupta ◽

Minghao Dang ◽

Krishna Bojja ◽

Huma Shehwana ◽

Tuan Tran ◽

...

Keyword(s):

T Cells ◽

Dendritic Cell ◽

Single Cell ◽

Rna Sequencing ◽

Immune Cell ◽

Myeloid Cell ◽

Wild Type ◽

Cell Clusters ◽

Md Anderson ◽

Antigen Presenting

BackgroundBrain immunity is largely myeloid cell dominated rather than lymphoid cells in healthy and diseased state including malignancies of glial origins called as gliomas. Despite this skewed myeloid centric immune contexture, immune checkpoint and T cell based therapeutic modalities are generalizably pursued in gliomas ignoring the following facts i) T cells are sparse in tumor brain ii) glioma patients are lymphopenic iii) gliomas harbor abundant and highly complex myeloid cell repertoire. We recognized these paradoxes pertaining to fundamental understanding of constituent immune cells and their functional states in the tumor immune microenvironment (TIME) of gliomas, which remains elusive beyond a priori cell types and/or states.MethodsTo dissect the TIME in gliomas, we performed single-cell RNA-sequencing on ~123,000 tumor-derived sorted CD45+ leukocytes from fifteen genomically classified patients comprising IDH-mutant primary (IMP; n=4), IDH-mutant recurrent (IMR; n=4), IDH-wild type primary (IWP; n=3), or IDH-wild type recurrent (IWR; n=4) gliomas (hereafter referred as glioma subtypes) and two non-glioma brains (NGBs) as controls.ResultsUnsupervised clustering analyses delineated predominant 34-myeloid cell clusters (~75%) over 28-lymphoid cell clusters (~25%) reflecting enormous heterogeneity within and across glioma subtypes. The glioma immune diversity spanned functionally imprinted phagocytic, antigen-presenting, hypoxia, angiogenesis and, tumoricidal myeloid to classical cytotoxic lymphoid subpopulations. Specifically, IDH-mutant gliomas were predominantly enriched for brain-resident microglial subpopulations in contrast to enriched bone barrow-derived infiltrates in IDH-wild type especially in a recurrent setting. Microglia attrition in IWP and IWR gliomas were concomitant with invading monocyte-derived cells with semblance to dendritic cell and macrophage like transcriptomic features. Additionally, microglial functional diversification was noted with disease severity and mostly converged to inflammatory states in IWR gliomas. Beyond dendritic cells, multiple antigen-presenting cellular states expanded with glioma severity especially in IWP and IWR gliomas. Furthermore, we noted differential microglia and dendritic cell inherent antigen presentation axis viz, osteopontin, and classical HLAs in IDH subtypes and, glioma-wide non-PD1 checkpoints associations in T cells like Galectin9 and Tim-3. As a general utility, our immune cell deconvolution approach with single-cell-matched bulk RNA sequencing data faithfully resolved 58-cell states which provides glioma specific immune reference for digital cytometry application to genomics datasets.ConclusionsAltogether, we identified prognosticator immune cell-signatures from TCGA cohorts as one of many potential immune responsiveness applications of the curated signatures for basic and translational immune-genomics efforts. Thus, we not only provide an unprecedented insight of glioma TIME but also present an immune data resource that can be exploited for immunotherapy applications.Ethics ApprovalThe brain tumor/tissue samples were collected as per MD Anderson internal review board (IRB)-approved protocol numbers LAB03-0687 and, LAB04-0001. One non-tumor brain tissue sample was collected from patient undergoing neurosurgery for epilepsy as per Baylor College of Medicine IRB-approved protocol number H-13798. All experiments were compliant with the review board of MD Anderson Cancer Center, USA.ConsentWritten informed consent was obtained from the patient for publication of this abstract and any accompanying images. A copy of the written consent is available for review by the Editor of this journal

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Single Cell Profiling Reveals Unique CXCL13 Positive T Cell Subsets in the Tumor Microenvironment of Lymphocyte Rich Classic Hodgkin Lymphoma

Blood ◽

10.1182/blood-2020-134929 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 32-33

Author(s):

Tomohiro Aoki ◽

Lauren C. Chong ◽

Katsuyoshi Takata ◽

Katy Milne ◽

Elizabeth Chavez ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

B Cells ◽

Single Cell ◽

Immune Cells ◽

Research Funding ◽

Immune Cell ◽

Expression Patterns ◽

The Other ◽

Tfh Cells

Introduction: Classic Hodgkin lymphoma (CHL) features a unique crosstalk between malignant cells and different types of normal immune cells in the tumor-microenvironment (TME). On the basis of histomorphologic and immunophenotypic features of the malignant Hodgkin and Reed-Sternberg (HRS) cells and infiltrating immune cells, four histological subtypes of CHL are recognized: Nodular sclerosing (NS), Mixed cellularity, Lymphocyte-rich (LR) and Lymphocyte-depleted CHL. Recently, our group described the high abundance of various types of immunosuppressive CD4+ T cells including LAG3+ and/or CTLA4+ cells in the TME of CHL using single cell RNA sequencing (scRNAseq). However, the TME of LR-CHL has not been well characterized due to the rarity of the disease. In this study, we aimed at characterizing the immune cell profile of LR-CHL at single cell resolution. METHODS: We performed scRNAseq on cell suspensions collected from lymph nodes of 28 primary CHL patients, including 11 NS, 9 MC and 8 LR samples, with 5 reactive lymph nodes (RLN) serving as normal controls. We merged the expression data from all cells (CHL and RLN) and performed batch correction and normalization. We also performed single- and multi-color immunohistochemistry (IHC) on tissue microarray (TMA) slides from the same patients. In addition, an independent validation cohort of 31 pre-treatment LR-CHL samples assembled on a TMA, were also evaluated by IHC. Results: A total of 23 phenotypic cell clusters were identified using unsupervised clustering (PhenoGraph). We assigned each cluster to a cell type based on the expression of genes described in published transcriptome data of sorted immune cells and known canonical markers. While most immune cell phenotypes were present in all pathological subtypes, we observed a lower abundance of regulatory T cells (Tregs) in LR-CHL in comparison to the other CHL subtypes. Conversely, we found that B cells were enriched in LR-CHL when compared to the other subtypes and specifically, all four naïve B-cell clusters were quantitatively dominated by cells derived from the LR-CHL samples. T follicular helper (TFH) cells support antibody response and differentiation of B cells. Our data show the preferential enrichment of TFH in LR-CHL as compared to other CHL subtypes, but TFH cells were still less frequent compared to RLN. Of note, Chemokine C-X-C motif ligand 13 (CXCL13) was identified as the most up-regulated gene in LR compared to RLN. CXCL13, which is a ligand of C-X-C motif receptor 5 (CXCR5) is well known as a B-cell attractant via the CXCR5-CXCL13 axis. Analyzing co-expression patterns on the single cell level revealed that the majority of CXCL13+ T cells co-expressed PD-1 and ICOS, which is known as a universal TFH marker, but co-expression of CXCR5, another common TFH marker, was variable. Notably, classical TFH cells co-expressing CXCR5 and PD-1 were significantly enriched in RLN, whereas PD-1+ CXCL13+ CXCR5- CD4+ T cells were significantly enriched in LR-CHL. These co-expression patterns were validated using flow cytometry. Moreover, the expression of CXCR5 on naïve B cells in the TME was increased in LR-CHL compared to the other CHL subtypes We next sought to understand the spatial relationship between CXCL13+ T cells and malignant HRS cells. IHC of all cases revealed that CXCL13+ T cells were significantly enriched in the LR-CHL TME compared to other subtypes of CHL, and 46% of the LR-CHL cases showed CXCL13+ T cell rosettes closely surrounding HRS cells. Since PD-1+ T cell rosettes are known as a specific feature of LR-CHL, we confirmed co-expression of PD-1 in the rosetting cells by IHC in these cases. Conclusions: Our results reveal a unique TME composition in LR-CHL. LR-CHL seems to be distinctly characterized among the CHL subtypes by enrichment of CXCR5+ naïve B cells and CD4+ CXCL13+ PD-1+ T cells, indicating the importance of the CXCR5-CXCL13 axis in the pathogenesis of LR-CHL. Figure Disclosures Savage: BeiGene: Other: Steering Committee; Merck, BMS, Seattle Genetics, Gilead, AstraZeneca, AbbVie: Honoraria; Roche (institutional): Research Funding; Merck, BMS, Seattle Genetics, Gilead, AstraZeneca, AbbVie, Servier: Consultancy. Scott:Janssen: Consultancy, Research Funding; Celgene: Consultancy; NanoString: Patents & Royalties: Named inventor on a patent licensed to NanoString, Research Funding; NIH: Consultancy, Other: Co-inventor on a patent related to the MCL35 assay filed at the National Institutes of Health, United States of America.; Roche/Genentech: Research Funding; Abbvie: Consultancy; AstraZeneca: Consultancy. Steidl:AbbVie: Consultancy; Roche: Consultancy; Curis Inc: Consultancy; Juno Therapeutics: Consultancy; Bayer: Consultancy; Seattle Genetics: Consultancy; Bristol-Myers Squibb: Research Funding.

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Prolonged activation of nasal immune cell populations and development of tissue-resident SARS-CoV-2 specific CD8 T cell responses following COVID-19

10.1101/2021.04.19.21255727 ◽

2021 ◽

Author(s):

Anna H.E. Roukens ◽

Marion König ◽

Tim Dalebout ◽

Tamar Tak ◽

Shohreh Azimi ◽

...

Keyword(s):

T Cells ◽

Immune System ◽

T Cell ◽

Nasal Mucosa ◽

Immune Cell ◽

Inflammatory Responses ◽

Upper Airway ◽

Effector Memory ◽

Long Term Effects ◽

Activated T Cells

AbstractThe immune system plays a major role in Coronavirus Disease 2019 (COVID-19) pathogenesis, viral clearance and protection against re-infection. Immune cell dynamics during COVID-19 have been extensively documented in peripheral blood, but remain elusive in the respiratory tract. We performed minimally-invasive nasal curettage and mass cytometry to characterize nasal immune cells of COVID-19 patients during and 5-6 weeks after hospitalization. Contrary to observations in blood, no general T cell depletion at the nasal mucosa could be detected. Instead, we observed increased numbers of nasal granulocytes, monocytes, CD11c+ NK cells and exhausted CD4+ T effector memory cells during acute COVID-19 compared to age-matched healthy controls. These pro-inflammatory responses were found associated with viral load, while neutrophils also negatively correlated with oxygen saturation levels. Cell numbers mostly normalized following convalescence, except for persisting CD127+ granulocytes and activated T cells, including CD38+ CD8+ tissue-resident memory T cells. Moreover, we identified SARS-CoV-2 specific CD8+ T cells in the nasal mucosa in convalescent patients. Thus, COVID-19 has both transient and long-term effects on the immune system in the upper airway.

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Single-Cell Analysis of the Neonatal Immune System Across the Gestational Age Continuum

Frontiers in Immunology ◽

10.3389/fimmu.2021.714090 ◽

2021 ◽

Vol 12 ◽

Author(s):

Laura S. Peterson ◽

Julien Hedou ◽

Edward A. Ganio ◽

Ina A. Stelzer ◽

Dorien Feyaerts ◽

...

Keyword(s):

T Cells ◽

Immune System ◽

Single Cell ◽

Gestational Age ◽

Immune Cell ◽

Single Cell Analysis ◽

Inflammatory Diseases ◽

Interferon Α ◽

Cytotoxic Lymphocytes ◽

Neonatal Immune System

Although most causes of death and morbidity in premature infants are related to immune maladaptation, the premature immune system remains poorly understood. We provide a comprehensive single-cell depiction of the neonatal immune system at birth across the spectrum of viable gestational age (GA), ranging from 25 weeks to term. A mass cytometry immunoassay interrogated all major immune cell subsets, including signaling activity and responsiveness to stimulation. An elastic net model described the relationship between GA and immunome (R=0.85, p=8.75e-14), and unsupervised clustering highlighted previously unrecognized GA-dependent immune dynamics, including decreasing basal MAP-kinase/NFκB signaling in antigen presenting cells; increasing responsiveness of cytotoxic lymphocytes to interferon-α; and decreasing frequency of regulatory and invariant T cells, including NKT-like cells and CD8+CD161+ T cells. Knowledge gained from the analysis of the neonatal immune landscape across GA provides a mechanistic framework to understand the unique susceptibility of preterm infants to both hyper-inflammatory diseases and infections.

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Recovery of Paired T Cell Receptors from Single-cell Seq-Well Libraries

10.21203/rs.2.13685/v1 ◽

2019 ◽

Author(s):

Ang A. Tu ◽

Todd M. Gierahn ◽

Brinda Monian ◽

Duncan M. Morgan ◽

Naveen K. Mehta ◽

...

Keyword(s):

T Cells ◽

Food Allergy ◽

T Cell ◽

Single Cell ◽

T Cell Receptors ◽

Immune Cell ◽

Cost Effective ◽

Antigen Specificity ◽

Activated T Cells ◽

Cell Receptors

Abstract High-throughput 3’ single-cell RNA-Sequencing (scRNA-Seq) allows for cost-effective, detailed characterization of thousands of individual immune cells from healthy and diseased tissues. Current techniques, however, are limited in their ability to elucidate essential immune cell features, including the variable sequences of T cell receptors (TCRs) that confer antigen specificity in T cells. Here, we present an enrichment strategy that enables simultaneous analysis of TCR variable sequences and corresponding full transcriptomes from 3’ barcoded scRNA-Seq samples. This approach is compatible with common 3’ scRNA-Seq methods, and adaptable to processed samples post hoc. We applied the technique to resolve clonotype-to-phenotype relationships among antigen-activated T cells from immunized mice and from patients with food allergy. We observed diverse but preferential cellular phenotypes manifest among subsets of expanded clonotypes, including functional Th2 states associated with food allergy. These results demonstrate the utility of our method when studying complex diseases in which clonotype-driven immune responses are critical to understanding the underlying biology.

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Global immune characterization of HBV/HCV-related hepatocellular carcinoma identifies macrophage and T-cell subsets associated with disease progression

Cell Discovery ◽

10.1038/s41421-020-00214-5 ◽

2020 ◽

Vol 6 (1) ◽

Author(s):

Guohe Song ◽

Yang Shi ◽

Meiying Zhang ◽

Shyamal Goswami ◽

Saifullah Afridi ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

T Cells ◽

T Cell ◽

Single Cell ◽

Immune Cells ◽

Immune Cell ◽

T Cell Subsets ◽

M2 Macrophage ◽

Advanced Hcc ◽

Immune Cell Subsets

AbstractDiverse immune cells in the tumor microenvironment form a complex ecosystem, but our knowledge of their heterogeneity and dynamics within hepatocellular carcinoma (HCC) still remains limited. To assess the plasticity and phenotypes of immune cells within HBV/HCV-related HCC microenvironment at single-cell level, we performed single-cell RNA sequencing on 41,698 immune cells from seven pairs of HBV/HCV-related HCC tumors and non-tumor liver tissues. We combined bio-informatic analyses, flow cytometry, and multiplex immunohistochemistry to assess the heterogeneity of different immune cell subsets in functional characteristics, transcriptional regulation, phenotypic switching, and interactions. We identified 29 immune cell subsets of myeloid cells, NK cells, and lymphocytes with unique transcriptomic profiles in HCC. A highly complex immunological network was shaped by diverse immune cell subsets that can transit among different states and mutually interact. Notably, we identified a subset of M2 macrophage with high expression of CCL18 and transcription factor CREM that was enriched in advanced HCC patients, and potentially participated in tumor progression. We also detected a new subset of activated CD8+ T cells highly expressing XCL1 that correlated with better patient survival rates. Meanwhile, distinct transcriptomic signatures, cytotoxic phenotypes, and evolution trajectory of effector CD8+ T cells from early-stage to advanced HCC were also identified. Our study provides insight into the immune microenvironment in HBV/HCV-related HCC and highlights novel macrophage and T-cell subsets that could be further exploited in future immunotherapy.

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Viral infection prevents diabetes by inducing regulatory T cells through NKT cell–plasmacytoid dendritic cell interplay

Journal of Experimental Medicine ◽

10.1084/jem.20101692 ◽

2011 ◽

Vol 208 (4) ◽

pp. 729-745 ◽

Cited By ~ 59

Author(s):

Julien Diana ◽

Vedran Brezar ◽

Lucie Beaudoin ◽

Marc Dalod ◽

Andrew Mellor ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Dendritic Cell ◽

Regulatory T Cells ◽

Viral Infection ◽

Pancreatic Islets ◽

Viral Infections ◽

Plasmacytoid Dendritic Cell ◽

Inkt Cells ◽

Pancreatic Lymph Nodes

Type 1 diabetes (T1D) is an autoimmune disease resulting from T cell–mediated destruction of insulin-producing β cells, and viral infections can prevent the onset of disease. Invariant natural killer T cells (iNKT cells) exert a regulatory role in T1D by inhibiting autoimmune T cell responses. As iNKT cell–plasmacytoid dendritic cell (pDC) cooperation controls viral replication in the pancreatic islets, we investigated whether this cellular cross talk could interfere with T1D development during viral infection. Using both virus-induced and spontaneous mouse models of T1D, we show that upon viral infection, iNKT cells induce TGF-β–producing pDCs in the pancreatic lymph nodes (LNs). These tolerogenic pDCs convert naive anti-islet T cells into Foxp3+ CD4+ regulatory T cells (T reg cells) in pancreatic LNs. T reg cells are then recruited into the pancreatic islets where they produce TGF-β, which dampens the activity of viral- and islet-specific CD8+ T cells, thereby preventing T1D development in both T1D models. These findings reveal a crucial cooperation between iNKT cells, pDCs, and T reg cells for prevention of T1D by viral infection.

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