Single-cell RNA-Seq reveals transcriptional heterogeneity and immune subtypes associated with disease activity in human myasthenia gravis

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.

Download Full-text

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.

Download Full-text

Single-Cell Mass Cytometry on Peripheral Blood Identifies Immune Cell Subsets Associated with Primary Biliary Cholangitis

10.1101/2020.02.24.962043 ◽

2020 ◽

Author(s):

Jin Sung Jang ◽

Brian Juran ◽

Kevin Y. Cunningham ◽

Vinod K. Gupta ◽

YoungMin Son ◽

...

Keyword(s):

T Cells ◽

Immune System ◽

B Cells ◽

Single Cell ◽

Peripheral Blood ◽

Immune Cell ◽

Memory B Cells ◽

Primary Biliary Cholangitis ◽

Mass Cytometry ◽

Peripheral Immune System

AbstractThe relationship between Primary Biliary Cholangitis (PBC), a chronic cholestatic autoimmune liver disease, and the peripheral immune system remains to be fully understood. Herein, we performed the first mass cytometry (CyTOF)-based, immunophenotyping analysis of the peripheral immune system in PBC at single-cell resolution. CyTOF was performed on peripheral blood mononuclear cells (PBMCs) from PBC patients (n=33) and age-/sex-matched healthy controls (n=33) to obtain immune cell abundance and marker expression profiles. Hiearchical clustering methods were applied to identify immune cell types and subsets significantly associated with PBC. Subsets of gamma-delta T cells (CD3+TCRgd+), CD8+ T cells (CD3+CD8+CD161+PD1+), and memory B cells (CD3-CD19+CD20+CD24+CD27+) were found to have lower abundance in PBC than in control. In contrast, higher abundance of subsets of monocytes and naïve B cells were observed in PBC compared to control. Furthermore, several naïve B cell (CD3-CD19+CD20+CD24-CD27-) subsets were significantly higher in PBC patients with cirrhosis (indicative of late-stage disease) than in those without cirrhosis. Alternatively, subsets of CD8+CD161+ T cells and memory B cells were lower in abundance in cirrhotic relative to non-cirrhotic PBC patients. Future immunophenotyping investigations could lead to better understanding of PBC pathogenesis and progression, and also to the discovery of novel biomarkers and treatment strategies.

Download Full-text

Exploring and analysing single cell multi-omics data with VDJView

10.21203/rs.2.14949/v2 ◽

2019 ◽

Author(s):

Jerome Samir ◽

Simone Rizzetto ◽

Money Gupta ◽

Fabio Luciani

Keyword(s):

Gene Expression ◽

T Cells ◽

B Cells ◽

Hypothesis Testing ◽

Single Cell ◽

Single Cells ◽

Cellular Heterogeneity ◽

Specific Gene ◽

T And B Cells ◽

Gene Signatures

Abstract Background Single cell RNA sequencing provides unprecedented opportunity to simultaneously explore the transcriptomic and immune receptor diversity of T and B cells. However, there are limited tools available that simultaneously analyse large multi-omics datasets integrated with metadata such as patient and clinical information.Results We developed VDJView, which permits the simultaneous or independent analysis and visualisation of gene expression, immune receptors, and clinical metadata of both T and B cells. This tool is implemented as an easy-to-use R shiny web-application, which integrates numerous gene expression and TCR analysis tools, and accepts data from plate-based sorted or high-throughput single cell platforms. We utilised VDJView to analyse several 10X scRNA-seq datasets, including a recent dataset of 150,000 CD8+ T cells with available gene expression, TCR sequences, quantification of 15 surface proteins, and 44 antigen specificities (across viruses, cancer, and self-antigens). We performed quality control, filtering of tetramer non-specific cells, clustering, random sampling and hypothesis testing to discover antigen specific gene signatures which were associated with immune cell differentiation states and clonal expansion across the pathogen specific T cells. We also analysed 563 single cells (plate-based sorted) obtained from 11 subjects, revealing clonally expanded T and B cells across primary cancer tissues and metastatic lymph-node. These immune cells clustered with distinct gene signatures according to the breast cancer molecular subtype. VDJView has been tested in lab meetings and peer-to-peer discussions, showing effective data generation and discussion without the need to consult bioinformaticians.Conclusions VDJView enables researchers without profound bioinformatics skills to analyse immune scRNA-seq data, integrating and visualising this with clonality and metadata profiles, thus accelerating the process of hypothesis testing, data interpretation and discovery of cellular heterogeneity. VDJView is freely available at https://bitbucket.org/kirbyvisp/vdjview .

Download Full-text

Immune Cell Profiling of COVID-19 Patients in the Recovery Stage by Single-Cell Sequencing

10.1101/2020.03.23.20039362 ◽

2020 ◽

Cited By ~ 12

Author(s):

Wen Wen ◽

Wenru Su ◽

Hao Tang ◽

Wenqing Le ◽

Xiaopeng Zhang ◽

...

Keyword(s):

T Cells ◽

B Cells ◽

B Cell ◽

Single Cell ◽

Hospital Discharge ◽

Immune Cell ◽

Cell Receptor ◽

B Cell Receptor ◽

Early Recovery ◽

Recovery Stage

AbstractCOVID-19, caused by SARS-CoV-2, has recently affected over 300,000 people and killed more than 10,000. The manner in which the key immune cell subsets change and their states during the course of COVID-19 remain unclear. Here, we applied single-cell technology to comprehensively characterize transcriptional changes in peripheral blood mononuclear cells during the recovery stage of COVID-19. Compared with healthy controls, in patients in the early recovery stage (ERS) of COVID-19, T cells decreased remarkably, whereas monocytes increased. A detailed analysis of the monocytes revealed that there was an increased ratio of classical CD14++ monocytes with high inflammatory gene expression as well as a greater abundance of CD14++IL1B+ monocytes in the ERS. CD4+ and CD8+ T cells decreased significantly and expressed high levels of inflammatory genes in the ERS. Among the B cells, the plasma cells increased remarkably, whereas the naïve B cells decreased. Our study identified several novel B cell-receptor (BCR) changes, such as IGHV3-23 and IGHV3-7, and confirmed isotypes (IGHV3-15, IGHV3-30, and IGKV3-11) previously used for virus vaccine development. The strongest pairing frequencies, IGHV3-23-IGHJ4, indicated a monoclonal state associated with SARS-CoV-2 specificity. Furthermore, integrated analysis predicted that IL-1β and M-CSF may be novel candidate target genes for inflammatory storm and that TNFSF13, IL-18, IL-2 and IL-4 may be beneficial for the recovery of COVID-19 patients. Our study provides the first evidence of an inflammatory immune signature in the ERS, suggesting that COVID-19 patients are still vulnerable after hospital discharge. Our identification of novel BCR signaling may lead to the development of vaccines and antibodies for the treatment of COVID-19.Highlights-The immune response was sustained for more than 7 days in the early recovery stage of COVID-19, suggesting that COVID-19 patients are still vulnerable after hospital discharge.-Single-cell analysis revealed a predominant subset of CD14++ IL1β+ monocytes in patients in the ERS of COVID-19.-Newly identified virus-specific B cell-receptor changes, such as IGHV3-23, IGHV3-7, IGHV3-15, IGHV3-30, and IGKV3-11, could be helpful in the development of vaccines and antibodies against SARS-CoV-2.-IL-1β and M-CSF were discovered as novel mediators of inflammatory cytokine storm, and TNFSF13, IL-2, IL-4, and IL-18 may be beneficial for recovery.

Download Full-text

Exploring and analysing single cell multi-omics data with VDJView

10.21203/rs.2.14949/v3 ◽

2020 ◽

Author(s):

Jerome Samir ◽

Simone Rizzetto ◽

Money Gupta ◽

Fabio Luciani

Keyword(s):

Gene Expression ◽

T Cells ◽

B Cells ◽

Hypothesis Testing ◽

Single Cell ◽

Single Cells ◽

Cellular Heterogeneity ◽

Specific Gene ◽

T And B Cells ◽

Gene Signatures

Abstract Background Single cell RNA sequencing provides unprecedented opportunity to simultaneously explore the transcriptomic and immune receptor diversity of T and B cells. However, there are limited tools available that simultaneously analyse large multi-omics datasets integrated with metadata such as patient and clinical information.Results We developed VDJView, which permits the simultaneous or independent analysis and visualisation of gene expression, immune receptors, and clinical metadata of both T and B cells. This tool is implemented as an easy-to-use R shiny web-application, which integrates numerous gene expression and TCR analysis tools, and accepts data from plate-based sorted or high-throughput single cell platforms. We utilised VDJView to analyse several 10X scRNA-seq datasets, including a recent dataset of 150,000 CD8+ T cells with available gene expression, TCR sequences, quantification of 15 surface proteins, and 44 antigen specificities (across viruses, cancer, and self-antigens). We performed quality control, filtering of tetramer non-specific cells, clustering, random sampling and hypothesis testing to discover antigen specific gene signatures which were associated with immune cell differentiation states and clonal expansion across the pathogen specific T cells. We also analysed 563 single cells (plate-based sorted) obtained from 11 subjects, revealing clonally expanded T and B cells across primary cancer tissues and metastatic lymph-node. These immune cells clustered with distinct gene signatures according to the breast cancer molecular subtype. VDJView has been tested in lab meetings and peer-to-peer discussions, showing effective data generation and discussion without the need to consult bioinformaticians.Conclusions VDJView enables researchers without profound bioinformatics skills to analyse immune scRNA-seq data, integrating and visualising this with clonality and metadata profiles, thus accelerating the process of hypothesis testing, data interpretation and discovery of cellular heterogeneity. VDJView is freely available at https://bitbucket.org/kirbyvisp/vdjview .

Download Full-text

The differential immune responses to COVID-19 in peripheral and lung revealed by single-cell RNA sequencing

10.1101/2020.08.15.20175638 ◽

2020 ◽

Author(s):

Gang Xu ◽

Furong Qi ◽

Hanjie Li ◽

Qianting Yang ◽

Haiyan Wang ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Single Cell ◽

Mononuclear Cells ◽

Immune Cell ◽

Close Association ◽

Suppressor Cells ◽

T Cell Subsets ◽

Peripheral Blood Mononuclear ◽

Peripheral T Cells

Understanding the mechanism that leads to immune dysfunction induced by SARS-CoV2 virus is crucial to develop treatment for severe COVID-19. Here, using single cell RNA-seq, we characterized the peripheral blood mononuclear cells (PBMC) from uninfected controls and COVID-19 patients, and cells in paired broncho-alveolar lavage fluid (BALF). We found a close association of decreased dendritic cells (DC) and increased monocytes resembling myeloid-derived suppressor cells (MDSC) which correlated with lymphopenia and inflammation in the blood of severe COVID-19 patients. Those MDSC-like monocytes were immune-paralyzed. In contrast, monocyte-macrophages in BALFs of COVID-19 patients produced massive amounts of cytokines and chemokines, but secreted little interferons. The frequencies of peripheral T cells and NK cells were significantly decreased in severe COVID-19 patients, especially for innate-like T and various CD8+ T cell subsets, compared to health controls. In contrast, the proportions of various activated CD4+ T cell subsets, including Th1, Th2 and Th17-like cells were increased and more clonally expanded in severe COVID-19 patients. Patients' peripheral T cells showed no sign of exhaustion or augmented cell death, whereas T cells in BALFs produced higher levels of IFNG, TNF, CCL4 and CCL5 etc. Paired TCR tracking indicated abundant recruitment of peripheral T cells to the patients' lung. Together, this study comprehensively depicts how the immune cell landscape is perturbed in severe COVID-19.

Download Full-text

Depression, Anxiety, and Social Environmental Adversity as Potential Modulators of the Immune Tumor Microenvironment in Breast Cancer Patients

Medical Sciences ◽

10.3390/medsci9020046 ◽

2021 ◽

Vol 9 (2) ◽

pp. 46

Author(s):

Eida M. Castro-Figueroa ◽

Karina I. Acevedo ◽

Cristina I. Peña-Vargas ◽

Normarie Torres-Blasco ◽

Idhaliz Flores ◽

...

Keyword(s):

Breast Cancer ◽

T Cells ◽

B Cells ◽

Tumor Microenvironment ◽

Immune Cell ◽

Depressive Symptomatology ◽

Anxiety Symptoms ◽

Trauma History ◽

Social Environmental ◽

The Impact

Background: Mounting data suggest that exposure to chronic stress is associated with worse breast cancer outcomes. This study aimed to explore the impact of social environmental adversity (SEA, e.g., child abuse, crime, sexual, and physical violence), depressive symptomatology, and anxiety on immune cell infiltration into the breast tumor microenvironment. Methods: Participants (n = 33) completed a series of surveys assessing depression and anxiety symptoms, adverse childhood events (ACE), and trauma history. Tumor-associated macrophages (CD68+), B cells (CD19+), and T cells (CD3+) were identified by immunohistochemical analyses of formalin-fixed paraffin-embedded tumor samples and quantified. Spearman rank tests were used to explore the relationships between the variables studied. Results: Exposure to SEA was high (ACE = 72%, exposure to crime = 47%, and exposure to physical/sexual assault = 73%) among participants. Moreover, 30% reported a comorbid history of depression and ACE; 39% reported one or more traumatic events, and clinically significant depression symptomatology, while 21% reported trauma history and significant anxiety symptomatology. Increased tumor-infiltrating B cells were significantly correlated with exposure to crime, anxiety symptoms, and exposure to an ACE. The ACE plus anxiety group presented the highest infiltration of B cells, T cells, and macrophages. Conclusion: These findings support a role for SEA, anxiety symptoms, and depression as potential modulators of the immune tumor microenvironment in breast cancer.

Download Full-text

FB5P-seq: FACS-based 5-prime end single-cell RNAseq for integrative analysis of transcriptome and antigen receptor repertoire in B and T cells

10.1101/795575 ◽

2019 ◽

Cited By ~ 5

Author(s):

Noudjoud Attaf-Bouabdallah ◽

Iñaki Cervera-Marzal ◽

Chuang Dong ◽

Laurine Gil ◽

Amédée Renand ◽

...

Keyword(s):

T Cells ◽

Single Cell ◽

Immune Cell ◽

Antigen Receptor ◽

Adaptive Immune System ◽

Integrative Analysis ◽

T Cell Subsets ◽

Bioinformatics Pipeline ◽

Human Tonsil ◽

Adaptive Immune

AbstractSingle-cell RNA sequencing (scRNA-seq) allows the identification, characterization, and quantification of cell types in a tissue. When focused on B and T cells of the adaptive immune system, scRNA-seq carries the potential to track the clonal lineage of each analyzed cell through the unique rearranged sequence of its antigen receptor (BCR or TCR, respectively), and link it to the functional state inferred from transcriptome analysis. Here we introduce FB5P-seq, a FACS-based 5’-end scRNA-seq method for cost-effective integrative analysis of transcriptome and paired BCR or TCR repertoire in phenotypically defined B and T cell subsets. We describe in details the experimental workflow and provide a robust bioinformatics pipeline for computing gene count matrices and reconstructing repertoire sequences from FB5P-seq data. We further present two applications of FB5P-seq for the analysis of human tonsil B cell subsets and peripheral blood antigen-specific CD4 T cells. We believe our novel integrative scRNA-seq method will be a valuable option to study rare adaptive immune cell subsets in immunology research.

Download Full-text

Single-Cell RNA Sequencing Reveals the Immunological Profiles of Renal Allograft Rejection in Mice

Frontiers in Immunology ◽

10.3389/fimmu.2021.693608 ◽

2021 ◽

Vol 12 ◽

Author(s):

Qixia Shen ◽

Yucheng Wang ◽

Jiaoyi Chen ◽

Lifeng Ma ◽

Xiaoru Huang ◽

...

Keyword(s):

T Cells ◽

B Cells ◽

Single Cell ◽

Rna Sequencing ◽

Allograft Rejection ◽

Renal Allograft ◽

Immune Cell ◽

Fold Increase ◽

Renal Allograft Rejection ◽

Single Cell Rna Sequencing

Allograft rejection is a common immunological feature in renal transplantation and is associated with reduced graft survival. A mouse renal allograft rejection model was induced and single-cell RNA sequencing (scRNA-seq) data of CD45+ leukocytes in kidney allografts on days 7 (D7) and 15 (D15) after operation was analyzed to reveal a full immunological profiling. We identified 20 immune cell types among 10,921 leukocytes. Macrophages and CD8+ T cells constituted the main populations on both timepoints. In the process from acute rejection (AR) towards chronic rejection (CR), the proportion of proliferating and naïve CD8+ T cells dropped significantly. Both B cells and neutrophils decreased by about 3 folds. On the contrary, the proportion of macrophages and dendritic cells (DCs) increased significantly, especially by about a 4.5-fold increase in Ly6cloMrc1+ macrophages and 2.6 folds increase in Ly6cloEar2+ macrophages. Moreover, myeloid cells harbored the richest ligand and receptor (LR) pairs with other cells, particularly for chemokine ligands such as Cxcl9, Cxcl10, Cxcl16 and Yars. However, macrophages with weak response to interferon gamma (IFNg) contributed to rejection chronicization. To conclude, reduction in CD8 T cells, B cells and neutrophils while increasing in Ly6cloMrc1+ macrophages and Ly6cloEar2+ macrophages, may contribute significantly to the progress from AR towards CR.

Download Full-text