scholarly journals Mapping the immune environment in clear cell renal carcinoma by single-cell genomics

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Nicholas Borcherding ◽  
Ajaykumar Vishwakarma ◽  
Andrew P. Voigt ◽  
Andrew Bellizzi ◽  
Jacob Kaplan ◽  
...  
Keyword(s):  
T Cell ◽  
Single Cell ◽  
Immune Cells ◽  
Clear Cell ◽  
Cell Receptor ◽  
Renal Tissue ◽  
High Response Rate ◽  
Cell Renal Cell Carcinoma ◽  
Tumor Mutational Burden ◽  
Macrophage Populations

AbstractClear cell renal cell carcinoma (ccRCC) is one of the most immunologically distinct tumor types due to high response rate to immunotherapies, despite low tumor mutational burden. To characterize the tumor immune microenvironment of ccRCC, we applied single-cell-RNA sequencing (SCRS) along with T-cell-receptor (TCR) sequencing to map the transcriptomic heterogeneity of 25,688 individual CD45+ lymphoid and myeloid cells in matched tumor and blood from three patients with ccRCC. We also included 11,367 immune cells from four other individuals derived from the kidney and peripheral blood to facilitate the identification and assessment of ccRCC-specific differences. There is an overall increase in CD8+ T-cell and macrophage populations in tumor-infiltrated immune cells compared to normal renal tissue. We further demonstrate the divergent cell transcriptional states for tumor-infiltrating CD8+ T cells and identify a MKI67 + proliferative subpopulation being a potential culprit for the progression of ccRCC. Using the SCRS gene expression, we found preferential prediction of clinical outcomes and pathological diseases by subcluster assignment. With further characterization and functional validation, our findings may reveal certain subpopulations of immune cells amenable to therapeutic intervention.

scholarly journals Mapping the Immune Landscape of Clear Cell Renal Cell Carcinoma by Single-Cell RNA-seq

2019 ◽  
Author(s):  
Ajaykumar Vishwakarma ◽  
Nicholas Bocherding ◽  
Michael S. Chimenti ◽  
Purshottam Vishwakarma ◽  
Kenneth Nepple ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
T Cell ◽  
Single Cell ◽  
T Cell Receptor ◽  
Immune Cells ◽  
Immune Cell ◽  
Clear Cell ◽  
Cell Receptor ◽  
Cell Renal Cell Carcinoma ◽  
Single Cell Rna Sequencing

AbstractThe immune cells within the tumor microenvironment are considered key determinants of response to cancer immunotherapy. Immune checkpoint blockade (ICB) has transformed the treatment of clear cell renal cell carcinoma (ccRCC), although the role of specific immune cell states remains unclear. To characterize the tumor microenvironment (TME) of ccRCC, we applied single-cell RNA sequencing (scRNA-seq) along with paired T cell receptor sequencing to map the transcriptomic heterogeneity of 24,904 individual CD45+ lymphoid and myeloid cells in matched tumor and blood from patients with ccRCC. We identified multiple distinct immune cell phenotypes for B and T (CD4 and CD8) lymphocytes, natural kill (NK) cells, and myeloid cells. Evaluation of T cell receptor (TCR) sequences revealed limited shared clonotypes between patients, whereas tumor-infiltrating T cell clonotypes were frequently found in peripheral blood, albeit in lower abundance. We further show that the circulating CD4+ T cell clonality is far less diverse than peripheral CD8+. Evaluation of myeloid subsets revealed unique gene programs defining monocytes, dendritic cells and tumor-associated macrophages. In summary, here we have leveraged scRNA-seq to refine our understanding of the relative abundance, diversity and complexity of the immune landscape of ccRCC. This report represents the first characterization of ccRCC immune landscape using scRNA-seq. With further characterization and functional validation, these findings may identify novel sub-populations of immune cells amenable to therapeutic intervention.One Sentence SummarySingle-cell RNA-sequencing reveals unique lymphoid and myeloid gene programs with putative functions in clear cell renal cancer patients

scholarly journals Integrated analysis of single‑cell and transcriptome based RNA‑seq multilayer network and WGCNA for construction and validation of an immune cell-related prognostic model in clear cell renal cell carcinoma

2021 ◽  
Author(s):  
Guanlin Wu ◽  
Miao Liu ◽  
Weifeng Yang ◽  
Shuai Zhu ◽  
Weiming Guo ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Single Cell ◽  
Risk Score ◽  
Immune Cells ◽  
Immune Cell ◽  
Cox Regression ◽  
Clear Cell ◽  
Marker Genes ◽  
Multilayer Network ◽  
Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common type of renal cancer (RCC). The increasing incidence and poor prognosis of ccRCC after tumour metastasis makes the study of its pathogenesis extremely important. Traditional studies mostly focus on the regulation of ccRCC by single gene, while ignoring the impact of tumour heterogeneity on disease progression. The purpose of this study is to construct a prognostic risk model for ccRCC by analysing the differential marker genes related to immune cells in the single-cell database for providing help in clinical diagnosis and targeted therapy. Single-cell data and ligand-receptor relationship pair data were downloaded from related publications, and ccRCC phenotype and expression profile data were downloaded from TCGA and CPTAC. The DEGs and marker genes of the immune cell were combined and then intersected with the ligand-receptor gene data, and the 981 ligand-receptor relationship pairs obtained were intersected with the target gene of the transcription factor afterwards; 7,987 immune cell multilayer network relationship pairs were finally observed. Then, the genes in the network and the genes in TCGA were intersected to obtain 966 genes for constructing a co-expression network. Subsequently, 53 genes in black and magenta modules related to prognosis were screened by WGCNA for subsequent analysis. Whereafter, using the data of TCGA, 28 genes with significant prognostic differences were screened out through univariate Cox regression analysis. After that, LASSO regression analysis of these genes was performed to obtain a prognostic risk scoring model containing 16 genes, and CPTAC data showed that the effectiveness of this model was good. The results of correlation analysis between the risk score and other clinical factors showed that age, grade, M, T, stage and risk score were all significantly different (p < 0.05), and the results of prognostic accuracy also reached the threshold of qualification. Combined with clinical information, univariate and multivariate Cox regression analyses verified that risk score was an independent prognostic factor (p < 0.05). A nomogram constructed based on a predictive model for predicting the overall survival was established, and internal validation performed well. Our findings suggest that the predictive model built based on the immune cells scRNA-seq will enable us to judge the prognosis of patients with ccRCC and provide more accurate directions for basic relevant research and clinical practice.

scholarly journals The T Cell Receptor Immune Repertoire Protects the Liver From Reconsitution

2020 ◽  
Vol 11 ◽  
Author(s):  
Qing Liang ◽  
Yudi Hu ◽  
Meina Zhang ◽  
Chunjie Lin ◽  
Wei Zhang ◽  
...  
Keyword(s):  
T Cell ◽  
Liver Fibrosis ◽  
Single Cell ◽  
T Cell Receptor ◽  
Immune Cells ◽  
Immune Cell ◽  
Cell Receptor ◽  
Cell Subpopulation ◽  
Immune Repertoire ◽  
Fibrotic Liver

Aberrant immune cell infiltrates and microcircumstances represent characteristic features of liver fibrosis. In this study, we profiled the transcriptomes of intrahepatic CD45+ immune cells, from mice, using single-cell RNA sequencing (scRNA-seq) technology to understand the landscape of intrahepatic immune cells during the pathogenesis of fibrosis. Analysis of approximately 10,000 single-cell transcriptomes revealed an increase in dendritic cells (DCs), macrophages, and neutrophils and a decrease in T and natural killer T (NKT) cells. In addition, we report changes in the transcriptomes of diverse immune cell types, implying a deteriorating intrahepatic immune microcircumstance. Furthermore, we uncovered a novel fibrosis-associated CD8 T (Ccl5+, Ccl4+) and CD4 T (mt-Co1+) cell subpopulation, which infiltrates fibrotic liver and is characterized by abnormal activation or inactivation as well as a TCR decline. The results from scRNA-seq and bulk immune repertoire sequencing (IR-seq) revealed an obvious decline in T cell receptor (TCR) clonotypes combined with shrinking VJ and VDJ segment usage, as well as lower complementarity-determining region 3 (CDR3) amino acid (AA) diversity from fibrotic liver. Interestingly, a deficiency of TCR IR (TcrbKO mice) led to a deterioration of liver fibrosis, coupled with activation of hepatic stellate cells (HSCs) induced by the upregulation of macrophage and γδ T cell distribution in fibrotic TcrbKO livers. Our findings reveal the landscape and dynamics of single immune cells in liver fibrosis, and clarify the protective role of TCR IR in response to chronic liver injury.

scholarly journals Single-cell landscape of immunological responses in COVID-19 patients

2020 ◽  
Author(s):  
Ji-Yuan Zhang ◽  
Xiang-Ming Wang ◽  
Xudong Xing ◽  
Zhe Xu ◽  
Chao Zhang ◽  
...  
Keyword(s):  
T Cell ◽  
Single Cell ◽  
T Cell Receptor ◽  
Immune Cells ◽  
Cell Types ◽  
Cell Receptor ◽  
T Cell Subsets ◽  
Interferon Response ◽  
Immunological Responses ◽  
Receptor Repertoire

AbstractIn COVID-19 caused by SARS-CoV-2 infection, the relationship between disease severity and the host immune response is not fully understood. Here we performed single-cell RNA sequencing in peripheral blood samples of five healthy donors and 13 COVID-19 patients including moderate, severe and convalescent cases. Through determining the transcriptional profiles of immune cells, coupled with assembled T cell receptor and B cell receptor sequences, we analyzed the functional properties of immune cells. Most cell types in COVID-19 patients showed a strong interferon-alpha response, and an overall acute inflammatory response. Moreover, intensive expansion of highly cytotoxic effector T cell subsets, such as CD4+ Effector-GNLY (Granulysin), CD8+ Effector-GNLY and NKT CD160, was associated with convalescence in moderate patients. In severe patients, the immune landscape featured a deranged interferon response, profound immune exhaustion with skewed T cell receptor repertoire and broad T cell expansion. These findings illustrate the dynamic nature of immune responses during the disease progression.

scholarly journals Single-cell sequencing unveils distinct immune microenvironment with CCR6-CCL20 crosstalk in human chronic pancreatitis

2021 ◽  
Author(s):  
Bomi Lee ◽  
Hong Namkoong ◽  
Yan Yang ◽  
Huang Huang ◽  
David Heller ◽  
...  
Keyword(s):  
T Cells ◽  
Chronic Pancreatitis ◽  
T Cell ◽  
Immune Responses ◽  
Single Cell ◽  
Immune Cells ◽  
Cell Receptor ◽  
List Type ◽  
Organ Donors ◽  
Single Cell Sequencing

ABSTRACTObjectiveChronic pancreatitis (CP) is a potentially fatal disease of the exocrine pancreas, with no specific or effective approved therapies. Due to difficulty in accessing pancreas tissues, little is known about local immune responses or pathogenesis in human CP. We sought to characterize pancreas immune responses using tissues derived from patients with different etiologies of CP and non-CP organ donors in order to identify key signaling molecules associated with human CP.DesignWe performed single-cell level cellular indexing of transcriptomes and epitopes by sequencing (CITE-Seq) and T cell receptor sequencing of pancreatic immune cells isolated from organ donors, hereditary, and idiopathic CP patients who underwent total pancreatectomy. We validated gene expression data by performing flow cytometry and functional assay in the second CP patient cohort.ResultsDeep single-cell sequencing revealed distinct immune characteristics and significantly enriched CCR6+ CD4+ T cells in hereditary compared with idiopathic CP. In hereditary CP, a reduction in T cell clonality was observed due to the increased CD4+ T (Th) cells that replaced tissue-resident CD8+ T cells. Shared TCR clonotype analysis among T cell lineages also unveiled unique interactions between CCR6+ Th and Th1 subsets, and TCR clustering analysis showed unique common antigen binding motifs in hereditary CP. In addition, we observed a significant upregulation of the CCR6 ligand (CCL20) among monocytes in hereditary CP as compared with those in idiopathic CP. The functional significance of CCR6 expression in CD4+ T cells was confirmed by flow cytometry and chemotaxis assay.ConclusionSingle-cell sequencing with pancreatic immune cells in human CP highlights pancreas-specific immune crosstalk through the CCR6-CCL20 axis that might be leveraged as a potential future target in human hereditary CP.Significance of this studyWhat is already known about this subject?Chronic pancreatitis (CP) is considered an irreversible fibroinflammatory pancreatic disease and remains a major source of morbidity among gastrointestinal diseases with no active approved therapy.Inflammation is a known hallmark and contributor to CP pathogenesis. However, little is known about local immune responses in human CP especially with different etiologies.What are the new findings?Single-cell RNA sequencing of pancreatic immune cells from CP patients and organ donors revealed distinct immune transcriptomic features in CP versus non-diseased controls and hereditary versus idiopathic CP.Single-cell T cell receptor sequencing unveiled pancreas-specific clonal expansion in CD8+ T cells and CD4+ T cells-driven unique TCR repertoire changes in hereditary CP.We identified that the CCR6-CCL20 axis was significantly upregulated in hereditary CP compared with controls or idiopathic CP suggesting a potential future target for human hereditary CP.How might it impact on clinical practice in the foreseeable future?The results of this study will improve our understanding of CP heterogeneity and identify distinct immune responses in different types of human CP that could provide novel conceptual directions for therapeutic strategies in treating hereditary and idiopathic CP.The CCR6-CCL20 axis found in hereditary CP could be a potential novel targetable signaling pathways in the treatment of hereditary CP.

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

Blood ◽  
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.

scholarly journals 192 Pooled T cell receptor screening (POTS) provides unbiased, high-throughput method for TCR discovery

2021 ◽  
Vol 9 (Suppl 3) ◽  
pp. A204-A204
Author(s):  
Jack Reid ◽  
Shihong Zhang ◽  
Ariunaa Munkhbat ◽  
Matyas Ecsedi ◽  
Megan McAfee ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Single Cell ◽  
T Cell Receptor ◽  
High Throughput ◽  
Ex Vivo ◽  
Cell Receptor ◽  
High Avidity ◽  
Reporter System ◽  
High Throughput Method

BackgroundT Cell Receptor (TCR)-T cell therapies have shown some promising results in cancer clinical trials, however the efficacy of treatment remains suboptimal. Outcomes could potentially be improved by utilizing highly functional TCRs for future trials. Current TCR discovery methods are relatively low throughput and rely on synthesis and screening of individual TCRs based on tetramer binding and peptide specificity, which is costly and labor intensive. We have developed and validated a pooled approach relying on directly cloned TCRs transduced into a fluorescent Jurkat reporter system (figure 1). This approach provides an unbiased, high-throughput method for TCR discovery.MethodsAs a model for POTS, T cells specific for a peptide derived adenovirus structural protein were sorted on tetramer and subjected to 10x single cell VDJ analysis. Pools of randomly paired TCR alpha and beta chains were cloned from the 10x cDNA into a lentiviral vector and transduced into a Jurkat reporter cells. Consecutive stimulations with cognate antigen followed by cell sorts were performed to enrich for functional TCRs. Full length TCRab pools were sequenced by Oxford Nanopore Technologies (ONT) and compared to a 10x dataset to find naturally paired TCRs.ResultsComparison between the ex vivo single cell VDJ sequencing and ONT sequencing of the transduced antigen specific TCRs showed more than 99% of the TCR pairs found in reporter positive Jurkat cells were naturally paired TCRs. The functionality of 8 TCR clonotypes discovered using POTS were compared and clone #2 showed the strongest response. Of the selected clonotypes, clone #2 showed a low frequency of 0.9% in the ex vivo single cell VDJ sequencing. After the first round of stimulation and sequencing, clone #2 takes up of 5% of all reporter-positive clones. The abundance of clone #2 further increased to 17% after another round of stimulation, sorting and sequencing, suggesting this method can retrieve and enrich for highly functional antigen specific TCRs.Abstract 192 Figure 1Outline of the POTS workflow.ConclusionsPOTS provides a high-throughput method for discovery of naturally paired, high-avidity T cell receptors. This method mitigates bias introduced by T cell differentiation state by screening TCRs in a clonal reporter system. Additionally, POTS allows for screening of low abundance clones when compared with traditional TCR discovery techniques. Pooled TCRs could also be screened in vivo with primary T cells in a mouse model to screen for the most functional and physiologically fit TCR for cancer treatment.

scholarly journals Updates on Immunotherapy and Immune Landscape in Renal Clear Cell Carcinoma

Cancers ◽  
2021 ◽  
Vol 13 (22) ◽  
pp. 5856
Author(s):  
Myung-Chul Kim ◽  
Zeng Jin ◽  
Ryan Kolb ◽  
Nicholas Borcherding ◽  
Jonathan Alexander Chatzkel ◽  
...  
Keyword(s):  
T Cell ◽  
Immune Cells ◽  
Immune Cell ◽  
Single Cell Analysis ◽  
Clear Cell ◽  
Cd8 T Cell ◽  
Cell Infiltration ◽  
Cellular Mechanisms ◽  
T Cell Infiltration ◽  
Immunological Mechanisms

Several clinicopathological features of clear cell renal cell carcinomas (ccRCC) contribute to make an “atypical” cancer, including resistance to chemotherapy, sensitivity to anti-angiogenesis therapy and ICIs despite a low mutational burden, and CD8+ T cell infiltration being the predictor for poor prognosis–normally CD8+ T cell infiltration is a good prognostic factor in cancer patients. These “atypical” features have brought researchers to investigate the molecular and immunological mechanisms that lead to the increased T cell infiltrates despite relatively low molecular burdens, as well as to decipher the immune landscape that leads to better response to ICIs. In the present study, we summarize the past and ongoing pivotal clinical trials of immunotherapies for ccRCC, emphasizing the potential molecular and cellular mechanisms that lead to the success or failure of ICI therapy. Single-cell analysis of ccRCC has provided a more thorough and detailed understanding of the tumor immune microenvironment and has facilitated the discovery of molecular biomarkers from the tumor-infiltrating immune cells. We herein will focus on the discussion of some major immune cells, including T cells and tumor-associated macrophages (TAM) in ccRCC. We will further provide some perspectives of using molecular and cellular biomarkers derived from these immune cell types to potentially improve the response rate to ICIs in ccRCC patients.

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