Transcriptomic profiling of human effector and regulatory T cell subsets identifies predictive population signatures
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ABSTRACT:
PROVIDER: PRJNA627356 | ENA |
REPOSITORIES: ENA
Dataset's files
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| SRR11575683.fastq.gz | Fastqsanger.gz | |||
| SRR11575684.fastq.gz | Fastqsanger.gz | |||
| SRR11575685.fastq.gz | Fastqsanger.gz | |||
| SRR11575686.fastq.gz | Fastqsanger.gz | |||
| SRR11575687.fastq.gz | Fastqsanger.gz |
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Project description:Transcriptomic profiling of human effector and regulatory T cell subsets identifies predictive population signatures
| PRJNA627356 | ENA
Project description:After activation, CD4+ Th cells differentiate into functionally specialized populations that coordinate distinct immune responses and protect against different types of pathogens. In humans, these effector and memory Th cell subsets can be readily identified in peripheral blood based on their differential expression of chemokine receptors that govern their homeostatic and inflammatory trafficking. Foxp3+ regulatory T (Treg) cells can also be divided into subsets that phenotypically mirror each of these effector populations and share expression of key transcription factors and effector cytokines. In this study, we performed comprehensive transcriptional profiling of 11 phenotypically distinct Th and Treg cell subsets sorted from peripheral blood of healthy individuals. Despite their shared phenotypes, we found that mirror Th and Treg subsets were transcriptionally dissimilar and that Treg cell populations showed limited transcriptional diversity compared with Th cells. We identified core transcriptional signatures shared across all Th and Treg cell populations and unique signatures that define each of the Th or Treg populations. Finally, we applied these signatures to bulk Th and Treg RNA-sequencing data and found enrichment of specific Th and Treg cell populations in different human tissues. These results further define the molecular basis for the functional specialization and differentiation of Th and Treg cell populations and provide a new resource for examining Th and Treg specialization in RNA-sequencing data.
| S-EPMC8085975 | biostudies-literature
Project description:This SuperSeries is composed of the SubSeries listed below.
2020-08-05 | GSE149090 | GEO
Project description:Effector CD8+ T cells are believed to be terminally differentiated cells having cytotoxic activity and the ability to produce effector cytokines such as INF-M-NM-3 and TNF-M-NM-1. We investigated the difference between CXCR1+ and CXCR1- subsets of human effector CD27-CD28-CD8+ T cells. Both subsets similarly expressed cytolytic molecules and exerted substantial cytolytic activity, whereas only the CXCR1- subset had IL-2 productivity and self-proliferative activity and was more resistant to cell death than the CXCR1+ subset. These differences were explained by the specific up-regulation of CAMK4, SPRY2, and IL-7R in the CXCR1- subset and that of pro-apoptotic DAPK1 in the CXCR1+ subset. The IL-2 producers were more frequently found in the IL-7R+ subset of the CXCR1- effector CD8+ T cells than in the IL-7R- subset. IL-7/IL-7R signaling promoted cell survival only in the CXCR1- subset. The present study has highlighted a novel subset of effector CD8+ T cells producing IL-2 and suggests the importance of this subset in the homeostasis of effector CD8+ T cells. To find the genes that potentially cause the difference in IL-2 productivity and cell survival between the CXCR1+ and CXCR1- human effector CD8+ T cell subsets, we performed microarray gene expression analysis. We highly purified each CD3+CD8+ subset for this analysis (> 95.3%) from 5 healthy individuals, and then compared the gene expression profiles of each subset.
2011-01-27 | E-GEOD-26890 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the following subset Series: GSE35711: Transcriptional Signatures as a Disease-Specific and Predictive Inflammatory Biomarker for Type 1 Diabetes [CF_S1S3_5Auto_20CF_10HC] GSE35712: Transcriptional Signatures as a Disease-Specific and Predictive Inflammatory Biomarker for Type 1 Diabetes [H1N1_S5_5Pre_5D0] GSE35716: Transcriptional Signatures as a Disease-Specific and Predictive Inflammatory Biomarker for Type 1 Diabetes [Pneu_S3S24_10Pneu_4HC] GSE35725: Transcriptional Signatures as a Disease-Specific and Predictive Inflammatory Biomarker for Type 1 Diabetes [T1D_114] Refer to individual Series
2012-09-01 | E-GEOD-35713 | biostudies-arrayexpress
Project description:Using killer cell lectin-like receptor G1 as a marker to distinguish terminal effector cells from memory precursors, we found that despite their diverse cell fates both subsets possessed remarkably similar gene expression profiles and functioned as equally potent killer cells. However, only the memory precursors were capable of making IL-2 thus defining a novel effector cell that was cytotoxic, expressed granzyme B, and produced inflammatory cytokines in addition to IL-2. This effector population then differentiated into long-lived protective memory T cells capable of self-renewal and rapid re-call responses. Mechanistic studies showed that cells that continued to receive antigenic stimulation during the later stages of infection were more likely to become terminal effectors. Importantly, curtailing antigenic stimulation towards the tail-end of the acute infection enhanced the generation of memory cells. These studies support the decreasing potential model of memory differentiation and show that the duration of antigenic stimulation is a critical regulator of memory formation Experiment Overall Design: An important question in memory development is understanding the differences between effector CD8 T cells that die versus effector cells that survive and give rise to memory cells. In this study we provide a comprehensive phenotypic, functional and genomic profiling of terminal effectors and memory precursors, towards better understanding the generation of these subsets. The two effector subsets were FACS purified during the early expansion phase (Days 4-5 post-infection) and extensively analyzed for their phenotypic (eg. CD127, CD62L, CD27, Bcl-2, Granzyme B, etc.) and functional properties (cytokine production, cytotoxicity, homeostatic proliferation, recall proliferation), and gene expression profiles (by genome-wide microarray analyses). Mechanistic studies involving the extent of proliferation and duration of antigen stimulation on memory differentiation potential of effectors were also performed using adoptive transfer techniques.
2008-06-11 | E-GEOD-10239 | biostudies-arrayexpress
Project description:Full title: Predictive Gene Signatures as Strong Prognostic Indicators of the Effectiveness of Bacillus Calmetteâ??Guérin (BCG) Immunotherapy in Primary pT1 Bladder Cancers Intravesical BCG immunotherapy is effective in prevention of recurrence and progression in many cases of non-muscle invasive bladder cancer, but many patients fail to respond. This study identified predictive gene signatures in primary pT1 bladder cancer with BCG immunotherapy. Fourty-Eight patients with primary pT1 bladder cancer treated with BCG immunotherapy were used. Microarray gene expression analysis of the 48 primary bladder cancers was carried out. Predictive gene signatures were individually selected based on the recurrence and progression status. Among 43,148 unique genes, 424 and 287 candidate predictive genes that could predict recurrence and progression, respectively, were selected. Time to recurrence or progression was shorter for patients with poor-predictive gene signatures than good-predictive gene signatures (log-rank test, p <0.001, respectively). Validation of predictive gene signatures with RT-PCR was nearly identical to those of microarray (log-rank test, p <0.05, respectively). In multivariate regression analysis, predictive gene signatures were the only independent predictors of recurrence (HR 3.38, p = 0.048) or progression (HR 10.49, p = 0.048) in validation cohorts. Predictive gene signatures have strong diagnostic value for determining the response to intravesical BCG immunotherapy in primary pT1 bladder cancer. Keywords: Gene expression, Bladder cancer, BCG Total RNA, extracted from the fresh frozen tissues of 48 pT1 bladder cancers, was isolated by TRIzol reagent (Life Technologies, NY, USA), according to the manufacturer's protocol. The quality and integrity of the RNA were confirmed by agarose gel electrophoresis and ethidium bromide staining, followed by visual examination under ultraviolet light. Five-hundred nanograms of total RNA were used for labeling hybridization according to the manufacturerâ??s protocol (Illumina HumanWG-6 BeadChip, version 2, Illumina, Inc., San Diego, CA, USA). Arrays were scanned with an Illumina Bead Array Reader confocal scanner (BeadStation 500GXDW; Illumina, Inc.) according to the manufacturer's instructions. Initial microarray gene expression data were obtained using Bead Studio software with gene expression analysis module (version 3.1.3, Illumina, Inc.).
2010-04-07 | E-GEOD-19423 | biostudies-arrayexpress
Project description:Full title: Predictive Gene Signatures as Strong Prognostic Indicators of the Effectiveness of Bacillus Calmette–Guérin (BCG) Immunotherapy in Primary pT1 Bladder Cancers Intravesical BCG immunotherapy is effective in prevention of recurrence and progression in many cases of non-muscle invasive bladder cancer, but many patients fail to respond. This study identified predictive gene signatures in primary pT1 bladder cancer with BCG immunotherapy. Fourty-Eight patients with primary pT1 bladder cancer treated with BCG immunotherapy were used. Microarray gene expression analysis of the 48 primary bladder cancers was carried out. Predictive gene signatures were individually selected based on the recurrence and progression status. Among 43,148 unique genes, 424 and 287 candidate predictive genes that could predict recurrence and progression, respectively, were selected. Time to recurrence or progression was shorter for patients with poor-predictive gene signatures than good-predictive gene signatures (log-rank test, p <0.001, respectively). Validation of predictive gene signatures with RT-PCR was nearly identical to those of microarray (log-rank test, p <0.05, respectively). In multivariate regression analysis, predictive gene signatures were the only independent predictors of recurrence (HR 3.38, p = 0.048) or progression (HR 10.49, p = 0.048) in validation cohorts. Predictive gene signatures have strong diagnostic value for determining the response to intravesical BCG immunotherapy in primary pT1 bladder cancer. Keywords: Gene expression, Bladder cancer, BCG
2010-03-26 | GSE19423 | GEO
Project description:Murine γδ T cells include several effector subsets that fulfil distinct functional roles. In pathological conditions, such as cancer, some γδ T cell subsets are highly protective whereas other subsets may exacerbate disease. γδ T cells are programmed for their effector function during their development in the thymus. Investigations of γδ T cell development have been hampered by the scarcity of surface markers distinguishing different development stages. In this study, we found that addition of CD117, CD200 and CD371 to existing markers, allowed identification of seven distinct development stages (named A, B, C, D, E, F and G) present in both the Vγ1.1+ and Vγ2+ thymocyte subsets. We provide evidence for the existence of three distinct pathways leading to export of γδ T cells, two of which express high levels of CD24. These pathways are dominated by different TCRδ repertoires shaped by TCR signalling or lack thereof. Each pathway express distinct cytokine and transcription factor profiles associated with γδT1, γδNKT and adaptive γδ T cells. Thus, the identification of additional γδ T cell development stages in this study connects three distinct development pathways to the programming of three γδ T cell effector subsets.
2017-10-18 | GSE97137 | GEO
Project description:The aim of this study was to identify differentially-expressed genes in CCR4hi/CXCR3- and CCR4lo CXCR3+ CCR6+ human Th17 cell subsets Human CD45RO+ memory T cells isolated from the peripheral blood of healthy adult donors were sorted into 4 predominant CCR7lo CD25- effector memory subsets: (1) Th1 - CCR6- CCR4lo CXCR3+; (2) Th2 - CCR6- CCR4hi CXCR3+; (3) Th17 - CCR6+ CCR4hi CXCR3-; (4) Th17.1 - CCR6+ CCR4lo CXCR3-. Sorted cells were cultured in media and activated via anti-CD3/anti-CD28 beads for 36 hours. All subsets were then harvested and used for RNA extraction and microarray experiments. Th1 vs Th2; Th1 vs Th17; Th1 vs Th17.1; Th2 vs Th17; Th2 vs Th17.1; Th17 vs Th17.1
2013-12-17 | E-GEOD-49703 | biostudies-arrayexpress