Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR24441220.fastq.gz | Fastqsanger.gz | |||
| SRR24441221.fastq.gz | Fastqsanger.gz | |||
| SRR24441222.fastq.gz | Fastqsanger.gz | |||
| SRR24441223.fastq.gz | Fastqsanger.gz | |||
| SRR24441224.fastq.gz | Fastqsanger.gz |
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Project description:Here we investigate the role of mucosal-associated invariant T (MAIT) cells in human and murine hepatocellular carcinoma (HCC). We isolated immune cells of syngeneic HCC cell line RIL-175 tumor-bearing or tumor-free livers and applied FACS sorting (CD45+ leukocytes) prior to 10X genomics based scRNA-seq. This is a complimentary dataset to the human scRNA-seq (deposited through dbGaP), highly multiplexed immunofluorescence microscopy using CODEX technology (deposited through TCIA) of paired patient samples.
2023-05-12 | GSE231712 | GEO
Project description:We applied a cell population transcriptomics strategy to sorted human memory CD8 T cells to define novel immune signatures of latent tuberculosis infection (LTBI) and understand the phenotype of tuberculosis (TB)-specific T cells. We found a 41-gene signature that could discriminate between memory CD8 T cells from healthy LTBI subjects and noninfected controls. The gene signature was dominated by genes known to be associated with mucosal associated invariant T cells (MAITs) and reflected the lower frequency of MAITs observed in individuals with LTBI. There was no evidence for a conventional CD8 T cell specific signature between the two cohorts. We therefore investigated the MAITs in more detail in these cohorts. Phenotyping based on Vα7.2 and CD161 expression and MR1 tetramers revealed 2 distinct populations of CD8+Vα7.2+CD161+ T cells: MR1 tetramer+ and MR1 tetramer−, both of which had a distinct gene expression profile compared to CD8 memory T cells. Transcriptomic analysis of LTBI vs. noninfected individuals did not reveal significant differences for MR1 tetramer+ cells. However, gene expression of MR1 tetramer− cells showed a very different profile with large inter-individual diversity and a TB-specific signature. This was further strengthened by a more diverse TCR-α and -β repertoire of MR1 tetramer− cells as compared to MR1 tetramer+. Thus, cell population transcriptomics revealed a dominant MAIT signature in CD8 memory T cells that upon detailed investigation provided novel insights into the phenotype of different MAIT populations implicated in tuberculosis.
2020-05-13 | GSE132790 | GEO
Project description:We applied a cell population transcriptomics strategy to sorted human memory CD8 T cells to define novel immune signatures of latent tuberculosis infection (LTBI) and understand the phenotype of tuberculosis (TB)-specific T cells. We found a 41-gene signature that could discriminate between memory CD8 T cells from healthy LTBI subjects and noninfected controls. The gene signature was dominated by genes known to be associated with mucosal associated invariant T cells (MAITs) and reflected the lower frequency of MAITs observed in individuals with LTBI. There was no evidence for a conventional CD8 T cell specific signature between the two cohorts. We therefore investigated the MAITs in more detail in these cohorts. Phenotyping based on Vα7.2 and CD161 expression and MR1 tetramers revealed 2 distinct populations of CD8+Vα7.2+CD161+ T cells: MR1 tetramer+ and MR1 tetramer−, both of which had a distinct gene expression profile compared to CD8 memory T cells. Transcriptomic analysis of LTBI vs. noninfected individuals did not reveal significant differences for MR1 tetramer+ cells. However, gene expression of MR1 tetramer− cells showed a very different profile with large inter-individual diversity and a TB-specific signature. This was further strengthened by a more diverse TCR-α and -β repertoire of MR1 tetramer− cells as compared to MR1 tetramer+. Thus, cell population transcriptomics revealed a dominant MAIT signature in CD8 memory T cells that upon detailed investigation provided novel insights into the phenotype of different MAIT populations implicated in tuberculosis.
2020-05-13 | GSE132932 | GEO
Project description:We applied a cell population transcriptomics strategy to sorted human memory CD8 T cells to define novel immune signatures of latent tuberculosis infection (LTBI) and understand the phenotype of tuberculosis (TB)-specific T cells. We found a 41-gene signature that could discriminate between memory CD8 T cells from healthy LTBI subjects and noninfected controls. The gene signature was dominated by genes known to be associated with mucosal associated invariant T cells (MAITs) and reflected the lower frequency of MAITs observed in individuals with LTBI. There was no evidence for a conventional CD8 T cell specific signature between the two cohorts. We therefore investigated the MAITs in more detail in these cohorts. Phenotyping based on Vα7.2 and CD161 expression and MR1 tetramers revealed 2 distinct populations of CD8+Vα7.2+CD161+ T cells: MR1 tetramer+ and MR1 tetramer−, both of which had a distinct gene expression profile compared to CD8 memory T cells. Transcriptomic analysis of LTBI vs. noninfected individuals did not reveal significant differences for MR1 tetramer+ cells. However, gene expression of MR1 tetramer− cells showed a very different profile with large inter-individual diversity and a TB-specific signature. This was further strengthened by a more diverse TCR-α and -β repertoire of MR1 tetramer− cells as compared to MR1 tetramer+. Thus, cell population transcriptomics revealed a dominant MAIT signature in CD8 memory T cells that upon detailed investigation provided novel insights into the phenotype of different MAIT populations implicated in tuberculosis.
2020-05-13 | GSE132931 | GEO
Project description:Transcriptional signature of MAITs in LTBI
| PRJNA549010 | ENA
Project description:Transcriptional signature of MAITs in LTBI (memory CD8 T cells and subsets of TRAV1-2+CD161+ MAITs)
| PRJNA549484 | ENA
Project description:Transcriptional signature of MAITs in LTBI (CD8+ or CD8-)
| PRJNA549485 | ENA
Project description:We sequenced DNA isolated from performing ChIP of full-length KLF6 and an Input sample in an HCC cell line. The goal is to determine KLF6 binding sites in a mouse-derived HCC cell line. Determination of KLF6 binding sites in an HCC cell line using 2 control input libraries and 2 KLF6-ChIP libraries
2016-01-27 | E-GEOD-54763 | biostudies-arrayexpress