Reverse translational discovery reveals dysregulation of CD4+ and CD8+ resident memory T, myeloid, and stromal cells in steroid-refractory, checkpoint inhibitor colitis
RNA-seq (gene expression) · human · 12 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Homo sapiens (human)
- Samples
- 12 samples: 8 × HS1-CL HS2-CL HS3-CL HS4-CL HS5-CL HS7-CL HS8-CL HS9-CL HS10-CL HS11-CL HS12-CL HS13-CL HS14-CL HS15-CL vs 4 × HS1-BL HS2-BL HS3-BL HS4-BL HS6-BL HS7-BL HS8-BL HS9-BL HS10-BL HS11-BL HS12-BL HS13-BL HS14-BL HS15-BLGroups are read from the sample names, not from the paper. Check the list below.
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
- Paper
- Dysregulation of CD4(+) and CD8(+) resident memory T, myeloid, and stromal cells in steroid-experienced, checkpoint inhibitor colitisJournal for immunotherapy of cancer · 2024
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE253723_RAW.tar (it can run to tens of gigabytes).
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1066821. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 12 samples.
How we read this: 2 replicated groups read from 12 sample titles; they account for 12 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM8026960 XAUT2-POOL-SCG7: HS1-CL HS2-CL HS3-CL HS4-CL HS5-CL HS7-CL HS8-CL HS9-CL HS10-CL HS11-CL HS12-CL HS13-CL HS14-CL HS15-CL HS1-CL HS2-CL HS3-CL HS…
- GSM8026961 XAUT2-POOL-SCG8: HS1-CL HS2-CL HS3-CL HS4-CL HS5-CL HS7-CL HS8-CL HS9-CL HS10-CL HS11-CL HS12-CL HS13-CL HS14-CL HS15-CL HS1-CL HS2-CL HS3-CL HS…
- GSM8026962 XAUT2-POOL-SCG1: HS1-CL HS2-CL HS3-CL HS4-CL HS5-CL HS7-CL HS8-CL HS9-CL HS10-CL HS11-CL HS12-CL HS13-CL HS14-CL HS15-CL HS1-CL HS2-CL HS3-CL HS…
- GSM8026963 XAUT2-POOL-SCG2: HS1-CL HS2-CL HS3-CL HS4-CL HS5-CL HS7-CL HS8-CL HS9-CL HS10-CL HS11-CL HS12-CL HS13-CL HS14-CL HS15-CL HS1-CL HS2-CL HS3-CL HS…
- GSM8026964 XAUT2-POOL-SCG3: HS1-CL HS2-CL HS3-CL HS4-CL HS5-CL HS7-CL HS8-CL HS9-CL HS10-CL HS11-CL HS12-CL HS13-CL HS14-CL HS15-CL HS1-CL HS2-CL HS3-CL HS…
- GSM8026965 XAUT2-POOL-SCG4: HS1-CL HS2-CL HS3-CL HS4-CL HS5-CL HS7-CL HS8-CL HS9-CL HS10-CL HS11-CL HS12-CL HS13-CL HS14-CL HS15-CL HS1-CL HS2-CL HS3-CL HS…
- GSM8026966 XAUT2-POOL-SCG5: HS1-CL HS2-CL HS3-CL HS4-CL HS5-CL HS7-CL HS8-CL HS9-CL HS10-CL HS11-CL HS12-CL HS13-CL HS14-CL HS15-CL HS1-CL HS2-CL HS3-CL HS…
- GSM8026967 XAUT2-POOL-SCG6: HS1-CL HS2-CL HS3-CL HS4-CL HS5-CL HS7-CL HS8-CL HS9-CL HS10-CL HS11-CL HS12-CL HS13-CL HS14-CL HS15-CL HS1-CL HS2-CL HS3-CL HS…
- GSM8026968 XAUT2-POOL-SCG9:HS1-BL HS2-BL HS3-BL HS4-BL HS6-BL HS7-BL HS8-BL HS9-BL HS10-BL HS11-BL HS12-BL HS13-BL HS14-BL HS15-BL HS1-BL HS2-BL HS3-BL HS…
- GSM8026969 XAUT2-POOL-SCG10:HS1-BL HS2-BL HS3-BL HS4-BL HS6-BL HS7-BL HS8-BL HS9-BL HS10-BL HS11-BL HS12-BL HS13-BL HS14-BL HS15-BL HS1-BL HS2-BL HS3-BL HS…
- GSM8026970 XAUT2-POOL-SCG11:HS1-BL HS2-BL HS3-BL HS4-BL HS6-BL HS7-BL HS8-BL HS9-BL HS10-BL HS11-BL HS12-BL HS13-BL HS14-BL HS15-BL HS1-BL HS2-BL HS3-BL HS…
- GSM8026971 XAUT2-POOL-SCG12:HS1-BL HS2-BL HS3-BL HS4-BL HS6-BL HS7-BL HS8-BL HS9-BL HS10-BL HS11-BL HS12-BL HS13-BL HS14-BL HS15-BL HS1-BL HS2-BL HS3-BL HS…
- GSE308745 The Cd4+ T cell population Partners with Tpex CD8 T cells to mediate Antitumor Immunity in the Tumor Microenvironment.[PB cohort2] 87 samples shares cd4, cd8
- GSE322527 Single-cell transcriptomes and T cell receptor sequences of CD4 or CD8 single positive T lymphocytes from peripheral blood or urine of lupus nephritis patients at flare. 26 samples shares cd4, cd8
- GSE285617 Characterization and effective expansion of CD4-CD8- TCRab+ T cells from individuals living with type 1 diabetes 24 samples shares cd4, cd8
- GSE295601 The Cd4+ T cell population Partners with Tpex CD8 T cells to mediate Antitumor Immunity in the Tumor Microenvironment. [P6] 18 samples shares cd4, cd8
- GSE298811 Immune dysregulation and stem-like CD8+ T cell enrichment in type 1 diabetes pancreatic lymph nodes 57 samples shares cd8, dysregulation
- GSE189754 Divergent spatial microdomains drive inflammation and repair in Ulcerative and Immune Checkpoint Therapy Colitis - CD45 scRNA-Seq 15 samples shares cd4, checkpoint
- GSE235244 Senescent cancer-associated fibroblasts in pancreatic adenocarcinoma suppress CD8+ T cell activation and inhibit response to immune checkpoint therapy [hPDAC] 8 samples shares cd8, checkpoint
- GSE210231 CD8+ T cell memory induced by successive SARS-CoV-2 mRNA vaccinations is characterized by shifts in clonal dominance 931 samples shares cd8
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.