Differentiation fate of a stem-like CD4 T cell controls immunity to cancer
RNA-seq (gene expression) · mouse · 10 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
- Mus musculus (mouse)
- Samples
- 10 samples: 8 distinct titles, 2 of them repeatedGroups 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.
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 GSE274801_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 PRJNA1148073 and SRA study SRP526487. Searching any of these in the dataset finder brings you back here.
How we read this: Read from 10 sample titles: 8 distinct titles with little repetition. 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.
- GSM8458196 RCC PD1+CD45RA- CD4 TILS GEX Patient K297
- GSM8458197 RCC PD1+CD45RA- CD4 TILS VDJ Patient K297
- GSM8458198 RCC PD1+CD45RA- CD4 TILS GEX Patient K416
- GSM8458199 RCC PD1+CD45RA- CD4 TILS VDJ Patient K416
- GSM8458200 Mouse untreated activated PD1+ T cells from TDLNS GEX
- GSM8458201 Mouse untreated activated PD1+ T cells from TDLNS VDJ
- GSM8458202 Mouse activated PD1+ T cells from Treg depleted TDLNS GEX
- GSM8458203 Mouse activated PD1+ T cells from Treg depleted TDLNS VDJ
- GSM8458204 Mouse activated PD1+ T cells from total CD4 depleted TDLNS GEX
- GSM8458205 Mouse activated PD1+ T cells from total CD4 depleted TDLNS VDJ
- GSE241173 CD4+ T cell-derived IL21 regulates stem cell fate in acute myeloid leukemia by activation of p38-MAPK signaling 21 samples shares cd4, fate
- GSE335842 Single-Cell RNA sequencing reveals clonally-expanded CD4+ tissue-resident memory T cells in Histidyl-tRNA Synthetase-induced myositis 38 samples shares cd4
- GSE296112 Augment proteasome inhibitor efficacy activates CD8+ T cell-mediated antitumor immunity in breast cancer 27 samples shares immunity
- GSE207516 Transcriptonal and epigenetic profiling of neuroblastoma cells based on CD49b expression 26 samples shares cd4
- GSE255495 Perturbing local steroidogenesis to improve breast cancer immunity 20 samples shares immunity
- GSE285138 A phosphorylation switch within the Mediator subunit MED15 controls cellular senescence and cognitive decline 24 samples shares controls
- GSE316054 Targeting the ADAR1 p150 isoform triggers tumor growth inhibition and antitumor immunity to overcome immunotherapy resistance 52 samples shares immunity
- GSE99063 CDK4/6 inhibition and tumor immunity 45 samples shares immunity
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.