Tumor-secreted FGF21 acts as an immune suppressor by rewiring cholesterol metabolism of CD8+ T cells
RNA-seq (gene expression) · mouse · 11 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
- 11 samples: 11 samples, each with a distinct title — no replicated groupsGroups 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.
Read the full summary ↓
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 GSE236180_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 PRJNA989185 and SRA study SRP446652. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 11 sample titles: 11 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.
- GSM7519374 N2N3N5_Tcell
- GSM7519375 N6N7N8_Tcell
- GSM7519376 NC124_Tcell
- GSM7519377 sh1sh3_Tcell
- GSM7519378 sh2sh4_Tcell
- GSM7519379 NC_1_tumor
- GSM7519380 NC_2_tumor
- GSM7519381 NC_6_tumor
- GSM7519382 sh_1_tumor
- GSM7519383 sh_2_tumor
- GSM7519384 sh_3_tumor
- GSE299133 Host MTDH orchestrates liver lipid metabolism and CD8+ T cells to suppress antitumor immunity [Hepatocytes] 18 samples shares cd8
- GSE279041 Targeting pyruvate metabolism generates distinct CD8+ T cell responses to gammaherpesvirus and B lymphoma 12 samples shares cd8
- GSE296763 Mitochondrial respiration is necessary for CD8 T cell proliferation and cell fate 99 samples shares cd8
- GSE334845 Discovery of Tcf7 regulators with clonally-resolved CRISPR screens identifies Trim28 as a mediator of CD8 T cell differentiation in tumors [RNA-Seq] 86 samples shares cd8
- GSE302682 Sleeping Beauty mutagenesis identifies BACH2 and other regulators promoting CD8+ T cell persistence and effector function under tumor-associated chronic antigen stimulation - RNAseq 66 samples shares cd8
- GSE276107 Host MTDH orchestrates liver lipid metabolism and CD8+ T cells to suppress antitumor immunity 44 samples shares cd8
- GSE337601 XCR1+ and CD11b+ migratory dendritic cells cooperate for the crosspriming of intratumoral CD8+ T cells with a tissue-resident memory phenotype [RNA-Seq] 36 samples shares cd8
- GSE306744 Pre-division TCF1 downregulation determines long-term effector and memory CD8 T cell fates [RNA-Seq] 31 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.