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Cell state and transcription factor modulation during extended CD8+ T-cell expansion ex vivo

GSE247647 Homo sapiens (human) RNA-seq (gene expression) 51 samples Submitted 2024/07/22 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 51 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
51 samples: 15 conditions, mostly in triplicateGroups 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.
Summary (written by the submitters)
Adoptive cell therapy is fast becoming a cornerstone of modern tumour immunotherapy. It relies on the relatively long-term (>2 week) ex vivo expansion of T cells either in the form of tumour-infiltrating cells, or bulk cells modified with the expression of heterologous signaling proteins, e.g., chimeric antigen receptors. However, relatively little is known about the developmental trajectories of T cells under these conditions at the systems level, and whether entire genetic pathways could be manipulated for clinical advantage.
Read the full summary ↓
Using bulk RNA-seq analysis of T cells expanded and rested over a 17-day period, we provide a resource of how gene expression changes as cells transition through distinct cellular states over the course of activation and ex-vivo expansion. We also performed experiments to investigate the role of FOSL1 in T-cell function.
This dataset
Open GSE247647 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

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.

1 · Just have a look

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.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE247647_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

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.

Raw reads on ENA ↗

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 PRJNA1039860 and SRA study SRP471668. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
15 conditions, mostly in triplicate
Naive CD8+ T cells B ×3 30 mins post activation B ×3 3 hours post activation B ×3 12 hours post activation B ×3 24 hours post activation B ×3 48 hours post activation B ×3 72 hours post activation B ×3 7 days post activation B ×3 +13 more

Supports a case/control comparison: 6 samples read as cases, 3 as controls.

How we read this: 15 replicated groups read from 51 sample titles; they account for 45 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.

Samples in this study

+ 11 more — browse all 51 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.