GEO series

Antigen experience history directs distinct functional states of CD8+ CAR T cells during the anti-leukemia response [RNA-seq]

GSE249732 Mus musculus (mouse) RNA-seq (gene expression) 30 samples Submitted 2024/11/10 Platform GPL24247

At a glance

RNA-seq (gene expression) · mouse · 30 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: 30 samples: 30 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.
Paper: Antigen experience history directs distinct functional states of CD8(+) CAR T cells during the antileukemia responseNature immunology · 2025

Summary (written by the submitters)

Adoptive transfer of immune cells expressing chimeric antigen receptors (CARs) is an effective therapy for B-lineage malignancies. However, most patients will relapse and this therapeutic has yet to show strong efficacy in other hematologic or solid tumors. One opportunity for improvement lies in the ability to select or generate T cells that have the highest potential for potent anti-tumor responses and T cell persistence.

Read the full summary ↓

Here, we dissect the biology of CD8+ CAR T cells by controlling whether the T cell has encountered cognate TCR antigen prior to CAR generation. We find that prior antigen experience influences multiple aspects of in vitro and in vivo CAR T cell functionality, boosting effector function and leukemia clearance in the setting of limiting target antigen density. However, this comes at the expense of proliferative capacity, resistance to dysfunction, and clearance of wildtype leukemia in the setting of limiting CAR+ cell dose. Epigenetic and transcriptomic comparisons of these cell populations uncover that modulation of the Runx2 transcription factor differentially impacts CAR T cell functionality depending on prior cell state. Collectively, our data demonstrate that prior antigen experience status determines functional attributes of a CAR T cell, as well as amenability to functional enhancement by transcription factor modulation.

Published in

Antigen experience history directs distinct functional states of CD8(+) CAR T cells during the antileukemia response

DeGolier KR, Danis E, D'Antonio M et al. · Nature immunology 2025 · PMID 39747430 · doi:10.1038/s41590-024-02034-1

This dataset

Open GSE249732 in finder → Find more mouse 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 GSE249732_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 PRJNA1050261 and SRA study SRP476731. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39747430) ↗

Study design

30 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 30 sample titles: 30 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.

Samples in this study

GSM7962170 Naïve, PreCAR, Exp1, TR1 [RNA-seq]
GSM7962171 Naïve, PreCAR, Exp1, TR2 [RNA-seq]
GSM7962172 Naïve, PreCAR, Exp1, TR3 [RNA-seq]
GSM7962173 Memory, PreCAR, Exp1, TR1 [RNA-seq]
GSM7962174 Memory, PreCAR, Exp1, TR2 [RNA-seq]
GSM7962175 Memory, PreCAR, Exp1, TR3 [RNA-seq]
GSM7962176 Naïve, PostCAR, Exp1, TR1 [RNA-seq]
GSM7962177 Naïve, PostCAR, Exp1, TR2 [RNA-seq]
GSM7962178 Naïve, PostCAR, Exp1, TR3 [RNA-seq]
GSM7962179 Memory, PostCAR, Exp1, TR1 [RNA-seq]
GSM7962180 Memory, PostCAR, Exp1, TR2 [RNA-seq]
GSM7962181 Memory, PostCAR, Exp1, TR3 [RNA-seq]
GSM7962182 Naïve, Tumor, Exp1, TR1 [RNA-seq]
GSM7962183 Naïve, Tumor, Exp1, TR2 [RNA-seq]
GSM7962184 Naïve, Tumor, Exp1, TR3 [RNA-seq]
GSM7962185 Memory, Tumor, Exp1, TR1 [RNA-seq]
GSM7962186 Memory, Tumor, Exp1, TR2 [RNA-seq]
GSM7962187 Memory, Tumor, Exp1, TR3 [RNA-seq]
GSM7962188 Naïve, PreCAR, Exp2, TR1 [RNA-seq]
GSM7962189 Naïve, PreCAR, Exp2, TR2 [RNA-seq]
GSM7962190 Memory, PreCAR, Exp2, TR1 [RNA-seq]
GSM7962191 Memory, PreCAR, Exp2, TR2 [RNA-seq]
GSM7962192 Naïve, PostCAR, Exp2, TR1 [RNA-seq]
GSM7962193 Naïve, PostCAR, Exp2, TR2 [RNA-seq]
GSM7962194 Memory, PostCAR, Exp2, TR1 [RNA-seq]
GSM7962195 Memory, PostCAR, Exp2, TR2 [RNA-seq]
GSM7962196 Naïve, Tumor, Exp2, TR1 [RNA-seq]
GSM7962197 Naïve, Tumor, Exp2, TR2 [RNA-seq]
GSM7962198 Memory, Tumor, Exp2, TR1 [RNA-seq]
GSM7962199 Memory, Tumor, Exp2, TR2 [RNA-seq]

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GSE342096 Distinct activation programs in naïve and memory CD8 T cells govern progeny stemness and effector persistence 37 samples shares cd8, distinct
GSE157232 The CD8+ T cell tolerance checkpoint triggers a transcriptionally and epigenetically distinct differentiation state defined by protein translation defects 30 samples shares cd8, distinct
GSE296763 Mitochondrial respiration is necessary for CD8 T cell proliferation and cell fate 99 samples shares cd8
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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.