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Modulating AP-1 enables CAR-T cells to establish an intratumoral stem-like reservoir and overcomes resistance to PD-1 blockade

GSE288687 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2026/01/06 Platform GPL30172
At a glance

RNA-seq (gene expression) · mouse · 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
Mus musculus (mouse)
Samples
12 samples: 12 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
Modulating AP-1 enables CAR T cells to establish an intratumoral stemlike reservoir and overcomes resistance to PD-1 blockadeScience immunology · 2026
Summary (written by the submitters)
CAR-T therapy has shown limited synergy with PD-1/PD-L1 blockade, but the mechanisms underlying resistance remain unclear. PD-1⁺TCF1⁺ stem-like T cells mediate responses to PD-1/PD-L1 blockade and are maintained by MHC-dependent interactions with DCs in tumor-draining lymph nodes (dLN). Because CAR-Ts recognize intact antigen, not peptide-MHC, their activation is confined to tumors, potentially preventing maintenance of this critical subset.
Read the full summary ↓
In ROR1⁺ lung cancer models, ROR1-targeting CAR-Ts rapidly down-regulated TCF1, became exhausted, and were not enhanced by PD-L1 blockade. Overexpression of the AP-1 transcription factor c-Jun, but not BATF, enabled formation of PD-1⁺TCF1⁺ reservoirs in tumors, not dLN, but did not prevent exhaustion, as PD-1 induced post-transcriptional c-Jun down-regulation. Remarkably, PD-L1 blockade restored c-Jun levels, dramatically increased CAR-Ts, and enabled near-complete ROR1+ tumor clearance. These findings identify PD-1 as a suppressor of c-Jun and reveal that MHC-independent CAR-Ts can be engineered to establish intratumoral stem-like reservoirs that overcome resistance to PD-1 blockade.
Published in
Modulating AP-1 enables CAR T cells to establish an intratumoral stemlike reservoir and overcomes resistance to PD-1 blockade
Snyder AJ, Garrison SM, Kluesner MG et al. · Science immunology 2026 · PMID 41790934 · doi:10.1126/sciimmunol.adw7685
This dataset
Open GSE288687 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 GSE288687_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 PRJNA1219070 and SRA study SRP561437. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41790934) ↗
Study design
12 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 12 sample titles: 12 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
Datasets on a similar topic

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