← BioTransfer GEO Dataset Finder
GEO series

scRNAseq and scTCRseq data from tumor-infiltrating lymphocytes

GSE298152 Mus musculus (mouse) Single-cell RNA-seq 16 samples Submitted 2025/05/27 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 16 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
16 samples: 8 conditions, mostly in duplicateGroups 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
Different tumour-resident memory T-cell subsets regulate responses to anti-PD-1 and anti-CTLA-4 cancer immunotherapiesNature communications · 2025
Summary (written by the submitters)
In cancer models, CD103+CD8 TRM cells are implicated in the response to anti-PD-1 immunotherapy, and a subset of CD4 TRM cells expressing the integrin CD49a is required for response to anti-CTLA-4 immunotherapy. We performed single-cell RNA sequencing on tumour-infiltrating T lymphocytes (TILs) isolated from colon carcinoma et unsupervised analyses reveal several TRM populations.
Published in
Different tumour-resident memory T-cell subsets regulate responses to anti-PD-1 and anti-CTLA-4 cancer immunotherapies
Damei I, Caidi A, Auclin E et al. · Nature communications 2025 · PMID 40593647 · doi:10.1038/s41467-025-60657-w
This dataset
Open GSE298152 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 GSE298152_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1268438 and SRA study SRP588085. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40593647) ↗
Study design
8 conditions, mostly in duplicate
GE_anti-CTLA4 ×2 GE_anti-PD1 ×2 GE_anti-PD1_anti-CTLA4 ×2 GE_isotype ×2 TCR_anti-CTLA4 ×2 TCR_anti-PD1 ×2 TCR_anti-PD1_anti-CTLA4 ×2 TCR_isotype ×2

Supports a between-group comparison across 16 samples.

How we read this: 8 replicated groups read from 16 sample titles; they account for 16 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
Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.