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A pan-immunotherapy signature to predict intratumoral CD8+ T cell expansions [scTCR_immunotherapies]

GSE304763 Mus musculus (mouse) Single-cell RNA-seq 91 samples Submitted 2025/08/09 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 91 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
91 samples: 91 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.
Summary (written by the submitters)
Effective cancer immunotherapy relies on the clonal proliferation and expansion of CD8+ T cells in the tumor. However, our insights into clonal expansions are limited, owing to an inability to track the same clones in tumors over time. Here, we developed a multi-site tumor mouse model system to track hundreds of expanding and contracting CD8+ T cell clones over multiple timepoints in tumors of the same individual.
Read the full summary ↓
Through coupling of clonal expansion dynamics and single-cell RNA/TCR-seq data, we identified a transcriptomic signature in PD-1+Ly108+ precursor exhausted cells that strongly predicts rates of intratumoral clone expansion. The signature correlates with expansion in mice, both with and without immunotherapies, and in patients undergoing PD-1 blockade therapy. Expression of the signature during treatment corresponds with positive clinical outcomes. Downregulation of the signature precedes clone contraction – a phase in which clones contract but maintain revivable precursor exhausted cells in the tumor. LAG-3 blockade re-activates the expansion signature, re-expanding pre-existing clones, including previously contracted clones. These findings reveal how the study of clonal expansion dynamics provide a powerful ‘pan-immunotherapy’ signature for monitoring immunotherapies with implications for their future development.
This dataset
Open GSE304763 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 GSE304763_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 PRJNA1302469 and SRA study SRP607072. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
91 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 91 sample titles: 91 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

+ 51 more — browse all 91 samples with per-sample file links →

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.