← BioTransfer GEO Dataset Finder
GEO series

A Glucocorticoid-Fas axis controls immune evasion during metastatic seeding [RNAseq_4T1-tdTomato]

GSE313249 Mus musculus (mouse) RNA-seq (gene expression) 30 samples Submitted 2025/12/17 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
A glucocorticoid-FAS axis controls immune evasion during metastatic seedingNature · 2026
Summary (written by the submitters)
Metastasis is the major cause of death for patients with Triple Negative Breast Cancer (TNBC) and other solid malignancies. Metastases arise from cancer cells that disseminate from the original tumour, survive systemic immune surveillance, and colonize new organs. Little is known about how initial disseminated tumour cells (DTCs) overcome anti-tumour immunity upon seeding a new organ.
Read the full summary ↓
Here we used a visible antigen in a model of TNBC with cognate CD8+ T cells to interrogate mechanisms of immune evasion in early metastatic seeding. Analysis of surviving DTCs revealed Glucocorticoid Receptor (GR) activation as a key driver of resistance to both CD8+ T cells and Natural Killer (NK) cells. Niche profiling using an optimized labelling tool uncovered Fas-FasL as a key pan-cytotoxic pathway against DTCs, which is repressed by GR activation. Pharmacologic inhibition of GR in combination with immunotherapy reduced metastatic burden and expanded lifespan in mice. Thus, we discovered a novel mechanism of immune evasion that operates specifically in DTCs, illustrating the unique immune-cancer interactions at this stage in the metastatic cascade. Our findings suggest that there are therapeutic opportunities to eliminate DTCs, separately from treatments aimed at primary tumours, with GR inhibition as one promising target.
Published in
A glucocorticoid-FAS axis controls immune evasion during metastatic seeding
Cassandras M, Sanchez X, Hsu L et al. · Nature 2026 · PMID 41781620 · doi:10.1038/s41586-026-10222-2
This dataset
Open GSE313249 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 GSE313249_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 PRJNA1378854 and SRA study SRP654084. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41781620) ↗
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
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.