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

GSE313241 Mus musculus Expression profiling by high throughput sequencing 7 samples Submitted 2025/12/17 Platform GPL24247
Summary
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. 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
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Direct links to NCBI, no account and no request form: the whole study as GSE313241_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 7 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1378833 and SRA study SRP654065. Searching any of these in the dataset finder brings you back here.

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