← BioTransfer GEO Dataset Finder
GEO series

MAIT cell enrichment in Lynch syndrome is associated with immune surveillance and colorectal cancer risk

GSE303880 Homo sapiens Expression profiling by high throughput sequencing; Other 3 samples Submitted 2026/03/16 Platform GPL24676
Summary
Tissue microenvironment characteristics associated with elevated risk of colorectal cancer (CRC) in Lynch syndrome (LS) are poorly characterized. We applied the multimodal single cell sequencing platform ExCITE-seq to define the colonic cellular composition and transcriptome of LS carriers with and without a history of CRC compared with general population controls. Our analysis revealed widespread remodeling in LS that included striking expansion of epithelial stem and progenitor cells, and loss of fibroblast populations. Although clonally expanded and terminally exhausted CD8 T cells were more prominent in individuals with a history of CRC, LS carriers without CRC displayed enrichment of cytotoxic mucosal-associated invariant T (MAIT) cells associated with CCL20 expression in epithelial progenitors, validated by orthogonal techniques including demonstration of a protective function in a murine model of CRC. These findings highlight cellular features that distinguish LS carriers and suggest a protective role of MAIT cells in human CRC surveillance.
Published in
MAIT cell enrichment in Lynch syndrome is associated with immune surveillance and colorectal cancer risk
Yang H, Dungan M, Madhu B et al. · Gut 2026 · PMID 42156170 · doi:10.1136/gutjnl-2025-337343
This dataset
Download

Direct links to NCBI, no account and no request form: the whole study as GSE303880_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 3 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1298017. Searching any of these in the dataset finder brings you back here.

Samples in this study

The sample list for this study is not cached yet. Press Sort into groups and it will be fetched from NCBI.

+ 3 more — browse all 3 samples with per-sample file links →

Similar datasets

Search all human 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.