GEO series
Comprehensive proteogenomic analysis identifies immune targets in microsatellite stable and unstable colorectal cancers
GSE312236
Homo sapiens
Expression profiling by high throughput sequencing
26 samples
2026/05/26
GPL24676
Summary
Treatment with immune checkpoint inhibitors in colorectal cancer (CRC) has largely benefited patients with microsatellite instability–high (MSI-H) and not the larger proportion of patient with microsatellite-stable (MSS) tumors. This clinical dichotomy has fueled the view that high mutational burden is the dominant driver of tumor immunogenicity and that MSS CRC fails to respond because it is “antigen poor”. To directly test this premise and define the origins of presented tumor antigens, we integrated HLA class I immunopeptidomics and matched RNA-seq from 26 primary CRC tumors spanning MSI-H and MSS subtypes. Using patient-specific canonical and cancer-specific proteogenomic databases, we identified 115,292 unique MHC-associated peptides (MAPs) across 61 HLA alleles, with a mean of 9,292 MAPs per tumor and no significant difference in MAP counts between MSI-H and MSS tumors. In toto, we identified 266 tumor antigens, all coded by unmutated genomic sequences, comprising 70 aberrantly expressed tumor-specific antigens (aeTSAs) and 196 tumor-associated antigens (TAAs). In our cohort, MSS tumors presented more TAAs and a comparable number of aeTSAs per tumor relative to MSI-H tumors. In TCGA-COAD stratified analyses (483 tumors), MSS tumors yielded more presentable aeTSAs and TAAs per patient than MSI-H tumors. Across both subtypes, aeTSAs arose predominantly from intronic translation, UTR usage, retroelement activation, and germline-like transcription, including recurrent aeTSAs from PIWIL1, L1TD1, and endogenous retroviral loci. Together, these data demonstrate that MSS CRC is not antigen poor and highlight non-canonical translation as a major, previously underappreciated contributor to the CRC immunopeptidome.
Download
NCBI GEO page ↗
Paper (PMID 42106149) ↗
{# Names what the click gives you. "Open in finder" meant nothing to a
visitor who arrived from a search engine and has never seen the tool. #}
Find more
human RNA-seq datasets →
Similar datasets
- GSE328275 Single-cell RNA sequencing of CD45+ immune cells across primary tumor, sentinel tumor-draining lymph node, and axillary lymph node in treatment-naive triple-negative breast cancer 28 samples
- GSE341753 Cohesin loading at regulatory elements shapes 3D genome folding during erythropoiesis [RNA-Seq] 12 samples
- GSE319969 Spatial and Bulk Transcriptomic Profiling Defines the Molecular Evolution of Cutaneous Squamous Cell Carcinoma and Reveals Stage-Specific Biomarkers of Clinical Relevance [RNA-Seq] 24 samples
- GSE313035 METIMMOX: Colorectal Cancer METastasis - Shaping Anti-tumor IMMunity by OXaliplatin 67 samples
- GSE339456 Integrated bulk and spatial transcriptomic analysis identifies progression-associated molecular signatures in biopsy-proven hypertensive nephropathy [RNA-seq] 35 samples
- GSE342462 Integrated transcriptomic and bioelectrical profiling of stem-like cellular states in a colorectal cancer using SdFFF and UHF-DEP 12 samples
- GSE336982 Obesity Promotes Lung Carcinogenesis Through Airway Immune Dysfunction 183 samples
- GSE330029 Temporal changes in metabolism guide oligodendrocyte precursor cell dynamics in aging and multiple sclerosis [BulkRNAseq] 108 samples
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.