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Genetic Control of tRNA-Derived Fragments Contributes to Cancer Risk

GSE304444 Homo sapiens Expression profiling by high throughput sequencing 6 samples Submitted 2025/08/05 Platform GPL24676
Summary
Transfer RNA-derived fragments (tRFs) are a class of small non-coding RNAs that have exhibited several functions in cancer. Recent studies have shown that mutations in tRNA genes can lead to global changes in tRF expression levels and may affect tRF function, highlighting the need to further elucidate the regulation and functions of tRFs in cancer. Here, we conducted a pan-cancer analysis of tRF quantitative trait loci (tRFQTLs), encompassing 16,703 genetic variants associated with tRF expression across 31 cancer types. A joint analysis of GWAS data revealed that tRFQTLs were preferentially enriched in cancer risk loci and colocalized with 106 GWAS variants, explaining a substantial portion of cancer heritability. Moreover, tRFs regulated by tRFQTLs were enriched in cancer-related pathways and correlated with drug response and immune infiltration. Notably, polygenic risk score models incorporating tRFQTLs improved high-risk population identification. Investigation of large-scale population cohorts revealed a tRFQTL, rs9461276, associated with colorectal cancer (CRC) risk. In biological assays, the rs9461276-C allele increased tRF-18-HSQS52D2 expression, which suppressed CRC malignant phenotypes. Mechanistically, tRF-18-HSQS52D2 bound to the 3'UTR of POU2F1, destabilizing the oncogenic transcript. Integrated RNA sequencing and ChIP-seq assays indicated that POU2F1 enhanced CRC cell proliferation by activating various pathological pathways associated with oxidative and glycolytic metabolism, mitotic stability, and cell cycle regulation. Finally, a database (Cancer-tRFQTL) was generated as a resource to support investigation into tRF-mediated mechanisms and genetic basis of tRF expression in human cancers. Overall, this study helps advance the understanding of tRFs in cancer pathogenesis.
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Direct links to NCBI, no account and no request form: the whole study as GSE304444_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 6 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1301318 and SRA study SRP606667. Searching any of these in the dataset finder brings you back here.

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