Transcriptomics

Dataset Information

0

Massively parallel screen uncovers many rare 3’ UTR variants regulating mRNA abundance of cancer driver genes [prime_editing_3utr]


ABSTRACT: Understanding the function of rare non-coding genetic variants represents a significant challenge. Here, we developed MapUTR, a screen to identify rare 3’ UTR variants affecting mRNA abundance post-transcriptionally. Among 17,301 rare variants, an average of 24.5% were functional, with 70% in cancer-related genes, many in critical cancer pathways. This observation motivated a further interrogation of 11,929 cancer somatic mutations, uncovering 3,928 (33%) functional mutations in well-established cancer driver genes, such as CDKN2A. Functional MapUTR variants were enriched in miRNA targets and protein-RNA interaction sites. Based on MapUTR, we define a new metric, untranslated tumor mutation burden (uTMB), reflecting the amount of somatic functional MapUTR variants of a tumor. We showed the potential of uTMB in predicting patient survival. Through prime editing, we characterized three variants in cancer-relevant genes (MFN2, FOSL2, and IRAK1), illustrating their cancer-driving potential. Our study elucidates the function of thousands of non-coding variants, nominates non-coding cancer driver mutations, and demonstrates their potential contributions to cancer.

ORGANISM(S): Homo sapiens

PROVIDER: GSE232570 | GEO | 2024/02/06

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2024-02-06 | GSE232572 | GEO
2024-02-06 | GSE232571 | GEO
2023-07-20 | PXD034007 | Pride
2022-06-06 | PXD031711 | Pride
2019-12-01 | GSE137527 | GEO
2023-01-10 | GSE218478 | GEO
2023-01-09 | GSE222435 | GEO
2023-01-09 | GSE222434 | GEO
2020-12-19 | GSE163517 | GEO
2020-04-22 | GSE125939 | GEO