4.8 Article

Pan-cancer assessment of mutational landscape in intrinsically disordered hotspots reveals potential driver genes

Journal

NUCLEIC ACIDS RESEARCH
Volume 50, Issue 9, Pages -

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/nar/gkac028

Keywords

-

Funding

  1. Hainan Province Science and Technology Special Fund [ZDYF2021SHFZ051]
  2. Hainan Provincial Natural Science Foundation of China [820MS053]
  3. Major Science and Technology Program of Hainan Province [ZDKJ202003, 2021037]
  4. National Natural Science Foundation of China [31871338, 31970646, 61873075, 32060152, 32070673, 81660433, 32170676]
  5. Hainan Province Clinical Medical Center
  6. Hainan Clinical Research Center [LCYX202102]
  7. Marshal Initiative Funding of Hainan Medical University [JBGS202103]
  8. HMU Marshal Initiative Funding [HMUMIF-21024]
  9. National Key Research and Development Program of China [2018YFC2000100]
  10. Natural Science Foundation for Distinguished Young Scholars of Heilongjiang Province [JQ2019C004]
  11. Heilongjiang Touyan Innovation Team Program
  12. Hainan ProvincialKey Laboratory of Carcinogenesis and Intervention [JCKF2021003]
  13. Innovation Research Fund for Graduate Students [Qhys2021-348, Qhys2021-350, Qhys2021-351, Qhys2021-377, HYYB2021A01, HYYS2021A31]

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This study comprehensively characterized the mutational landscapes of intrinsically disordered protein regions (IDRs) in cancer and developed a computational method to identify putative driver genes in these regions. The results showed that IDRs have higher mutation frequencies across diverse cancers and mutations in these regions disrupt phase separation in key cellular pathways. Additionally, clinically relevant genes enriched in IDR mutational hotspots were identified and associated with cancer patient survival. The combination of mutational effects on IDRs can significantly improve the sensitivity of driver detection and offer new therapeutic avenues for cancer treatment.
Large-scale cancer genome sequencing has enabled the catalogs of somatic mutations; however, the mutational impact on intrinsically disordered protein regions (IDRs) has not been systematically investigated to date. Here, we comprehensively characterized the mutational landscapes of IDRs and found that IDRs have higher mutation frequencies across diverse cancers. We thus developed a computational method, ROI-Driver, to identify putative driver genes enriching IDR and domain hotspots in cancer. Numerous well-known cancer-related oncogenes or tumor suppressors that play important roles in cancer signaling regulation, development and immune response were identified at a higher resolution. In particular, the incorporation of IDR structures helps in the identification of novel potential driver genes that play central roles in human protein-protein interaction networks. Interestingly, we found that the putative driver genes with IDR hotspots were significantly enriched with predicted phase separation propensities, suggesting that IDR mutations disrupt phase separation in key cellular pathways. We also identified an appreciable number of clinically relevant genes enriching IDR mutational hotspots that exhibited differential expression patterns and are associated with cancer patient survival. In summary, combinations of mutational effects on IDRs significantly increase the sensitivity of driver detection and are likely to open new therapeutic avenues for various cancers.

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