| Literature DB >> 33875650 |
Kuan-Lin Huang1, Adam D Scott2, Daniel Cui Zhou2, Liang-Bo Wang2, Amila Weerasinghe2, Abdulkadir Elmas3, Ruiyang Liu2, Yige Wu2, Michael C Wendl2, Matthew A Wyczalkowski2, Jessika Baral2, Sohini Sengupta2, Chin-Wen Lai4, Kelly Ruggles5, Samuel H Payne6, Benjamin Raphael7, David Fenyö5, Ken Chen8, Gordon Mills9, Li Ding10.
Abstract
Advances in mass-spectrometry have generated increasingly large-scale proteomics datasets containing tens of thousands of phosphorylation sites (phosphosites) that require prioritization. We develop a bioinformatics tool called HotPho and systematically discover 3D co-clustering of phosphosites and cancer mutations on protein structures. HotPho identifies 474 such hybrid clusters containing 1255 co-clustering phosphosites, including RET p.S904/Y928, the conserved HRAS/KRAS p.Y96, and IDH1 p.Y139/IDH2 p.Y179 that are adjacent to recurrent mutations on protein structures not found by linear proximity approaches. Hybrid clusters, enriched in histone and kinase domains, frequently include expression-associated mutations experimentally shown as activating and conferring genetic dependency. Approximately 300 co-clustering phosphosites are verified in patient samples of 5 cancer types or previously implicated in cancer, including CTNNB1 p.S29/Y30, EGFR p.S720, MAPK1 p.S142, and PTPN12 p.S275. In summary, systematic 3D clustering analysis highlights nearly 3,000 likely functional mutations and over 1000 cancer phosphosites for downstream investigation and evaluation of potential clinical relevance.Entities:
Year: 2021 PMID: 33875650 DOI: 10.1038/s41467-021-22481-w
Source DB: PubMed Journal: Nat Commun ISSN: 2041-1723 Impact factor: 14.919