Spatially interacting phosphorylation sites and mutations in cancer

Kuan lin Huang, Adam D. Scott, Daniel Cui Zhou, Liang Bo Wang, Amila Weerasinghe, Abdulkadir Elmas, Ruiyang Liu, Yige Wu, Michael C. Wendl, Matthew A. Wyczalkowski, Jessika Baral, Sohini Sengupta, Chin Wen Lai, Kelly Ruggles, Samuel H. Payne, Benjamin Raphael, David Fenyö, Ken Chen, Gordon Mills, Li Ding

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Article number2313
JournalNature communications
Volume12
Issue number1
DOIs
StatePublished - Dec 2021

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Physics and Astronomy(all)

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