3D clusters of somatic mutations in cancer reveal numerous rare mutations as functional targets.
Many mutations in cancer are of unknown functional significance. Standard methods use statistically significant recurrence of mutations in tumor samples as an indicator of functional impact. We extend such analyses into the long tail of rare mutations by considering recurrence of mutations in clusters of spatially close residues in protein structures. Analyzing 10,000 tumor exomes, we identify more than 3000 rarely mutated residues in proteins as potentially functional and experimentally validate several in RAC1 and MAP2K1. These potential driver mutations (web resources: 3dhotspots.org and cBioPortal.org) can extend the scope of genomically informed clinical trials and of personalized choice of therapy.
['Gao|Jianjiong|J|0000-0002-5739-1781', 'Chang|Matthew T|MT|', 'Johnsen|Hannah C|HC|', 'Gao|Sizhi Paul|SP|', 'Sylvester|Brooke E|BE|', 'Sumer|Selcuk Onur|SO|', 'Zhang|Hongxin|H|', 'Solit|David B|DB|', 'Taylor|Barry S|BS|', 'Schultz|Nikolaus|N|', 'Sander|Chris|C|']
D004252:DNA Mutational Analysis D059472:Exome D023281:Genomics D006801:Humans D048369:MAP Kinase Kinase 1 D009154:Mutation D009363:Neoplasm Proteins D009369:Neoplasms D017434:Protein Structure, Tertiary D020830:rac1 GTP-Binding Protein
Protein structures Driver mutations Cancer genomics Precision medicine