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Genome Med. 2017 Jan 23;9(1):4. doi: 10.1186/s13073-016-0393-x.

3D clusters of somatic mutations in cancer reveal numerous rare mutations as functional targets.

Author information

1
Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA. jgao@cbio.mskcc.org.
2
Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
3
Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
4
Departments of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, USA.
5
Louis V. Gerstner Jr. Graduate School of Biomedical Sciences, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
6
Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
7
Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
8
Weill Cornell Medical College, Cornell University, New York, NY, USA.
9
Department of Cell Biology, Harvard Medical School, Boston, MA, USA.
10
cBio Center, Dana-Farber Cancer Institute, Boston, MA, USA.
11
Computational Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.

Abstract

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.

KEYWORDS:

Cancer genomics; Driver mutations; Precision medicine; Protein structures

PMID:
28115009
PMCID:
PMC5260099
DOI:
10.1186/s13073-016-0393-x
[Indexed for MEDLINE]
Free PMC Article

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