Structural and functional impact of cancer-related missense somatic mutations.

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TitleStructural and functional impact of cancer-related missense somatic mutations.
Publication TypeJournal Article
Year of Publication2011
AuthorsShi, Z, Moult, J
JournalJ Mol Biol
Date Published2011 Oct 21
KeywordsBreast Neoplasms, Colorectal Neoplasms, Databases, Factual, Female, Humans, Liver Neoplasms, Lymphatic Metastasis, Mutation, Oncogene Proteins, Phenotype, Tumor Suppressor Proteins

A number of large-scale cancer somatic genome sequencing projects are now identifying genetic alterations in cancers. Evaluation of the effects of these mutations is essential for understanding their contribution to tumorigenesis. We have used SNPs3D, a software suite originally developed for analyzing nonsynonymous germ-line variants, to identify single-base mutations with a high impact on protein structure and function. Two machine learning methods are used: one identifying mutations that destabilize protein three-dimensional structure and the other utilizing sequence conservation and detecting all types of effects on in vivo protein function. Incorporation of detailed structure information into the analysis allows detailed interpretation of the functional effects of mutations in specific cases.  Data from a set of breast and colorectal tumors were analyzed. In known cancer genes, mutations approaching 100% of mutations are found to impact protein function, supporting the view that these methods are appropriate for identifying driver mutations. Overall, 50-60% of all somatic missense mutations are predicted to have a high impact on structural stability or to more generally affect the function of the corresponding proteins. This value is similar to the fraction of all possible missense mutations that have a high impact and is much higher than the corresponding one for human population single-nucleotide polymorphisms, at about 30%. The majority of mutations in tumor suppressors destabilize protein structure, while mutations in oncogenes operate in more varied ways, including destabilization of less active conformational states. The set of high-impact mutations encompasses the possible drivers.

Alternate JournalJ. Mol. Biol.
PubMed ID21763698
Grant ListR01 LM007174 / LM / NLM NIH HHS / United States
R01LM007174 / LM / NLM NIH HHS / United States