Abstract
Functional consequences of somatic mutations in cancer using protein pocket-based prioritization approach
Highlights
A number of large-scale cancer genome sequencing projects have generated a large volume of somatic mutations; identifying the functional consequences and roles of somatic mutations in tumorigenesis remains a major challenge
Do the somatic mutations located in protein pocket regions tend to be actionable mutations? and (2) are those specific mutations more likely to be involved in tumorigenesis and anticancer drug responses? Through our systematic analyses, we showed that genes harboring protein pocket somatic mutations tend to be cancer genes
Since we only focused on mapping somatic mutations onto human protein structures, we filtered out proteins whose organisms were not human, using human protein information from BioMart [30] to obtain a high-quality list of 606 human proteins
Summary
A number of large-scale cancer genome sequencing projects have generated a large volume of somatic mutations; identifying the functional consequences and roles of somatic mutations in tumorigenesis remains a major challenge. Espinosa et al [21] proposed a predictor, InCa (Index of Carcinogenicity) that integrates somatic mutation profiles from the Catalogue of Somatic Mutations in Cancer (COSMIC) database and the neutral mutations from the 1000 Genomes project into protein structure and interaction interface information Using these data, they developed the InCa classifier model to predict cancer-related mutations with 83% specificity and 77% sensitivity. Several independent research groups found that the presence of mutations in the EGFR gene (point mutations in exon 21 or deletions in exon 19) could activate the gene by altering the ATP binding site, leading to an enhancement of the gefitinib response [24,25] It has been debated whether mutations in the protein pocket regions alter protein functions through the ligand-independent mechanisms [26]
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