title: Genome-wide mutational spectra analysis reveals significant cancer-specific heterogeneity.
abstract: Cancer is widely recognized as a genetic disease in which somatic mutations are sequentially accumulated to drive tumor progression. Although genomic landscape studies are informative for individual cancer types, a comprehensive comparative study of tumorigenic mutations across cancer types based on integrative data sources is still a pressing need. We systematically analyzed ~10(6) non-synonymous mutations extracted from COSMIC, involving ~8000 genome-wide screened samples across 23 major human cancers at both the amino acid and gene levels. Our analysis identified cancer-specific heterogeneity that traditional nucleotide variation analysis alone usually overlooked. Particularly, the amino acid arginine (R) turns out to be the most favorable target of amino acid alteration in most cancer types studied (P < 10(-9), binomial test), reflecting its important role in cellular physiology. The tumor suppressor gene TP53 is mutated exclusively with the HYDIN, KRAS, and PTEN genes in large intestine, lung, and endometrial cancers respectively, indicating that TP53 takes part in different signaling pathways in different cancers. While some of our analyses corroborated previous observations, others indicated relevant candidates with high priority for further experimental validation. Our findings have many ramifications in understanding the etiology of cancer and the underlying molecular mechanisms in particular cancers.
authors.affiliation: 1] Center for Bioinformatics &Systems Biology, Department of Radiology, Wake Forest School of Medicine, Winston-Salem 27157, USA [2] College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China.
authors.forename: Hua
authors.initials: H
authors.lastname: Tan
authors.affiliation: School of Mathematical Sciences, Beijing Normal University, Beijing 100875, China.
authors.forename: Jiguang
authors.initials: J
authors.lastname: Bao
authors.affiliation: Center for Bioinformatics &Systems Biology, Department of Radiology, Wake Forest School of Medicine, Winston-Salem 27157, USA.
authors.forename: Xiaobo
authors.initials: X
authors.lastname: Zhou
mesh_terms: D000596:Amino Acids / Q000235:genetics*; D014408:Biomarkers, Tumor / Q000235:genetics; D002874:Chromosome Mapping / Q000379:methods; D030541:Databases, Genetic; D052138:Genes, Neoplasm / Q000235:genetics*; D005819:Genetic Markers / Q000235:genetics; D020022:Genetic Predisposition to Disease / Q000235:genetics; D015894:Genome, Human / Q000235:genetics*; D006801:Humans; D009154:Mutation / Q000235:genetics; D009363:Neoplasm Proteins / Q000235:genetics*; D009369:Neoplasms / Q000453:epidemiology / Q000235:genetics*; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*
chemical_list: D000596:Amino Acids; D014408:Biomarkers, Tumor; D005819:Genetic Markers; D009363:Neoplasm Proteins