title: Understanding Genotype-Phenotype Effects in Cancer via Network Approaches.
abstract: Cancer is now increasingly studied from the perspective of dysregulated pathways, rather than as a disease resulting from mutations of individual genes. A pathway-centric view acknowledges the heterogeneity between genomic profiles from different cancer patients while assuming that the mutated genes are likely to belong to the same pathway and cause similar disease phenotypes. Indeed, network-centric approaches have proven to be helpful for finding genotypic causes of diseases, classifying disease subtypes, and identifying drug targets. In this review, we discuss how networks can be used to help understand patient-to-patient variations and how one can leverage this variability to elucidate interactions between cancer drivers.
authors.affiliation: National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, United States of America.
authors.forename: Yoo-Ah
authors.initials: YA
authors.lastname: Kim
authors.affiliation: National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, United States of America.
authors.forename: Dong-Yeon
authors.initials: DY
authors.lastname: Cho
authors.affiliation: National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, United States of America.
authors.forename: Teresa M
authors.initials: TM
authors.lastname: Przytycka
mesh_terms: D000818:Animals; D003198:Computer Simulation; D020022:Genetic Predisposition to Disease / Q000235:genetics; D005838:Genotype; D006801:Humans; D008954:Models, Biological; D009363:Neoplasm Proteins / Q000235:genetics* / Q000378:metabolism*; D009369:Neoplasms / Q000503:physiopathology*; D010641:Phenotype; D025941:Protein Interaction Mapping / Q000379:methods*; D015398:Signal Transduction
chemical_list: D009363:Neoplasm Proteins