title: Association analysis of the perturbation of interactions in biological pathways and anticancer drug activity.
abstract: Understanding how different genomic mutational landscapes in patients with cancer lead to different responses to anticancer drugs is an important challenge for realizing precision medicine for cancer. Many studies have analyzed the comprehensive anticancer drug-response profiles and genomic profiles of cancer cell lines to identify the relationship between the anticancer drug response and genomic alternations. However, few studies have focused on interpreting these profiles with a network perspective. In this work, we analyzed genomic alterations in cancer cell lines by considering which interactions in the signaling pathway were perturbed by mutations. With our interaction-centric approach, we identified novel interaction/drug response associations for two drugs (afatinib and ixabepilone) for which no gene-centric association could be found. When we compared the performance of classifiers for predicting the responses to 164 drugs, the classifiers trained with interaction-centric features outperformed the classifiers trained with gene-centric features, despite the smaller number of features (p-value = 2.0 × 10(-3)). By incorporating the interaction information from signaling pathways, we revealed associations between genomic alterations and drug responses that could be missed when using a gene-centric approach.
authors.affiliation: Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea; Department of Convergence Technology Research, Korea Institute of Science and Technology Information, Daejeon, Republic of Korea.
authors.forename: Junehawk
authors.initials: J
authors.lastname: Lee
authors.affiliation: Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea; Bio-Synergy Research Center, Daejeon, Republic of Korea. Electronic address: dhlee@kaist.ac.kr.
authors.forename: Doheon
authors.initials: D
authors.lastname: Lee
mesh_terms: D003198:Computer Simulation; D056726:Genetic Association Studies / Q000379:methods; D006801:Humans; D008957:Models, Genetic; D009154:Mutation / Q000235:genetics; D009363:Neoplasm Proteins / Q000235:genetics*; D009369:Neoplasms / Q000188:drug therapy* / Q000235:genetics*; D010597:Pharmacogenetics / Q000379:methods; D057285:Precision Medicine / Q000379:methods*; D025941:Protein Interaction Mapping / Q000379:methods; D015398:Signal Transduction / Q000187:drug effects / Q000235:genetics*; D016896:Treatment Outcome
chemical_list: D009363:Neoplasm Proteins
keywords: Domain–domain interaction; Drug response prediction; Precision medicine; Signaling pathway