title: A systematic study on drug-response associated genes using baseline gene expressions of the Cancer Cell Line Encyclopedia.
abstract: We have studied drug-response associated (DRA) gene expressions by applying a systems biology framework to the Cancer Cell Line Encyclopedia data. More than 4,000 genes are inferred to be DRA for at least one drug, while the number of DRA genes for each drug varies dramatically from almost 0 to 1,226. Functional enrichment analysis shows that the DRA genes are significantly enriched in genes associated with cell cycle and plasma membrane. Moreover, there might be two patterns of DRA genes between genders. There are significantly shared DRA genes between male and female for most drugs, while very little DRA genes tend to be shared between the two genders for a few drugs targeting sex-specific cancers (e.g., PD-0332991 for breast cancer and ovarian cancer). Our analyses also show substantial difference for DRA genes between young and old samples, suggesting the necessity of considering the age effects for personalized medicine in cancers. Lastly, differential module and key driver analyses confirm cell cycle related modules as top differential ones for drug sensitivity. The analyses also reveal the role of TSPO, TP53, and many other immune or cell cycle related genes as important key drivers for DRA network modules. These key drivers provide new drug targets to improve the sensitivity of cancer therapy.
authors.affiliation: Department of Mathematics, Shanghai Normal University, Shanghai 200234, P. R. China.
authors.forename: Xiaoming
authors.initials: X
authors.lastname: Liu
authors.affiliation: Department of Civil and Environmental Engineering, National University of Singapore, Singapore 117576, Singapore.
authors.forename: Jiasheng
authors.initials: J
authors.lastname: Yang
authors.affiliation: Department of Mathematics, Hebei University of Science and Technology, Shijiazhuang, Hebei 050018, P. R. China.
authors.forename: Yi
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: Department of Mathematics, Shanghai Normal University, Shanghai 200234, P. R. China.
authors.forename: Yun
authors.initials: Y
authors.lastname: Fang
authors.affiliation: Department of Mathematics, Shanghai Normal University, Shanghai 200234, P. R. China.
authors.forename: Fayou
authors.initials: F
authors.lastname: Wang
authors.affiliation: Department of Mathematics, Shanghai Normal University, Shanghai 200234, P. R. China.
authors.forename: Jun
authors.initials: J
authors.lastname: Wang
authors.affiliation: Department of Mathematics, Shanghai Normal University, Shanghai 200234, P. R. China.
authors.forename: Xiaoqi
authors.initials: X
authors.lastname: Zheng
authors.affiliation: Department of Mathematics, Hebei University of Science and Technology, Shijiazhuang, Hebei 050018, P. R. China.|Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
authors.forename: Jialiang
authors.initials: J
authors.lastname: Yang
mesh_terms: D000367:Age Factors; D000970:Antineoplastic Agents / Q000737:chemistry* / Q000494:pharmacology; D054316:Biomarkers, Pharmacological / Q000737:chemistry; D002453:Cell Cycle / Q000235:genetics; D045744:Cell Line, Tumor; D019008:Drug Resistance, Neoplasm / Q000235:genetics; D005260:Female; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D006801:Humans; D008297:Male; D009369:Neoplasms / Q000188:drug therapy / Q000235:genetics*; D012737:Sex Factors; D049490:Systems Biology
chemical_list: D000970:Antineoplastic Agents; D054316:Biomarkers, Pharmacological