title: Prediction of dynamical drug sensitivity and resistance by module network rewiring-analysis based on transcriptional profiling.
abstract: Revealing functional reorganization or module rewiring between modules at network levels during drug treatment is important to systematically understand therapies and drug responses. The present article proposed a novel model of module network rewiring to characterize functional reorganization of a complex biological system, and described a new framework named as module network rewiring-analysis (MNR) for systematically studying dynamical drug sensitivity and resistance during drug treatment. MNR was used to investigate functional reorganization or rewiring on the module network, rather than molecular network or individual molecules. Our experiments on expression data of patients with Hepatitis C virus infection receiving Interferon therapy demonstrated that consistent module genes derived by MNR could be directly used to reveal new genotypes relevant to drug sensitivity, unlike the other differential analyses of gene expressions. Our results showed that functional connections and reconnections among consistent modules bridged by biological paths were necessary for achieving effective responses of a drug. The hierarchical structures of the temporal module network can be considered as spatio-temporal biomarkers to monitor the efficacy, efficiency, toxicity, and resistance of the therapy. Our study indicates that MNR is a useful tool to identify module biomarkers and further predict dynamical drug sensitivity and resistance, characterize complex dynamic processes for therapy response, and provide biologically systematic clues for pharmacogenomic applications.
authors.affiliation: Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.
authors.forename: Tao
authors.initials: T
authors.lastname: Zeng
authors.affiliation: Department of Medicine, Royal Berkshire Hospital, Reading, UK.
authors.forename: Diane Catherine
authors.initials: DC
authors.lastname: Wang
authors.affiliation: Fudan University Center for Clinical Bioinformatics, Zhongshan Hospital, Fudan University Shanghai School of Medicine, China. Electronic address: xiangdong.wang@clintransmed.org.
authors.forename: Xiangdong
authors.initials: X
authors.lastname: Wang
authors.affiliation: Department of Infectious Diseases, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China. Electronic address: xufeng99@yahoo.com.
authors.forename: Feng
authors.initials: F
authors.lastname: Xu
authors.affiliation: Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China; Institute of Industrial Science, University of Tokyo, Tokyo 153-8505, Japan. Electronic address: lnchen@sibs.ac.cn.
authors.forename: Luonan
authors.initials: L
authors.lastname: Chen
mesh_terms: D000890:Anti-Infective Agents / Q000009:adverse effects* / Q000493:pharmacokinetics / Q000627:therapeutic use; D015415:Biomarkers / Q000378:metabolism; D001711:Biotransformation; D004342:Drug Hypersensitivity / Q000378:metabolism* / Q000517:prevention & control; D004352:Drug Resistance, Microbial; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation / Q000187:drug effects*; D006801:Humans; D007239:Infections / Q000188:drug therapy* / Q000378:metabolism / Q000382:microbiology; D008954:Models, Biological; D010597:Pharmacogenetics / Q000379:methods / Q000639:trends; D049490:Systems Biology / Q000379:methods* / Q000639:trends
chemical_list: D000890:Anti-Infective Agents; D015415:Biomarkers
keywords: Bioinformatics; Drug sensitivity; Network; Resistance; Systems biology