title: Context-specific functional module based drug efficacy prediction.
abstract: BACKGROUND
  It is necessary to evaluate the efficacy of individual drugs on patients to realize personalized medicine. Testing drugs on patients in clinical trial is the only way to evaluate the efficacy of drugs. The approach is labour intensive and requires overwhelming costs and a number of experiments. Therefore, preclinical model system has been intensively investigated for predicting the efficacy of drugs. Current computational drug sensitivity prediction approaches use general biological network modules as their prediction features. Therefore, they miss indirect effectors or the effects from tissue-specific interactions.
  
  
  RESULTS
  We developed cell line specific functional modules. Enriched scores of functional modules are utilized as cell line specific features to predict the efficacy of drugs. Cell line specific functional modules are clusters of genes, which have similar biological functions in cell line specific networks. We used linear regression for drug efficacy prediction. We assessed the prediction performance in leave-one-out cross-validation (LOOCV). Our method was compared with elastic net model, which is a popular model for drug efficacy prediction. In addition, we analysed drug sensitivity-associated functions of five drugs - lapatinib, erlotinib, raloxifene, tamoxifen and gefitinib- by our model.
  
  
  CONCLUSIONS
  Our model can provide cell line specific drug efficacy prediction and also provide functions which are associated with drug sensitivity. Therefore, we could utilize drug sensitivity associated functions for drug repositioning or for suggesting secondary drugs for overcoming drug resistance.
authors.affiliation: Department of Bio and Brain Engineering, 291 Daehak-ro, Yuseong-gu, Daejeon, Republic of Korea.|Bio-Synergy Research Center, 291 Daehak-ro, Yuseong-gu, Daejeon, Republic of Korea.
authors.forename: Woochang
authors.initials: W
authors.lastname: Hwang
authors.affiliation: Department of Bio and Brain Engineering, 291 Daehak-ro, Yuseong-gu, Daejeon, Republic of Korea.
authors.forename: Jaejoon
authors.initials: J
authors.lastname: Choi
authors.affiliation: Department of Bio and Brain Engineering, 291 Daehak-ro, Yuseong-gu, Daejeon, Republic of Korea.
authors.forename: Mijin
authors.initials: M
authors.lastname: Kwon
authors.affiliation: Department of Bio and Brain Engineering, 291 Daehak-ro, Yuseong-gu, Daejeon, Republic of Korea. dhlee@kaist.ac.kr.|Bio-Synergy Research Center, 291 Daehak-ro, Yuseong-gu, Daejeon, Republic of Korea. dhlee@kaist.ac.kr.
authors.forename: Doheon
authors.initials: D
authors.lastname: Lee
mesh_terms: D002460:Cell Line; D004353:Drug Evaluation, Preclinical; D058492:Drug Repositioning; D004358:Drug Therapy; D006801:Humans; D016014:Linear Models; D008954:Models, Biological; D057285:Precision Medicine / Q000379:methods*