title: DISIS: prediction of drug response through an iterative sure independence screening.
abstract: Prediction of drug response based on genomic alterations is an important task in the research of personalized medicine. Current elastic net model utilized a sure independence screening to select relevant genomic features with drug response, but it may neglect the combination effect of some marginally weak features. In this work, we applied an iterative sure independence screening scheme to select drug response relevant features from the Cancer Cell Line Encyclopedia (CCLE) dataset. For each drug in CCLE, we selected up to 40 features including gene expressions, mutation and copy number alterations of cancer-related genes, and some of them are significantly strong features but showing weak marginal correlation with drug response vector. Lasso regression based on the selected features showed that our prediction accuracies are higher than those by elastic net regression for most drugs.
authors: Department of Mathematics, Shanghai Normal University, Shanghai, China.
authors: Yun
authors: Y
authors: Fang
authors: Department of Mathematics, Shanghai Ocean University, Shanghai, China.
authors: Yufang
authors: Y
authors: Qin
authors: Department of Mathematics, Shanghai Normal University, Shanghai, China.
authors: Naiqian
authors: N
authors: Zhang
authors: Department of Mathematics, Shanghai Normal University, Shanghai, China.
authors: Jun
authors: J
authors: Wang
authors: Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, China.
authors: Haiyun
authors: H
authors: Wang
authors: Department of Mathematics, Shanghai Normal University, Shanghai, China.
authors: Xiaoqi
authors: X
authors: Zheng
mesh_terms: D000465:Algorithms; D000970:Antineoplastic Agents / Q000494:pharmacology / Q000627:therapeutic use; D045744:Cell Line, Tumor; D066264:Datasets as Topic; D019008:Drug Resistance, Neoplasm; D006801:Humans; D008962:Models, Theoretical; D009369:Neoplasms / Q000188:drug therapy / Q000235:genetics; D010597:Pharmacogenetics / Q000379:methods; D057285:Precision Medicine / Q000379:methods; D015203:Reproducibility of Results
chemical_list: D000970:Antineoplastic Agents