Interpretable prediction of drug-cell line response by triple matrix factorization

作     者：Xiao-Ying Yan Shao-Wu Zhang Siu-Ming Yiu Jian-Yu Shi Xiao-Ying Yan;Shao-Wu Zhang;Siu-Ming Yiu;Jian-Yu Shi

作者机构：Key Laboratory of Information Fusion Technology of Ministry of EducationSchool of AutomationNorthwestern Polytechnical UniversityXi'an 710072China College of Computer ScienceXi’an Shiyou UniversityXi’an 710065China Department of Computer ScienceThe University of Hong KongHong Kong 999077China School of Life SciencesNorthwestern Polytechnical UniversityXi’an 710072China 

出 版 物：《Quantitative Biology》 (定量生物学（英文版）)

年 卷 期：2021年第9卷第4期

页      面：426-439页

核心收录：

学科分类：1007[医学-药学(可授医学、理学学位)] 1006[医学-中西医结合] 100706[医学-药理学] 100602[医学-中西医结合临床] 10[医学] 

基　　金：supported by the National Natural Science Foundation of China(Nos.61872297 61873202)as well as by Shaanxi Provincial Key R&D Program,China(No.2020KW-063) 

主　　题：drug response drug sensitivity drug resistance triple matrix factorization 

摘      要：Background:One of the challenges in personalized medicine is to determine specific drugs and their dosages for patient individuals who are undergoing a common *** technique of cell lines provides a safe approach to capture the drug responses of patient individuals when given specific drugs with varied ***,it is still costly to determine drug responses in cells w.r.t dosages by biological *** methods provide a promising screening to infer possible drug responses in the cells of patient individuals on a large ***,existing computational approaches are insufficient to interpret the underlying reason for drug ***:In this work,we propose an interpretable model for analyzing and predicting drug responses across cell *** proposed model bridges drug features(e.g.f chemical structure fingerprints),cell features(e.g.f gene expression profiles),and drug responses across cells(measured by IC50)by a triple matrix factorization(TMF),such that the underlying reason for drug responses in specific cells is possibly *** .The comparison with state-of-the-art computational approaches demonstrates the superiority of our *** importantly,a case study of drug responses in lung-related cell lines shows its interpretable ability to find out highly occurring drug substructures,crucial mutated genes,as well as significant pairs between substructures and mutated genes in terms of drug sensitivity and ***:TMF is an effective and interpretable approach for predicting cell lines responses to drugs,and can dig out crucial pairs of chemical substructures and genes,which uncovers the underlying reason for drug responses in specific cells.