Comprehensive anticancer drug response prediction based on a simple cell line-drug complex network model

BMC Bioinformatics

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[1] 0000 0000 8954 0417, grid.413012.5, School of Science, Yanshan University, 066004, Qinhuangdao, China;0000 0001 0701 1077, grid.412531.0, Department of Mathematics, Shanghai Normal University, 200234, Shanghai, China;

关键词: Anticancer drug response;    Cell line-drug complex network;    Computational prediction model;    Cell line;    Precision medicine;   

DOI  :  10.1186/s12859-019-2608-9

来源: publisher

【 摘 要 】

BackgroundAccurate prediction of anticancer drug responses in cell lines is a crucial step to accomplish the precision medicine in oncology. Although many popular computational models have been proposed towards this non-trivial issue, there is still room for improving the prediction performance by combining multiple types of genome-wide molecular data.ResultsWe first demonstrated an observation on the CCLE and GDSC datasets, i.e., genetically similar cell lines always exhibit higher response correlations to structurally related drugs. Based on this observation we built a cell line-drug complex network model, named CDCN model. It captures different contributions of all available cell line-drug responses through cell line similarities and drug similarities. We executed anticancer drug response prediction on CCLE and GDSC independently. The result is significantly superior to that of some existing studies. More importantly, our model could predict the response of new drug to new cell line with considerable performance. We also divided all possible cell lines into “sensitive” and “resistant” groups by their response values to a given drug, the prediction accuracy, sensitivity, specificity and goodness of fit are also very promising.ConclusionCDCN model is a comprehensive tool to predict anticancer drug responses. Compared with existing methods, it is able to provide more satisfactory prediction results with less computational consumption.

【 授权许可】

CC BY