A Network Flow-Based Method to Predict Anticancer Drug Sensitivity |
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| Authors: | Yufang Qin Ming Chen Haiyun Wang Xiaoqi Zheng |
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| Institution: | 1College of Information Technology, Shanghai Ocean University, Shanghai, China;2Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, China;3Department of Mathematics, Shanghai Normal University, Shanghai, China;Southern Illinois University School of Medicine, UNITED STATES |
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| Abstract: | Predicting anticancer drug sensitivity can enhance the ability to individualize patient treatment, thus making development of cancer therapies more effective and safe. In this paper, we present a new network flow-based method, which utilizes the topological structure of pathways, for predicting anticancer drug sensitivities. Mutations and copy number alterations of cancer-related genes are assumed to change the pathway activity, and pathway activity difference before and after drug treatment is used as a measure of drug response. In our model, Contributions from different genetic alterations are considered as free parameters, which are optimized by the drug response data from the Cancer Genome Project (CGP). 10-fold cross validation on CGP data set showed that our model achieved comparable prediction results with existing elastic net model using much less input features. |
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