Prediction of cancer patients response to therapeutic agent is important for personalized treatment. Because experimental verification of reactions between large cohort of patients and drugs is time-intensive, expensive and impractical, preclinical prediction model based on large-scale pharmacogenomic of cancer cell line is highly expected. However, most of the existing computational studies are primarily based on genomic profiles of cancer cell lines while ignoring relationships among genes and failing to capture functional similarity of cell lines.