Pathway-Based Drug Repositioning for Cancers: Computational Prediction and Experimental Validation

Michio Iwata, Lisa Hirose, Hiroshi Kohara, Jiyuan Liao, Ryusuke Sawada, Sayaka Akiyoshi, Kenzaburo Tani, Yoshihiro Yamanishi

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)


Developing drugs with anticancer activity and low toxic side-effects at low costs is a challenging issue for cancer chemotherapy. In this work, we propose to use molecular pathways as the therapeutic targets and develop a novel computational approach for drug repositioning for cancer treatment. We analyzed chemically induced gene expression data of 1112 drugs on 66 human cell lines and searched for drugs that inactivate pathways involved in the growth of cancer cells (cell cycle) and activate pathways that contribute to the death of cancer cells (e.g., apoptosis and p53 signaling). Finally, we performed a large-scale prediction of potential anticancer effects for all the drugs and experimentally validated the prediction results via three in vitro cellular assays that evaluate cell viability, cytotoxicity, and apoptosis induction. Using this strategy, we successfully identified several potential anticancer drugs. The proposed pathway-based method has great potential to improve drug repositioning research for cancer treatment.

Original languageEnglish
Pages (from-to)9583-9595
Number of pages13
JournalJournal of Medicinal Chemistry
Issue number21
Publication statusPublished - Nov 8 2018

All Science Journal Classification (ASJC) codes

  • Molecular Medicine
  • Drug Discovery


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