Predicting selective drug targets in cancer through metabolic networks.

TitlePredicting selective drug targets in cancer through metabolic networks.
Publication TypeJournal Articles
Year of Publication2011
AuthorsFolger O, Jerby L, Frezza C, Gottlieb E, Ruppin E, Shlomi T
JournalMol Syst Biol
Date Published2011
KeywordsCell Line, Tumor, Cell Proliferation, Computational Biology, Cytostatic Agents, Down-Regulation, Drug Delivery Systems, Gene Expression Regulation, Neoplastic, HUMANS, Metabolic Networks and Pathways, Models, Biological, Neoplasms, RNA, Small Interfering

The interest in studying metabolic alterations in cancer and their potential role as novel targets for therapy has been rejuvenated in recent years. Here, we report the development of the first genome-scale network model of cancer metabolism, validated by correctly identifying genes essential for cellular proliferation in cancer cell lines. The model predicts 52 cytostatic drug targets, of which 40% are targeted by known, approved or experimental anticancer drugs, and the rest are new. It further predicts combinations of synthetic lethal drug targets, whose synergy is validated using available drug efficacy and gene expression measurements across the NCI-60 cancer cell line collection. Finally, potential selective treatments for specific cancers that depend on cancer type-specific downregulation of gene expression and somatic mutations are compiled.

Alternate JournalMol. Syst. Biol.
PubMed ID21694718
PubMed Central IDPMC3159974
Grant List / / Cancer Research UK / United Kingdom