title: Linking pathway gene expressions to the growth inhibition response from the National Cancer Institute's anticancer screen and drug mechanism of action.
abstract: Novel strategies are proposed to quantitatively analyze and relate biological pathways to drug responses using gene expression and small-molecule growth inhibition data (GI(50)) derived from the National Cancer Institute's 60 cancer cells (NCI(60)). We have annotated groups of drug GI(50) responses with pathways defined by the Kyoto Encyclopedia of Genes and Genomes (KEGG) and BioCarta, and functional categories defined by Gene Ontology (GO), through correlations between pathway gene expression patterns and drug GI(50) profiles. Drug-gene-pathway relationships may then be utilized to find drug targets or target-specific drugs. Significantly correlated pathways and the gene products involved represent interesting targets for further exploration, whereas drugs that are significantly correlated with only certain pathways are more likely to be target specific. Separate pathway clustering finds that pathways engaged in the same biological process tend to have similar drug correlation patterns. The biological and statistical significances of our method are established by comparison to known small-molecule inhibitor-gene target relationships reported in the literature and by standard randomization procedures. The results of our pathway, gene expression and drug-induced growth inhibition associations, can serve as a basis for proposing testable hypotheses about potential anticancer drugs, their targets, and mechanisms of action.
authors.affiliation: Developmental Therapeutics Program, Screening Technologies Branch, Laboratory of Computational Technologies, National Cancer Institute-Frederick, Frederick, MD 21702, USA.
authors.forename: R
authors.initials: R
authors.lastname: Huang
authors.forename: A
authors.initials: A
authors.lastname: Wallqvist
authors.forename: N
authors.initials: N
authors.lastname: Thanki
authors.forename: D G
authors.initials: DG
authors.lastname: Covell
mesh_terms: D000970:Antineoplastic Agents / Q000145:classification / Q000494:pharmacology*; D016208:Databases, Factual; D030541:Databases, Genetic; D019008:Drug Resistance, Neoplasm / Q000235:genetics; D004354:Drug Screening Assays, Antitumor; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods; D007928:Lethal Dose 50; D009316:National Institutes of Health (U.S.); D009369:Neoplasms / Q000235:genetics / Q000378:metabolism*; D011237:Predictive Value of Tests; D014407:Tumor Cells, Cultured / Q000187:drug effects; D014481:United States
chemical_list: D000970:Antineoplastic Agents