Impact of drug discovery on stem cell biology

Despite the rapid technical progress in pharmaceutical industry in the past decade, it is still a great challenge to find new drugs and the situation seems more and more serious. However, the history of pharmaceutical industry clearly indicated that the significance of drug discovery went far beyond providing new drugs. For instance, drugs or candidates could be used as selective probes to reveal novel cellular mechanisms, which is a fundamental tenet of chemical biology. More interestingly, accumulating evidence indicates that drugs and candidates can find important use in stem cell biology. Not only approved drugs but also undeveloped pharmacological agents could serve as efficient agents to regulate stem cell fate. Moreover, the target and activity knowledge accumulated during the drug discovery process will help select the stem cell fate modulators in a rational manner. As the progress in stem cell biology will bring positive influence to drug discovery, it can be expected that the current drug discovery efforts will finally bear great fruits in the future.     

Functional Module Connectivity Map (FMCM): A Framework for Searching Repurposed Drug Compounds for Systems Treatment of Cancer and an Application to Colorectal Adenocarcinoma

Drug repurposing has become an increasingly attractive approach to drug development owing to the ever-growing cost of new drug discovery and frequent withdrawal of successful drugs caused by side effect issues. Here, we devised Functional Module Connectivity Map (FMCM) for the discovery of repurposed drug compounds for systems treatment of complex diseases, and applied it to colorectal adenocarcinoma. FMCM used multiple functional gene modules to query the Connectivity Map (CMap). The functional modules were built around hub genes identified, through a gene selection by trend-of-disease-progression (GSToP) procedure, from condition-specific gene-gene interaction networks constructed from sets of cohort gene expression microarrays. The candidate drug compounds were restricted to drugs exhibiting predicted minimal intracellular harmful side effects. We tested FMCM against the common practice of selecting drugs using a genomic signature represented by a single set of individual genes to query CMap (IGCM), and found FMCM to have higher robustness, accuracy, specificity, and reproducibility in identifying known anti-cancer agents. Among the 46 drug candidates selected by FMCM for colorectal adenocarcinoma treatment, 65% had literature support for association with anti-cancer activities, and 60% of the drugs predicted to have harmful effects on cancer had been reported to be associated with carcinogens/immune suppressors. Compounds were formed from the selected drug candidates where in each compound the component drugs collectively were beneficial to all the functional modules while no single component drug was harmful to any of the modules. In cell viability tests, we identified four candidate drugs: GW-8510, etacrynic acid, ginkgolide A, and 6-azathymine, as having high inhibitory activities against cancer cells. Through microarray experiments we confirmed the novel functional links predicted for three candidate drugs: phenoxybenzamine (broad effects), GW-8510 (cell cycle), and imipenem (immune system). We believe FMCM can be usefully applied to repurposed drug discovery for systems treatment of other types of cancer and other complex diseases.