The application of established drug compounds to novel therapeutic indications, known as drug repositioning, offers several advantages over traditional drug development, including reduced development costs and shorter paths to approval. Recent approaches to drug repositioning employ high-throughput experimental approaches to assess a compound’s potential therapeutic qualities. Here we present a systematic computational approach to predict novel therapeutic indications based on comprehensive testing of molecular signatures in drug-disease pairs. We integrated gene expression measurements from 100 diseases and gene expression measurements on 164 drug compounds yielding predicted therapeutic potentials for these drugs. We demonstrate the ability to recover many known drug and disease relationships using computationally derived therapeutic potentials, and also predict many new indications for these drugs. We experimentally validated a prediction for the anti-ulcer drug cimetidine as a candidate therapeutic in the treatment of lung adenocarcinoma, and demonstrate both in vitro and in vivo using mouse xenograft models. This novel computational method provides a novel and systematic approach to reposition established drugs to treat a wide range of human diseases.
Summary In the nervous system, neural stem cells (NSC) are necessary for the generation of new neurons and for cognitive function. Here we show that FoxO3, a member of a transcription factor family known to extend lifespan in invertebrates, regulates the NSC pool. We find that adult FoxO3−/− mice have fewer NSC in vivo than wild type counterparts. NSC isolated from adult FoxO3−/− mice have decreased self-renewal and an impaired ability to generate different neural lineages. Identification of the FoxO3-dependent gene expression profile in NSC suggests that FoxO3 regulates the NSC pool by inducing a program of genes that preserves quiescence, prevents premature differentiation, and controls oxygen metabolism. The ability of FoxO3 to prevent the premature depletion of NSC might have important implications for counteracting brain aging in long-lived species.
Inflammatory Bowel Disease (IBD) is a chronic inflammatory disorder of the gastrointestinal tract for which there are few safe and effective therapeutic options for long-term treatment and disease maintenance. In this study, we applied a computational approach to discover novel drug therapies for IBD in silico using publicly available molecular data measuring gene expression in IBD samples and 164 small-molecule drug compounds. Among the top compounds predicted to be therapeutic for IBD by our approach were prednisolone, a corticosteroid known to treat IBD, and topiramate, an anticonvulsant drug not previously described to demonstrate efficacy for IBD or any related disorders of inflammation or the gastrointestinal tract. We experimentally validated our topiramate prediction in vivo using a trinitrobenzenesulfonic acid (TNBS) induced rodent model of IBD. The experimental results demonstrate that oral administration of topiramate is able to significantly reduce gross pathological signs and microscopic damage in primary affected colon tissue in a TNBS-induced rodent model of IBD. These finding suggest that topiramate might serve as a novel therapeutic option for IBD in humans, and support the use of public molecular data and computational approaches to discover novel therapeutic options for IBD.
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