Journal
SCIENCE TRANSLATIONAL MEDICINE
Volume 3, Issue 96, Pages -Publisher
AMER ASSOC ADVANCEMENT SCIENCE
DOI: 10.1126/scitranslmed.3001318
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Funding
- Lucile Packard Foundation for Children's Health
- Hewlett Packard Foundation
- National Institute of General Medical Sciences [R01 GM079719]
- National Cancer Institute [R01 CA138256]
- National Library of Medicine [T15 LM007033]
- Howard Hughes Medical Institute
- Pharmaceutical Research and Manufacturers of America Foundation
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The application of established drug compounds to new 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 use high-throughput experimental approaches to assess a compound's potential therapeutic qualities. Here, we present a systematic computational approach to predict novel therapeutic indications on the basis of 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 recovered many known drug and disease relationships using computationally derived therapeutic potentials and also predict many new indications for these 164 drugs. We experimentally validated a prediction for the antiulcer drug cimetidine as a candidate therapeutic in the treatment of lung adenocarcinoma, and demonstrate its efficacy both in vitro and in vivo using mouse xenograft models. This computational method provides a systematic approach for repositioning established drugs to treat a wide range of human diseases.
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