Document Detail


Drug repositioning framework by incorporating functional information.
MedLine Citation:
PMID:  24067419     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
As a shortcut for drug development, drug repositioning draws more and more attention in pharmaceutical industry to identify new indications for marketed drugs or drugs failed in late clinical trial phase. At the same time, the abundant high-throughput data pushes the computationally repositioning drugs a hot topic in the area of systems biology. Here, the authors propose a general framework for repositioning drug by incorporating various functional information. The framework starts with the identification of differentially expressed gene sets under disease state and drug treatment. Then the disease and drug are associated by the overlap of these two gene sets via biological function. The authors provide two strategies to assess the functional overlap. In the first strategy, functional relevance are evaluated by leveraging genes' lethality information to reveal drug's potential of curing diseases. In the second strategy, biological process perturbation profiles are identified by mapping differentially expressed genes into pathways and gene ontology (GO) terms. Their associations are assessed and used to rank drugs' potential of curing diseases. The preliminary results on prostate cancer demonstrate that our new framework improves the drug repositioning efficiency and various function information could complement each other. Importantly, the new framework will enhance the biological interpretation and rationale of drug repositioning and provide insights into drug action mechanisms.
Authors:
Zikai Wu; Yong Wang; Luonan Chen
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  IET systems biology     Volume:  7     ISSN:  1751-8849     ISO Abbreviation:  IET Syst Biol     Publication Date:  2013 Oct 
Date Detail:
Created Date:  2013-09-26     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101301198     Medline TA:  IET Syst Biol     Country:  England    
Other Details:
Languages:  eng     Pagination:  188-94     Citation Subset:  IM    
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