title: Cogena, a novel tool for co-expressed gene-set enrichment analysis, applied to drug repositioning and drug mode of action discovery.
abstract: Drug repositioning, finding new indications for existing drugs, has gained much recent attention as a potentially efficient and economical strategy for accelerating new therapies into the clinic. Although improvement in the sensitivity of computational drug repositioning methods has identified numerous credible repositioning opportunities, few have been progressed. Arguably the "black box" nature of drug action in a new indication is one of the main blocks to progression, highlighting the need for methods that inform on the broader target mechanism in the disease context.
  
  
  
  We demonstrate that the analysis of co-expressed genes may be a critical first step towards illumination of both disease pathology and mode of drug action. We achieve this using a novel framework, co-expressed gene-set enrichment analysis (cogena) for co-expression analysis of gene expression signatures and gene set enrichment analysis of co-expressed genes. The cogena framework enables simultaneous, pathway driven, disease and drug repositioning analysis. Cogena can be used to illuminate coordinated changes within disease transcriptomes and identify drugs acting mechanistically within this framework. We illustrate this using a psoriatic skin transcriptome, as an exemplar, and recover two widely used Psoriasis drugs (Methotrexate and Ciclosporin) with distinct modes of action. Cogena out-performs the results of Connectivity Map and NFFinder webservers in similar disease transcriptome analyses. Furthermore, we investigated the literature support for the other top-ranked compounds to treat psoriasis and showed how the outputs of cogena analysis can contribute new insight to support the progression of drugs into the clinic. We have made cogena freely available within Bioconductor or https://github.com/zhilongjia/cogena .
  
  
  
  In conclusion, by targeting co-expressed genes within disease transcriptomes, cogena offers novel biological insight, which can be effectively harnessed for drug discovery and repositioning, allowing the grouping and prioritisation of drug repositioning candidates on the basis of putative mode of action.
authors.affiliation: Department of Chemistry and Biology, College of Science, National University of Defense Technology, Changsha, Hunan, 410073, People's Republic of China.|William Harvey Research Institute, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK.
authors.forename: Zhilong
authors.initials: Z
authors.lastname: Jia
authors.affiliation: Hunan Key Laboratory of Medical Epigenomics, Department of Dermatology, Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, People's Republic of China.
authors.forename: Ying
authors.initials: Y
authors.lastname: Liu
authors.affiliation: College of Computer, National University of Defense Technology, Changsha, 410073, People's Republic of China.|National Laboratory for Parallel and Distributed Processing, National University of Defense Technology, Changsha, 410073, People's Republic of China.
authors.forename: Naiyang
authors.initials: N
authors.lastname: Guan
authors.affiliation: Beijing Institute of Radiation Medicine, Beijing, 100850, People's Republic of China.
authors.forename: Xiaochen
authors.initials: X
authors.lastname: Bo
authors.affiliation: College of Computer, National University of Defense Technology, Changsha, 410073, People's Republic of China. zgluo@nudt.edu.cn.|National Laboratory for Parallel and Distributed Processing, National University of Defense Technology, Changsha, 410073, People's Republic of China. zgluo@nudt.edu.cn.
authors.forename: Zhigang
authors.initials: Z
authors.lastname: Luo
authors.affiliation: William Harvey Research Institute, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK. m.r.barnes@qmul.ac.uk.
authors.forename: Michael R
authors.initials: MR
authors.lastname: Barnes
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D055808:Drug Discovery / Q000379:methods*; D058492:Drug Repositioning; D020869:Gene Expression Profiling / Q000379:methods*; D053263:Gene Regulatory Networks; D012984:Software; D064878:Web Browser; D057188:Workflow
keywords: Drug repositioning; Mode of action; Pathway analysis; Psoriasis