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Discovery of therapeutic agents for prostate cancer using genome-scale metabolic modeling and drug repositioning

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dc.contributor.authorTURANLI, BESTE
dc.contributor.authorsTuranli, Beste; Zhang, Cheng; Kim, Woonghee; Benfeitas, Rui; Uhlen, Mathias; Arga, Kazim Yalcin; Mardinoglu, Adil
dc.date.accessioned2022-03-14T10:18:11Z
dc.date.available2022-03-14T10:18:11Z
dc.date.issued2019-04
dc.description.abstractBackground: Genome-scale metabolic models (GEMs) offer insights into cancer metabolism and have been used to identify potential biomarkers and drug targets. Drug repositioning is a time-and cost-effective method of drug discovery that can be applied together with GEMs for effective cancer treatment. Methods: In this study, we reconstruct a prostate cancer (PRAD)-specific GEM for exploring prostate cancer metabolism and also repurposing new therapeutic agents that can be used in development of effective cancer treatment. We integrate global gene expression profiling of cell lines with >1000 different drugs through the use of prostate cancer GEM and predict possible drug-gene interactions. Findings: We identify the key reactions with altered fluxes based on the gene expression changes and predict the potential drug effect in prostate cancer treatment. We find that sulfamethoxypyridazine, azlocillin, hydroflumethiazide, and ifenprodil can be repurposed for the treatment of prostate cancer based on an in silico cell viability assay. Finally, we validate the effect of ifenprodil using an in vitro cell assay and show its inhibitory effect on a prostate cancer cell line. Interpretation: Our approach demonstate how GEMs can be used to predict therapeutic agents for cancer treatment based on drug repositioning. Besides, it paved a way and shed a light on the applicability of computational models to real-world biomedical or pharmaceutical problems. (C) 2019 The Authors. Published by Elsevier B.V.
dc.identifier.doi10.1016/j.ebiom.2019.03.009
dc.identifier.issn2352-3964
dc.identifier.pubmed30905848
dc.identifier.urihttps://hdl.handle.net/11424/244326
dc.identifier.wosWOS:000466175100052
dc.language.isoeng
dc.publisherELSEVIER SCIENCE BV
dc.relation.ispartofEBIOMEDICINE
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectGenome-scale metabolic models
dc.subjectDrug repositioning
dc.subjectDrug repurposing
dc.subjectProstate cancer
dc.subjectApproved drugs
dc.subjectLIPID-METABOLISM
dc.subjectPERIPHERAL ZONE
dc.subjectNMDA RECEPTORS
dc.subjectEXPRESSION
dc.subjectGROWTH
dc.subjectCELLS
dc.subjectACID
dc.subjectTARGET
dc.subjectGENES
dc.titleDiscovery of therapeutic agents for prostate cancer using genome-scale metabolic modeling and drug repositioning
dc.typearticle
dspace.entity.typePublication
local.avesis.ide8362405-8fa8-40f3-a0d3-54a6565ee1e5
local.import.packageSS16
local.indexed.atWOS
local.indexed.atSCOPUS
local.indexed.atPUBMED
local.journal.numberofpages11
local.journal.quartileQ1
oaire.citation.endPage396
oaire.citation.startPage386
oaire.citation.titleEBIOMEDICINE
oaire.citation.volume42
relation.isAuthorOfPublication3e8c4f64-93ae-4b42-953c-35c8b07586b3
relation.isAuthorOfPublication.latestForDiscovery3e8c4f64-93ae-4b42-953c-35c8b07586b3

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