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dc.contributor.authorKalantarMotamedi, Yasaman
dc.contributor.authorChoi, Ran Joo
dc.contributor.authorKoh, Siang-Boon
dc.contributor.authorBramhall, Jo L
dc.contributor.authorFan, Tai-Ping
dc.contributor.authorBender, Andreas
dc.date.accessioned2021-11-23T00:30:26Z
dc.date.available2021-11-23T00:30:26Z
dc.date.issued2021-09-24
dc.identifier.issn2589-0042
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/330946
dc.description.abstractResistance to current therapies is common for pancreatic cancer and hence novel treatment options are urgently needed. In this work, we developed and validated a computational method to select synergistic compound combinations based on transcriptomic profiles from both the disease and compound side, combined with a pathway scoring system, which was then validated prospectively by testing 30 compounds (and their combinations) on PANC-1 cells. Some compounds selected as single agents showed lower GI50 values than the standard of care, gemcitabine. Compounds suggested as combination agents with standard therapy gemcitabine based on the best performing scoring system showed on average 2.82-5.18 times higher synergies compared to compounds that were predicted to be active as single agents. Examples of highly synergistic in vitro validated compound pairs include gemcitabine combined with Entinostat, thioridazine, loperamide, scriptaid and Saracatinib. Hence, the computational approach presented here was able to identify synergistic compound combinations against pancreatic cancer cells.
dc.format.mediumElectronic-eCollection
dc.languageeng
dc.publisherElsevier BV
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titlePrediction and identification of synergistic compound combinations against pancreatic cancer cells.
dc.typeArticle
prism.issueIdentifier9
prism.publicationDate2021
prism.publicationNameiScience
prism.startingPage103080
prism.volume24
dc.identifier.doi10.17863/CAM.78390
dcterms.dateAccepted2021-08-31
rioxxterms.versionofrecord10.1016/j.isci.2021.103080
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2021-09-03
dc.contributor.orcidBender, Andreas [0000-0002-6683-7546]
dc.identifier.eissn2589-0042
rioxxterms.typeJournal Article/Review


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International