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dc.contributor.authorKinnersley, B
dc.contributor.authorSud, A
dc.contributor.authorCoker, EA
dc.contributor.authorTym, JE
dc.contributor.authorDi Micco, P
dc.contributor.authorAl-Lazikani, B
dc.contributor.authorHoulston, RS
dc.date.accessioned2018-09-13T10:55:32Z
dc.date.issued2018-11-21
dc.identifier.citationJCO clinical cancer informatics, 2018, 2 pp. 1 - 11
dc.identifier.issn2473-4276
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/2682
dc.identifier.eissn2473-4276
dc.identifier.doi10.1200/cci.18.00077
dc.description.abstractPURPOSE: The high attrition rate of cancer drug development programs is a barrier to realizing the promise of precision oncology. We have examined whether the genetic insights from genome-wide association studies of cancer can guide drug development and repurposing in oncology. MATERIALS AND METHODS: Across 37 cancers, we identified 955 genetic risk variants from the National Human Genome Research Institute-European Bioinformatics Institute genome-wide association study catalog. We linked these variants to target genes using strategies that were based on linkage disequilibrium, DNA three-dimensional structure, and integration of predicted gene function and expression. With the use of the Informa Pharmaprojects database, we identified genes that are targets of unique drugs and assessed the level of enrichment that would be afforded by incorporation of genetic information in preclinical and phase II studies. For targets not under development, we implemented machine learning approaches to assess druggability. RESULTS: For all preclinical targets incorporating genetic information, a 2.00-fold enrichment of a drug being successfully approved could be achieved (95% CI, 1.14- to 3.48-fold; P = .02). For phase II targets, a 2.75-fold enrichment could be achieved (95% CI, 1.42- to 5.35-fold; P < .001). Application of genetic information suggests potential repurposing of 15 approved nononcology drugs. CONCLUSION: The findings illustrate the value of using insights from the genetics of inherited cancer susceptibility discovery projects as part of a data-driven strategy to inform drug discovery. Support for cancer germline genetic information for prospective targets is available online from the Institute of Cancer Research.
dc.formatPrint
dc.format.extent1 - 11
dc.languageeng
dc.language.isoeng
dc.publisherAMER SOC CLINICAL ONCOLOGY
dc.rights.urihttps://creativecommons.org/licenses/by/4.0
dc.subjectHumans
dc.subjectNeoplasms
dc.subjectGenetic Predisposition to Disease
dc.subjectDrug Development
dc.titleLeveraging Human Genetics to Guide Cancer Drug Development.
dc.typeJournal Article
dcterms.dateAccepted2018-09-11
rioxxterms.versionofrecord10.1200/cci.18.00077
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0
rioxxterms.licenseref.startdate2018-12
rioxxterms.typeJournal Article/Review
dc.relation.isPartOfJCO clinical cancer informatics
pubs.notesNot known
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Cancer Therapeutics
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Cancer Therapeutics/Computational Biology and Chemogenomics
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Genetics and Epidemiology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Genetics and Epidemiology/Cancer Genomics
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Cancer Therapeutics
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Cancer Therapeutics/Computational Biology and Chemogenomics
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Genetics and Epidemiology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Genetics and Epidemiology/Cancer Genomics
pubs.publication-statusPublished
pubs.volume2
pubs.embargo.termsNot known
icr.researchteamComputational Biology and Chemogenomics
icr.researchteamCancer Genomics
dc.contributor.icrauthorKinnersley, Benjamin
dc.contributor.icrauthorSud, Amit
dc.contributor.icrauthorAl-Lazikani, Bissan
dc.contributor.icrauthorHoulston, Richard


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