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dc.contributor.authorSeed, G
dc.contributor.authorYuan, W
dc.contributor.authorMateo, J
dc.contributor.authorCarreira, S
dc.contributor.authorBertan, C
dc.contributor.authorLambros, M
dc.contributor.authorBoysen, G
dc.contributor.authorFerraldeschi, R
dc.contributor.authorMiranda, S
dc.contributor.authorFigueiredo, I
dc.contributor.authorRiisnaes, R
dc.contributor.authorCrespo, M
dc.contributor.authorRodrigues, DN
dc.contributor.authorTalevich, E
dc.contributor.authorRobinson, DR
dc.contributor.authorKunju, LP
dc.contributor.authorWu, Y-M
dc.contributor.authorLonigro, R
dc.contributor.authorSandhu, S
dc.contributor.authorChinnaiyan, AM
dc.contributor.authorde Bono, JS
dc.date.accessioned2017-08-14T13:45:35Z
dc.date.issued2017-10-15
dc.identifier.citationClinical cancer research : an official journal of the American Association for Cancer Research, 2017, 23 (20), pp. 6070 - 6077
dc.identifier.issn1078-0432
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/772
dc.identifier.eissn1557-3265
dc.identifier.doi10.1158/1078-0432.ccr-17-0972
dc.description.abstractPurpose: Precise detection of copy number aberrations (CNA) from tumor biopsies is critically important to the treatment of metastatic prostate cancer. The use of targeted panel next-generation sequencing (NGS) is inexpensive, high throughput, and easily feasible, allowing single-nucleotide variant calls, but CNA estimation from this remains challenging.Experimental Design: We evaluated CNVkit for CNA identification from amplicon-based targeted NGS in a cohort of 110 fresh castration-resistant prostate cancer biopsies and used capture-based whole-exome sequencing (WES), array comparative genomic hybridization (aCGH), and FISH to explore the viability of this approach.Results: We showed that this method produced highly reproducible CNA results (r = 0.92), with the use of pooled germline DNA as a coverage reference supporting precise CNA estimation. CNA estimates from targeted NGS were comparable with WES (r = 0.86) and aCGH (r = 0.7); for key selected genes (BRCA2, MYC, PIK3CA, PTEN, and RB1), CNA estimation correlated well with WES (r = 0.91) and aCGH (r = 0.84) results. The frequency of CNAs in our population was comparable with that previously described (i.e., deep deletions: BRCA2 4.5%; RB1 8.2%; PTEN 15.5%; amplification: AR 45.5%; gain: MYC 31.8%). We also showed, utilizing FISH, that CNA estimation can be impacted by intratumor heterogeneity and demonstrated that tumor microdissection allows NGS to provide more precise CNA estimates.Conclusions: Targeted NGS and CNVkit-based analyses provide a robust, precise, high-throughput, and cost-effective method for CNA estimation for the delivery of more precise patient care. Clin Cancer Res; 23(20); 6070-7. ©2017 AACR.
dc.formatPrint-Electronic
dc.format.extent6070 - 6077
dc.languageeng
dc.language.isoeng
dc.publisherAMER ASSOC CANCER RESEARCH
dc.rights.urihttps://www.rioxx.net/licenses/all-rights-reserved
dc.subjectHumans
dc.subjectProstatic Neoplasms
dc.subjectBRCA2 Protein
dc.subjectBiopsy
dc.subjectReproducibility of Results
dc.subjectComputational Biology
dc.subjectGenetic Heterogeneity
dc.subjectMale
dc.subjectComparative Genomic Hybridization
dc.subjectDNA Copy Number Variations
dc.subjectHigh-Throughput Nucleotide Sequencing
dc.subjectBiomarkers, Tumor
dc.subjectWhole Exome Sequencing
dc.titleGene Copy Number Estimation from Targeted Next-Generation Sequencing of Prostate Cancer Biopsies: Analytic Validation and Clinical Qualification.
dc.typeJournal Article
dcterms.dateAccepted2017-07-19
rioxxterms.funderThe Institute of Cancer Research
rioxxterms.identifier.projectUnspecified
rioxxterms.versionofrecord10.1158/1078-0432.ccr-17-0972
rioxxterms.licenseref.urihttps://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2017-10
rioxxterms.typeJournal Article/Review
dc.relation.isPartOfClinical cancer research : an official journal of the American Association for Cancer Research
pubs.issue20
pubs.notes12 months
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/Cancer Biomarkers
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Clinical Studies
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Clinical Studies/Cancer Biomarkers
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Clinical Studies/Prostate Cancer Targeted Therapy Group
pubs.organisational-group/ICR/Students
pubs.organisational-group/ICR/Students/PhD and MPhil
pubs.organisational-group/ICR/Students/PhD and MPhil/16/17 Starting Cohort
pubs.organisational-group/ICR/Students/PhD and MPhil/18/19 Starting Cohort
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/Cancer Biomarkers
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Clinical Studies
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Clinical Studies/Cancer Biomarkers
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Clinical Studies/Prostate Cancer Targeted Therapy Group
pubs.organisational-group/ICR/Students
pubs.organisational-group/ICR/Students/PhD and MPhil
pubs.organisational-group/ICR/Students/PhD and MPhil/16/17 Starting Cohort
pubs.organisational-group/ICR/Students/PhD and MPhil/18/19 Starting Cohort
pubs.publication-statusPublished
pubs.volume23
pubs.embargo.terms12 months
icr.researchteamCancer Biomarkers
icr.researchteamProstate Cancer Targeted Therapy Group
dc.contributor.icrauthorSeed, George
dc.contributor.icrauthorCarreira, Suzanne
dc.contributor.icrauthorMiranda, Susana
dc.contributor.icrauthorDe Bono, Johann


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