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dc.contributor.authorRoss-Adams, H.
dc.contributor.authorLamb, A. D.
dc.contributor.authorDunning, M. J.
dc.contributor.authorHalim, S.
dc.contributor.authorLindberg, J.
dc.contributor.authorMassie, C. M.
dc.contributor.authorEgevad, L. A.
dc.contributor.authorRussell, R.
dc.contributor.authorRamos-Montoya, A.
dc.contributor.authorVowler, S. L.
dc.contributor.authorSharma, N. L.
dc.contributor.authorKay, J.
dc.contributor.authorWhitaker, H.
dc.contributor.authorClark, J.
dc.contributor.authorHurst, R.
dc.contributor.authorGnanapragasam, V. J.
dc.contributor.authorShah, N. C.
dc.contributor.authorWarren, A. Y.
dc.contributor.authorCooper, C. S.
dc.contributor.authorLynch, A. G.
dc.contributor.authorStark, R.
dc.contributor.authorMills, I. G.
dc.contributor.authorGrönberg, H.
dc.contributor.authorNeal, D. E.
dc.contributor.authorShaw, Greg
dc.contributor.authorHori, Satoshi
dc.contributor.authorBaridi, Ajoeb
dc.contributor.authorTran, Maxine
dc.contributor.authorWadhwa, Karan
dc.contributor.authorNelson, Adam
dc.contributor.authorPatel, Keval
dc.contributor.authorThomas, Benjamin
dc.contributor.authorLuxton, Hayley
dc.contributor.authorGnanpragasam, Vincent
dc.contributor.authorDoble, Andrew
dc.contributor.authorKastner, Christof
dc.contributor.authorAho, Tevita
dc.contributor.authorHaynes, Beverley
dc.contributor.authorPartridge, Wendy
dc.contributor.authorCromwell, Elizabeth
dc.contributor.authorSangrasi, Asif
dc.contributor.authorBurge, Jo
dc.contributor.authorGeorge, Anne
dc.contributor.authorStearn, Sara
dc.contributor.authorCorcoran, Marie
dc.contributor.authorCoret, Hansley
dc.contributor.authorBasnett, Gillian
dc.contributor.authorFrancis, Indu
dc.contributor.authorWhitington, Thomas
dc.contributor.authorYuan, Yinyin
dc.contributor.authorCamCaP Study Group
dc.identifier.citationRoss-Adams , H , Lamb , A D , Dunning , M J , Halim , S , Lindberg , J , Massie , C M , Egevad , L A , Russell , R , Ramos-Montoya , A , Vowler , S L , Sharma , N L , Kay , J , Whitaker , H , Clark , J , Hurst , R , Gnanapragasam , V J , Shah , N C , Warren , A Y , Cooper , C S , Lynch , A G , Stark , R , Mills , I G , Grönberg , H , Neal , D E , Shaw , G , Hori , S , Baridi , A , Tran , M , Wadhwa , K , Nelson , A , Patel , K , Thomas , B , Luxton , H , Gnanpragasam , V , Doble , A , Kastner , C , Aho , T , Haynes , B , Partridge , W , Cromwell , E , Sangrasi , A , Burge , J , George , A , Stearn , S , Corcoran , M , Coret , H , Basnett , G , Francis , I , Whitington , T , Yuan , Y & CamCaP Study Group 2015 , ' Integration of copy number and transcriptomics provides risk stratification in prostate cancer : a discovery and validation cohort study ' , EBioMedicine , vol. 2 , no. 9 , pp. 1133-1144 .
dc.identifier.otherORCID: /0000-0002-7876-7338/work/35946872
dc.descriptionStudy data are deposited in NCBI GEO (unique identifier number GSE70770).en
dc.description.abstractBackground : Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome. Methods : In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behaviour, and compared with either CNA or transcriptomics alone. Findings : We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 103 men. These subgroups were able to consistently predict biochemical relapse (p = 0.0017 and p = 0.016 respectively) and were further validated in a third cohort with long-term follow-up (p = 0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer ( MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p = 0.0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions. Interpretation : For the first time in prostate cancer this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to the generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts.
dc.subjectBiochemical relapseen
dc.subjectGene signatureen
dc.subjectPersonalised medicineen
dc.subjectProstate canceren
dc.subjectRisk stratificationen
dc.subjectRC0254 Neoplasms. Tumors. Oncology (including Cancer)en
dc.subjectQH301 Biologyen
dc.subjectQH426 Geneticsen
dc.subjectBiochemistry, Genetics and Molecular Biology(all)en
dc.subjectSDG 3 - Good Health and Well-beingen
dc.titleIntegration of copy number and transcriptomics provides risk stratification in prostate cancer : a discovery and validation cohort studyen
dc.typeJournal articleen
dc.contributor.institutionUniversity of St Andrews. School of Medicineen
dc.contributor.institutionUniversity of St Andrews. Statisticsen
dc.description.statusPeer revieweden

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