Show simple item record

Files in this item

Thumbnail

Item metadata

dc.contributor.authorLuca, Bogdan-Alexandru
dc.contributor.authorBrewer, Daniel S.
dc.contributor.authorEdwards, Dylan R.
dc.contributor.authorEdwards, Sandra
dc.contributor.authorWhitaker, Hayley C.
dc.contributor.authorMerson, Sue
dc.contributor.authorDennis, Nening
dc.contributor.authorCooper, Rosalin A.
dc.contributor.authorHazell, Steven
dc.contributor.authorWarren, Anne Y.
dc.contributor.authorEeles, Rosalind
dc.contributor.authorLynch, Andy G.
dc.contributor.authorRoss-Adams, Helen
dc.contributor.authorLamb, Alastair D.
dc.contributor.authorNeal, David E.
dc.contributor.authorSethia, Krishna
dc.contributor.authorMills, Robert D.
dc.contributor.authorBall, Richard Y.
dc.contributor.authorCurley, Helen
dc.contributor.authorClark, Jeremy
dc.contributor.authorMoulton, Vincent
dc.contributor.authorCooper, Colin S.
dc.date.accessioned2017-10-26T09:30:22Z
dc.date.available2017-10-26T09:30:22Z
dc.date.issued2018-12
dc.identifier250732666
dc.identifier508134e5-95e0-4ec6-b8a9-9fc00ab46e4c
dc.identifier85014514714
dc.identifier.citationLuca , B-A , Brewer , D S , Edwards , D R , Edwards , S , Whitaker , H C , Merson , S , Dennis , N , Cooper , R A , Hazell , S , Warren , A Y , Eeles , R , Lynch , A G , Ross-Adams , H , Lamb , A D , Neal , D E , Sethia , K , Mills , R D , Ball , R Y , Curley , H , Clark , J , Moulton , V & Cooper , C S 2018 , ' DESNT : a poor prognosis category of human prostate cancer ' , European Urology Focus , vol. 4 , no. 6 , pp. 842-850 . https://doi.org/10.1016/j.euf.2017.01.016en
dc.identifier.issn2405-4569
dc.identifier.otherRIS: urn:72853BB717C1FC8BD5A61B76021F7F36
dc.identifier.otherORCID: /0000-0002-7876-7338/work/35946868
dc.identifier.urihttps://hdl.handle.net/10023/11922
dc.descriptionThis work was funded by the Bob Champion Cancer Trust, The Masonic Charitable Foundation successor to The Grand Charity, The King Family, and The University of East Anglia. We acknowledge support from Movember, from Prostate Cancer UK, Callum Barton, and from The Andy Ripley Memorial Fund. We would like to acknowledge the support of the National Institute for Health Research which funds the Cambridge Bio-medical Research Centre, Cambridge UK.en
dc.description.abstractBackground : A critical problem in the clinical management of prostate cancer is that it is highly heterogeneous. Accurate prediction of individual cancer behaviour is therefore not achievable at the time of diagnosis leading to substantial overtreatment. It remains an enigma that, in contrast to breast cancer, unsupervised analyses of global expression profiles have not currently defined robust categories of prostate cancer with distinct clinical outcomes. Objective:  To devise a novel classification framework for human prostate cancer based on unsupervised mathematical approaches. Design, setting, and participants:  Our analyses are based on the hypothesis that previous attempts to classify prostate cancer have been unsuccessful because individual samples of prostate cancer frequently have heterogeneous compositions. To address this issue, we applied an unsupervised Bayesian procedure called Latent Process Decomposition to four independent prostate cancer transcriptome datasets obtained using samples from prostatectomy patients and containing between 78 and 182 participants. Outcome measurements and statistical analysis: Biochemical failure was assessed using log-rank analysis and Cox regression analysis. Results and limitations:  Application of Latent Process Decomposition identified a common process in all four independent datasets examined. Cancers assigned to this process (designated DESNT cancers) are characterized by low expression of a core set of 45 genes, many encoding proteins involved in the cytoskeleton machinery, ion transport, and cell adhesion. For the three datasets with linked prostate-specific antigen failure data following prostatectomy, patients with DESNT cancer exhibited poor outcome relative to other patients (p = 2.65 × 10−5, p = 4.28 × 10−5, and p = 2.98 × 10−8). When these three datasets were combined the independent predictive value of DESNT membership was p = 1.61 × 10−7 compared with p = 1.00 × 10−5 for Gleason sum. A limitation of the study is that only prediction of prostate-specific antigen failure was examined. Conclusions:  Our results demonstrate the existence of a novel poor prognosis category of human prostate cancer and will assist in the targeting of therapy, helping avoid treatment-associated morbidity in men with indolent disease. Patient Summary:  Prostate cancer, unlike breast cancer, does not have a robust classification framework. We propose that this failure has occurred because prostate cancer samples selected for analysis frequently have heterozygous compositions (individual samples are made up of many different parts that each have different characteristics). Applying a mathematical approach that can overcome this problem we identify a novel poor prognosis category of human prostate cancer called DESNT.
dc.format.extent9
dc.format.extent2345350
dc.language.isoeng
dc.relation.ispartofEuropean Urology Focusen
dc.subjectPoor prognosis categoryen
dc.subjectNovel prostate cancer classificationen
dc.subjectDESNT prostate canceren
dc.subjectLatent Process Decompositionen
dc.subjectRC0254 Neoplasms. Tumors. Oncology (including Cancer)en
dc.subjectDASen
dc.subjectSDG 3 - Good Health and Well-beingen
dc.subject.lccRC0254en
dc.titleDESNT : a poor prognosis category of human prostate canceren
dc.typeJournal articleen
dc.contributor.institutionUniversity of St Andrews. School of Medicineen
dc.contributor.institutionUniversity of St Andrews. Statisticsen
dc.contributor.institutionUniversity of St Andrews. Cellular Medicine Divisionen
dc.identifier.doi10.1016/j.euf.2017.01.016
dc.description.statusPeer revieweden


This item appears in the following Collection(s)

Show simple item record