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dc.contributor.authorLuca, B-A
dc.contributor.authorBrewer, DS
dc.contributor.authorEdwards, DR
dc.contributor.authorEdwards, S
dc.contributor.authorWhitaker, HC
dc.contributor.authorMerson, S
dc.contributor.authorDennis, N
dc.contributor.authorCooper, RA
dc.contributor.authorHazell, S
dc.contributor.authorWarren, AY
dc.contributor.authorCancerMap Group,
dc.contributor.authorEeles, R
dc.contributor.authorLynch, AG
dc.contributor.authorRoss-Adams, H
dc.contributor.authorLamb, AD
dc.contributor.authorNeal, DE
dc.contributor.authorSethia, K
dc.contributor.authorMills, RD
dc.contributor.authorBall, RY
dc.contributor.authorCurley, H
dc.contributor.authorClark, J
dc.contributor.authorMoulton, V
dc.contributor.authorCooper, CS
dc.date.accessioned2017-11-15T12:05:27Z
dc.date.issued2018-12-01
dc.identifier.citationEuropean urology focus, 2018, 4 (6), pp. 842 - 850
dc.identifier.issn2405-4569
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/907
dc.identifier.eissn2405-4569
dc.identifier.doi10.1016/j.euf.2017.01.016
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.formatPrint-Electronic
dc.format.extent842 - 850
dc.languageeng
dc.language.isoeng
dc.publisherELSEVIER
dc.rights.urihttps://creativecommons.org/licenses/by/4.0
dc.subjectCancerMap Group
dc.subjectCytoskeleton
dc.subjectHumans
dc.subjectProstatic Neoplasms
dc.subjectNeoplasm Recurrence, Local
dc.subjectKallikreins
dc.subjectProstate-Specific Antigen
dc.subjectPrognosis
dc.subjectProstatectomy
dc.subjectProportional Hazards Models
dc.subjectBayes Theorem
dc.subjectGene Expression Profiling
dc.subjectCell Adhesion
dc.subjectIon Transport
dc.subjectMale
dc.titleDESNT: A Poor Prognosis Category of Human Prostate Cancer.
dc.typeJournal Article
dcterms.dateAccepted2017-01-28
rioxxterms.versionofrecord10.1016/j.euf.2017.01.016
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0
rioxxterms.licenseref.startdate2018-12
rioxxterms.typeJournal Article/Review
dc.relation.isPartOfEuropean urology focus
pubs.issue6
pubs.notesNo embargo
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/Genetics and Epidemiology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Genetics and Epidemiology/Oncogenetics
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Oncogenetics
pubs.organisational-group/ICR/Primary Group/Royal Marsden Clinical Units
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/Genetics and Epidemiology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Genetics and Epidemiology/Oncogenetics
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Oncogenetics
pubs.organisational-group/ICR/Primary Group/Royal Marsden Clinical Units
pubs.publication-statusPublished
pubs.volume4
pubs.embargo.termsNo embargo
icr.researchteamOncogenetics
dc.contributor.icrauthorEeles, Rosalind


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