Connell, SP;
Hanna, M;
McCarthy, F;
Hurst, R;
Webb, M;
Curley, H;
Walker, H;
... Clark, J; + view all
(2019)
A Four-Group Urine Risk Classifier for Predicting Outcome in Prostate Cancer Patients.
BJU International
, 124
(4)
pp. 609-620.
10.1111/bju.14811.
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Abstract
OBJECTIVES: To develop a risk classifier using urine-derived extracellular vesicle RNA (UEV-RNA) capable of providing diagnostic information of disease status prior to biopsy, and prognostic information for men on active surveillance (AS). PATIENTS AND METHODS: Post-digital rectal examination UEV-RNA expression profiles from urine (n = 535, multiple centres) were interrogated with a curated NanoString panel. A LASSO-based Continuation-Ratio model was built to generate four Prostate-Urine-Risk (PUR) signatures for predicting the probability of normal tissue (PUR-1), D'Amico Low-risk (PUR-2), Intermediate-risk (PUR-3), and High-risk (PUR-4) PCa. This model was applied to a test cohort (n = 177) for diagnostic evaluation, and to an AS sub-cohort (n = 87) for prognostic evaluation. RESULTS: Each PUR signature was significantly associated with its corresponding clinical category (p<0.001). PUR-4 status predicted the presence of clinically significant Intermediate or High-risk disease, AUC = 0.77 (95% CI: 0.70-0.84). Application of PUR provided a net benefit over current clinical practice. In an AS sub-cohort (n=87), groups defined by PUR status and proportion of PUR-4 had a significant association with time to progression (p<0.001; IQR HR = 2.86, 95% CI:1.83-4.47). PUR-4, when utilised continuously, dichotomised patient groups with differential progression rates of 10% and 60% five years post-urine collection (p<0.001, HR = 8.23, 95% CI:3.26-20.81). CONCLUSION: UEV-RNA can provide diagnostic information of aggressive PCa prior to biopsy, and prognostic information for men on AS. PUR represents a new & versatile biomarker that could result in substantial alterations to current treatment of PCa patients. This article is protected by copyright. All rights reserved.
| Type: | Article |
|---|---|
| Title: | A Four-Group Urine Risk Classifier for Predicting Outcome in Prostate Cancer Patients |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1111/bju.14811 |
| Publisher version: | https://doi.org/10.1111/bju.14811 |
| Language: | English |
| Additional information: | © 2019 The Authors BJU International Published by John Wiley & Sons Ltd on behalf of BJU International This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made |
| Keywords: | Active Surveillance, Biomarker, Liquid Biopsy, Machine Learning, Prostate Cancer, Urine |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Surgery and Interventional Sci UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Surgery and Interventional Sci > Department of Targeted Intervention |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10075021 |
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