Validation of a Urine-Based Proteomics Test to Predict Clinically Significant Prostate Cancer: Complementing mpMRI Pathway

Maria Frantzi ¹, Ana C Morillo ², Guillermo Lendinez ³

¹Department of Biomarker Research, Mosaiques Diagnostics GmbH, Hannover, Germany.
²Department of Urology, Maimonides Institute of Biomedical Research of Cordoba (IMIBIC), Reina Sofía University Hospital, University of Cordoba (UCO), Cordoba, Spain.
³Department of Urology, Virgen del Rocio University Hospital/IBiS, Seville, Spain.
⁴Department of Morphological Sciences, Cordoba University, Cordoba, Spain.
⁵Department of Radiology, Maimonides Institute of Biomedical Research of Cordoba (IMIBIC), Reina Sofía University Hospital, University of Cordoba (UCO), Cordoba, Spain.
⁶Department of Radiology, Virgen del Rocio University Hospital/IBiS, Seville, Spain.
⁷Department of Urology, Medical University of Innsbruck, Innsbruck, Austria.
⁸Institute for Molecular Cardiovascular Research (IMCAR), RWTH Aachen University Hospital, Aachen, Germany.
⁹Lipids and Atherosclerosis Unit, Internal Medicine Unit, Maimonides Institute of Biomedical Research of Cordoba (IMIBIC), Reina Sofía University Hospital, University of Cordoba (UCO), Cordoba, Spain.
¹⁰Institute of Cardiovascular and Medical Science, University of Glasgow, Glasgow, UK.

⁰Department of Biomarker Research, Mosaiques Diagnostics GmbH, Hannover, Germany.

Pathobiology : Journal of Immunopathology, Molecular and Cellular Biology +

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November 11, 2024

View abstract on PubMed

Summary

A new 19-biomarker model (19-BM) accurately predicts clinically significant prostate cancer (csPCa) in biopsy-naive men. This test, when combined with MRI, improves diagnostic accuracy and can reduce unnecessary biopsies.

Area Of Science

Urology
Oncology
Proteomics

Background

Prostate cancer (PCa) is the most common cancer in men, necessitating accurate prediction of clinically significant PCa (csPCa).
A previously developed 19-biomarker model (19-BM) using capillary electrophoresis-mass spectrometry (CE-MS) showed promise.
This study aimed to validate the 19-BM in a prospective, multicenter cohort of biopsy-naive patients.

Purpose Of The Study

To validate the diagnostic performance of the 19-biomarker model (19-BM) for predicting clinically significant prostate cancer (csPCa).
To compare the accuracy of 19-BM against prostate-specific antigen (PSA) and PSA density.
To evaluate the added value of integrating 19-BM with multiparametric magnetic resonance imaging (mpMRI).

Main Methods

Urine samples from 101 biopsy-naive patients were analyzed using CE-MS.
The 19-BM score was calculated using support vector machine-based software.
All patients underwent mpMRI, and diagnostic nomograms were explored in conjunction with mpMRI.

Main Results

The 19-BM achieved an AUC of 0.81, outperforming PSA (AUC:0.56) and PSA density (AUC:0.69).
In patients with PI-RADS ≤3, 19-BM demonstrated 86% sensitivity and 88% specificity.
Integrating 19-BM with mpMRI significantly improved accuracy (AUC:0.90) compared to individual methods.

Conclusions

The 19-BM shows favorable reproducibility for predicting csPCa.
19-BM effectively identified insignificant PCa in patients with PI-RADS ≤3, minimizing missed csPCa cases.
The 19-BM test can complement mpMRI, potentially reducing the need for invasive biopsies.

Keywords:

Biomarker Multiparametric magnetic resonance imaging Prostate cancer Proteomics Urine