Published March 9, 2026
| Version v1
Dataset
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Prospective validation of a urine-based proteomics test for predicting clinically signi cant prostate cancer in biopsy-naive patients
Authors/Creators
- Morillo, Ana1
- Nigusu Jobre, Kirubel2
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LENDINEZ CANO, GUILLERMO3
- Blanca-Pedregosa, Ana1
- Lopez Ruiz, Daniel4
- Parada, Jose5
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Heidegger, Isabel6
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Culig, Zoran6
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Lopez-Beltran, Antonio7
- Carrasco-Valiente, Julia1
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Mischak, Harald2, 8
- Medina, Rafael3
- Campos Hernandez, Juan1
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Frantzi, Maria2
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Gómez Gómez, Enrique1
- 1. Maimonides Institute of Biomedical Research of Cordoba (IMIBIC), University of Cordoba (UCO), Department of Urology, Reina Sofía University Hospital, Cordoba, Spain
- 2. Department of Biomarker Research, Mosaiques diagnostics GmbH, Hannover, Germany
- 3. Department of Urology, Virgen del Rocio University Hospital/ IBiS, Seville Spain
- 4. Maimonides Institute of Biomedical Research of Cordoba (IMIBIC), University of Cordoba (UCO), Department of Radiology, Reina Sofía University Hospital, Cordoba, Spain
- 5. Department of Radiology, Virgen del Rocio University Hospital/ IBiS, Seville Spain
- 6. Medical University of Innsbruck, Department of Urology, Innsbruck, Austria
- 7. Department of Pathology, University of Cordoba, Cordoba, Spain
- 8. Institute of Cardiovascular and Medical Science, University of Glasgow, Glasgow, United Kingdom.
Description
Prostate cancer (PCa) remains a major health burden, while existing diagnostic approaches are limited by overdiagnosis that leads to unnecessary biopsies, and by underdetection of clinically significant disease (csPCa).
This study aims to prospectively validate a urine-based 19-biomarker model (19-BM) using capillary electrophoresis–mass spectrometry (CE-MS) for predicting csPCa in patients at risk.
The proteomics/ peptidomics datasets from 161 biopsy-naïve patients at risk for csPCa, who underwent pre-biopsy CE-MS analysis in urine, are provided.
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Additional details
Related works
- Is supplement to
- Data paper: 10.21203/rs.3.rs-8933198/v1 (DOI)
Funding
- Ministerio de Ciencia, Innovación y Universidades
- FIS [Ministry of Science and Innovation, ISC III, FEDER]) PI22/01769
- Federal Ministry of Education and Research
- ProSTRAT-AI (Federal Ministry of Education and Research/BMBF/EUREKA Network) 01DS23014
- European Commission
- PROMOTE (101169245: HORIZON – MSCA-2023-DN-01-01) 101169245