Mass Spectrometry-Based Biomarkers to Detect Prostate Cancer: A Multicentric Study Based on Non-Invasive Urine Collection without Prior Digital Rectal Examination.
Maria Frantzi, Zoran Culig, Isabel Heidegger, Marika Mokou, Agnieszka Latosinska, Marie C Roesch, Axel S Merseburger, Manousos Makridakis, Antonia Vlahou, Ana Blanca-Pedregosa, Julia Carrasco-Valiente, Harald Mischak, Enrique Gomez-Gomez
Author Information
Maria Frantzi: Department of Biomarker Research, Mosaiques Diagnostics GmbH, 30659 Hannover, Germany. ORCID
Zoran Culig: Experimental Urology Department of Urology, Medical University of Innsbruck, 6020 Innsbruck, Austria.
Isabel Heidegger: Experimental Urology Department of Urology, Medical University of Innsbruck, 6020 Innsbruck, Austria. ORCID
Marika Mokou: Department of Biomarker Research, Mosaiques Diagnostics GmbH, 30659 Hannover, Germany. ORCID
Agnieszka Latosinska: Department of Biomarker Research, Mosaiques Diagnostics GmbH, 30659 Hannover, Germany.
Marie C Roesch: Department of Urology, University Hospital Schleswig-Holstein, Campus Lübeck, 23538 Lübeck, Germany.
Axel S Merseburger: Department of Urology, University Hospital Schleswig-Holstein, Campus Lübeck, 23538 Lübeck, Germany.
Manousos Makridakis: Systems Biology Center, Biomedical Research Foundation, Academy of Athens, 11527 Athens, Greece. ORCID
Antonia Vlahou: Systems Biology Center, Biomedical Research Foundation, Academy of Athens, 11527 Athens, Greece. ORCID
Ana Blanca-Pedregosa: Maimonides Biomedical Research Institute of Córdoba, Department of Urology, University of Cordoba, 14004 Cordoba, Spain. ORCID
Julia Carrasco-Valiente: Maimonides Biomedical Research Institute of Córdoba, Department of Urology, University of Cordoba, 14004 Cordoba, Spain.
Harald Mischak: Department of Biomarker Research, Mosaiques Diagnostics GmbH, 30659 Hannover, Germany.
Enrique Gomez-Gomez: Maimonides Biomedical Research Institute of Córdoba, Department of Urology, University of Cordoba, 14004 Cordoba, Spain.
(1) Background: Prostate cancer (PCa) is the most frequently diagnosed cancer in men. Wide application of prostate specific antigen test has historically led to over-treatment, starting from excessive biopsies. Risk calculators based on molecular and clinical variables can be of value to determine the risk of PCa and as such, reduce unnecessary and invasive biopsies. Urinary molecular studies have been mostly focusing on sampling after initial intervention (digital rectal examination and/or prostate massage). (2) Methods: Building on previous proteomics studies, in this manuscript, we aimed at developing a biomarker model for PCa detection based on urine sampling without prior intervention. Capillary electrophoresis coupled to mass spectrometry was applied to acquire proteomics profiles from 970 patients from two different clinical centers. (3) Results: A case-control comparison was performed in a training set of 413 patients and 181 significant peptides were subsequently combined by a support vector machine algorithm. Independent validation was initially performed in 272 negative for PCa and 138 biopsy-confirmed PCa, resulting in an AUC of 0.81, outperforming current standards, while a second validation phase included 147 PCa patients. (4) Conclusions: This multi-dimensional biomarker model holds promise to improve the current diagnosis of PCa, by guiding invasive biopsies.
