Subject: prostate cancer
Subject: proteomics
Subject: biomarker
Subject: non-invasive diagnosis
Subject: non-invasive prognosis
Subject: ELISA
Year: 2022
Type: Article
Title: Potential Role of Seven Proteomics Tissue Biomarkers for Diagnosis and Prognosis of Prostate Cancer in Urine
Author: Vujicic, Ivo
Author: Rusevski, Aleksandar
Author: Stankov, Oliver
Author: Popov, Zivko
Author: Dimovski, Aleksandar
Author: Davalieva, Katarina
Abstract: As the currently available tests for the clinical management of prostate cancer (PCa) are still far from providing precise diagnosis and risk stratification, the identification of new molecular marker(s) remains a pertinent clinical need. Candidate PCa biomarkers from the published proteomic comparative studies of prostate tissue (2002–2020) were collected and systematically evaluated. AZGP1, MDH2, FABP5, ENO1, GSTP1, GSTM2, and EZR were chosen for further evaluation in the urine of 85 PCa patients and controls using ELISA. Statistically significant differences in protein levels between PCa and BPH showed FABP5 (p = 0.019) and ENO1 (p = 0.015). A biomarker panel based on the combination of FABP5, ENO1, and PSA provided the highest accuracy (AUC = 0.795) for PCa detection. The combination of FABP5, EZR, AZGP1, and MDH2 showed AUC = 0.889 in PCa prognosis, with 85.29% of the samples correctly classified into low and high Gleason score (GS) groups. The addition of PSA to the panel slightly increased the AUC to 0.914. AZGP1, FABP5, and EZR showed significant correlation with GS, stage, and percentage of positive biopsy cores. Although validation using larger patient cohorts will be necessary to establish the credibility of the proposed biomarker panels in a clinical context, this study opens a way for the further testing of more high-quality proteomics biomarkers, which could ultimately add value to the clinical management of PCa.
Publisher: MDPI AG
Relation: Diagnostics
Identifier: oai:repository.ukim.mk:20.500.12188/27944
Identifier: http://hdl.handle.net/20.500.12188/27944Identifier: 10.3390/diagnostics12123184
Identifier: https://www.mdpi.com/2075-4418/12/12/3184/pdfIdentifier: 12
Identifier: 12
Identifier: 3184
