ORIGINAL ARTICLE   Free access

Minerva Urology and Nephrology 2021 February;73(1):98-106

DOI: 10.23736/S2724-6051.19.03529-X

Copyright © 2019 EDIZIONI MINERVA MEDICA

language: English

Prospective evaluation of urinary steroids and prostate carcinoma-induced deviation: preliminary results

Stefano DE LUCA ¹, Eleonora AMANTE ^{2, 3} ✉, Cristian FIORI ¹, Giorgio ALLEVA ¹, Eugenio ALLADIO ², Federico MARINI ⁴, Diletta GARROU ¹, Matteo MANFREDI ¹, Daniele AMPARORE ¹, Enrico CHECCUCCI ¹, Serena PRUNER ², Alberto SALOMONE ^{2, 3}, Roberto M. SCARPA ¹, Marco VINCENTI ^{2, 3}, Francesco PORPIGLIA ¹

¹ Division of Urology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy; ² Department of Chemistry, University of Turin, Turin, Italy; ³ A. Bertinaria Anti-Doping Center, Orbassano, Turin, Italy; ⁴ Department of Chemistry, Sapienza University, Rome, Italy

BACKGROUND: The serum prostate-specific antigen is the most widespread biomarker for prostate disease. Its low specificity for prostatic malignancies is a matter of concern and the reason why new biomarkers for screening purposes are needed. The correlation between altered production of the main steroids and prostate carcinoma (PCa) occurrence is historically known. The purpose of this study is to evaluate the modifications of a comprehensive urinary endogenous steroidal profile (USP) induced by PCa, by multivariate statistical methods.
METHODS: A total of 283 Italian subjects were included in the study, 139 controls and 144 PCa-affected patients. The USP, including 17 steroids and five urinary steroidal ratios, was quantitatively evaluated using gas chromatography coupled with single quadrupole mass spectrometry (GC-MS). The data were interpreted using a chemometric, multivariate approach (intrinsically more sensible to alterations with respect to traditional statistics) and a model for the discrimination of cancer-affected profiles was built.
RESULTS: Two multivariate classification models were calculated, the former including three steroids with the highest statistical significance (e.g. testosterone, etiocholanolone and 7β-OH-DHEA) and PSA values, the latter considering the three steroids’ levels only. Both models yielded high sensitivity and specificity scores near to 70%, resulting significantly higher than PSA alone.
CONCLUSIONS: Three USP steroids resulted significantly altered in our PCa population. These preliminary results, combined with the simplicity and low-cost of the analysis, open to further investigation of the potential role of this restricted USP in PCa diagnosis.

KEY WORDS: Urine; Steroids; Prostatic neoplasms; Biomarkers; Gas chromatography-mass spectrometry