Beatriz E Sánchez1, Adolfo Aguayo1, Braulio Martínez2, Fabiola Rodríguez1, Melanie Marmolejo1, Yevgeniya Svyryd1, Leonora Luna1, Luis A Muñoz1, Miguel A Jiménez3, Mariano Sotomayor4, Florencia Vargas V5, Osvaldo M Mutchinick6. 1. Department of Genetics, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico. 2. Department of Pathology, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico. 3. Department of Urology, Instituto Nacional de Cancerología, Mexico City, Mexico. 4. Department of Urology, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico. 5. Department of Gastroenterology, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico. 6. Department of Genetics, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico. Electronic address: osvaldo@unam.mx.
Abstract
BACKGROUND: Prostate cancer (PCa) is the most common malignancy in Mexican men. Serum prostate-specific antigen (PSA) is the usual noninvasive biomarker used for its detection. Its low specificity can increase the number of unnecessary prostate biopsies and the incidence of unpleasant complications for patients. The androgen-receptor gene (AR-CAG) repeat length and the percentage of promoter methylation (PPM) of genes glutathione-S-transferase P1 (GSTP1) and Ras association domain family 1 isoform A (RASSF1A) improve PCa detection. As an option for noninvasive assessment, we evaluated a combined analysis of all these biomarkers. PATIENTS AND METHODS: A total of 186 patients scheduled for biopsy were included in the present study. PSA and AR-CAG repeats were analyzed in blood samples. The PPM of GSTP1 and RASSF1A genes was estimated in prostate tissue and urinary sediment cells (USCs) and plasma DNA using quantitative methylation-specific polymerase chain reaction. The predictive values for PCa and benign prostatic hyperplasia (BPH), logistic regression analysis, receiver operating characteristic curve, and decision curve analysis were used to assess the differential diagnosis. RESULTS: Statistically significant differences between PCa and BPH patients were observed for all biomarkers, with higher positive and negative predictive values when all biomarkers were included in the analysis, attaining USC values of 89.2% and 78.0%, respectively. The differential diagnosis accuracy of PSA (area under the curve, 0.59) increased to 0.70 and 0.68, respectively, when the combined analysis of PPM of RASSF1Aplasma or GSTP1AUSC and AR-CAG repeats was performed. Decision curve analysis showed the utility of the combined analysis to decrease the number of unnecessary biopsies. CONCLUSION: The results showed that combined analysis of the proposed biomarkers in plasma and USCs significantly increased the confidence for the differential diagnosis for PCa and BPH. This noninvasive practice might help in the early detection of PCa and patient follow-up, avoiding to some extent unnecessary prostate biopsies.
BACKGROUND:Prostate cancer (PCa) is the most common malignancy in Mexican men. Serum prostate-specific antigen (PSA) is the usual noninvasive biomarker used for its detection. Its low specificity can increase the number of unnecessary prostate biopsies and the incidence of unpleasant complications for patients. The androgen-receptor gene (AR-CAG) repeat length and the percentage of promoter methylation (PPM) of genes glutathione-S-transferase P1 (GSTP1) and Ras association domain family 1 isoform A (RASSF1A) improve PCa detection. As an option for noninvasive assessment, we evaluated a combined analysis of all these biomarkers. PATIENTS AND METHODS: A total of 186 patients scheduled for biopsy were included in the present study. PSA and AR-CAG repeats were analyzed in blood samples. The PPM of GSTP1 and RASSF1A genes was estimated in prostate tissue and urinary sediment cells (USCs) and plasma DNA using quantitative methylation-specific polymerase chain reaction. The predictive values for PCa and benign prostatic hyperplasia (BPH), logistic regression analysis, receiver operating characteristic curve, and decision curve analysis were used to assess the differential diagnosis. RESULTS: Statistically significant differences between PCa and BPH patients were observed for all biomarkers, with higher positive and negative predictive values when all biomarkers were included in the analysis, attaining USC values of 89.2% and 78.0%, respectively. The differential diagnosis accuracy of PSA (area under the curve, 0.59) increased to 0.70 and 0.68, respectively, when the combined analysis of PPM of RASSF1Aplasma or GSTP1AUSC and AR-CAG repeats was performed. Decision curve analysis showed the utility of the combined analysis to decrease the number of unnecessary biopsies. CONCLUSION: The results showed that combined analysis of the proposed biomarkers in plasma and USCs significantly increased the confidence for the differential diagnosis for PCa and BPH. This noninvasive practice might help in the early detection of PCa and patient follow-up, avoiding to some extent unnecessary prostate biopsies.
Authors: Benedikt Hoeh; Jan L Hohenhorst; Rocco Flammia; Benedikt Horlemann; Gabriele Sorce; Francesco Chierigo; Zhe Tian; Fred Saad; Markus Graefen; Michele Gallucci; Alberto Briganti; Carlo Terrone; Shahrokh F Shariat; Luis A Kluth; Andreas Becker; Felix K H Chun; Pierre I Karakiewicz Journal: Int Urol Nephrol Date: 2021-11-16 Impact factor: 2.370