Zinc α2-glycoprotein as a potential novel urine biomarker for the early diagnosis of prostate cancer

OBJECTIVE To examine the potential utility as a novel biomarker in the urine of zinc a 2-glygoprotein (ZAG) for the early diagnosis of prostate cancer. PATIENTS AND METHODS The urine of 127 consecutive candidates for a transrectal ultrasound prostatic biopsy with a mean age of 65.7 +/- 8.7 years and mean PSA 9.1 +/- 5.3 ng/mL was collected. Western blot analysis and immunohistochemistry for ZAG were performed. Receiver operating characteristic curves and logistic regression models were used to estimate the predictive ability of ZAG and to determine the optimal sensitivity and specificity by using various cut-off values for the prediction of prostate cancer. RESULTS In all, 42 patients had prostate cancer, 29 showed high grade prostatic intraepithelial neoplasia and 56 were negative. Receiver operating characteristic curve analysis showed a significant predictive ability of ZAG for prostate cancer. The area under the curve (AUC) for the prediction of prostate cancer was 0.68 (95% CI 0.59-0.78). The combination of ZAG with PSA showed a significant improvement in the predictive ability (P = 0.010), with AUC equal to 0.75 (95% CI 0.66-0.85). Separate analysis in patients with PSA levels of 4-10 ng/mL (70.1%) showed that ZAG had a discriminative power with AUC equal to 0.68. The optimal cut-off was 1.13 for ZAG, which corresponded to 6.88 times greater odds for prostate cancer. CONCLUSIONS Urine detected ZAG showed promising results in the prediction of prostate cancer. Further validation is required to establish ZAG as a novel biomarker.