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


Ioannis Katafigiotis, Department of Urology, Athens University Medical School – LAIKO Hospital, 17 Agiou Thoma str., 11527 Athens, Greece. e-mail: katafigiotis@yahoo.com


Study Type – Diagnosis (exploratory cohort)

Level of Evidence 2b

What's known on the subject? and What does the study add?

The use of biomarkers to detect a cancer early, especially prostate cancer, is not a new idea and PSA has been proved to be the best biomarker for the early diagnosis of prostate cancer. Since the introduction and wide use of PSA various efforts have been made to find novel biomarkers in both serum and urine of individuals at high risk for prostate cancer. The best example of a biomarker detected in the urine after a vigorous digital rectal examination is PCA3, which is used mainly in the subgroup of patients with PSA 4–10 ng/mL whose prostate biopsy was repeatedly negative for prostate cancer in order to decide the performance or not of a new biopsy. Proteomics is a state of the art new biotechnology used to identify the proteome of a certain tissue meaning the whole group of proteins related to the anatomy and biochemistry of the tissue. Using proteomics can effectively and more specifically identify proteins that can be used as potential biomarkers for the early diagnosis of prostate cancer. Zinc α2-glycoprotein has been studied in the past as a protein related to cancer cachexia and it has been measured in both prostate tissue and serum in patients with prostate cancer. Zinc α2-glycoprotein has also been recently identified by proteomics in prostate tissue showing different values in patients with prostate cancer and benign prostate hyperplasia. It is the first time that zinc α2-glycoprotein has been systematically measured and studied in an easily obtained biological fluid such as urine showing a very optimistic potential both as a novel solo biomarker and as an adjunct to PSA for the early diagnosis of prostate cancer.

PSA has revolutionized the way we approximate prostate cancer diagnosis. Even though PSA is still the best biomarker for the diagnosis of prostate cancer it constitutes an organ-specific and not a disease-specific biomarker and diagnostic dilemmas are often raised concerning the performance or not of a prostate biopsy. Thus novel biomarkers are required in order to improve the diagnostic ability of PSA. Increasingly in the literature it is stated that the future of prostate cancer diagnosis could be not a single biomarker but a band of different biomarkers that as a total could give the possibility of an individual having prostate cancer. By detecting and measuring zinc α2-glycoprotein in the urine we believe that interesting conclusions can be made: first that proteomics is the way to detect with accuracy proteins that could be proved to be valuable novel biomarkers; second that zinc α2-glycoprotein detected in the urine could be used both as a solo biomarker and as an adjunct to PSA for the early diagnosis of prostate cancer.


  • • To examine the potential utility as a novel biomarker in the urine of zinc α2-glygoprotein (ZAG) for the early diagnosis of prostate cancer.


  • • 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.


  • • 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.


  • • Urine detected ZAG showed promising results in the prediction of prostate cancer.
  • • Further validation is required to establish ZAG as a novel biomarker.