Purpose: Aberrant gene promoter methylation profiles have been well-studied in human prostate cancer. Therefore, we rationalize that multigene methylation analysis could be useful as a diagnostic biomarker. We hypothesize that a new method of multigene methylation analysis could be a good diagnostic and staging biomarker for prostate cancer.
Experimental design: To test our hypothesis, prostate cancer samples (170) and benign prostatic hyperplasia samples (69) were examined by methylation-specific PCR for three genes: adenomatous polyposis coli (APC), glutathione S-transferase pi (GSTP1), and multidrug resistance 1 (MDR1). The methylation status of representative samples was confirmed by bisulfite DNA sequencing analysis. We further investigated whether methylation score (M score) can be used as a diagnostic and staging biomarker for prostate cancer. The M score of each sample was calculated as the sum of the corresponding log hazard ratio coefficients derived from multivariate logistic regression analysis of methylation status of various genes for benign prostatic hyperplasia and prostate cancer. The optimal sensitivity and specificity of the M score for diagnosis and for staging of prostate cancer was determined by receiver-operator characteristic (ROC) curve analysis. A pairwise comparison was employed to test for significance using the area under the ROC curve analysis. For each clinicopathologic finding, the association with prostate-specific antigen (PSA) failure-free probability was determined using Kaplan-Meier curves and a log-rank test was used to determine significance. The relationship between M score and clinicopathologic findings was analyzed by either the Mann-Whitney U test, Kruskal-Wallis test, or the Spearman rank correlation test.
Results: The frequency of positive methylation-specific PCR bands for APC, GSTP1, and MDR1 genes in prostate cancer samples was 64.1%, 54.0%, and 55.3%, respectively. In benign prostatic hyperplasia samples, it was 8.7%, 5.8%, and 11.6%, respectively. There was a significant correlation of M score with high pT category (P < 0.001), high Gleason sum (P < 0.001), high preoperative PSA (P = 0.027), and advanced pathologic features. For all patients, the M score had a sensitivity of 75.9% and a specificity of 84.1% as a diagnostic biomarker using a cutoff value of 1.0. In patients with low or borderline PSA levels (<10.0 ng/mL), the M score was significantly higher in prostate cancers than in benign prostatic hyperplasias (2.635 +/- 0.200 and 0.357 +/- 0.121, respectively). ROC curve analysis revealed that the M score had a sensitivity of 65.4% and a specificity of 94.2% when 1.0 was used as a cutoff value. For all patients, M score can distinguish organ-confined (< or =pT(2)) from locally advanced cancer (> or =pT(3)) with a sensitivity of 72.1% and a specificity of 67.8%. Moreover, considering patients with PSA levels of <10 ng/mL, the M score has a sensitivity of 67.1% and a specificity of 85.7%. The ROC curve analysis showed a significant difference between M score and PSA (P = 0.010).
Conclusions: This is the first report demonstrating that M score is a new method for multigene methylation analysis that can serve as a good diagnostic and staging biomarker for prostate cancer.