PURPOSE: Our study was designed to evaluate promoter CpG island hypermethylation in the diagnosis and prognosis of prostate cancer. EXPERIMENTAL DESIGN: Primary prostate cancers from 53 patients, pelvic lymph nodes, noncancerous prostate tissues, and prostate cell lines were analyzed. Real-time methylation-specific PCR was used to identify CpG island hypermethylation at five promising gene loci (i.e., GSTP1, APC, PTGS2, MDR1, and RASSF1a). RESULTS: At three gene loci (GSTP1, APC, and PTGS1) and CpG island, hypermethylation was highly prevalent in prostate cancers (71-91%), and analysis of receiver operator curves showed that hypermethylation at these three gene loci can distinguish between prostate cancer and noncancerous prostatic tissue (i.e., benign hyperplasia) with a sensitivity of 71.1% to 96.2% and a specificity of 92.9% to 100%. Using sensitive SYBR green methylation-specific PCR technology, we observed a respective 28% and 71% hypermethylation rate at the RASSF1a and MDR1 loci in benign prostate hyperplasia, which may represent early nonaggressive carcinogenesis. Methylation characteristics in prostate cancer metastases (i.e., pelvic lymph nodes) were comparable to the respective primary cancer. Statistical analysis showed no correlation between the methylation status of a single gene locus and clinicopathologic variables (e.g., preoperative prostate specific antigen levels, Gleason score, capsular penetration, involvement of seminal vesicle, and age). In contrast, the methylation of two (GSTP1/APC; GSTP1/PTGS2) or three (GSTP1/APC/PTGS2) gene loci correlated with prognostic indicators (i.e., pathologic stage, extraprostatic extension, and Gleason score, but not with prostate specific antigen levels). CONCLUSIONS: Our data suggest that the evaluation of DNA hypermethylation at three gene loci (i.e., GSTP1, APC, and PTGS2) is of diagnostic and prognostic value in prostate cancer.
PURPOSE: Our study was designed to evaluate promoter CpG island hypermethylation in the diagnosis and prognosis of prostate cancer. EXPERIMENTAL DESIGN:Primary prostate cancers from 53 patients, pelvic lymph nodes, noncancerous prostate tissues, and prostate cell lines were analyzed. Real-time methylation-specific PCR was used to identify CpG island hypermethylation at five promising gene loci (i.e., GSTP1, APC, PTGS2, MDR1, and RASSF1a). RESULTS: At three gene loci (GSTP1, APC, and PTGS1) and CpG island, hypermethylation was highly prevalent in prostate cancers (71-91%), and analysis of receiver operator curves showed that hypermethylation at these three gene loci can distinguish between prostate cancer and noncancerous prostatic tissue (i.e., benign hyperplasia) with a sensitivity of 71.1% to 96.2% and a specificity of 92.9% to 100%. Using sensitive SYBR green methylation-specific PCR technology, we observed a respective 28% and 71% hypermethylation rate at the RASSF1a and MDR1 loci in benign prostate hyperplasia, which may represent early nonaggressive carcinogenesis. Methylation characteristics in prostate cancer metastases (i.e., pelvic lymph nodes) were comparable to the respective primary cancer. Statistical analysis showed no correlation between the methylation status of a single gene locus and clinicopathologic variables (e.g., preoperative prostate specific antigen levels, Gleason score, capsular penetration, involvement of seminal vesicle, and age). In contrast, the methylation of two (GSTP1/APC; GSTP1/PTGS2) or three (GSTP1/APC/PTGS2) gene loci correlated with prognostic indicators (i.e., pathologic stage, extraprostatic extension, and Gleason score, but not with prostate specific antigen levels). CONCLUSIONS: Our data suggest that the evaluation of DNA hypermethylation at three gene loci (i.e., GSTP1, APC, and PTGS2) is of diagnostic and prognostic value in prostate cancer.
Authors: Jennifer A Rusiecki; Laura E Beane Freeman; Matthew R Bonner; Melannie Alexander; Ligong Chen; Gabriella Andreotti; Kathryn H Barry; Lee E Moore; Hyang-Min Byun; Freya Kamel; Michael Alavanja; Jane A Hoppin; Andrea Baccarelli Journal: Environ Mol Mutagen Date: 2016-12-20 Impact factor: 3.216
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