Abstract
Methylation-mediated suppression of detoxification, DNA repair, and tumor suppressor genes has been implicated in cancer development and progression. Studies also have indicated that concordant methylation of multiple genes (methylator phenotypes), rather than a single gene, may predict cancer prognosis. The current study was designed to determine whether a methylator phenotype exists in ovarian cancer, whether methylation frequencies differ between malignant ovarian tumors and ovarian tumors with low malignant potential (LMP or borderline), and whether methylation of multiple genes affects patient survival. The current study included 234 consecutively diagnosed patients with either LMP (n = 19 patients) or malignant (n = 215 patients) ovarian tumors. DNA samples were extracted from fresh frozen tissues and were analyzed for methylation in the promoter region of 6 genes (p16, breast cancer 1 [BRCA1], insulin-like growth factor-binding protein 3 [IGFBP-3], glutathione S-transferase pi 1 [GSTP1], estrogen receptor-alpha [ER-alpha], and human MutL homologue 1 [hMLH1]) by using methylation-specific polymerase chain reaction analysis. The frequencies of methylation in malignant tumors and LMP tumors were 0% and 0% for GSTP1, respectively; 9% and 0% for hMLH1, respectively; 21% and 5% for BRCA1, respectively; 42% and 21% for p16, respectively; 44% and 26% for IGFBP-3, respectively; and 57% and 42% for ER-alpha, respectively. A methylator phenotype was not detected, but a calculated methylation index (MI) that was based on the total number of genes methylated in each tumor was associated with ovarian cancer risk and progression. A higher MI was associated with malignant tumors (odds ratio, 10.11; 95% confidence interval [95% CI], 1.19-85.75) and disease progression (hazards ratio, 6.53; 95% CI, 1.39-30.65). Although a methylator phenotype was not identified, the current results suggested that methylation of multiple genes may play an important role in ovarian cancer development and progression and may have clinical implications in prognosis.
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