Unbalanced estrogen metabolism in ovarian cancer

Abstract

Greater exposure to estrogens is a risk factor for ovarian cancer. To investigate the role of estrogens in ovarian cancer, a spot urine sample and a saliva sample were obtained from 33 women with ovarian cancer and 34 age-matched controls. Thirty-eight estrogen metabolites, conjugates and DNA adducts were analyzed in the urine samples using ultraperformance liquid chromatography/tandem mass spectrometry, and the ratio of adducts to metabolites and conjugates was calculated for each sample. The ratio of depurinating estrogen-DNA adducts to estrogen metabolites and conjugates was significantly higher in cases compared to controls (p < 0.0001), demonstrating high specificity and sensitivity. DNA was purified from the saliva samples and analyzed for genetic polymorphisms in the genes for two estrogen-metabolizing enzymes. Women with two low-activity alleles of catechol-O-methyltransferase plus one or two high-activity alleles of cytochrome P450 1B1 had higher levels of estrogen-DNA adducts and were more likely to have ovarian cancer. These findings indicate that estrogen metabolism is unbalanced in ovarian cancer and suggest that formation of estrogen-DNA adducts plays a critical role in the initiation of ovarian cancer.

Keywords: CYP1B1; SNPs; catechol-O-methyltransferase; ovarian cancer, estrogen-DNA adducts, unbalanced estrogen metabolism.

Figure 1

Proposed metabolic pathway in cancer initiation by estrogens.

Figure 2

Ratio of urinary depurinating estrogen-DNA adducts to estrogen metabolites and conjugates for women diagnosed with ovarian cancer (cases) or not diagnosed with cancer (controls). The ratio is defined in the Materials and Methods Section. The dotted line representing a ratio of 43 is the cross-over point for sensitivity and specificity of the ratio (see Fig. 3). Insert: Ratios presented as median values and ranges (min to max). The diamonds represent the mean values.

Figure 3

Sensitivity and specificity at cut-points from 0 to 350 of the DNA adduct ratio in 33 cases of ovarian cancer and 34 non-cancer controls; sensitivity equals specificity at an adduct ratio cut-off value of 43.

Figure 4

Maximum likelihood path analysis of having polymorphic alleles in CYP1B1 and COMT, the adduct ratio, and having ovarian cancer in 67 women (33 cases and 34 controls). The slope coefficients represent the effect sizes in sequential regression analyses. The path from high-risk genotypes shows a significant increase in the DNA adduct ratio. The second path coefficient indicates a significant increase in the risk of ovarian cancer.