Estrogen Metabolism Genes Research Articles

Are CYP17 Genotypes a Biomarker for Ovarian Cancer in Patients With Cancer History in Their Family?

BRCA1 and BRCA2 genes are responsible for 5-10% of breast and ovarian cancer cases. However, the vast majority of ovarian and breast cancer cases do not display the hereditary form of the disease. Estrogen-metabolizing genes may also contribute to the predisposition of breast or ovarian cancer. Polymorphic variants of the estrogen-metabolizing gene, CYP17, have been associated with the risk of hormone-related cancers. In this study we investigated the CYP17 polymorphisms in ovarian cancer patients harboring mutations in the BRCA1 and BRCA2 genes, patients displaying familial characteristics but not carrying mutations and patients with sporadic ovarian cancer. Association between the allele frequencies, the CYP17 genotype and tumor characteristics or clinical parameters was evaluated. Our data suggest evidence for an association between ovarian cancer risk and the CYP17 genotype in the subgroup of patients with familial disease in whom no mutations in the BRCA genes are found. Although there were no statistically significant differences in the genotype distribution between the control group and the subgroup of patients with BRCA mutations, the frequency of the CYP17 A2 allele was significantly higher in the subgroup of patients without BRCA mutations. We found a four- to eightfold higher risk in ovarian cancer patients with family history but without BRCA mutations. Our data indicate that the CYP17 A2 allele polymorphism may confer an increased risk and can provide a biomarker for ovarian cancer patients in whom no mutations in the BRCA genes are observed.

Ten Polymorphisms of Estrogen-Metabolizing Genes and a Family History of Colon Cancer—An Association Study of Multiple Gene-Gene Interactions

Estrogen replacement therapy is associated with a reduced risk of colon cancer. Therefore, we evaluated the following ten estrogen metabolism-associated single-nucleotide polymorphisms (SNPs) by sequencing-on-chip technology using solid-phase polymerase chain reaction (PCR) on oligonucleotide microarrays: catechol-O-methyltransferase (COMT) Val158Met G-->A, 17-beta-hydroxysteroid dehydrogenase type 1 (HSD17) vlV A-->C, cytochrome P-450 (CYP) 17 A2 allele T-->C, CYP1A1 MspI RFLP T-->C, CYP1A1 Ile462Val A-->G, CYP19 Arg264Cys C-->T, CYP19 C1558T C-->T, CYP 1B1 Leu432Val, CYP1B1 Asn453Ser, and estrogen receptor (ER) alpha IVS1 -401-->C in 76 patients with a family history of colon cancer and 722 healthy controls. Using stepwise logistic regression models, we found that none of the investigated SNPs is associated with a family history of colon cancer in a univariate and multivariate logistic regression model. In addition, when all two-way interactions of the investigated SNPs were ascertained, no significant interactions between SNPs were observed. In conclusion, we found no association between the carriage of one or multiple SNPs of the estrogen metabolism and a family history of colon cancer.

066 Risk of endometriosis, disease presentation, disease location, and polymorphisms of catechol estrogen metabolism genes

066 Risk of endometriosis, disease presentation, disease location, and polymorphisms of catechol estrogen metabolism genes

Estrogen-metabolizing gene polymorphisms and lipid levels in women with different hormonal status

Endogenous and exogenous sex steroid hormones have multiple effects on lipid and lipoprotein metabolism. It is also known that estrogen has antiatherogenic actions, therefore we considered examining whether there was any association between polymorphisms in estrogen-metabolizing genes and lipid levels in women. We investigated the association between variants in genes related to estrogen biosynthesis (CYP19-TTTA(n)) and estrogen catabolism (CYP1A1*2A, CYP1A1*2C, CYP1A2-Asn516Asn, CYP3A4*1B, and COMT-Val158Met) with serum lipid levels in a cross-sectional study with 472 Brazilian women of European descent. They were divided into three subgroups according to their hormonal status: premenopausal women (n=187), postmenopausal women exposed to hormonal replacement therapy (HRT) (n=118), and postmenopausal women unexposed to HRT (n=167). The postmenopausal women receiving HRT who were carriers of the CYP3A4*1B variant showed lower low-density lipoprotein cholesterol levels than wild-type homozygotes. Premenopausal women homozygous for the CYP1A1*2C allele had higher high-density lipoprotein cholesterol levels than heterozygotes. While the CYP1A1*2C variant probably has a higher catalytic activity, the functional implications of the CYP3A4 polymorphism are still uncertain. These data are the first attempt to associate estrogen metabolism genes to lipid levels in women.

Common variants in estrogen metabolism and DNA repair genes associated risk of breast cancer in young women

9507 Background: Breast cancer is a complex disease. The majority of cases occur in women without a family history and are considered sporadic. Currently for most women clinical evaluation of breast cancer risk utilizes epidemiological factors related to endogenous estrogen exposure. Estrogen and its related metabolites affect breast carcinogenesis by serving both as promoters of ductal epithelial cell growth and mutagenic precursors. Genomic instability caused by compromised DNA repair can also contribute to breast cancer development. Multiple low penetrance gene variants in these pathways may have a role in determining breast cancer risk in the general population. Methods: A case-control associative study of 5076 Caucasian women, 1812 breast cancer cases and 3264 cancer-free controls, was analyzed for common polymorphisms in fifteen genes involved in estrogen metabolism and DNA repair pathways. All polymorphisms were known to or likely to cause functional alterations and most resulted in non-synonymous amino acid substitutions. Overall analyses and stratification into likely pre-, peri- and post-menopausal age groups (30–44, 45–54, and over 55, respectively) were performed to derive odds ratios (ORs) and p-values. Results: Partitioning the study into the three age groups identified strong associations that were confined to the 30–44 age group. A total of nine polymorphisms were significantly (p≤0.05) associated with risk in this age group. The range of ORs varied from 0.7 to 1.6 with p-values as low as 0.001. Conclusions: Common variants in genes involved estrogen metabolism and DNA repair have significant impact on breast cancer risk in the youngest age group. The consideration of these variants could contribute to improved clinical management of breast cancer risk by identifying young women at the highest risk of developing the disease. Author Disclosure Employment or Leadership Consultant or Advisory Role Stock Ownership Honoraria Research Funding Expert Testimony Other Remuneration InterGenetics InterGenetics InterGenetics

Estrogen-metabolizing gene polymorphisms and age at natural menopause in Caucasian women

Lifestyle parameters, personal history and genetic factors are thought to affect the timing of natural menopause in humans. Based on their biological function, estrogen-metabolizing gene polymorphisms have been regarded as candidate genes for early menopause. In the present cross-sectional, multi-centre study, we analysed nine single nucleotide polymorphisms of six estrogen-metabolizing genes [three estrogen-synthesizing genes, i.e. 17-beta-hydroxysteroid dehydrogenase type 1 (17-beta HSD), cytochrome P-450 (CYP) 17 and CYP19; and three estrogen-inactivating genes, i.e. catechol-O-methyltransferase (COMT), CYP1A1 and CYP1B1] by sequencing-on-chip-technology in 1360 Caucasian women with natural menopause. Women's lifestyle parameters, reproductive and personal histories were ascertained. Carriage of at least one mutant allele of the CYP1B1-4 Asn453Ser A--> G polymorphism (P = 0.004) and the number of full-term pregnancies (P < 0.001) were found to be independently associated with age at natural menopause. Women with at least one polymorphic allele of CYP1B1-4 experienced natural menopause earlier than non-carriers of the polymorphism [mean (SD) 48.6 (5.0) versus 49.4 (4.3) years]. Women with no, one, two and three or more full-term pregnancies experienced natural menopause at 48.5 (5.0), 48.8 (4.8), 49.5 (4.2) and 49.6 (4.6) years, respectively. We present the most comprehensive data on estrogen-metabolizing gene polymorphisms and timing of natural menopause to date. The number of full-term pregnancies and the CYP1B1-4 polymorphism are significant predictors of timing of natural menopause in Caucasian women.

Prevention of Hormone-Related Cancers: Breast Cancer

Carcinogenesis in the breast is a hormonally dependent process. Evidence implicating estrogen as a key breast carcinogen comes from various lines of investigation. Traditional epidemiologic studies demonstrate associations between estrogen exposure, both exogenous and endogenous, and increased breast cancer risk. Ongoing genetic epidemiologic studies also show associations between specific polymorphisms in estrogen-metabolizing genes and risk, albeit inconsistently. The application of these findings to the treatment and, more recently, the prevention of breast cancer has led to the development of agents that either (1) inhibit estrogen action at the estrogen receptor (selective estrogen receptor modulators (SERMs]); or (2) inhibit estrogen-synthesizing enzymes, thereby abrogating synthesis of this hormone (aromatase inhibitors). Large phase III trials have evaluated the ability of such agents to reduce the incidence of breast cancer in women at increased risk of the disease. The National Surgical Adjuvant Breast and Bowel Project (NSABP) P-1: Breast Cancer Prevention Trial (BCPT) demonstrated the superiority of the SERM tamoxifen to placebo in reducing breast cancer risk, leading to the Food and Drug Administration approval of tamoxifen for risk reduction. The implementation of tamoxifen for this indication has not become widespread in clinical practice, however, for a variety of reasons that we discuss. Results from the NSABP Study of Tamoxifen and Raloxifene, which compares the risk-reducing efficacy as well as toxicity of these two SERMs in a similar high-risk population, will be available in the near future. Based on promising data involving reduction of contralateral breast cancer risk in adjuvant studies, several aromatase inhibitors, including letrozole, anastrozole, and exemestane, are being incorporated into trials evaluating their efficacy as preventive agents in women at increased risk.

Polymorphisms of estrogen-metabolizing genes and risk of hepatocellular carcinoma in Taiwan females

Estrogen has been related to the development of hepatocellular carcinoma (HCC). In this molecular epidemiological study, we used logistic regression to compare the genotype frequencies of estrogen-metabolizing genes that are involved in estrogen biogenesis ( CYP17), hydroxylation ( CYP1A1) and inactivation of the reactive metabolites ( catechol-O-methyltransferase, COMT) in HCC patients and control subjects, and determined their relationship with the risk of female HCC. The heterozygous or homozygous variants of high activity CYP17 ( A2), high inducibility CYP1A1( m1), and low activity COMT ( L) alleles were considered as high-risk genotypes. We found that the risk of HCC was elevated in women harboring either heterozygous or homozygous variants of the CYP1A1 gene and the respective OR (and 95% confidence interval) were 6.61 (1.35, 32.43) and 12.00 (1.73, 83.46). Moreover, we found that the risk of HCC was increased in the female subjects harboring higher numbers of high-risk genotypes, but not in male subjects. The OR for female HCC associated with two putative high-risk genotypes was 12.63 (1.50, 106.37), and the OR for three putative high-risk genotypes was 16.67 (1.82, 152.77). These findings strongly suggest that estrogen play a critical role in female hepatocarcinogenesis.

Estrogen-metabolizing gene polymorphisms in the assessment of breast carcinoma risk and fibroadenoma risk in Caucasian women.

Genes encoding enzymes involved in estrogen metabolism are held to be candidate genes for associations with breast disease. In these candidate genes, no critical combination of single-nucleotide polymorphisms (SNPs) for assessing breast carcinoma risk has been reported to date. In a large case-control study, the authors investigated 10 estrogen-metabolizing SNPs in 396 patients with breast carcinoma, 154 patients with fibroadenoma, and 1936 healthy control patients without breast carcinoma in their personal history. The following 10 SNPs were analyzed using sequencing-on-chip technology via a solid-phase polymerase chain reaction assay performed on oligonucleotide microarrays: catechol-O-methyltransferase Val158Met G-->A, 17-beta-hydroxysteroid dehydrogenase type 1 vIV A-->C, cytochrome P-450 (CYP) family 17 A2 allele T-->C, CYP1A1-1 MspI restriction fragment length polymorphism (RFLP) T-->C, CYP1A1-2 Ile462Val A-->G, CYP19-1 Trp39Arg T-->C, CYP19-2 Arg264Cys C-->T, CYP19-3 Cys1558Thr C-->T, steroid-5-alpha reductase type 2 Val89Leu G-->C, and vitamin D receptor BsmI RFLP. A total of 21,350 genotypes were evaluated. Associations and two-way interaction models were calculated using stepwise logistic regression. In a multiple model, CYP1A1-1 (P = 0.004) and CYP1A1-2 (P = 0.03) were found to be associated with significantly decreased and increased risks of breast carcinoma, respectively. When two-way interactions involving investigated SNPs were ascertained, no significant interactions among polymorphisms were noted. Comparison of patients with fibroadenoma with control patients revealed significantly increased and decreased risks of fibroadenoma when the mutant alleles of CYP17 (P = 0.02) and CYP1A1-1 (P = 0.04), respectively, were present. The authors obtained the first SNP data indicating that CYP17 and CYP1A1-1 play a role in the pathogenesis of fibroadenoma. Although the authors were not able to develop interaction models involving SNPs, they did provide evidence that CYP1A1 is a low-penetrance susceptibility gene with respect to breast carcinoma in a large series of Caucasian women.

A family-based genetic association study of variants in estrogen-metabolism genes COMT and CYP1B1 and breast cancer risk.

In this paper, we report findings from a family-based association study examining the association between polymorphisms in two key estrogen-metabolism genes CYP1B1 (codon 432 G --> C and codon 453 A --> G variants) and COMT (codon 158 G --> A variant) and female breast cancer. We conducted the study among 280 nuclear families containing one or more daughters with breast cancer with a total of 1124 family members (702 with available constitutional DNA and questionnaire data and 421 without). These nuclear families were selected from breast cancer families participating in the Metropolitan New York Registry (MNYR) - one of the six centers of NCI's Breast Cooperative Family Registry. We used likelihood-based statistical methods to examine the allelic associations. We found none of the variant alleles of the CYP1B1 and COMT genes to be associated with breast cancer in these families. This was consistent with results from matched case-control analyses using all available sib-ships in these families. However, we found that parental carrier status of the CYP1B1 codon 453 variant G allele and the COMT codon 158 variant A allele was associated with breast cancer risk in daughters (independent of the daughters' own genotype). In conclusion, findings from this family-based study indicate that a woman's own CYP1B1 or COMT genotypes are not associated with her breast cancer risk. Although the study found that parental carrier status of certain CYP1B1 or COMT genotypes might be associated with daughter's breast cancer risk, the biological basis as well as independent confirmation of this finding need to be investigated in future larger family-based studies before making meaningful inferences.

Estrogen-metabolizing gene polymorphisms, but not estrogen receptor-alpha gene polymorphisms, are associated with the onset of menarche in healthy postmenopausal Japanese women.

Both onset and cessation of menstruation have strong genetic inclination. We aimed to identify genetic factors influencing the onset of menarche and natural menopause in a Japanese population by investigating the polymorphisms of estrogen receptor-alpha and estrogen-metabolizing enzyme genes. Three hundred seventeen postmenopausal Japanese women, aged 46 yr and over, were enrolled in this study under informed consent. Genomic DNA was extracted from peripheral leukocytes, and PCR-based restriction fragment length polymorphism assays were used to determine estrogen receptor-alpha: PvuII, XbaI, and estrogen-metabolizing enzymes; CYP17, estrogen biosynthesis (high activity, A2/A2, CYP1A1), hydroxylation (high inducibility, vt/vt, and COMT), inactivation (low activity, L/L) genotypes. There were no significant differences in ages at menarche and natural menopause or years of menstruation among each PvuII or XbaI genotype and seven combinations of PvuII and XbaI genotypes. We found that ages at menarche in women with A1/A2 (higher activity of CYP17; 13.6 +/- 1.2 yr) were significantly earlier than in those with A1/A1 (lower activity of CYP17; 14.1 +/- 1.3 yr). There were no significant differences in age at natural menopause and years of menstruation among each CYP17, CYP1A1, or COMT genotype. The small sample size of each combination of estrogen-metabolizing genotypes made it impractical to evaluate the effects of the interdependency of each genotype, including extreme genotype categories such as A2/A2L/Lvt/vt vs. A1/A1H/Hwt/wt genotypes, on ages at menarche and/or natural menopause. The results suggest that the estrogen-metabolizing CYP17 genotype influences age at menarche in healthy postmenopausal Japanese women.

Multifactor-Dimensionality Reduction Reveals High-Order Interactions among Estrogen-Metabolism Genes in Sporadic Breast Cancer

One of the greatest challenges facing human geneticists is the identification and characterization of susceptibility genes for common complex multifactorial human diseases. This challenge is partly due to the limitations of parametric-statistical methods for detection of gene effects that are dependent solely or partially on interactions with other genes and with environmental exposures. We introduce multifactor-dimensionality reduction (MDR) as a method for reducing the dimensionality of multilocus information, to improve the identification of polymorphism combinations associated with disease risk. The MDR method is nonparametric (i.e., no hypothesis about the value of a statistical parameter is made), is model-free (i.e., it assumes no particular inheritance model), and is directly applicable to case-control and discordant-sib-pair studies. Using simulated case-control data, we demonstrate that MDR has reasonable power to identify interactions among two or more loci in relatively small samples. When it was applied to a sporadic breast cancer case-control data set, in the absence of any statistically significant independent main effects, MDR identified a statistically significant high-order interaction among four polymorphisms from three different estrogen-metabolism genes. To our knowledge, this is the first report of a four-locus interaction associated with a common complex multifactorial disease.