CYP17 gene polymorphism in relation to breast cancer risk: a case-control study

Association between CYP17 T-34C rs743572 and breast cancer risk

Association between CYP17 T-34C (rs743572) polymorphism and breast cancer (BC) risk was controversial. In order to derive a more definitive conclusion, we performed this meta-analysis. We searched in the databases of PubMed, EMBASE and Cochrane for eligible publications. Pooled odds ratios (ORs) with 95% confidence intervals (95% CIs) were used to assess the strength of association between CYP17 T-34C polymorphism and breast cancer risk. Forty-nine studies involving 2,7104 cases and 3,4218 control subjects were included in this meta-analysis. In overall, no significant association between CYP17 T-34C polymorphism and breast cancer susceptibility was found among general populations. In the stratified analysis by ethnicity and source, significant associations were still not detected in all genetic models; besides, limiting the analysis to studies with controls in agreement with HWE, we also observed no association between CYP17 T-34C polymorphism and breast cancer risk. For premenopausal women, we didn't detect an association between rs743572 and breast cancer risk; however, among postmenopausal women, we observed that the association was statistically significant under the allele contrast genetic model (OR = 1.10, 95% CI = 1.03-1.17, P = 0.003), but not in other four models. In conclusion, rs743572 may increase breast cancer risk in postmenopausal individuals, but not in premenopausal folks and general populations.

Review of the Gene-Environment Interaction Literature in Cancer: What Do We Know?

BACKGROUND

Risk of cancer is determined by a complex interplay of genetic and environmental factors. Although the study of gene-environment interactions (G×E) has been an active area of research, little is reported about the known findings in the literature.

METHODS

To examine the state of the science in G×E research in cancer, we performed a systematic review of published literature using gene-environment or pharmacogenomic flags from two curated databases of genetic association studies, the Human Genome Epidemiology (HuGE) literature finder and Cancer Genome-Wide Association and Meta Analyses Database (CancerGAMAdb), from January 1, 2001, to January 31, 2011. A supplemental search using HuGE was conducted for articles published from February 1, 2011, to April 11, 2013. A 25% sample of the supplemental publications was reviewed.

RESULTS

A total of 3,019 articles were identified in the original search. From these articles, 243 articles were determined to be relevant based on inclusion criteria (more than 3,500 interactions). From the supplemental search (1,400 articles identified), 29 additional relevant articles (1,370 interactions) were included. The majority of publications in both searches examined G×E in colon, rectal, or colorectal; breast; or lung cancer. Specific interactions examined most frequently included environmental factors categorized as energy balance (e.g., body mass index, diet), exogenous (e.g., oral contraceptives) and endogenous hormones (e.g., menopausal status), chemical environment (e.g., grilled meats), and lifestyle (e.g., smoking, alcohol intake). In both searches, the majority of interactions examined were using loci from candidate genes studies and none of the studies were genome-wide interaction studies (GEWIS). The most commonly reported measure was the interaction P-value, of which a sizable number of P-values were considered statistically significant (i.e., <0.05). In addition, the magnitude of interactions reported was modest.

CONCLUSION

Observations of published literature suggest that opportunity exists for increased sample size in G×E research, including GWAS-identified loci in G×E studies, exploring more GWAS approaches in G×E such as GEWIS, and improving the reporting of G×E findings.

Role of cytochrome P450 genes in breast cancer etiology and treatment: effects on estrogen biosynthesis, metabolism, and response to endocrine therapy

PURPOSE

The cytochrome P450 (CYP) genes are oxygenases involved in estrogen biosynthesis and metabolism, generation of DNA damaging procarcinogens, and response to anti-estrogen therapies. Since lifetime estrogen exposure is an established risk factor for breast cancer, determining the role of CYP genes in breast cancer etiology may provide critical information for understanding tumorigenesis and response to treatment.

METHODS

This review summarizes literature available in PubMed published between 1993 and 2013 that focuses on studies evaluating the effects of DNA variants in CYP genes on estrogen synthesis, metabolism, and generation of procarcinogens in addition to response to anti-estrogen therapies.

RESULTS

Evaluation of DNA variants in estrogen metabolism genes was largely inconclusive. Meta-analyses of data from CYP19A1 support an association between the number of (TTTA) n repeats in intron 4 and breast cancer risk, but the biological mechanism for this relationship is unknown. Associations between single nucleotide polymorphism in CYP1B1 and DNA damage caused by procarcinogenic estrogen metabolites were ambiguous. Variants in CYP2D6 are associated with altered metabolism tamoxifen; however, current data do not support widespread clinical testing. The effect of variants in CYP19A1 in response to aromatase inhibitors is also questionable.

CONCLUSION

Evaluation of DNA variants in CYP genes involved with estrogen metabolism or treatment response has been inconclusive, reflecting small samples sizes, tumor heterogeneity, and differences between populations. Better-powered studies that account for genetic backgrounds and tumor phenotypes are thus necessary.

The CYP17A1 -34T > C polymorphism and breast cancer risk in BRCA1 and BRCA2 mutation carriers

Exposure to estrogen has a major effect on breast cancer risk. A polymorphism (-34 T > C; rs743572) in the cytochrome P450c17alpha gene (CYP17A1) encoding an enzyme which controls estrogen levels was reportedly associated with breast cancer risk in average risk populations. The effect of this polymorphism on breast or ovarian cancer risk for BRCA1 and BRCA2 mutation carriers has not been thoroughly investigated. With this aim, 2,221 BRCA1 and BRCA2 mutation carriers (1,313 with breast cancer, 279 with ovarian cancer, and 695 asymptomatic carriers), with either BRCA1 (n = 1693) or BRCA2 (n = 528) germline mutations from seven centers were genotyped for the -34 T > C CYP17 polymorphism. Genotyping was accomplished using Taqman allelic discrimination, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) or PCR-based restriction-fragment length polymorphism analysis, and limited sequencing. Data were analyzed using Cox proportional hazards models. The hazard ratios (HRs) for breast cancer was 1.02 (95% CI 0.89-1.17, p = 0.74) and 1.10 (95% CI 0.72-1.67, p = 0.66) for BRCA1 and BRCA2 mutation carriers, respectively. The HRs for ovarian cancer were 1.17 (0.94-1.46, p = 0.17) and 0.91 (0.31-2.67, p = 0.86) for BRCA1 and BRCA2 mutation carriers, respectively. Results remained unaltered when the Israeli cohort (primarily Ashkenazim) was evaluated separately. In conclusion, there was no overall evidence for an association of the -34 T > C CYP17 polymorphism with either breast or ovarian cancer risk in BRCA1 or BRCA2 mutation carriers.

Factors influencing the association between CYP17 T34C polymorphism and the risk of breast cancer: meta-regression and subgroup analysis

A number of studies have been investigated the association between CYP17 T34C polymorphism and the risk of breast cancer; the results of these studies are inconsistent, however. This fact implies that the effect of CYP17 T34C polymorphism on susceptibility to breast cancer may be modified by other risk factors. In order to provide a more definitive conclusion, a full meta-analysis combining and summarizing 24 studies was first performed. Both traditional method and Bayesian approach were applied. Odds ratio was estimated using a dominant mode of inheritance after a biological justification for the choice of genetic model. The results of homogeneity analysis (H = 1.16, I (2) = 25.4%, and P = 0.127) suggested the presence of heterogeneity across the studies. Thus, random effects models simulated by the DerSimonian-Laird method were employed. The capability of a Bayesian approach was highlighted in the estimation of a pooled odds ratio and 95% confidence interval. The results of meta-analysis (OR = 1.001, CI = 0.832-1.208) suggest no significant association in the combined populations. Furthermore, Bayesian meta-regression and subgroup analysis were conducted to investigate the sources of heterogeneity. The risk factors evaluated in the study were menopausal status, ethnicity, age at menarche, age at first birth, parity, use of oral contraceptives, body mass index (BMI), and use of hormone repair therapy (HRT). After these population stratifications, there was evidence indicating that a possible impact of menopausal status, age at menarche, and BMI on the association between CYP17 T34C polymorphism and the risk of breast cancer.

Lack of association between CYP17 MspA1 polymorphism and breast cancer risk: a meta-analysis of 22,090 cases and 28,498 controls

Epidemiological studies have evaluated the association between CYP17 MspA1 polymorphism and breast cancer risk. However, the results remain conflicting rather than conclusive. To derive a more precise estimation of the relationship, we performed this meta-analysis. Systematic searches of the PubMed and Medline databases were performed. A total of 35 studies including 22,090 cases and 28,498 controls were identified. Genotype distributions of CYP17 in the controls of all studies were in agreement with Hardy-Weinberg equilibrium (HWE) except for three studies. When all 35 studies were pooled into the meta-analysis, there was no evidence for significant association between CYP17 MspA1 polymorphism and breast cancer risk (for A1/A2 vs. A1/A1: OR = 1.00, 95% CI = 0.96-1.04; for A2/A2 vs. A1/A1: OR = 1.03, 95% CI = 0.97-1.08; for dominant model: OR = 1.01, 95% CI = 0.97-1.05; for recessive model: OR = 1.03, 95% CI = 0.98-1.08). In the subgroup analyses by ethnicity, menopausal status and source of controls, no significant associations were found in all genetic models. When sensitivity analyses were performed by excluding HWE-violating studies, all the results were not materially altered. In summary, the meta-analysis strongly suggests that CYP17 MspA1 polymorphism is not associated with increased breast cancer risk.

No association between CYP17 T-34C polymorphism and breast cancer risk: a meta-analysis involving 58,814 subjects

Breast cancer is one of the most common malignant tumors worldwide. To date, many articles have evaluated the association between Cytochrome P450c17 (CYP17) T-34C polymorphism and breast cancer risk. However, the results remain inconclusive. In order to derive a more precise estimation of the association, a meta-analysis was performed in this study. By searching Medline, ISI Web of Knowledge, Cochrane, ScienceDirect, EBSCO, CNKI, and SinoMed databases, 43 studies including 26,008 cases and 32,806 controls were collected for CYP17 T-34C polymorphism. Crude ORs with 95% CIs were used to assess the strength of association between CYP17 T-34C polymorphism and breast cancer risk. The pooled ORs were performed for codominant model, dominant model, and recessive model, respectively. Overall, no significant associations between CYP17 T-34C polymorphism and breast cancer susceptibility were found for TT versus CC (OR = 0.96; 95% CI: 0.89-1.05), TC versus CC (OR = 0.97; 95% CI: 0.89-1.06), TT + TC versus CC (OR = 0.97; 95% CI: 0.89-1.05) and TT versus TC + CC (OR = 0.98; 95% CI: 0.93-1.03). In the stratified analysis by ethnicity, menopausal status, and sources of controls, significant associations were still not detected in all genetic models. In conclusion, this meta-analysis strongly suggests that CYP17 T-34C polymorphism is not associated with breast cancer risk.

Estrogen-biosynthesis gene CYP17 and its interactions with reproductive, hormonal and lifestyle factors in breast cancer risk: results from the Long Island Breast Cancer Study Project

The genes that are involved in estrogen biosynthesis, cellular binding and metabolism may contribute to breast cancer susceptibility. We examined the effect of the CYP17 promoter T --> C polymorphism and its interactions with the reproductive history, exogenous hormone use and selected lifestyle risk factors on breast cancer risk among 1037 population-based incident cases and 1096 population-based controls in the Long Island Breast Cancer Study Project. Overall, there were no associations between the CYP17 genotype and breast cancer risk. Among postmenopausal women, the joint exposure to higher body mass index (BMI) and the variant C allele was associated with an increased risk of breast cancer [odds ratio (OR), 1.60; 95% confidence interval (CI), 1.15-2.22]. The joint exposure to the variant C allele and long-term use of hormone replacement therapy (HRT) (>51 months) was related to an increased risk of breast cancer (OR, 1.51; 95% CI, 0.99-2.31) especially estrogen receptor-positive, progesterone receptor-positive breast cancer (OR, 1.87; 95% CI, 1.08-3.25). Among the control population, the CYP17 variant C allele was inversely associated with long-term use of postmenopausal HRT and a higher BMI in postmenopausal women. In conclusion, the findings suggest that the CYP17 variant C allele may increase breast cancer risk in conjunction with long-term HRT use and high BMI in postmenopausal women.

CYP17 genotype is associated with short menstrual cycles, early oral contraceptive use and BRCA mutation status in young healthy women

The CYP17 gene is involved in steroid hormone metabolism and has been proposed as a low penetrance gene for breast cancer. We aimed to investigate the associations between the CYP17 genotype and breast cancer risk factors, such as age at menarche, menstrual cycle length, oral contraceptive (OC) use, and BRCA mutation status among 258 healthy young women, aged < or =40, from 158 breast cancer high-risk families. Questionnaires including questions on reproductive factors and OC use were completed and blood samples were obtained from all women. CYP17 (rs743572) was genotyped with sequencing in 254 women. The main findings were that short menstrual cycles (<27 days) were significantly more common with increasing number of variant A2 alleles (8%, 17% and 32%; P(trend) = 0.002, adjusted for family clustering). Each A2 allele was associated with a 7 months earlier OC start (17.8, 17.0, and 16.6 years; P(trend) = 0.014, adjusted for age at menarche, ever-smoking and family clustering). Homozygosity for the A2 allele was more common among known non-carriers from BRCA1/2 families compared with other high-risk women OR 2.92 (95% CI 1.49-5.73; P = 0.002, adjusted for family clustering). We found no association between CYP17 genotype and age at menarche. In conclusion, this study suggests that short menstrual cycles, age at first OC use and BRCA mutation status may need to be considered in studies exploring the relationships between CYP17 and risk factors for early onset breast cancer.

Biomonitoring: Is body burden relevant to public health?

Biomonitoring is the study of the presence and concentration of chemicals in humans usually by the measurement of blood, urine or breath (exhaled air). Properly conducted, these data provide a picture of the amount of a chemical or agent actually absorbed into the body for a specific period of time. This review provides a history of biomonitoring, as well as the limitations and potential benefits of these studies. Examples of the proper and possibly improper use of biomonitoring and the impact made on our society are provided. Reasons for having comprehensive national biomonitoring programs are summarized, along with the societal benefits and risks. A brief discussion of the history of the NHANES program and select results from the 2005 Report are presented. By 2010, it has been predicted that the Centers for Disease Control (CDC) will be monitoring nearly 1000 chemicals in persons from all regions of the nation. The measurement of chemicals and biomarkers has revolutionized the field of exposure assessment. Overall, we recommend an approach of careful interpretation, understanding that the data obtained are useful for establishing baseline information about exposure, rather than equating detection with risk. We present suggestions for contextualizing biomonitoring results in order to provide the public with the tools to distinguish genuine health risks from trivial ones.

CYP17 and breast cancer: no overall effect, but what about interactions?

Three large studies published in recent issues of Breast Cancer Research reported no overall evidence of an association between the CYP17 5'-untranslated region MspA1 polymorphism and breast cancer. The present commentary briefly highlights a few important observations and discusses some additional approaches to further assessment of associations between CYP17 common variants and breast cancer risk. In particular, the evolution of evidence on breast cancer and the CYP17 MspA1 variant suggests that determination of possible interactions between gene variants postulated to influence risk and nongenetic risk factors would be more efficiently accomplished by pooled analyses, ideally involving all studies of breast cancer, than by attempting to synthesize published information. Furthermore, such analyses would also be relevant to investigation of potential gene-gene interactions between CYP17 and other common variants in genes encoding enzymes that are involved in the synthesis and inactivation of sex steroid hormones, preferably using optimal sets of single nucleotide polymorphisms.