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

Cytochrome P450: Implications for human breast cancer

The treatment options for breast cancer include endocrine therapy, targeted therapy and chemotherapy. However, some patients with triple-negative breast cancer cannot benefit from these methods. Therefore, novel therapeutic targets should be developed. The cytochrome P450 enzyme (CYP) is a crucial metabolic oxidase, which is involved in the metabolism of endogenous and exogenous substances in the human body. Some products undergoing the metabolic pathway of the CYP enzyme, such as hydroxylated polychlorinated biphenyls and 4-chlorobiphenyl, are toxic to humans and are considered to be potential carcinogens. As a class of multi-gene superfamily enzymes, the subtypes of CYPs are selectively expressed in breast cancer tissues, especially in the basal-like type. In addition, CYPs are essential for the activation or inactivation of anticancer drugs. The association between CYP expression and cancer risk, tumorigenesis, progression, metastasis and prognosis has been widely reported in basic and clinical studies. The present review describes the current findings regarding the importance of exploring metabolic pathways of CYPs and gene polymorphisms for the development of vital therapeutic targets for breast cancer.

A Complex Systems Model of Breast Cancer Etiology: The Paradigm II Conceptual Model

BACKGROUND

The etiology of breast cancer is a complex system of interacting factors from multiple domains. New knowledge about breast cancer etiology continues to be produced by the research community, and the communication of this knowledge to other researchers, practitioners, decision makers, and the public is a challenge.

METHODS

We updated the previously published Paradigm model (PMID: 25017248) to create a framework that describes breast cancer etiology in four overlapping domains of biologic, behavioral, environmental, and social determinants. This new Paradigm II conceptual model was part of a larger modeling effort that included input from multiple experts in fields from genetics to sociology, taking a team and transdisciplinary approach to the common problem of describing breast cancer etiology for the population of California women in 2010. Recent literature was reviewed with an emphasis on systematic reviews when available and larger epidemiologic studies when they were not. Environmental chemicals with strong animal data on etiology were also included.

RESULTS

The resulting model illustrates factors with their strength of association and the quality of the available data. The published evidence supporting each relationship is made available herein, and also in an online dynamic model that allows for manipulation of individual factors leading to breast cancer (https://cbcrp.org/causes/).

CONCLUSIONS

The Paradigm II model illustrates known etiologic factors in breast cancer, as well as gaps in knowledge and areas where better quality data are needed.

IMPACT

The Paradigm II model can be a stimulus for further research and for better understanding of breast cancer etiology.

Evaluation of CYP17A1 and CYP1B1 polymorphisms in male breast cancer risk

Breast cancer in men is a rare and still poorly characterized disease. Inherited mutations in BRCA1, BRCA2 and PALB2 genes, as well as common polymorphisms, play a role in male breast cancer genetic predisposition. Male breast cancer is considered a hormone-dependent tumor specifically related to hyperestrogenism. Polymorphisms in genes involved in estrogen biosynthesis and metabolism pathways, such as CYP17A1 and CYP1B1, have been associated with breast cancer risk. Here, we aimed to investigate the role of CYP17A1 and CYP1B1 polymorphisms in male breast cancer risk. A series of 597 male breast cancer cases and 1022 male controls, recruited within the Italian Multicenter Study on male breast cancer, was genotyped for CYP17A1 rs743572, CYP1B1 rs1056836 and rs1800440 polymorphisms by allelic discrimination real-time PCR with TaqMan probes. Associations with male breast cancer risk were estimated using logistic regression. No statistically significant associations between male breast cancer risk and the three analyzed polymorphisms emerged. Similar results were obtained also when BRCA1/2 mutational status was considered. No significant differences in the distribution of the genotypes according to estrogen receptor status emerged. In conclusion, our study, based on a large series of male breast cancer cases, is likely to exclude a relevant role of CYP17A1 and CYP1B1 polymorphisms in male breast cancer predisposition. Overall, these results add new data to the increasing evidence that polymorphisms in these genes may not be associated with breast cancer risk.

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.

CYP17 genotype modifies the impact of anthropometric variation on salivary estradiol in healthy women

Several studies demonstrate that human ovarian function is responsive to the energetic environment, which has led to the development of theoretical models that explain this phenomenon. Although many genes are involved in ovarian hormone production, the possibility that genetic polymorphism may affect ovarian response to energetic conditions has not been considered. Cytochrome P450c17α is an enzyme that produces androgen precursors used to make estrogens during ovarian steroidogenesis, and is encoded by the CYP17 gene. A functionally significant variant within the promoter region of CYP17 has been linked to variation in steroid production, and some evidence suggests that this polymorphism could alter transcription of CYP17 in an insulin-dependent manner. We tested the hypothesis that the CYP17 variant affected the relationship between anthropometric measurements and salivary estradiol in healthy women in the United States (n = 28). PCR-RLFP analysis was used to genotype women for the genetic variant, and estradiol was assayed from saliva by EIA. Moderated regression analysis of these preliminary data revealed a significant interaction between waist-to-hip ratio and CYP17 genotype (P = 0.004). Our study provides evidence that gene-environment interactions should be considered in future adaptive models for human ovarian function. Moreover, our results stand to illuminate possible associations between this genetic variant and reproductive disease.

CYP17A1 T-34C polymorphism is not associated with endometrial cancer risk

The association between CYP17A1 T-34C polymorphism and endometrial cancer risk has been inconsistent and underpowered. To clarify the effect of CYP17A1 T-34C polymorphism on the risk of endometrial cancer, a meta-analysis of all available studies relating CYP17A1 T-34C polymorphism to the risk of endometrial cancer was conducted. The authors searched PubMed, EMBASE, Scopus, and VisionCite databases updated on March 2013. Data were extracted by two independent authors and pooled odds ratio (OR) with 95 % confidence interval (CI) was calculated. Finally, seven studies with 1,570 endometrial cancer cases and 2,474 controls were included in the meta-analysis. There was no statistically significant association between CYP17A1 T-34C polymorphism and endometrial cancer under heterogeneous codominant model (OR = 0.91, 95 %CI = 0.68-1.21). Although CYP17A1 T-34C polymorphism was marginally associated with endometrial cancer risk under homogeneous codominant model (OR = 0.69, 95 %CI = 0.49-0.99), the significant association was not stable after sensitivity analysis. We concluded that CYP17A1 T-34C polymorphism might not be one risk factor in the carcinogenesis of endometrial cancer. Further large and well-designed studies are needed to confirm this association.

CYP17 gene polymorphisms and prostate cancer risk: a meta-analysis based on 38 independent studies

BACKGROUND

The results of recent published studies focusing on CYP17 polymorphisms in prostate cancer (PCa) susceptibility are often conflicting. We performed a meta-analysis based on 38 independent studies to evaluate the association.

METHODS

Data were collected from the following electronic databases: PubMed, Excerpta Medica Database, and Chinese Biomedical Literature Database, with the last report up to September 2010. Meta-analysis was conducted in a fixed/random effect model.

RESULTS

Thirty-eight independent studies including 34,782 cases and 38,626 controls on the association of CYP17 gene polymorphisms with PCa risk in different ethnic groups were identified. The meta-analysis was performed for five polymorphisms: rs743572 (A1/A2, 38 studies), rs6162 (C/T, 3 studies), rs619824 (C/A, 4 studies), rs2486758 (T/C, 4 studies), and rs10883782 (A/G, 4 studies). When all groups were pooled, we did not detect the association of rs743572 polymorphism with PCa risk. In the subgroup analysis, a significant association of rs743572 polymorphism and PCa was found in Black population (A2/A2 vs. A1/A1 + A2/A1: OR = 1.70, 95% CI = 1.08-2.69, P = 0.02), but not in Caucasian or Asian population. For other polymorphisms, we found that rs619824 polymorphism was associated with a significant decreased risk of PCa (A vs. C: OR = 0.95, 95% CI = 0.92-0.99, P = 0.01), and rs2486758 polymorphism was associated with a significant increased risk of PCa (C vs. T: OR = 1.07, 95% CI = 1.03-1.12, P = 0.002).

CONCLUSION

This meta-analysis suggests that rs743572 polymorphism is associated with PCa risk in Black population, but not in Caucasian or Asian population. Moreover, our study suggests that rs619824 and rs2486758 polymorphisms are associated with PCa risk.