Research Article, J Biochem Physiol Vol: 1 Issue: 1

Four CYP19A1 Polymorphisms and Breast Cancer Risk: A MetaAnalysis

Yougen Wu^1*, Xiaofeng Qu², Ju Xia¹, Yuting Gu¹, Qingqing Qian^1,2 and Yang Hong^1,3*

¹National Institute of Clinical Research, The Fifth People’s Hospital of Shanghai, Fudan University, Shanghai 200240, China

²Department of Pharmacy, The Fifth People’s Hospital of Shanghai, Fudan University, Shanghai 200240, China

³Department of Osteology, The Fifth People’s Hospital of Shanghai, Fudan University, Shanghai 200240, China

*Corresponding Author : Yougen Wu
National Institute of Clinical Research, The Fifth People’s Hospital of Shanghai, Fudan University, Shanghai 200240, China
Tel: +86 21 24289472
Fax: +86 21 24289472
E-mail: wu05055225@126.com

Yang Hong
National Institute of Clinical Research, The Fifth People’s Hospital of Shanghai, Fudan University, Shanghai 200240, China
Tel: +86 21 24289472
Fax: +86 21 24289472
E-mail: hongyang@fudan.edu.cn

Received: February 07, 2018 Accepted: February 22, 2018 Published: February 28, 2018

Citation: Wu Y, Qu X, Xia J, Gu Y, Qian Q, et al. (2018) Four CYP19A1 Polymorphisms and Breast Cancer Risk: A Meta-Analysis. J Biochem Physiol 1:1.

Abstract

Keywords: CYP19A1; Polymorphism; Breast cancer; Risk; Meta-analysis

Introduction

Breast cancer is the most common malignancy among women worldwide. Numerous studies suggest that breast carcinogenesis and progression is influenced by steroid hormones, particularly estrogens [1,2].

Some genetic variations of steroid hormone pathway genes involved in the metabolism of androgens and estrogens are associated with the risk of breast cancer [3,4]. The cytochrome P450 family 19 subfamily a member 1 (CYP19A1) gene is located on chromosome 15q21.2 region and encodes aromatase, which converts androstenedione and testosterone into estrone and estradiol, respectively [5]. CYP19A1 mutations can alter aromatase activity, which affects estrogen levels indirectly, and may ultimately alter susceptibility to breast cancer [6,7].

To date, an increasing number of studies have evaluated the potential association between the CYP19A1 polymorphisms and the risk of breast cancer in diverse populations. Four CYP19A1 genetic polymorphisms including rs700519 (Arg264Cys) located in exon 7 codon 264, the rs10046 located in the 3’ untranslated region (3’- UTR), CYP19A1 polymorphism at codon 39 Trp/Arg (rs2236722), and the rs4646 located in the 3’-UTR have been focused on a large scale. However, the results are inconsistent and inconclusive.

One previous meta-analysis suggested no association between CYP19A1 rs700519 polymorphism and breast cancer risk [6], and another meta-analysis indicated that rs10046 polymorphism on CYP19A1 did not affect breast cancer risk [8]. However, limited studies were included in both meta-analyses. Recently, several more studies assessing the association between the CYP19A1 polymorphisms (rs700519 and rs10046) and breast cancer risk have been published. We therefore conducted an updated meta-analysis to clarify the association of the CYP19A1 polymorphisms (rs700519 and rs10046) with risk of breast cancer in different populations. In addition, we performed a meta-analysis of another two CYP19A1 (rs2236722 and rs4646) gene polymorphisms for the first time to evaluate their relevance in susceptibility to breast cancer risk.

Materials and Methods

Literature and search strategy

PubMed, Web of Science and Embase database were searched (until April 30, 2017) for eligible articles. The search strategy used combinations of the following keywords: “CYP19” or “CYP19A1” and “polymorphism” or “variant” or “mutation” and “breast cancer”.

Inclusion and exclusion criteria

Eligible studies had to meet the following criteria: (1) studies addressed the potential association of four CYP19A1 genetic polymorphisms [rs700519, rs10046, rs2236722, and rs4646] and breast cancer risk, (2) studies based on case–control design and (3) studies with sufficient data about genotype distribution of controls and cases. The exclusion criteria were: (1) studies with no sufficient data about genotype distribution of controls and cases, (2) duplicate publications and (3) comments, case reports, abstract and review articles (including meta-analysis).

Data extraction

The following data was extracted: (1) name of the first author, (2) year of publication, (3) country of origin, (4) ethnicity, (5) source of control groups ( hospital-based or population-based controls or mixed), (6) number of genotyped cases and controls, Data was extracted from the final selected studies independently by two authors.

Statistical analysis

The relationship between CYP19A1 polymorphisms and breast cancer risk was assessed by a combined odds ratio (OR) with corresponding 95% confidence interval (95% CI) under co-dominant model, dominant model, and recessive model, respectively. Subgroup analyses based on ethnicity (Caucasians/Asians) was performed. The significance of the pooled OR estimate was determined by a Z test. The statistical significance was set at p value < 0.05.

Cochran’s chi-square-based Q and I² statistics were used to evaluate heterogeneity across studies. If heterogeneity did not exist (P value > 0.1 for the Q test) among studies, the fixed effects model was used [9]; otherwise, the random effects model was applied [10]. I2 statistic was calculated to quantify the proportion of the total heterogeneity among studies. Generally, I² values of 75%, 50%, and 25% indicated high, moderate, and low heterogeneity, respectively.

Sensitivity analysis was conducted to assess the influence of each study on the overall estimate by excluding studies one by one and recalculating the combined results of the remaining studies.

Publication bias of literatures was detected by funnel-plot analysis and Egger’s test [11]. Data analyzes were performed with STATA version 11.0 (Stata Corporation, College Station, Texas, USA).

Results

Characteristics of the studies

We retrieved a total of 38 studies according to the inclusion/ exclusion criteria, of which included a total of 13 studies containing 4,099 cases and 5,624 controls for the rs700519 polymorphism (Table 1) [12-24] , 22 studies containing 12,589 cases and 17,277 controls referring to the rs10046 polymorphism (Table 2) [7,8,23-39], 6 studies with 957 cases and 1,368 controls involved in the rs2236722 polymorphisms (Table 3) [12,40-44], and 4 studies with 4,970 cases and 5,925 controls involved in the rs4646 polymorphism (Table 4) [28,38,45,46]. A detailed flow chart of the exclusion and inclusion process was showed in Figure 1.

Table 1: Characteristics of case–control studies included in CYP19A1 R264C polymorphism (rs700519) and breast cancer risk.

Table 2: Characteristics of case–control studies included in CYP19A1 polymorphism (rs10046) and breast cancer risk.

Table 3: Characteristics of case–control studies included in CYP19A1 polymorphism (rs2236722) and breast cancer risk.

Table 4: Characteristics of case–control studies included in CYP19A1 polymorphism (rs4646) and breast cancer risk.

Figure 1: Flow chart of meta-analysis for exclusion/inclusion of studies. Thirty-eight eligible studies were included.

Quantitative synthesis

The summary of meta-analysis and heterogeneity test results for CYP19A1 polymorphisms with breast cancer risk were presented in Table 5. For rs700519 polymorphism, no significant associations were found with the risk of breast cancer in overall or race-based populations in any of the genetic models tested. For CYP19A1 rs10046 polymorphism, we found no significant association with breast cancer risk in overall population. The analysis by racial/ethnic subgroups also failed to produce significant associations in any of the genetic models tested. Furthermore, we observed no significant association for CYP19A1 rs2236722 polymorphism with the risk of breast cancer in overall or ethnicity-based populations. I2 > 75.0 % was observed in overall analyses. Sensitivity analysis was conducted to investigate the influence of each study on the overall pooled OR. The exclusion of Surekha et al., 2014 study made the biggest drop for heterogeneity values and still no significant association of the CYP19A1 rs2236722 polymorphism with breast cancer risk was observed (data not shown).

Table 5: Meta-analysis of CYP19A1 genes polymorphisms and breast cancer risk.

For CYP19A1 rs4646 polymorphism, the meta-analysis showed that individuals with the CC/AC genotype were significantly associated with an increased breast cancer risk as compared with AA genotype in overall or Caucasian populations (Overall: OR=1.179, 95% CI=1.056–1.315; Caucasian: OR=1.199, 95% CI=1.068-1.346). However, we found no evidence of association between CYP19A1 rs4646 polymorphism and susceptibility to breast cancer among Asian women (Table 5, Figure 2).

Figure 2: Meta-analysis of OR for rs4646 polymorphism associated with breast cancer (CC+AC vs. AA).

Potential publication bias

The shape of funnel plot did not show obvious asymmetry (Figure 3). Egger’s test revealed no statistical evidence for publication bias (All P>0.05).

Figure 3: Funnel plot analysis to detect publication bias. Each point represents a separate study for the indicated association. OR, odds ratio Log (OR), natural logarithm of OR. OR is plotted on the horizontal axis and the standard error of log (OR) on the vertical axis. (a) Funnel plot for the association between R264C polymorphism and breast cancer risk under dominant model; (b) Funnel plot for the association between rs10046 polymorphism and breast cancer risk under dominant model; (c) Funnel plot for the association between rs2236722 polymorphism and breast cancer risk under dominant model; (d) Funnel plot for the association between rs4646 polymorphism and breast cancer risk under dominant model.

Discussion

CYP19A1 is a key estrogen biosynthesis enzyme and play an important role in the development of breast cancer. In the current study, we have analyzed an almost 1.63 and 1.83 fold larger number of studies than Ma [6] and Pineda [8], respectively. We found no statistically significant association between breast cancer risk and CYP19A1 polymorphisms (rs700519 and rs10046), which is consistent with the results of the previous meta-analysis for breast cancer [6,8]. Our results confirmed and established the trend of association between the CYP19A1 polymorphisms (rs700519 and rs10046) and breast cancer risk indicated by the meta-analysis of Ma and Pineda [6,8]. To explain the result, we can speculate that the effect of CYP19A1 rs700519 polymorphism on breast cancer risk is limited. CYP19A1 rs700519 polymorphism is not the only factor that influences aromatase activity for estrogens biosynthesis. In fact, R264C and R264H polymorphisms differentially influenced human aromatase activity and function [47].

The present meta-analysis is the first to evaluate the association between CYP19A1 polymorphisms (rs2236722 and rs4646) and breast cancer risk. Pooled analysis found no evidence of association between CYP19A1 polymorphism (rs2236722) and susceptibility to breast cancer. In addition, the sensitivity analysis results showed that Surekha et al., 2014 study was the source of heterogeneity [44]. The conclusion remained unchanged even after the fore-mentioned study was excluded. Overall, the CYP19A1 rs2236722 is a rare polymorphism, the result should be interpreted cautiously owing to the relatively small sample size within these two ethnic populations for CYP19A1 rs2236722 polymorphism. Relationship between CYP19A1 rs2236722 polymorphism and CYP19A1 enzyme activity are also needed for confirmation in the future studies.

It is particularly worth noting that the association of CYP19A1 rs4646 polymorphism with breast cancer risk was observed in overall and Caucasian populations, but not in Asian populations. One possibility is that the sample size for rs4646 among Asian populations is too small to show significant evidence. It is also possible that the effect strength of genetic alterations predisposing to human diseases is different in different racial populations [48].

Conclusion

The present meta-analysis suggests that three variants (rs700519, rs10046, and rs2236722) in the CYP19A1 gene are not significantly associated with breast cancer risk. One SNP (rs4646) may contribute to increasing susceptibility to breast cancer. More well-designed association studies with larger sample size of different ethnic populations will be needed to confirm the risk identified in the current meta-analysis.

Acknowledgement

Financial support: No financial support was received for the study.

Conflict of interest

Yougen Wu and Xiaofeng Qu have contributed equally to the work

The authors declare no conflict of interest.

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