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

Four CYP19A1 Polymorphisms and Breast Cancer Risk: A MetaAnalysis

Yougen Wu1*, Xiaofeng Qu2, Ju Xia1, Yuting Gu1, Qingqing Qian1,2 and Yang Hong1,3*

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: [email protected]

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: [email protected]

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

Many molecular epidemiological studies have investigated an association between CYP19A1 gene single-nucleotide polymorphisms (SNPs) and breast cancer risk, but results have remained controversial and inconclusive. In order to reveal the real association, we performed an updated meta-analysis including two CYP19A1 gene polymorphisms (rs700519, rs10046). Moreover, 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. A systematic database search was conducted to retrieve eligible articles. The odds ratio (OR) with 95% confidence interval (95% CI) were used to assess the strength of the association.A total of 38 eligible studies were included in the meta-analysis, and the results showed that three CYP19A1 gene polymorphisms (rs700519, rs10046, and rs2236722) had no relationship with an increased/decreased breast cancer risk in overall or ethnicity-based populations (all P values were more than 0.05); CYP19A1 rs4646 polymorphism was significant associated with an increased breast
cancer risk in overall populations under dominant genetic model (CC+AC vs. AA, OR=1.179, 95% CI=1.056 - 1.315, P-value=0.003). However, we did not find an association between CYP19A1 rs4646 polymorphism and breast cancer susceptibility among Asian populations (P value was more than 0.05).The meta-analysis indicates that CYP19A1 rs4646 polymorphism may be associated with breast cancer risk. Further epidemiological studies with larger sample sizes are needed to validate the association between CYP19A1 rs4646 polymorphism and breast cancer risk in various populations.

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.

First author (Year) Country Ethnicity Source Cases Controls
CC CT TT CT+TT CC+CT CC CT TT CT+TT CC+CT
Miyoshi (2000) [12] Japan Asian H 109 - - 89 - 85 - - 93 -
Lee (2003) [13] Korea Asian H 150 134 4 138 284 176 106 6 112 282
Hefler (2004) [14] Austria Caucasian P 367 22 0 22 389 1503 107 9 116 1610
Song (2006) [15] China Asian P 84 22 2 24 106 87 24 1 25 111
Hu (2007) [16] China Asian H 87 24 1 25 111 84 22 2 24 106
Gulyaeva (2008) [17] Russia Caucasian H 100 8 0 8 108 168 10 4 14 178
Justenhoven (2008) [18] Germany Caucasian P 549 49 1 50 598 561 60 1 61 621
Sangrajrang (2009) [19] Thailand Asian H 331 201 31 232 532 297 167 19 186 464
Wang (2009) [20] China Asian H 97 78 25 103 175 98 77 25 102 175
Khvostova (2012) [21] Russia Caucasian H 283 39 1 40 322 477 57 2 59 534
Chattopadhyay (2014) [22] India Asian P 226 115 19 134 341 258 91 11 102 349
Sun (2015) [23] China Asian H 410 111 9 120 521 392 143 11 154 535
Pan (2016) [24] China Asian H 225 87 9 96 312 289 96 5 101 385

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

First author (Year) Country Ethnicity Source Cases Controls
CC CT TT CT+TT CC+CT CC CT TT CT+TT CC+CT
Kristensen (2000) [25] Norway Caucasian HP 95 240 146 386 335 69 114 53 167 183
Haiman (2002) [26] US Caucasian H 103 240 118 358 343 134 310 167 477 444
Dunning (2004) [7] UK Caucasian H 610 1286 739 2025 1896 808 1773 1049 2822 2581
Ralph-1 (2007) [27] US Caucasian H 349 830 461 1291 1179 758 1650 883 2533 2408
Ralph-2 (2007) [27] US Caucasian H 129 231 142 373 360 222 503 274 777 725
Chen (2008) [28] China Asian H 125 308 178 486 433 163 436 277 713 599
Zhang (2008) [29] China Asian H 55 151 94 245 206 94 176 120 296 270
Iwasaki-1 (2009) [30] Japan Asian H 118 188 82 270 306 125 194 69 263 319
Iwasaki-2 (2009) [30] Japan Asian H 24 41 14 55 65 22 44 13 57 66
Iwasaki-3 (2009) [30] Brasil Caucasian H 133 179 67 246 312 121 200 58 258 321
Yoshimoto (2011) [31] Japan Asian H 239 427 160 587 666 97 120 60 180 217
Pineda (2012) [8] Spain Caucasian H 135 278 109 387 413 281 629 311 940 910
Clendenen (2013) [32] US and Sweden Mixed P 306 548 308 856 854 549 1032 523 1555 1581
Iwasaki (2013) [33] Japan Asian H 116 253 253 - 117 252 252 -
Ghisari (2014) [34] Denmark Caucasian P 23 8 0 8 31 79 29 6 35 108
Zins (2014) [35] Austria Caucasian P 65 142 67 209 207 55 136 62 198 191
Sun (2015) [23] China Asian H 111 264 155 419 375 126 290 130 420 416
Yang (2015) [36] China Asian H 30 48 34 82 78 25 82 32 114 107
Pan (2016) [24] China Asian H 49 185 100 285 234 89 192 111 303 281
Farzaneh (2016) [37] Iran Asian H 23 68 33 101 91 30 55 15 70 85
Kopp (2016) [38] Denmark Caucasian P 159 346 182 528 505 146 353 188 541 499
Ghisari (2017) [39] Denmark Caucasian P 36 68 38 106 104 47 93 56 149 140

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

First author (Year) Country Ethnicity Source Cases Controls
TT CT CC CT+CC TT+CT TT CT CC CT+CC TT+CT
Miyoshi (2000) [12] Japan Asian H 195 - - 8 - 180 - - 19 -
Hirose (2004) [40] Japan Asian H 227 20 1 21 247 561 38 4 42 599
Sobczuk (2009) [41] Poland Caucasian H 20 45 35 80 65 18 58 30 88 76
TÜZÜNER (2010) [42] Turkey Caucasian P 3 52 0 52 55 27 64 0 64 91
Ramalhinho (2012) [43] Portugal Caucasian H 40 - - 61 - 65 - - 56 -
Surekha (2014) [44] India Asian P 227 23 0 23 250 170 78 0 78 248

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

First author (Year) Country Ethnicity Source Cases Controls
CC AC AA AC+AA CC+AC CC AC AA AC+AA CC+AC
Chen (2008) [28] China Asian H 298 260 53 313 558 441 358 77 435 799
Boone (2014) [45] US Caucasian P - - 540 - 2984 - - 756 - 3452
Alanazi (2015) [46] Kingdom of Saudi Arabia Asian P 94 46 8 54 140 99 47 8 55 146
Kopp (2016) [38] Denmark Caucasian P 372 265 50 315 637 371 262 54 316 633

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).

Polymorphisms Comparisons No. of studies Sample size OR [95% CI] P value I2 (P) Model
Cases Controls
CYP19A1 R264C  
Overall TT vs. CC 12 3011 4486 1.178 [0.877, 1.583] p=0.277 0.0% (p=0.638) F
TC vs. CC 12 3799 5350 1.062 [0.951, 1.185] p=0.286 33.1% (p=0.125) F
TT+TC vs. CC 13 4099 5624 1.034 [0.894, 1.196] p=0.653 43.9% (p=0.045) R
TT vs. TC+CC 12 3901 5446 1.141 [0.853, 1.526] p=0.374 0.0% (p=0.696) F
Caucasian TT vs. CC 4 1301 2725 0.387 [0.107, 1.398] p=0.148 0.0% (p=0.735) F
TC vs. CC 4 1417 2943 0.950 [0.747, 1.207] p=0.672 0.0% (p=0.586) F
TT+TC vs. CC 4 1419 2959 0.909 [0.718, 1.152] p=0.431 0.0% (p=0.634) F
TT vs. TC+CC 4 1419 2959 0.386 [0.107, 1.394] p=0.146 0.0% (p=0.733) F
Asian TT vs. CC 8 1710 1761 1.283 [0.942, 1.747] p=0.114 0.0% (p=0.588) F
TC vs. CC 8 2382 2407 1.102 [0.920, 1.322] p=0.292 48.2% (p=0.061) R
TT+TC vs. CC 9 2680 2665 1.073 [0.895, 1.287] p=0.447 55.9% (p=0.020) R
TT vs. TC+CC 8 2482 2487 1.236 [0.913, 1.674] p=0.171 0.0% (p=0.650) F
rs10046  
Overall TT vs. CC 21 6144 8497 1.058 [0.951, 1.177] p=0.297 46.8% (p=0.010) R
TC vs. CC 21 8993 12451 1.020 [0.932, 1.117] p=0.668 45.2% (p=0.013) R
TT+TC vs. CC 22 12589 17277 1.030 [0.946, 1.121] p=0.498 46.9% (p=0.008) R
TT vs. TC+CC 21 12220 16908 1.022 [0.969, 1.079] p=0.423 25.6% (p=0.139) F
Caucasian TT vs. CC 11 4735 6710 0.979 [0.855, 1.120] p=0.755 47.6% (p=0.039) R
TC vs. CC 11 5685 8510 0.975 [0.907, 1.050] p=0.506 16.4% (p=0.288) F
TT+TC vs. CC 11 7754 11617 0.969 [0.876, 1.071] p=0.533 38.4% (p=0.093) R
TT vs. TC+CC 11 7754 11617 0.993 [0.930, 1.061] p=0.838 22.3% (p=0.231) F
Asian TT vs. CC 9 1624 1598 1.219 [0.997, 1.490] p=0.053 41.4% (p=0.091) R
TC vs. CC 9 2454 2360 1.139 [0.924, 1.404] p=0.224 59.4% (p=0.011) R
TT+TC vs. CC 10 3673 3556 1.145 [0.971, 1.352] p=0.108 50.3% (p=0.034) R
TT vs. TC+CC 9 3303 3187 1.081 [0.964, 1.212] p=0.184 32.4% (p=0.158) F
rs2236722  
Overall CC vs. TT 2 283 613 0.979 [0.464, 2.066] p=0.956 0.0% (p=0.656) F
CT vs. TT 4 617 1014 1.007 [0.295, 3.436] p=0.991 92.1% (p=0.000) R
CC+CT vs. TT 6 957 1368 0.955 [0.404, 2.258] p=0.916 90.1% (p=0.000) R
CC+CT vs. TTa 5 707 1120 1.272 [0.644, 2.513] p=0.489 77.8% (p=0.001) R
CC vs. CT+TT 2 348 709 1.281 [0.729, 2.251] p=0.389 0.0% (p=0.484) F
Caucasian CC vs. TT 1 228 565 1.050 [0.471, 2.342] p=0.905 NA R
CT vs. TT 2 120 167 2.143 [0.205, 22.448] p=0.525 90.4% (p=0.001) R
CC+CT vs. TT 3 256 318 1.931 [0.728, 5.125] p=0.186 78.9% (p=0.000) R
CC vs. CT+TT 1 100 106 1.364 [0.757, 2.459] p=0.302 NA R
Asian CC vs. TT 1 55 48 0.618 [0.069, 5.558] p=0.667 NA R
CT vs. TT 2 497 847 0.534 [0.094, 3.043] p=0.479 95.3% (p=0.000) R
CC+CT vs. TT 3 701 1050 0.475 [0.151, 1.494] p=0.203 90.4% (p=0.000) R
CC+CT vs. TTa 2 451 802 0.727 [0.234, 2.254] p=0.581 80.2% (p=0.025) R
CC vs. CT+TT 1 248 603 0.606 [0.067, 5.452] p=0.655 NA R
rs4646  
Overall CC vs. AA 3 875 1050 1.022 [0.781, 1.337] p=0.877 0.0% (p=0.933) F
AC vs. AA 3 682 806 1.065 [0.810, 1.402] p=0.651 0.0% (p=0.980) F
CC+AC vs. AA 4 4970 5925 1.179 [1.056, 1.315] p=0.003 0.0% (p=0.766) F
CC vs. AC+AA 3 1446 1717 0.971 [0.843, 1.118] p=0.680 0.0% (p=0.902) F
Caucasian CC vs. AA 1 422 425 1.083 [0.718, 1.633] p=0.704 NA R
AC vs. AA 1 315 316 1.092 [0.717, 1.664] p=0.681 NA R
CC+AC vs. AA 2 4211 4895 1.199 [1.068, 1.346] p=0.002 0.0% (p=0.614) F
CC vs. AC+AA 1 687 687 1.006 [0.814, 1.244] p=0.957 NA R
Asian CC vs. AA 2 453 625 0.978 [0.685, 1.395] p=0.901 0.0% (p=0.952) F
AC vs. AA 2 367 490 1.046 [0.729, 1.501] p=0.807 0.0% (p=0.896) F
CC+AC vs. AA 2 759 1030 1.008 [0.715, 1.422] p=0.964 0.0% (p=0.918) F
CC vs. AC+AA 2 759 1030 0.944 [0.781, 1.140] p=0.547 0.0% (p=0.911) F

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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