# Association of the Three Common SNPs of Cyclooxygenase-2 Gene (rs20417, rs689466, and rs5275) with the Susceptibility of Breast Cancer: An Updated Meta-Analysis Involving 34,590 Subjects

Authors: Zhi-Jun Dai; Yong-Ping Shao; Xiao-Bin Ma; Dan Xu; Wei Tang; Hua-Feng Kang; Shuai Lin; Meng Wang; Hong-Tao Ren; Xi-Jing Wang
Journal: Disease Markers
 (2014)

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## Abstract

Several single nucleotide polymorphisms have been identified in cyclooxygenase-2 (COX-2) genes (e.g., −765 G>C (rs20417), −1195G>A (rs689466), and 8473 C>T (rs5275)). The association of these SNPs with the risk of different cancer types is still controversial. This study aims to evaluate the correlation between these SNPs and breast cancer risk in different ethnic groups. We have searched PubMed, Web of Knowledge, and Embase for relevant studies. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to estimate the strength of the associations. A total of 13 studies (15,330 cases and 19,260 controls) were eligible for meta-analysis. This meta-analysis showed that COX-2 rs20417 polymorphism was correlated with an increased risk of breast cancer in Caucasians, while rs689466 was associated with a decreased risk of breast cancer in Caucasians. The rs5275 polymorphism had no association with breast cancer risk.


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## Body

## 1. Introduction

Breast cancer is the most common cancer in women worldwide [1]. It is a multifactorial disease caused by complex genetic and environmental factors [2]. Allele variants in oncogenes are candidate genetic risk factors that may alter breast cancer onset and outcome. Previous researches have suggested that the risk of breast cancer is affected by multiple environmental factors as well as genetic alterations, such as genetic polymorphisms [3, 4].Cyclooxygenase (COX), also known as prostaglandin endoperoxide synthetase (PTGS), plays an important role in the inflammatory process by converting arachidonic acid to prostaglandins (PG) [5]. There are two COX isoforms: COX-1 and COX-2. COX-1 is present in many tissues and is involved in PG synthesis. By contrast, COX-2 is not detected in most normal tissues but is often overexpressed in many tumor types [6]. COX-2 can be rapidly induced by a variety of mitogenic and inflammatory stimuli and elevate the production of prostaglandins, which contribute to tumor occurrence and progression by modulating cell proliferation, apoptosis, and angiogenesis [6–8]. In breast cancer, several studies have suggested that moderate to high COX-2 expression is related to the genesis of mammary tumors and the expression level is associated with the aggressiveness of breast cancer, including large tumor size, positive axillary lymph node metastases, and HER2-positive tumor status [9–11]. Targeted inhibition of COX-2 blocked the proliferation of breast cancer cell linesin vitro and prevented the occurrence of rat breast cancer chemically induced by DMBA [12].Genetic polymorphisms in COX-2 have been shown to alter its expression and influence the susceptibility to various carcinomas [13, 14], including breast cancer [15]. The human COX-2 gene (also known as PTGS2) is located on chromosome 1q25.2-q25.3 and consists of 10 exons spanning 8.3 kb [16]. Several single-nucleotide polymorphisms (SNPs) in COX-2 have been identified, of which three functional SNPs, −765 G>C (rs20417), −1195G>A (rs689466) in the promoter region, and the 8473 C>T (rs5275) in the 3′UTR of COX-2, have been widely investigated [13–15].Previous functional studies have suggested that the rs20417 polymorphism may eliminate a Sp1-binding site but create an E2F binding site and result in altered COX-2 expression [13]. The rs5275 polymorphism was shown to be associated with the alteration of mRNA level of the gene as sequences within the 3′UTR are important for message stability and translational efficiency [17]. There are many studies that have investigated the association between COX-2 polymorphisms and breast cancer risk. However, the results are inconsistent. For example, Fawzy et al. reported that rs5275 polymorphism was associated with the BC in Egyptian women. The individuals with rs5275 CC genotypes showed significant increase in plasma PGE2 levels [18]. However, Brasky et al. demonstrated that rs5275 had no association with breast cancer risk in Caucasians [19]. In our previous study, variant genotypes of COX-2 rs20417 G>C (GC/CC) were associated with increased breast cancer risk. Furthermore, the increased risk was more prominent among the younger subjects (OR = 1.61, 95% CI = 1.00–2.61). The variant genotypes were also associated with tumor size (OR = 3.01, 95% CI = 1.47–6.12) [20].To clarify the role of COX-2 polymorphisms in breast cancer risk, Yu et al. conducted a meta-analysis on the associations between several COX-2 polymorphisms and breast cancer risk. The results suggested borderline increased risk of breast cancer with rs5277 but no significant associations with the rs20417 and rs5275 polymorphisms [15]. However, of the studies included in their meta-analysis, only two studies were carried out in Asians [23, 28] and the rs689466 polymorphism was not involved. To make a more precise estimation, we conduct the present meta-analysis on all eligible case-control studies to evaluate the association between the three common SNPs (rs20417, rs689466, and rs5275) and breast cancer susceptibility.


## 2. Materials and Methods

### 2.1. Publication Search

We searched the electronic databases of PubMed, Web of Knowledge, and Embase to collect articles with case-control studies related to the association of COX-2 polymorphisms with breast cancer risk. The keywords were as follows: breast cancer/breast carcinoma, Cyclooxygenase-2/COX-2/PTGS, and polymorphism/genotype/SNP. All qualified studies prior to February 28, 2014, were included. The eligible literature must be published in English. Furthermore, reference lists of main reports and review articles were also reviewed manually to identify additional relevant publications.


### 2.2. Selection Criteria

The following criteria were used to select studies for further meta-analysis: (1) case-control studies; (2) studies that evaluated the associations between COX-2 polymorphisms and breast cancer risk; (3) studies that contained at least two comparison groups (cancer versus control); (4) studies that included detailed genotyping data.


### 2.3. Data Extraction and Synthesis

Articles were reviewed independently by two reviewers and data with discrepancies were discussed by all authors. For each included study, the following information was collected: first author, year of publication, country of origin, ethnicity, source of control, total number of cases and controls, and genotyping methods as well as number of cases and controls with the different genotypes. Different ethnic groups were categorized as Caucasian, Asian, African, and “mixed.” All the case and control groups were well controlled. The noncancer controls had no history of gynecologic disease, and there was no present evidence of any malignant disease. The histories of chronic inflammatory condition or other malignancies of the patients were not considered in this study.


### 2.4. Statistical Analysis

The associations between COX-2 polymorphisms and breast cancer risk were measured by odds ratio (OR) with 95% confidence interval (CI). The significance of the pooled OR was determined by theZ test.The meta-analysis assessed association by using 4 different genetic models: (1) dominant genetic model—the comparison groups were the wild-type homozygous genotype versus the variant allele-positive genotypes (AA + Aa versus aa); (2) recessive genetic model—the comparison groups were the variant homozygous genotype versus the rest (AA versus aa + Aa); (3) homozygous genetic model—comparison was between the 2 homozygous genotypes (AA versus aa); and (4) allele contrast genetic model—the comparison was between the heterozygous and the homozygous wild-type genotype groups (Aa versus aa (where “a” is the wild-type allele and “A” is the variant allele)).Statistical heterogeneity among studies was assessed with theQ and I
2 statistics. If the P value of heterogeneity test was more than 0.1 (P
≥
0.1), the pooled OR estimate of the study was calculated by the fixed-effects model. Otherwise, the random-effects model was used [11]. The value of the I index is used to assess the degree of heterogeneity (I
2 < 25%: no heterogeneity; 25% < I
2 < 50%: moderate heterogeneity; 50% < I
2 < 75%: high heterogeneity; I
2 > 75%: extreme high heterogeneity). Publication bias was evaluated by the funnel plot and further assessed by the method of Egger’s linear regression test. All statistical analyses were carried out with the review manager version 5.1 (Revman; The Cochrane Collaboration, Oxford, UK).


## 2.1. Publication Search

We searched the electronic databases of PubMed, Web of Knowledge, and Embase to collect articles with case-control studies related to the association of COX-2 polymorphisms with breast cancer risk. The keywords were as follows: breast cancer/breast carcinoma, Cyclooxygenase-2/COX-2/PTGS, and polymorphism/genotype/SNP. All qualified studies prior to February 28, 2014, were included. The eligible literature must be published in English. Furthermore, reference lists of main reports and review articles were also reviewed manually to identify additional relevant publications.


## 2.2. Selection Criteria

The following criteria were used to select studies for further meta-analysis: (1) case-control studies; (2) studies that evaluated the associations between COX-2 polymorphisms and breast cancer risk; (3) studies that contained at least two comparison groups (cancer versus control); (4) studies that included detailed genotyping data.


## 2.3. Data Extraction and Synthesis

Articles were reviewed independently by two reviewers and data with discrepancies were discussed by all authors. For each included study, the following information was collected: first author, year of publication, country of origin, ethnicity, source of control, total number of cases and controls, and genotyping methods as well as number of cases and controls with the different genotypes. Different ethnic groups were categorized as Caucasian, Asian, African, and “mixed.” All the case and control groups were well controlled. The noncancer controls had no history of gynecologic disease, and there was no present evidence of any malignant disease. The histories of chronic inflammatory condition or other malignancies of the patients were not considered in this study.


## 2.4. Statistical Analysis

The associations between COX-2 polymorphisms and breast cancer risk were measured by odds ratio (OR) with 95% confidence interval (CI). The significance of the pooled OR was determined by theZ test.The meta-analysis assessed association by using 4 different genetic models: (1) dominant genetic model—the comparison groups were the wild-type homozygous genotype versus the variant allele-positive genotypes (AA + Aa versus aa); (2) recessive genetic model—the comparison groups were the variant homozygous genotype versus the rest (AA versus aa + Aa); (3) homozygous genetic model—comparison was between the 2 homozygous genotypes (AA versus aa); and (4) allele contrast genetic model—the comparison was between the heterozygous and the homozygous wild-type genotype groups (Aa versus aa (where “a” is the wild-type allele and “A” is the variant allele)).Statistical heterogeneity among studies was assessed with theQ and I
2 statistics. If the P value of heterogeneity test was more than 0.1 (P
≥
0.1), the pooled OR estimate of the study was calculated by the fixed-effects model. Otherwise, the random-effects model was used [11]. The value of the I index is used to assess the degree of heterogeneity (I
2 < 25%: no heterogeneity; 25% < I
2 < 50%: moderate heterogeneity; 50% < I
2 < 75%: high heterogeneity; I
2 > 75%: extreme high heterogeneity). Publication bias was evaluated by the funnel plot and further assessed by the method of Egger’s linear regression test. All statistical analyses were carried out with the review manager version 5.1 (Revman; The Cochrane Collaboration, Oxford, UK).


## 3. Results

### 3.1. Characteristics of Studies

As shown in Figure1, a total of 378 potential publications were initially extracted. After reading the abstracts, we excluded 176 irrelevant studies, 113 studies with insufficient data, and 53 duplicated ones. In-depth reading of the remaining articles led to further exclusion of 12 articles with no detailed genotyping data, 6 studies with no case-control, 3 laboratory studies, and 4 systematic review articles. Finally, 13 studies from 11 articles were collected for this meta-analysis.Figure 1
Flow chart of studies selection in this meta-analysis.Overall, 13 studies on COX-2 polymorphisms and breast cancer risk were identified [16, 18–27], including a total of 15,330 cases and 19,260 case-free controls. The characteristics of the included studies are listed in Table 1. Among the eligible 13 studies, nine studies were carried out in Caucasians from USA, Austria, Denmark, Brazil, and nine European countries. Two were based on Asian background and were carried out in China. Only one study carried out in Egypt was based on African background. One study was on mixed ethnic groups. All studies were case-controlled. All breast cancers were confirmed by histology or pathology. Moreover, controls were mainly matched by age. Five studies were hospital-based and eight were population-based.Table 1
Characteristics of the studies included in the meta-analysis.
First author
Year
Country
Ethnicity
Study design
Genotyping method
Source of control
Total sample size (case/control)
SNP number
Gao [20]
2014
China
Asian
CC
TaqMan
Hospital
465/799
1, 3
Fawzy [18]
2013
Egypt
African
CC
PCR-RFLP
Hospital
160/150
3
Brasky [19]
2011
USA
Caucasian
CC
TaqMan
Population
1077/1910
2, 3
Piranda [16]
2010
Brazil
Caucasian
CC
TaqMan
Population
318/273
1, 2, 3
Dossus [21]
2010
USA, Europe
Caucasian
CC
Illumina
Population
6292/8135
1, 2, 3
Abraham [22]
2009
EPIC
Caucasian
CC
TaqMan
Population
2200/2280
3
Gao [23]
2007
China
Asian
CC
PCR-RFLP
Hospital
601/643
1, 2, 3
Cox 1 [24]
2007
USA
Caucasian
CC
TaqMan
Population
1270/1762
1, 3
Cox 2 [24]
2007
USA
Caucasian
CC
TaqMan
Population
317/634
3
Cox 3 [24]
2007
USA
Caucasian
CC
TaqMan
Population
702/703
3
Vogel [25]
2007
Denmark
Caucasian
CC
TaqMan
Hospital
361/361
3
Langsenlehner [26]
2006
Austria
Caucasian
CC
TaqMan
Hospital
500/500
3
Shen [27]
2006
USA
Mixed
CC
PCR-RFLP
Population
1067/1110
1, 3
CC: case-control; PCR: polymerase chain reaction; RFLP: restriction fragment length polymorphism. EPIC: European Prospective Investigation of Cancer (a prospective study of diet and cancer being carried out in nine European countries). SNP: single-nucleotide polymorphisms; SNP number 1: −765G>C (rs20417); 2: −1195G>A (rs689466); 3: 8473T>C (rs5275).


### 3.2. Meta-Analysis Results

As shown in Table2, the frequencies of the minor allele varied widely across the eligible studies, ranging from 0.06 to 0.28 (rs20417), 0.12 to 0.54 (rs689466), and 0.18 to 0.45 (rs5275). The average frequencies of the minor allele in the three polymorphisms were 0.17, 0.22, and 0.33, respectively.Table 2
COX-2 polymorphisms genotype distribution and allele frequency in cases and controls.
First author
Genotype (N)
Allele frequency (N)
MAF
Case
Control
Case
Control
Total
AA
AB
BB
Total
AA
AB
BB
A
B
A
B
rs20417
Gao 2014 [20]
465
394
67
4
799
719
76
4
855
75
1514
84
0.08
Piranda 2010 [16]
308
157
127
24
264
129
117
18
441
175
375
153
0.28
Dossus 2010 [21]
6254
4394
1646
214
8092
5694
2166
232
10434
2074
13554
2630
0.17
Gao 2007 [23]
601
526
73
2
643
582
59
2
1125
77
1223
63
0.06
Cox 1 2007 [24]
1243
865
336
42
1715
1185
485
45
2066
420
2855
575
0.17
Shen 2006 [27]
1067
670
387
1105
691
414
—
—
—
—
—
rs689466
Brasky 2011 [19]
1077
660
271
34
1910
1199
471
54
1591
339
2869
579
0.18
Piranda 2010 [16]
289
224
62
3
245
190
51
3
510
68
431
57
0.12
Dossus 2010 [21]
6247
4020
1928
299
8115
5143
2562
410
9968
2526
12848
3382
0.20
Gao 2007 [23]
601
121
305
175
643
150
327
166
547
655
627
659
0.54
rs5275
Gao 2014 [20]
465
299
132
34
799
515
244
40
730
200
1274
324
0.22
Fawzy 2013 [18]
160
53
71
36
150
69
67
14
177
143
205
95
0.45
Brasky 2011 [19]
1077
432
447
108
1910
732
782
226
1311
663
2246
1234
0.31
Piranda 2010 [16]
294
125
149
20
244
120
99
25
399
189
339
149
0.32
Dossus 2010 [21]
6133
2697
2664
772
7946
3512
3501
933
8058
4208
10525
5367
0.34
Abraham 2009 [22]
2172
927
985
260
2265
996
1010
259
2839
1505
3002
1528
0.35
Gao 2007 [23]
601
404
179
18
643
429
194
20
987
215
1052
234
0.18
Cox 1 2007 [24]
1249
541
567
141
1720
699
808
213
1649
849
2206
1234
0.34
Cox 2 2007 [24]
301
140
131
30
610
270
259
81
411
191
799
421
0.32
Cox 3 2007 [24]
644
281
296
67
651
278
294
79
858
430
850
452
0.33
Vogel 2007 [25]
361
167
150
44
361
155
165
41
484
238
475
247
0.33
Langsenlehner 2006 [26]
500
214
224
62
500
234
232
33
652
348
700
298
0.35
Shen 2006 [27]
1060
475
585
1102
467
635
—
—
—
—
—
A represents the major allele; B represents the minor allele. MAF: minor allele frequencies.The main results of this meta-analysis were listed in Table3. There were 6 studies with 9,938 cases and 12,618 controls for rs20417. As shown in Table 3 and Figure 2, rs20417 polymorphism has association with breast cancer risk in the overall population based on homozygote comparison (CC versus GG: OR = 1.21, 95% CI = 1.02–1.42, P
=
0.03) and the recessive model (CC versus GG + GC: OR = 1.22, 95% CI = 1.03–1.43, P
=
0.02). However, there are no significant associations in other genetic models (C versus G: OR = 1.04, 95% CI = 0.98–1.10, P
=
0.17; heterozygote comparison (GC versus GG): OR = 0.97, 95% CI = 0.91–1.03, P
=
0.35; dominant model (GC + CC versus GG): OR = 1.01, 95% CI = 0.96–1.08, P
=
0.64). In the stratified analysis by ethnicity, the effects remained in Caucasians (homozygote comparison: OR = 1.20, 95% CI = 1.02–1.42, P
=
0.03; recessive model: OR = 1.21, 95% CI = 1.03–1.43, P
=
0.02), but not in Asians (Table 3).Table 3
Meta-analysis of the association between COX-2 polymorphisms and breast cancer risk.
Comparisons
OR
95% CI
P value
Heterogeneity
Effects model
I
2
P value
B versus A
rs20417
1.04
0.98–1.10
0.17
56%
0.06
R
Caucasian
1.02
0.96–1.08
0.50
0%
0.92
F
Asian
1.45
1.15–1.84
0.002
0%
0.47
F
rs689466
0.99
0.94–1.04
0.69
33%
0.21
F
Caucasian
0.97
0.92–1.03
0.34
0%
0.58
F
Asian
1.14
0.97–1.33
—
—
—
—
rs5275
1.01
0.98–1.05
0.50
56%
0.01
R
Caucasian
1.00
0.97–1.04
0.80
41%
0.09
R
Asian
1.03
0.89–1.19
0.70
0%
0.51
F
BB versus AA
rs20417
1.21
1.02–1.42
0.03
0%
0.97
F
Caucasian
1.20
1.02–1.42
0.03
0%
0.92
F
Asian
1.54
0.49–4.78
0.46
0%
0.68
F
rs689466
1.01
0.88–1.15
0.93
22%
0.28
F
Caucasian
0.95
0.82–1.10
0.52
0%
0.69
F
Asian
1.31
0.95–1.80
—
—
—
—
rs5275
1.04
0.96–1.12
0.34
66%
0.0008
R
Caucasian
1.01
0.94–1.10
0.72
58%
0.01
R
Asian
1.26
0.85–1.85
0.25
7%
0.30
F
AB versus AA
rs20417
0.97
0.91–1.03
0.35
93%
<0.00001
R
Caucasian
0.94
0.88–1.01
0.07
95%
<0.00001
R
Asian
1.49
1.15–1.91
0.002
0%
0.53
F
rs689466
0.98
0.92–1.05
0.59
0%
0.59
F
Caucasian
0.97
0.91–1.04
0.44
0%
0.74
F
Asian
1.16
0.87–1.54
—
—
—
—
rs5275
0.99
0.95–1.04
0.81
0%
0.56
F
Caucasian
0.99
0.95–1.04
0.81
0%
0.47
F
Asian
0.96
0.80–1.14
0.96
0%
0.78
F
AB + BB versus AA
rs20417
1.01
0.96–1.08
0.64
54%
0.05
R
Caucasian
1.00
0.93–1.06
0.93
0%
0.84
F
Asian
1.49
1.16–1.91
0.002
0%
0.49
F
rs689466
0.90
0.87–0.95
0.0005
94%
<0.00001
R
Caucasian
0.88
0.83–0.94
<0.0001
96%
<0.00001
R
Asian
1.21
0.92–1.58
—
—
—
—
rs5275
1.02
0.98–1.07
0.33
62%
0.002
R
Caucasian
1.02
0.97–1.07
0.42
66%
0.002
R
Asian
0.99
0.84–1.17
0.92
0%
0.86
F
BB versus AA + AB
rs20417
1.22
1.03–1.43
0.02
0%
0.98
F
Caucasian
1.21
1.03–1.43
0.02
0%
0.94
F
Asian
146
0.47–4.56
0.51
0%
0.70
F
rs689466
1.01
0.89–1.15
0.85
0%
0.48
F
Caucasian
0.96
0.83–1.11
0.59
0%
0.76
F
Asian
1.18
0.92–1.51
—
—
—
—
rs5275
1.04
0.97–1.12
0.27
65%
0.0009
R
Caucasian
1.02
0.95–1.10
0.60
60%
0.01
R
Asian
1.28
0.87–1.87
0.21
15%
0.28
F
A: represents the major allele; B: represents the minor allele; F: fixed-effects model; R: random-effects model.Figure 2
. Forest plots of COX-2 rs20417 polymorphism and breast cancer risk in the overall population (CC versus GG + GC). The squares and horizontal lines correspond to the study specific OR and 95% CI. The area of the squares reflects the weight (inverse of the variance). The diamond represents the summary OR and 95% CI.There were 4 studies with 8,214 cases and 10,202 controls for assessing the relationship between COX-2 rs689466 polymorphism and breast cancer susceptibility. As shown in Table3 and Figure 3, there was no association in these four genotypes (A versus G: OR = 0.99, 95% CI = 0.94–1.04, P
=
0.69; homozygote comparison (AA versus GG): OR = 1.01, 95% CI = 0.88–1.15, P
=
0.93; heterozygote comparison (AG versus GG): OR = 0.98, 95% CI = 0.92–1.05, P
=
0.59; recessive model (AA versus GG + AG): OR = 1.01, 95% CI = 0.89–1.15, P
=
0.85). However, rs689466 polymorphism has association with breast cancer risk based on the recessive model (AA + AG versus GG: OR = 0.90, 95% CI = 0.87–0.95, P
=
0.002). In the stratified analysis, when analyzed by the dominant model, the OR was 0.88 (95% CI = 0.83–0.94) (P
<
0.0001) among Caucasians. These results suggested that the individuals with AA or AG alleles have a 12% decreased risk of breast cancer compared with those with GG allele in Caucasians.Figure 3
Forest plots of COX-2 rs689466 polymorphism and breast cancer risk in the overall population (AA + AG versus GG). The squares and horizontal lines correspond to the study specific OR and 95% CI. The area of the squares reflects the weight (inverse of the variance). The diamond represents the summary OR and 95% CI.13 studies with 15,017 cases and 18,901 controls were used to evaluate the relationship between COX-2 rs5275 polymorphism with breast cancer risk. As shown in Table3 and Figure 4, there was no significant association in rs5275 polymorphism (homozygote comparison: OR = 1.04, 95% CI = 0.96–1.12, P
=
0.34; heterozygote comparison: OR = 0.99, 95% CI = 0.95–1.04, P
=
0.81; dominant model: OR = 1.02, 95% CI = 0.98–1.07, P
=
0.33, and recessive model: OR = 1.04, 95% CI = 0.97–1.12, P
=
0.27). When stratified by ethnicity, there was also no association between rs5275 and breast cancer risk in both Caucasians and Asians (Table 3).Figure 4
Forest plots of COX-2 rs5275 polymorphism and breast cancer risk in the overall population (TT + TC versus CC). The squares and horizontal lines correspond to the study specific OR and 95% CI. The area of the squares reflects the weight (inverse of the variance). The diamond represents the summary OR and 95% CI.


### 3.3. Publication Bias

In this meta-analysis, we performed funnel plot and Egger’s test to access the publication bias. As shown in Figure5, the funnel plots failed to detect any obvious asymmetry in all genotypes in overall population, and the results of Egger’s test revealed no publication bias (P
>
0.05). Therefore, no significant publication bias was found in this meta-analysis.Funnel plot assessing evidence of publication bias from the eligible studies. (a) −765 G>C (rs20417); (b) −1195G>A (rs689466); and (c) 8473 C>T (rs5275).
(a)
(b)
(c)


## 3.1. Characteristics of Studies

As shown in Figure1, a total of 378 potential publications were initially extracted. After reading the abstracts, we excluded 176 irrelevant studies, 113 studies with insufficient data, and 53 duplicated ones. In-depth reading of the remaining articles led to further exclusion of 12 articles with no detailed genotyping data, 6 studies with no case-control, 3 laboratory studies, and 4 systematic review articles. Finally, 13 studies from 11 articles were collected for this meta-analysis.Figure 1
Flow chart of studies selection in this meta-analysis.Overall, 13 studies on COX-2 polymorphisms and breast cancer risk were identified [16, 18–27], including a total of 15,330 cases and 19,260 case-free controls. The characteristics of the included studies are listed in Table 1. Among the eligible 13 studies, nine studies were carried out in Caucasians from USA, Austria, Denmark, Brazil, and nine European countries. Two were based on Asian background and were carried out in China. Only one study carried out in Egypt was based on African background. One study was on mixed ethnic groups. All studies were case-controlled. All breast cancers were confirmed by histology or pathology. Moreover, controls were mainly matched by age. Five studies were hospital-based and eight were population-based.Table 1
Characteristics of the studies included in the meta-analysis.
First author
Year
Country
Ethnicity
Study design
Genotyping method
Source of control
Total sample size (case/control)
SNP number
Gao [20]
2014
China
Asian
CC
TaqMan
Hospital
465/799
1, 3
Fawzy [18]
2013
Egypt
African
CC
PCR-RFLP
Hospital
160/150
3
Brasky [19]
2011
USA
Caucasian
CC
TaqMan
Population
1077/1910
2, 3
Piranda [16]
2010
Brazil
Caucasian
CC
TaqMan
Population
318/273
1, 2, 3
Dossus [21]
2010
USA, Europe
Caucasian
CC
Illumina
Population
6292/8135
1, 2, 3
Abraham [22]
2009
EPIC
Caucasian
CC
TaqMan
Population
2200/2280
3
Gao [23]
2007
China
Asian
CC
PCR-RFLP
Hospital
601/643
1, 2, 3
Cox 1 [24]
2007
USA
Caucasian
CC
TaqMan
Population
1270/1762
1, 3
Cox 2 [24]
2007
USA
Caucasian
CC
TaqMan
Population
317/634
3
Cox 3 [24]
2007
USA
Caucasian
CC
TaqMan
Population
702/703
3
Vogel [25]
2007
Denmark
Caucasian
CC
TaqMan
Hospital
361/361
3
Langsenlehner [26]
2006
Austria
Caucasian
CC
TaqMan
Hospital
500/500
3
Shen [27]
2006
USA
Mixed
CC
PCR-RFLP
Population
1067/1110
1, 3
CC: case-control; PCR: polymerase chain reaction; RFLP: restriction fragment length polymorphism. EPIC: European Prospective Investigation of Cancer (a prospective study of diet and cancer being carried out in nine European countries). SNP: single-nucleotide polymorphisms; SNP number 1: −765G>C (rs20417); 2: −1195G>A (rs689466); 3: 8473T>C (rs5275).


## 3.2. Meta-Analysis Results

As shown in Table2, the frequencies of the minor allele varied widely across the eligible studies, ranging from 0.06 to 0.28 (rs20417), 0.12 to 0.54 (rs689466), and 0.18 to 0.45 (rs5275). The average frequencies of the minor allele in the three polymorphisms were 0.17, 0.22, and 0.33, respectively.Table 2
COX-2 polymorphisms genotype distribution and allele frequency in cases and controls.
First author
Genotype (N)
Allele frequency (N)
MAF
Case
Control
Case
Control
Total
AA
AB
BB
Total
AA
AB
BB
A
B
A
B
rs20417
Gao 2014 [20]
465
394
67
4
799
719
76
4
855
75
1514
84
0.08
Piranda 2010 [16]
308
157
127
24
264
129
117
18
441
175
375
153
0.28
Dossus 2010 [21]
6254
4394
1646
214
8092
5694
2166
232
10434
2074
13554
2630
0.17
Gao 2007 [23]
601
526
73
2
643
582
59
2
1125
77
1223
63
0.06
Cox 1 2007 [24]
1243
865
336
42
1715
1185
485
45
2066
420
2855
575
0.17
Shen 2006 [27]
1067
670
387
1105
691
414
—
—
—
—
—
rs689466
Brasky 2011 [19]
1077
660
271
34
1910
1199
471
54
1591
339
2869
579
0.18
Piranda 2010 [16]
289
224
62
3
245
190
51
3
510
68
431
57
0.12
Dossus 2010 [21]
6247
4020
1928
299
8115
5143
2562
410
9968
2526
12848
3382
0.20
Gao 2007 [23]
601
121
305
175
643
150
327
166
547
655
627
659
0.54
rs5275
Gao 2014 [20]
465
299
132
34
799
515
244
40
730
200
1274
324
0.22
Fawzy 2013 [18]
160
53
71
36
150
69
67
14
177
143
205
95
0.45
Brasky 2011 [19]
1077
432
447
108
1910
732
782
226
1311
663
2246
1234
0.31
Piranda 2010 [16]
294
125
149
20
244
120
99
25
399
189
339
149
0.32
Dossus 2010 [21]
6133
2697
2664
772
7946
3512
3501
933
8058
4208
10525
5367
0.34
Abraham 2009 [22]
2172
927
985
260
2265
996
1010
259
2839
1505
3002
1528
0.35
Gao 2007 [23]
601
404
179
18
643
429
194
20
987
215
1052
234
0.18
Cox 1 2007 [24]
1249
541
567
141
1720
699
808
213
1649
849
2206
1234
0.34
Cox 2 2007 [24]
301
140
131
30
610
270
259
81
411
191
799
421
0.32
Cox 3 2007 [24]
644
281
296
67
651
278
294
79
858
430
850
452
0.33
Vogel 2007 [25]
361
167
150
44
361
155
165
41
484
238
475
247
0.33
Langsenlehner 2006 [26]
500
214
224
62
500
234
232
33
652
348
700
298
0.35
Shen 2006 [27]
1060
475
585
1102
467
635
—
—
—
—
—
A represents the major allele; B represents the minor allele. MAF: minor allele frequencies.The main results of this meta-analysis were listed in Table3. There were 6 studies with 9,938 cases and 12,618 controls for rs20417. As shown in Table 3 and Figure 2, rs20417 polymorphism has association with breast cancer risk in the overall population based on homozygote comparison (CC versus GG: OR = 1.21, 95% CI = 1.02–1.42, P
=
0.03) and the recessive model (CC versus GG + GC: OR = 1.22, 95% CI = 1.03–1.43, P
=
0.02). However, there are no significant associations in other genetic models (C versus G: OR = 1.04, 95% CI = 0.98–1.10, P
=
0.17; heterozygote comparison (GC versus GG): OR = 0.97, 95% CI = 0.91–1.03, P
=
0.35; dominant model (GC + CC versus GG): OR = 1.01, 95% CI = 0.96–1.08, P
=
0.64). In the stratified analysis by ethnicity, the effects remained in Caucasians (homozygote comparison: OR = 1.20, 95% CI = 1.02–1.42, P
=
0.03; recessive model: OR = 1.21, 95% CI = 1.03–1.43, P
=
0.02), but not in Asians (Table 3).Table 3
Meta-analysis of the association between COX-2 polymorphisms and breast cancer risk.
Comparisons
OR
95% CI
P value
Heterogeneity
Effects model
I
2
P value
B versus A
rs20417
1.04
0.98–1.10
0.17
56%
0.06
R
Caucasian
1.02
0.96–1.08
0.50
0%
0.92
F
Asian
1.45
1.15–1.84
0.002
0%
0.47
F
rs689466
0.99
0.94–1.04
0.69
33%
0.21
F
Caucasian
0.97
0.92–1.03
0.34
0%
0.58
F
Asian
1.14
0.97–1.33
—
—
—
—
rs5275
1.01
0.98–1.05
0.50
56%
0.01
R
Caucasian
1.00
0.97–1.04
0.80
41%
0.09
R
Asian
1.03
0.89–1.19
0.70
0%
0.51
F
BB versus AA
rs20417
1.21
1.02–1.42
0.03
0%
0.97
F
Caucasian
1.20
1.02–1.42
0.03
0%
0.92
F
Asian
1.54
0.49–4.78
0.46
0%
0.68
F
rs689466
1.01
0.88–1.15
0.93
22%
0.28
F
Caucasian
0.95
0.82–1.10
0.52
0%
0.69
F
Asian
1.31
0.95–1.80
—
—
—
—
rs5275
1.04
0.96–1.12
0.34
66%
0.0008
R
Caucasian
1.01
0.94–1.10
0.72
58%
0.01
R
Asian
1.26
0.85–1.85
0.25
7%
0.30
F
AB versus AA
rs20417
0.97
0.91–1.03
0.35
93%
<0.00001
R
Caucasian
0.94
0.88–1.01
0.07
95%
<0.00001
R
Asian
1.49
1.15–1.91
0.002
0%
0.53
F
rs689466
0.98
0.92–1.05
0.59
0%
0.59
F
Caucasian
0.97
0.91–1.04
0.44
0%
0.74
F
Asian
1.16
0.87–1.54
—
—
—
—
rs5275
0.99
0.95–1.04
0.81
0%
0.56
F
Caucasian
0.99
0.95–1.04
0.81
0%
0.47
F
Asian
0.96
0.80–1.14
0.96
0%
0.78
F
AB + BB versus AA
rs20417
1.01
0.96–1.08
0.64
54%
0.05
R
Caucasian
1.00
0.93–1.06
0.93
0%
0.84
F
Asian
1.49
1.16–1.91
0.002
0%
0.49
F
rs689466
0.90
0.87–0.95
0.0005
94%
<0.00001
R
Caucasian
0.88
0.83–0.94
<0.0001
96%
<0.00001
R
Asian
1.21
0.92–1.58
—
—
—
—
rs5275
1.02
0.98–1.07
0.33
62%
0.002
R
Caucasian
1.02
0.97–1.07
0.42
66%
0.002
R
Asian
0.99
0.84–1.17
0.92
0%
0.86
F
BB versus AA + AB
rs20417
1.22
1.03–1.43
0.02
0%
0.98
F
Caucasian
1.21
1.03–1.43
0.02
0%
0.94
F
Asian
146
0.47–4.56
0.51
0%
0.70
F
rs689466
1.01
0.89–1.15
0.85
0%
0.48
F
Caucasian
0.96
0.83–1.11
0.59
0%
0.76
F
Asian
1.18
0.92–1.51
—
—
—
—
rs5275
1.04
0.97–1.12
0.27
65%
0.0009
R
Caucasian
1.02
0.95–1.10
0.60
60%
0.01
R
Asian
1.28
0.87–1.87
0.21
15%
0.28
F
A: represents the major allele; B: represents the minor allele; F: fixed-effects model; R: random-effects model.Figure 2
. Forest plots of COX-2 rs20417 polymorphism and breast cancer risk in the overall population (CC versus GG + GC). The squares and horizontal lines correspond to the study specific OR and 95% CI. The area of the squares reflects the weight (inverse of the variance). The diamond represents the summary OR and 95% CI.There were 4 studies with 8,214 cases and 10,202 controls for assessing the relationship between COX-2 rs689466 polymorphism and breast cancer susceptibility. As shown in Table3 and Figure 3, there was no association in these four genotypes (A versus G: OR = 0.99, 95% CI = 0.94–1.04, P
=
0.69; homozygote comparison (AA versus GG): OR = 1.01, 95% CI = 0.88–1.15, P
=
0.93; heterozygote comparison (AG versus GG): OR = 0.98, 95% CI = 0.92–1.05, P
=
0.59; recessive model (AA versus GG + AG): OR = 1.01, 95% CI = 0.89–1.15, P
=
0.85). However, rs689466 polymorphism has association with breast cancer risk based on the recessive model (AA + AG versus GG: OR = 0.90, 95% CI = 0.87–0.95, P
=
0.002). In the stratified analysis, when analyzed by the dominant model, the OR was 0.88 (95% CI = 0.83–0.94) (P
<
0.0001) among Caucasians. These results suggested that the individuals with AA or AG alleles have a 12% decreased risk of breast cancer compared with those with GG allele in Caucasians.Figure 3
Forest plots of COX-2 rs689466 polymorphism and breast cancer risk in the overall population (AA + AG versus GG). The squares and horizontal lines correspond to the study specific OR and 95% CI. The area of the squares reflects the weight (inverse of the variance). The diamond represents the summary OR and 95% CI.13 studies with 15,017 cases and 18,901 controls were used to evaluate the relationship between COX-2 rs5275 polymorphism with breast cancer risk. As shown in Table3 and Figure 4, there was no significant association in rs5275 polymorphism (homozygote comparison: OR = 1.04, 95% CI = 0.96–1.12, P
=
0.34; heterozygote comparison: OR = 0.99, 95% CI = 0.95–1.04, P
=
0.81; dominant model: OR = 1.02, 95% CI = 0.98–1.07, P
=
0.33, and recessive model: OR = 1.04, 95% CI = 0.97–1.12, P
=
0.27). When stratified by ethnicity, there was also no association between rs5275 and breast cancer risk in both Caucasians and Asians (Table 3).Figure 4
Forest plots of COX-2 rs5275 polymorphism and breast cancer risk in the overall population (TT + TC versus CC). The squares and horizontal lines correspond to the study specific OR and 95% CI. The area of the squares reflects the weight (inverse of the variance). The diamond represents the summary OR and 95% CI.


## 3.3. Publication Bias

In this meta-analysis, we performed funnel plot and Egger’s test to access the publication bias. As shown in Figure5, the funnel plots failed to detect any obvious asymmetry in all genotypes in overall population, and the results of Egger’s test revealed no publication bias (P
>
0.05). Therefore, no significant publication bias was found in this meta-analysis.Funnel plot assessing evidence of publication bias from the eligible studies. (a) −765 G>C (rs20417); (b) −1195G>A (rs689466); and (c) 8473 C>T (rs5275).
(a)
(b)
(c)


## 4. Discussion

The present meta-analysis, including 15,330 cases and 19,260 controls from 13 case-control studies, was conducted to evaluate the association between the three common SNPs [−765 G>C (rs20417), −1195 G>A (rs689466), and 8473 C>T (rs5275)] in the COX-2 gene and breast cancer risk.A previous study by Yu et al. [15] failed to detect an association between rs20417 and breast cancer risk. There were only three studies with 2,901 cases and 3,463 controls for rs20417 in Yu’s meta-analysis [15]. In this study, there were six studies with 9,938 cases and 12,618 controls included to evaluate the relationship between rs20417 polymorphism and breast cancer risk. The results showed that rs20417 polymorphism was associated with breast cancer risk in the overall population based on homozygote comparison (CC versus GG: OR = 1.21, 95% CI = 1.02–1.42, P
=
0.03). Moreover, in a stratified analysis by ethnicity using the recessive model, we found that the association remained in Caucasians (homozygote comparison: OR = 1.20, 95% CI = 1.02–1.42, P
=
0.03; recessive model: OR = 1.21, 95% CI = 1.03–1.43, P
=
0.02), but not in Asians. These results suggest ethnic differences in genetic backgrounds and the environment in which they live play a possible role in breast carcinogenesis [29].In Zhu et al.’s meta-analysis [30], they showed that individuals with the rs20417 were associated with higher cancer risk than those with the −765GG genotype. Stratified analysis further revealed that this effect was maintained in colorectal carcinoma and esophageal cancer in Asian descents. However, the rs5275 polymorphism was not associated with cancer risk although in breast and lung cancer this allele was correlated with decreased risk.In the present meta-analysis, 13 studies with 15,017 cases and 18,901 controls concerning the rs5275 polymorphism were included. We found no significant association of rs5275 polymorphism with breast cancer risk (homozygote comparison: OR = 1.04, 95% CI = 0.96–1.12,P
=
0.34; heterozygote comparison: OR = 0.99, 95% CI = 0.95–1.04, P
=
0.81; dominant model: OR = 1.02, 95% CI = 0.98–1.07, P
=
0.33, and recessive model: OR = 1.04, 95% CI = 0.97–1.12, P
=
0.27). When stratified by ethnicity, similar results were observed in both Caucasians and Asians.In the previous meta-analysis by Tang et al. [14], there was an association of the rs689466 polymorphism with cancer risk in Asian populations but not in Europeans. Our results indicate that rs689466 polymorphism has association with breast cancer risk based on the recessive model (AA + AG versus GG: OR = 0.90, 95% CI = 0.87–0.95, P
=
0.002). In the stratified analysis, when analyzed by the dominant model, the OR was 0.88 (95% CI = 0.83–0.94) (P
<
0.0001) among Caucasians.Some limitations of this meta-analysis should be noted. Firstly, this meta-analysis was based on pooled data and no individual data was available; thus, we could not assess the risk of cancer according to stratification by age, environment factors, and other risk factors of breast cancer. Secondly, most of the included studies did not investigate the chronic inflammatory condition and the history of taking nonsteroidal anti-inflammatory drugs. Thirdly, the included studies are mainly based on Caucasian background. There were only two studies based on Asian background and one based on African background. Larger scale multicenter studies based on Asians or Africans are warranted to further validate the association between COX-2 polymorphisms and breast cancer risk.


## 5. Conclusion

In summary, this meta-analysis points to the COX-2 rs20417 C allele as a risk factor for breast cancer among Caucasian subjects. On the contrary, the rs689466 allele has a decreased risk of breast cancer in Caucasians. The rs5275 C status does not seem capable of predicting breast cancer risk in both Caucasians and Asians.



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*Source: 484729-2014-08-18.xml*