Current evidence on the relationship between polymorphisms in the COX-2 gene and breast cancer risk: a meta-analysis
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- Yu, K., Chen, A., Yang, C. et al. Breast Cancer Res Treat (2010) 122: 251. doi:10.1007/s10549-009-0688-3
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The association between single-nucleotide polymorphisms (SNPs) in the COX-2 gene and breast cancer risk is still ambiguous. We here try to derive a more precise estimation of the relationship by performing a meta-analysis based on currently available evidence from literature. More than 15 SNPs have been studied, and the most studied genetic variants were rs5275, rs5277, and rs20417. Crude odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the strength of association between each polymorphism and breast cancer risk under the codominant model, dominant model, and recessive model, respectively (nine studies with 6,968 cases and 9,126 controls for rs5275; three studies with 2,901 cases and 3,463 controls for rs20417; two studies with 5,551 cases and 6,208 controls for rs5277). No overall significant associations were observed in single-locus analysis between the three polymorphisms of COX-2 and breast cancer risk, though a borderline significant increased risk of breast cancer was detected with rs5277 in a recessive model (OR: 1.217, 95% CI: 0.958–1.547, P = 0.107). The results were not changed when studies were stratified by ethnicity. In conclusion, the present meta-analysis suggests that none of the most studied three SNPs (rs5275, rs20417, and rs5277) in the COX-2 gene is a conspicuous low-penetrant risk factor for developing breast cancer. There is a need for further large studies into the role of these polymorphisms (especially rs5277) and other potentially functional polymorphisms/haplotypes in the COX-2 gene as breast cancer risk modifiers.
For most sporadic breast cancers and more than half of familial breast cancers, a substantial component of risk may be determined by the effect of multiple low-penetrance susceptibility genes . Recently, several common low-penetrance loci, such as rs2981582 in FGFR2, rs3817198 in LSP1, rs1053485 in CASP8, and rs2046210 at 6q25 located upstream of ESR1 have been identified through genome-wide association studies [2, 3]. It has also been widely accepted that common variants within genes involving breast carcinogenesis-related pathways are candidate loci for breast cancer susceptibility . Numerous association studies regarding genes that are involved in estrogen metabolism pathway, carcinogen metabolism pathway, DNA repair pathway, and immunosurveillance pathway have been performed. Genes involved in the prostaglandin pathway could play potential roles in breast cancer susceptibility [5–8]. Accumulating evidence has showed that the inducible prostaglandin synthase cyclooxygenase-2 (COX-2, the gene encoding this protein is PTGS2) is implicated in breast cancer tumorigenesis. COX-2 is overexpressed in approximately 40% of human breast cancers , and its expression is particularly positively associated with human epidermal growth factor receptor-2 (HER2), a pivotal breast cancer oncogene protein [10, 11]. HER2-induced mammary tumorigenesis and angiogenesis are reduced in COX-2 knockout mice .
There are different polymorphism sites in the COX-2 gene. Some of them are suggested to be functional and indicated to be associated with COX-2 expression level. For instance, a previous study showed that the −765C allele of the single-nucleotide polymorphism (SNP) rs20417 (−765G>C) was associated with significantly reduced COX-2 expression compared with the −765G allele, and this effect was postulated to be mediated by the loss of Sp1 transcription factor binding to its cognate element , although Szczeklik et al. further demonstrated that −765G>C eliminates an Sp1-binding site but creates an E2F-binding site . Another potential functional SNP is rs689466 (−1195G>A), Zhang et al. reported that reporter gene expressions driven by −1195A-containing COX-2 promoters were 4- to 6-fold greater than those driven by the −1195G-containing counterparts . Thus far, some association studies regarding the contribution of SNPs in the COX-2 gene to breast cancer risk have been performed. To the best of our knowledge, rs5275 (8473T>C), rs20417 (−765G>C) and rs5277 are the most extensively studied polymorphisms. However, the small effect of each single polymorphism on breast cancer risk and the relatively small sample size in each published study made the results inconclusive and controversial.
In consideration of the putative role of COX-2 in breast carcinogenesis, we conduct the present meta-analysis to evaluate the association between genetic variants in the COX-2 gene and breast cancer risk. Although, a meta-analysis regarding this issue has been reported by Zhu et al. recently , it is regrettably that, in that report, some eligible studies [17, 18] were not included by the authors, thereby might bias the results and make their conclusions questionable. Moreover, since then, additional studies with larger sample sizes have been reported , which warrants the current meta-analysis to be a more precise estimation.
We searched Medline, PubMed, and Web of Science (updated to November 1, 2009) using the following search terms: “COX2” or “COX-2’’ or “Cyclooxygenase-2” or “Cyclooxygenase 2” or “PTGS2” or “prostaglandin endoperoxide synthase 2” and “genetic variant” or ‘‘polymorphism’’ and “breast’’. All the searched studies were retrieved, and their references were checked as well for other relevant publications. Review articles were also searched to find additional eligible studies. Only those published studies in English language with full text articles were included. For overlapping studies, only the first published one was selected; for republished studies, only the one with the largest sample numbers was included.
Eligible studies and data extraction
The inclusion criteria were: (a) evaluation of the polymorphisms in the COX-2 gene and breast cancer risk, (b) retrospective case–control studies or prospective cohort studies, (c) with sufficient available data to estimate an odds ratio (OR) with its 95% confidence interval (95% CI), (d) in English language, and (e) fulfilling Hardy–Weinberg equilibrium in the control group (P > 0.01 was eligible).
The following variables were extracted from each study if available: first author’s surname, publication year, country, ethnicity, numbers of cases and controls, and numbers of cases and controls of different genotypes, respectively. Different ethnicity descents were categorized as Caucasian, Asian, African American, or mixed. We did not define any minimum number of patients to include a study in this meta-analysis. Information was carefully extracted from all eligible publications independently by two of the authors (Yu, K. D. and Chen, A. X.). Disagreement was resolved by discussion between the two authors. If they could not reach a consensus, a third investigator (Shao, Z. M.) adjudicated the disagreements.
Crude ORs with their 95% CIs were used to assess the strength of association between each studied polymorphism and breast cancer risk. Four different ORs were calculated: (i) heterozygous versus common homozygous carriers, (ii) rare homozygous versus common homozygous carriers, (iii) rare allele carriers versus common homozygous carriers (dominant model), and (iv) rare homozygous versus common allele carriers (recessive model). Heterogeneity assumption was checked by the Q-test and a P-value greater than 0.10 indicates a lack of heterogeneity among studies. The pooled OR was calculated by a fixed-effects model (the Mantel–Haenszel method) or a random-effects model (the DerSimonian and Laird method) according to the heterogeneity . The potential publication bias was examined visually in a funnel plot of log [OR] against its standard error (SE), and the degree of asymmetry was tested using Egger’s test (P < 0.05 considered representative of statistical significance). We also performed sensitivity analysis by omitting each study to find potential outliers . All of the statistical analyses were performed using Stata/SE version 10.0 (Stata Corporation, College Station, TX, USA).
Characteristics of all the association studies regarding polymorphisms in the COX-2 gene and breast cancer risk
Cases (n = 10,482)
Controls (n = 12,732)
rs4648310; rs689467; rs2206593; rs5275; rs5277; rs20424; rs4648276
rs20417; rs5277; rs20432; rs5275; rs4648298
rs2143416; rs2745557; rs2206593; rs5275
rs689466; rs20417; rs5275
rs20417; rs20432; rs5275
Characteristics of studies included for meta-analyses of the three SNPs
Pooled ORs of the three SNPs in different models
rs5275 (n = 9; 6,968:9,126*)
rs20417 (n = 3; 2,901:3,463)
rs5277 (n = 2; 5,551:6,208)
OR (95% CI)
OR (95% CI)
OR (95% CI)
Codominant (Het. versus Common Hom.)
Codominant (Rare Hom. versus Common Hom.)
Dominant (Rare Hom. + Het. versus Common Hom.)
Recessive (Rare Hom. versus Het. + Common Hom.)
The present meta-analysis systematically evaluated the association between the genetic variants in the COX-2 gene and breast cancer risk. Our results indicate that, among the most studied three SNPs (rs5275, rs20417, and rs5277), no one is a conspicuous low-penetrant risk factor for developing breast cancer, although rs5277 reached a borderline significance. Having analyzed a 2-fold larger number of studies than a previous meta-analysis , our results provide the most powerful conclusion thus far. It is important to point out that, the results of the present study are not in accordance with the previous Zhu’s report , which meta-analyzed the relationships between two SNPs (rs5275 and rs20417) and breast cancer, and concluded that the CC genotype of rs5275 was associated with a decreased risk compared with the TT or TC/TT genotypes. The potential explanation of discrepancy might be that the Zhu’s meta-analysis did not include recent large sample size studies  as well as ignored some previously eligible reports [17, 18]. Our current meta-analysis including all eligible studies warrants the reliability of outcomes.
The pathways of breast carcinogen metabolism are complex, mediated by the activities of multiple susceptibility genes. Therefore, it is plausible that the effect of a single gene might have more limited impact on breast cancer than that has been anticipated. The failure of demonstrating remarkable association between each of the three polymorphisms in the COX-2 gene and breast cancer risk does not rule out the possibility that other polymorphisms (or combinations of alleles) in the same gene could be substantially relevant to breast carcinogenesis. For instance, Li et al.  reported a novel SNP in exon 2 of the COX-2 gene associated with breast cancer. Gao et al.  also observed that no overall significant associations were detected in the single-locus analysis between three polymorphisms (−1195G>A, rs20417 (−765G>C), and rs5275 (8473C>T)) of the COX-2 and breast cancer risk; however, a significantly increased risk of breast cancer was associated with the haplotypes constructed by these three SNPs. Therefore, a more comprehensive haplotype-based approach rather than single polymorphism-based strategy may provide more precise information on genetic contribution of the COX-2 to breast cancer etiology.
Some limitations of this meta-analysis should be acknowledged. First, though most controls were selected mainly from healthy populations, some had benign breast disease , which might lead to misclassification bias because those controls have potential risks of developing breast cancer . Second, the overall outcomes were based on individual unadjusted ORs, while a more precise evaluation should be adjusted by other potentially suspected factors. Third, although the available data on rs5275 and rs5277 comprise at least 5,500 cases and at least 6,000 controls, the present data on rs20417 are insufficient (approximately 3,000 cases and 3,500 controls) to enable reliable assessment yet. Relatively limited study number also made it impossible to perform subgroup analysis for rs5277 and rs20417. Finally, lack of individual data of each study prevents more detailed analyses, such as joint effects of SNP–SNP or gene–environment factors.
In summary, this meta-analysis suggests a lack of association between three SNPs (rs5275, rs5277, and rs20417) in the COX-2 gene and breast cancer risk. Further studies regarding other SNPs (or haplotypes) in the COX-2 gene and breast cancer risk are necessary to better understand the role of COX-2 in breast carcinogenesis. We also encourage further evaluations on the contribution of rs5277 to breast cancer risk in larger, more comprehensive, and well-designed association studies.
This research is supported by grants from the National Basic Research Program of China (2006CB910501) and the National Natural Science Foundation of China (30971143, 30972936).