Introduction

Breast cancer (BC) is the most common cancers worldwide and a major cause of mortality in women in developed countries. Over the past several years, breast cancer incidence rates have increased by approximately 30% in Westernized counties owing to changes in reproductive patterns and, more recently, to increased screening [1]. BC pathogenesis is a multistep and multifactorial process owing to a complex series of interactions among genetic, environmental, and endocrine factors [2]. Among the former, genetic polymorphisms, such as variants of pro- and anti-inflammatory cytokines such as -interleukin (IL) and tumor necrosis factors (TNF), have been most extensively investigated.

TNF-alpha is a potent pro-inflammatory cytokine initially identified as a serum factor that induces necrosis of transplanted tumors in mice [3]. It is one of the earliest cytokines to be produced in inflammatory response [4]. This production initiates a cytokine cascade involving the production of IL-1, IL-6, and other mediators, as well as TNF itself. High levels of TNF-alpha may cause organ dysfunction [5]. It has been shown that the blood level of T TNF-alpha is increased in solid tumors [6]. Therefore, it seems likely that the expression level of TNF-alpha may be involved in cancer pathogenesis and progression.

Several single-nucleotide polymorphisms in the TNFA promoter can greatly influence the expression level of TNF-alpha [7]. Among these, a common polymorphism in the promoter, a G to A substitution at position −308, has been studied intensively as a putative determinant of susceptibility to various disease, including rheumatoid arthritis, psoriasis, and BC; although the effect is small, the A allele of the TNFA −308 polymorphism is significantly associated with increased TNF-alpha production [8]. Similarly, the T allele of TNF-A 857 polymorphism located in the 5′-flanking region also shows higher transcriptional activity [9].

In fact, numerous studies have investigated genetic polymorphisms and BC susceptibility or progression. However, the association between BC risk and polymorphisms found in TNFA is still controversial. Many studies have found that pro-inflammatory genotypes of TNFA were associated with BC risk [10, 11]. However, other studies have suggested that polymorphisms of TNFA may not be significantly associated with BC risk. These mixed results were likely due to small sample sizes and low statistical power. The low statistical power of individual studies to detect small differences between cases and controls is one factor to explain the lack of conclusive results.

To better address the association between TNFA polymorphisms and BC risk, we performed a meta-analysis of all eligible studies, including a subgroup analysis based on ethnicity.

Materials and methods

Identification of eligible studies

We performed an extensive search of studies that examined the association of the TNFA polymorphisms with BC. All eligible studies were identified by searching the PubMed database. The following terms were used: (“lacteal gland” OR “mammary gland” OR “breast”) AND (“cancer” OR “carcinoma”) AND (“polymorphism” OR “polymorphisms”) AND (“tumor necrosis factor-alpha” OR “TNF-alpha” OR “TNFA”OR “TNF-A”). References of cited articles were reviewed to identify additional studies not indexed by Medline. No language or country restrictions were applied. Included studies were required to meet the following criteria: (a) based on unrelated individuals, pedigree data were excluded; (b) genotype distributions of both cases and controls were available; and (3) genotype distribution of the control population must be in Hardy–Weinberg equilibrium (HWE).

Data extraction

Information was carefully extracted from all eligible publications independently by two of the authors, according to the inclusion criteria. Disagreement was resolved by discussion between the authors. If these two authors could not reach a consensus, a third author was consulted to resolve the dispute and a final majority decision was made. For each study, the following information was collected: the first author’s last name, year of publication, country in which the study was performed, ethnicity of the study population, numbers of genotyped cases and controls, source of control groups (population-or hospital-based), source of DNA, and other variables that could be sources of bias. Patient ethnicity was categorized as Caucasian, Asian, and African.

Statistical analysis

Meta-analysis

We calculated summary odd ratios (ORs) corresponding to a 95% confidence interval (CI) to assess the strength of association between TNFA polymorphisms and breast cancer. We examined the association between TNFA −308 allele A and BC risk compared with that for allele G (A vs. G); homozygote AA was contrasted with GG. Recessive (AA vs. GA + GG) and dominant (AA + GA vs. GG) models for allele A were also used. The same contrasts were performed for allele T of the TNFA −857 polymorphism, allele C of the TNFA −1031 polymorphism, and allele C of the TNFA −1210 polymorphism, respectively. As the AA genotypes of TNFA −238 were much less frequent than GA and GG genotypes, so we just examined the contrast of the allelic effect of A (minor allele) versus G (common allele), and also examined the contrast of A/A + G/A versus G/G genotypes. The same contrasts were performed for allele A of the TNFA −863 polymorphism.

We used the Cochrane Q-test to assess the heterogeneity among studies. If the Q-test revealed a P value of more than 0.05, the fixed-effects model (the Mantel–Haenszel method) was selected to pool the data [12]. Otherwise, the random-effects model (the DerSimonian and Laird method) was used [13]. For sensitivity analysis, we excluded smaller studies and recalculated the summary ORs (95% CIs) using only larger studies to reflect the influence of the individual data. The potential publication bias was estimated by visual inspection of funnel plots [14], in which the standard error of log (OR) of each study was plotted against its log (OR); an asymmetric plot indicates a possible publication bias. We also used the method of Begg and Mazumdar [15] to calculate P values for rank correlation and Egger’s weighted regression method [16] to calculate P values for bias (P < 0.05 was considered representative of statistical significance). All statistical analyses were performed using STATA (v.10.1; Stata Corporation, College Station, TX).

Results

Included studies

Thirteen relevant studies with a total number of 10,236 cases and 13,143 controls were included in this analysis [10, 11, 17–27]. Characteristics of the included studies are shown in Table 1. The most commonly investigated genotypes were TNFA −308, −238, −863, −1031, −1210, and −857, which were reported in 13, 3, 2, 3, 2, and 2 studies, respectively. All studies used healthy volunteers or blood donors as control subjects. Populations were categorized into Caucasian, Asian, and African.

Table 1 Characteristics of individual studies included in the meta-analysis
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Effect of allele and subgroup analysis

TNF-A −308

Summary results of this meta-analysis for the association between the TNFA −308 polymorphism and BC are shown in Table 2. The meta-analysis did not reveal an association between BC and the TNFA −308 A allele in the overall population (OR = 1.050, 95%CI = 0.889–1.241; Fig. 1). However, stratification by ethnicity indicated that the TNFA −308 A allele was associated with a decreased risk of BC compared with the G allele in Caucasian individuals (OR = 0.927, 95%CI = 0.879–0.978; Fig. 2). The overall OR for the A/A versus G/G genotype of the TNFA promoter −308 was 0.976(95%CI 0.824–1.155), and an association was not found. However, stratification by ethnicity indicated that the AA genotype was a risk factor for BC in African, but not in Caucasian or Asian populations. The same results were seen when we compared the A/A and G/A genotypes or the A/A and G/A + G/G genotypes. For the A/A + G/A versus GG genotype, the OR was 1.203 (95%CI 0.851–1.229), 0.915 (95%CI 0.861–0.972), 1.774 (95%CI 0.447–7.037), and 1.746 (95%CI 0.476–6.048) in the overall, Caucasian, Asian, and African populations, respectively.

Table 2 Summary results of various comparisons
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Fig. 1
figure 1

OR and 95% CI of individual studies and pooled data for the association between the TNFA −308 allele A and BC in overall populations

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Fig. 2
figure 2

OR and 95% CI of individual studies and pooled data for the association between the TNFA −308 allele A and BC in European populations

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Other genotypes

The meta-analysis did not reveal an association between BC and TNFA −238 G>A polymorphism, and the same results were obtained between BC and any other polymorphisms in the overall population (Table 2). As these genotypes were investigated in small number of studies, we did not perform subgroup analysis. And more studies were needed to examine whether BC is associated with these polymorphisms.

Sensitivity analysis

With regard to TNFA −308 polymorphism, the results pattern was not impacted by any single study in all subgroup studies (data not shown).

Publication bias

Funnel plot from comparisons of A versus G of TNFA −308 was generated to assess publication bias (Fig. 3). The Begg’s and Egger’s Test was performed to statistically evaluate funnel plot symmetry; the results indicated no significant publication bias (Table 2).

Fig. 3
figure 3

Begg’s funnel plots for the associations: (a) allele A versus allele G in the overall populations; (b) allele A versus allele G in European populations

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Discussion

TNFA is located within the HLA class III region in chromosome 6p21.3, and contains several sites of single-nucleotide polymorphisms, which modify gene expression. TNF-alpha has shown an anti-tumor activity in a variety of tumor cell lines, including BC cell lines [28]. TNF-alpha causes arrest of the cell cycle in the transition from G1 to S phase in mammary carcinoma cells [29] and induces apoptosis in tumor cells, similar to the Fas ligand [30]. −238 G/A and −308 G/A promoter polymorphisms of TNF are shown to be associated with the TNF expression both in vivo and in vitro [31–33]. TNFA −857T, −863A, and −1031C are also found to increase TNF promoter activity [9] and lipopolysaccharide-induced TNFA production [34], although contradictory findings have also been reported [35, 36].

This study investigated the relationship between TNFA polymorphisms and BC susceptibility. For TNFA −308 genotypes, the overall results of this meta-analysis showed no significant BC susceptibility with the TNFA −308 promoter A/G polymorphism. However, stratification by ethnicity revealed a significant association between BC risk and the TNFA polymorphism in the European study populations. The available data indicate that the TNFA −308 A allele is an ethnic-specific protective factor for BC, and the A/A genotype is a risk factor for BC in African individuals, although the small number of Caucasian and African studies available to date reduces the confidences of this conclusion. There was no heterogeneity among the Caucasian and African studies, suggesting a strong association of the TNFA −308 A/G polymorphism with BC by ethnicity.

This meta-analysis of the A allele and A/A + A/G genotype of TNFA −308 locus revealed a significant association with BC in European populations, but no such association with the A/A versus G/G, A/A versus G/A genotype, and A/A versus A/G + G/G genotypes. Contrasting results were seen in African individuals. As only eight Caucasian and two African population studies were included, these results should be interpreted with caution. More Caucasian and African studies are needed to confirm this possible association.

The ORs of the A/A versus G/G genotype and AA versus A/G + G/G genotype of TNFA −308 locus were decreased in European populations, versus African and Asian populations, although the difference did not reach statistical significance. This finding may be due to low statistical power owing to the low frequency of the A/A genotype. The meta-analysis consistently showed no heterogeneity among studies in European populations. Taken together, these findings suggest that the TNFA −308 A/G polymorphism may protect against for BC in European individuals. However, because only eight studies in European populations were included, this result should be interpreted with caution. More European studies are needed to determine this possible association.

The finding that the association between the TNFA −308 A/G polymorphism and BC differs according to ethnicity is somewhat surprising; however, many factors may contribute to this difference. First, genetic heterogeneity for BC may exist in different ethnic populations. Second, clinical heterogeneity may be involved, and the contribution of differences in patient populations may cause different results. Third, different linkage disequilibrium (LD) patterns may contribute to the discrepancy. This polymorphism may be in LD with a nearby causal variant in one ethnic group, but not in another. Fourth, the difference might arise from chance, such as type I error, or due to multiple testing that inflates the type I error.

No association was found between BC and TNFA −238, −863, −857, −1031, and −1210 genotypes. As studies investigated these genotypes were not much enough, these results should be interpreted with caution, and more studies are needed.

In conclusion, results of this meta-analysis indicate that the TNFA −308 A allele may protect against BC in European individuals, but it is not likely to confer susceptibility to BC in worldwide populations. In addition, the AA genotype may be a risk factor for BC in African individuals. TNFA −238, −863, −857, −1031, and −1210 genotypes were not association with BC risk. Further detailed investigation with large numbers of worldwide participants is needed to clarify the role of these polymorphisms in BC.