Journal of Cancer Research and Therapeutics

ORIGINAL ARTICLE
Year
: 2016  |  Volume : 12  |  Issue : 2  |  Page : 543--549

Association between fibroblast growth factor receptor-2 gene polymorphism and risk of breast cancer in Chinese populations: A HuGE review and meta-analysis


Yong-Bin Yang1, Zhan-Xue Zhao2, Wei Huang2, Hui Liu1, Yan-Li Tan1, Wei-Ming Wang3,  
1 Department of Pathology, Health Science Center, Hebei University, Baoding, People's Republic of China
2 Library, Hebei University, Baoding, People's Republic of China
3 Department of Obstetrics and Gynecology, Affiliated Hospital of Hebei University, Baoding, People's Republic of China

Correspondence Address:
Wei-Ming Wang
Department of Obstetrics and Gynecology, Affiliated Hospital of Hebei University, No. 212 Yuhuadonglu, Baoding-071 000
People's Republic of China

Abstract

Aim of study: To evaluate the effect of fibroblast growth factor receptor.2. (FGFR2) on genetic susceptibility for breast cancer. (BC) in Chinese populations. Materials and Methods: A computerized literature search was carried out in PubMed, Chinese Biomedical Database. (CBM), and Chinese National Knowledge Infrastructure. (CNKI) to collect relevant articles. Pooled odds ratio. (OR) and 95% confidence interval. (CI) were used to assess the strength of the associations. Results: A total of 21 articles involving a total of 15 polymorphisms of the FGFR2 gene were included in the meta-analysis. Due to the limited studies for rs17102287, rs2981578, rs3135718, rs3803662, rs3750817, rsl0510097, rsl7542768, rs13387042, and rs1982073; we only pooled the six polymorphisms. (rs11200014, rs1219648, rs2420946, rs2912778, rs2981579, and rs2981582) into this meta.analysis. Overall, significantly increased BC risk was associated with five polymorphisms. (rs2981579, rs2981582, rs1219648, rs2420946, and rs2912778) when all studies were pooled into the meta.analysis. When stratified by ethnicity and source of controls, similar results were also detected. However, for rs2981579 no significant association was found among Chinese Han in all genetic models. Conclusion: Our meta-analysis suggests that FGFR2 is likely an important genetic marker contributing to susceptibility of BC. We recommend that these single nucleotide polymorphisms to be included in future association studies and functional assays.



How to cite this article:
Yang YB, Zhao ZX, Huang W, Liu H, Tan YL, Wang WM. Association between fibroblast growth factor receptor-2 gene polymorphism and risk of breast cancer in Chinese populations: A HuGE review and meta-analysis.J Can Res Ther 2016;12:543-549


How to cite this URL:
Yang YB, Zhao ZX, Huang W, Liu H, Tan YL, Wang WM. Association between fibroblast growth factor receptor-2 gene polymorphism and risk of breast cancer in Chinese populations: A HuGE review and meta-analysis. J Can Res Ther [serial online] 2016 [cited 2020 Jan 26 ];12:543-549
Available from: http://www.cancerjournal.net/text.asp?2016/12/2/543/148715


Full Text



 Introduction



Breast cancer (BC) is the most frequently diagnosed cancer and the leading cause of cancer death in females worldwide, accounting for 23% (1.38 million) of the total new cancer cases and 14% (458,400) of the total cancer deaths in 2008.[1] The age-standardized incidence and mortality rates of BC in China in 2008 were 31.71 per 100,000 and 6.48 per 100,000, respectively.[2] It also shows a continuously increasing trend in morbidity of BC in China over recent years.[1],[2] In general, BC etiologic heterogeneity can be attributed to genetic and nongenetic risk factors. However, the association between genetic factors and BC receives more and more attention in recent studies.[3]

Genome-wide association studies (GWAS) have identified multiple genetic variants associated with BC, including fibroblast growth factor receptor-2 (FGFR2). FGFR2 gene, one of the common low-penetrant genes, has been identified as a potential BC susceptibility gene, which encodes a tyrosine kinase receptor that is a member of the family of individually distinct FGFRs involved in tumorigenesis. FGFR2 is amplified and overexpressed in BC,[4],[5],[6] and data suggest that FGFR2 is a tumor suppressor gene in prostate cancer and urothelial cancer.[7] Some publications [8],[9],[10],[11],[12],[13],[14] have reported the role of FGFR2 polymorphism in BC risk, but provided controversial or inconclusive results. In order to lessen the impact of different genetic background, we performed this meta-analysis to assess the relationship of FGFR2 gene polymorphism with risk of BC in Chinese populations.

 Materials and Methods



Materials

A computerized literature search was carried out in PubMed, Embase, Springer Link, Ovid, Chinese Biomedical Database (CBM), Chinese Wanfang Database, and Chinese National Knowledge Infrastructure (CNKI) to collect articles of case–control studies on associations between FGFR2 polymorphism and susceptibility to BC before 18 March 2014. References of the retrieved articles were also screened for original studies. The search strategy involved exploring 'FGFR2' or 'fibroblast growth factor receptor 2' combined with 'breast cancer'. The PubMed search was run using the terms: (FGFR2 [All Fields] OR “fibroblast growth factor receptor 2”[All Fields]) AND “breast cancer”[All Fields] AND (“China”[All Fields] OR “Chinese”[All Fields]).

Inclusion/exclusion criteria

Eligible studies had to meet all of the following criteria: (1) Case–control study or cohort study studying on associations between FGFR2 gene and BC susceptibility; (2) the diagnosis of BC patients was confirmed histologically or pathologically; (3) sufficient published data about sample size, odds ratio (OR), and their 95% confidence interval (CI); and (4) all participants were Chinese. Studies were excluded when they were: (1) Not case–control study or cohort study; (2) duplicate of previous publication; (3) based on incomplete data; (4) meta-analyses, letters, reviews, or editorial articles.

Data extraction

For each study, the following data were extracted independently by two authors: Authors, years of publication, geographical location of participants, source of controls, numbers of cases and controls, genotype frequencies, and Hardy–Weinberg equilibrium (HWE) test. The results were compared and disagreements were discussed and resolved with consensus. The categorization of ethnicity comprised Han and other ethnic Chinese. Studies with different ethnic groups were considered as individual studies for our analyses.

Statistical analysis

Pooled ORs and 95% CIs were used to assess the strength of the associations. Pooled ORs and 95% CIs for all studies combined were calculated. Furthermore, subgroup analyses were performed by ethnicity and sources of controls. Chi-square test was used for HWE of genotypes in control group of each reviewed study. Statistical heterogeneity among studies was assessed with the Q-statistics.[15] Dependent on the results of heterogeneity test among individual studies, the fixed effect model (Mantel–Haenszel) or random effect model (DerSimonian and Laird) was selected to summarize the combined OR. The significance of the pooled OR was determined by the z-test. Publication bias was investigated with the funnel plot, in which the standard error (SE) of log OR of each study was plotted against its OR. Funnel-plot asymmetry was further assessed by the method of Egger's linear regression test.[16] Analyses were performed using the software Stata version 10.0 (Stata Corp, College Station, Texas, USA). All the P values were two sided. P value less than 0.05 was considered statistically significant.

 Results



Characteristics of studies

The combined search yielded 56 references. Study selection process has been shown in [Figure 1]. A total of 21 articles [17],[18],[19],[20],[21],[22],[23],[24],[25],[26],[27],[28],[29],[30],[31],[32],[33],[34],[35],[36],[37] were finally included in this meta-analysis. Of which, four studies included 1,799 BC cases and 2,075 controls were conducted for rs11200014; 11 studies included 6.130 cases and 6,218 controls for rs2981582; and 3 studies included 760 cases and 760 controls for rs2912778. Eight studies were available for the rs2420946 with 2,636 cases and 2,756 controls, for rs1219648 with 4,121 cases and 4,497 controls, and for rs2981579 with 2,548 cases and 2,906 controls, respectively. For the rs17102287, rs2981578, rs3135718, and rs3803662 polymorphism; two studies each were included. There was only one study for rs3750817, rsl0510097, rsl7542768, rs13387042, and rs1982073. The detailed characteristics of the included studies are shown in [Table 1].{Figure 1}{Table 1}

Association of rs11200014 polymorphism with BC

Significant heterogeneity was present among the included studies (P < 0.05). Using random effect model, there were no significant associations under any models in overall and subgroup analyses [Table 2].{Table 2}

Association of rs1219648 polymorphism with BC

Overall, the per-allele OR of the rs1219648 polymorphism for BC was 1.20 (95% CI 1.13–1.28) with corresponding results under dominant, recessive, homozygous, and heterozygous genetic models of 1.20 (95% CI 1.01–1.41), 1.30 (95% CI 1.16–1.45), 1.43 (95% CI 1.26–1.62), and 1.21 (95% CI 1.08–1.37), respectively. In the stratified analysis by ethnicity and source of controls, significantly increased risks were also found [Table 3].{Table 3}

Association of rs2420946 polymorphism with BC

In the overall analysis, the risk allele of rs2420946 was significantly associated with elevated BC (OR = 1.15, 95% CI 1.06–1.24). Significant associations were also found under dominant (OR = 1.24; 95% CI 1.11–1.39) and homozygous genetic models (OR = 1.31; 95% CI 1.12–1.54) [Table 4]. When studies were stratified for source of controls, significant risks were found among hospital-based studies in allele and dominant genetic models, while only in dominant model for population-based studies. In the stratified analysis by ethnicity, significant associations were also detected in Chinese Han under allele and dominant genetic models.{Table 4}

Association of rs2912778 polymorphism with BC

Three studies were all population-based, and no one mentioned the ethnicity. Under allele model, the per-allele overall OR of the T variant for BC was 1.20 (95% CI 1.04–1.39). However, we failed to detect any association to BC risk in other genetic models (dominant model, OR = 3.72, 95% CI 0.88–15.62; recessive model, OR = 0.74, 95% CI 0.45–1.22; homozygous model, OR = 2.22; 95% CI 0.84–5.89; and heterozygous model, OR = 0.49, 95% CI 0.22–1.06).

Association of rs2981579 polymorphism with BC

Significant associations were detected in all genetic models for overall analyses (allele model, OR = 1.17, 95% CI 1.09–1.27; dominant model, OR = 1.21, 95% CI 1.08–1.36; recessive model, OR = 1.26, 95% CI 1.11-1.43; homozygous model, OR = 1.37, 95% CI 1.18–1.59; and heterozygous model, OR = 1.20, 95% CI 1.05–1.37). When studies were stratified for ethnicity and source of controls, significant risks were also found among population-based studies and Chinese not mentioned ethnicity in all genetic models [Table 5].{Table 5}

Association of rs2981582 polymorphism with BC

In overall analyses, the significant increased risks were found under the allele, dominant, recessive, and homozygous models (allele model, OR = 1.20, 95% CI 1.13–1.26; dominant model, OR = 1.27, 95% CI 1.18–1.36; recessive model, OR = 1.24, 95% CI 1.05–1.45; and homozygous model, OR = 1.38, 95% CI 1.22–1.55). Similar results were also detected in the subgroup analysis [Table 6].{Table 6}

Sensitive analysis

In order to compare the difference and evaluate the sensitivity of the meta-analyses, we used both models (the fixed effect and random effect model) to evaluate the stability of the meta-analysis. The results of allele models for rs2912778 in overall analysis, for rs2420946 in hospital-based studies and Chinese Han were altered, as well as recessive and heterozygous models for rs1219648 in hospital-based studies (data not shown). All the other results were not materially altered. Hence, results of the sensitivity analysis suggest that the data in this meta-analysis are relatively stable and credible.

Bias diagnosis

The Begg's funnel plot and Egger's test were performed to assess the publication bias of literatures. The shape of the funnel plots did not reveal obvious asymmetry. Then, the Egger's test was used to provide statistical evidence of funnel plot symmetry. The statistical results still did not show publication bias in allele model of overall analysis for rs11200014 (t = 0.60, P = 0.607), rs1219648 (t = −0.54, P = 0.609), rs2420946 (t = 0.40, P = 0.704), rs2912778 (t = −0.23, P = 0.858), rs2981579 (t = −0.69, P = 0.513), and rs2981582 (t = −0.17, P = 0.867).

 Discussion



Large sample and unbiased epidemiological studies of predisposition genes polymorphisms could provide insight into the in vivo relationship between candidate genes and diseases. This is the first most comprehensive meta-analysis examining the FGFR2 polymorphisms and the risk of BC in Chinese populations, which will be helpful in providing a new insight of gene polymorphisms in BC development. Its strength was based on the accumulation of published data concerning Chinese to detect significant differences. In total, the meta-analysis involved 21 articles for BC which included 15 polymorphisms in FGFR2 gene (rs11200014, rs1219648, rs2420946, rs2912778, rs2981579, rs2981582, rs17102287, rs2981578, rs3135718, rs3803662, rs3750817, rsl0510097, rsl7542768, rs13387042, and rs1982073). Due to the limited studies for rs17102287, rs2981578, rs3135718, rs3803662, rs3750817, rsl0510097, rsl7542768, rs13387042, and rs1982073; we only pooled the other six polymorphisms (rs11200014, rs1219648, rs2420946, rs2912778, rs2981579, and rs2981582) into this meta-analysis.

Our results demonstrated that the rs2981579, rs2981582, rs1219648, rs2420946, and rs2912778 polymorphisms of FGFR2 are risk factors for developing BC. For rs2912778, the significant association was only detected in the allele model. Considering the limited sample size and sensitivity analysis, the result for rs2912778 should be interpreted with cautions. In the stratified analysis by ethnicity, significant associations were observed both in Chinese Han and others in some genetic models for rs1219648 and rs2981582, suggesting a similar role of these polymorphisms in different Chinese ethnicity with different genetic backgrounds and living environment. However, no associations were found in Chinese Han population for rs2981579. In the stratified analysis according to source of controls, significantly increased BC susceptibility in FGFR2 risk allele carriers were also found among population-based and hospital-based controls for rs1219648, rs2420946, and rs2981582. The results were consistent with previously published meta-analyses,[38],[39],[40],[41] which showed an increased risk of BC associated with rs2981582, rs1219648, rs2981579, and rs2420946 polymorphisms among Asians. However, these previously published meta-analyses included a smaller number of polymorphisms in FGFR2 gene, and they did not calculate pooled ORs for studies in Chinese populations.

In interpreting the results, the main limitations of the study should be considered. Firstly, lack of original data of the reviewed studies limited our further evaluation of potential interactions, because the interactions between gene-to-gene, gene-to-environment, and even different polymorphic loci of the same gene may modulate cancer risk. Secondly, because some relevant published and unpublished studies which were likely to have null results were not included, a possible bias, especially the outcome-reporting bias, could not be ruled out, although the result for publication bias was not statistically significant. Thirdly, the conclusions for rs17102287, rs2981578, rs3135718, rs3803662, rs3750817, rsl0510097, rsl7542768, rs13387042, and rs1982073 cannot be drawn because of the relevant small sample size.

In conclusion, our meta-analysis indicates that five functional polymorphisms (rs2981579, rs2981582, rs1219648, rs2420946, and rs2912778) in the promoter of FGFR2 gene are associated with BC susceptibility in Chinese populations and might be potential biomarkers for BC risk. However, larger well-designed studies with subjects of the same ethnic background and tissue-specific biochemical and biological characteristics are required to validate these findings. Moreover, gene–gene and gene–environment interactions should also be considered in the future analysis.

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