Abstract
BackgroundA large number of single nucleotide polymorphisms (SNPs) associated with cervical cancer have been identified through candidate gene association studies and genome-wide association studies (GWAs). However, some studies have yielded different results for the same SNP. To obtain a more comprehensive understanding, we performed a meta-analysis on previously published case–control studies involving the SNPs associated with cervical cancer.MethodsElectronic searches of PubMed and Embase were conducted for all publications about the association between gene polymorphisms and cervical cancer. One-hundred and sixty-seven association studies were included in our research. For each SNP, three models (the allele, dominant and recessive effect models) were adopted in the meta-analysis. For each model, the effect summary odds ratio (OR) and 95% CI were calculated. Heterogeneity between studies was evaluated by Cochran’s Q test. If the p value of Q test was less than 0.01, a random effect model was used; otherwise, a fixed effect model was used.ResultsThe results of our meta-analysis showed that: (1) There were 8, 2 and 8 SNPs that were significantly associated with cervical cancer (P < 0.01) in the allele, dominant and recessive effect models, respectively. (2) rs1048943 (CYP1A1 A4889G) showed the strongest association with cervical cancer in the allele effect model (1.83[1.57, 2.13]); in addition, rs1048943 (CYP1A1 A4889G) had a very strong association in the dominant and recessive effect model. (3) 15, 11 and 10 SNPs had high heterogeneity (P < 0.01) in the three models, respectively. (4) There was no published bias for most of the SNPs according to Egger’s test (P < 0.01) and Funnel plot analysis. For some SNPs, their association with cervical cancer was only tested in a few studies and, therefore, might have been subjected to published bias. More studies on these loci are required.ConclusionOur meta-analysis provides a comprehensive evaluation of cervical cancer association studies.Electronic supplementary materialThe online version of this article (doi:10.1186/s12881-015-0168-z) contains supplementary material, which is available to authorized users.
Highlights
A large number of single nucleotide polymorphisms (SNPs) associated with cervical cancer have been identified through candidate gene association studies and genome-wide association studies (GWAs)
Our meta-analysis provides a comprehensive evaluation of cervical cancer association studies
The studies to be included in the meta-analysis were selected in accordance with the following criteria: (1) the articles must have been published between January of 1990 and June of 2014; (2) the studies must employ a case–control design and must examine the association between Single nucleotide polymorphisms (SNP) and cervical cancer; (3) data on the SNP genotypes of patients and controls must be available; (4) the studies must be published as a full paper, not as a meeting abstract or review; and (5) NOT-human leukocyte antigen (HLA)
Summary
A large number of single nucleotide polymorphisms (SNPs) associated with cervical cancer have been identified through candidate gene association studies and genome-wide association studies (GWAs). Gostout BS found that TNF-α-308G > A does not increase the incidence rate of cervical cancer (OR (95% CI) =0.98 [0.64, 1.50]) [10] These controversial results may be caused by small sample sizes, racial or ethnic differences, or clinical and genetic heterogeneity. Metaanalysis is a very effective method by which the results of many studies with small sample sizes are combined Through this method, the relationship of some SNPs, such as TNF-α-308G > A and TNF-α-238G > A, associated with cervical cancer has been proven. To comprehensively and systematically assess the association between all of the available SNPs and cervical cancer susceptibility, we searched the PubMed database and Embase and performed a meta-analysis on the results of the selected studies. As far as we know, this is the most detailed meta-analysis of SNPs and cervical cancer to date
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