Human 8-oxoguanine DNA glycosylase gene polymorphism (Ser326Cys) and cancer risk: updated meta-analysis

Abstract

Genetic polymorphism of human 8-oxoguanine glycosylase 1 (hOGG1) has been reported to have a relationship with the risk of the development of various cancers. Many studies have described the influence of Ser326Cys polymorphism of the hOGG1 gene on cancer susceptibility. However, the results have remained inconclusive and controversial. Therefore, we performed a meta-analysis to more precisely determine the relationship between the hOGG1 polymorphism and the development of cancer.Electronic databases including PubMed, Embase, Google Scholar, and the Korean Studies Information Service System (KISS) were searched. The odds ratio (OR), 95% confidence interval (CI), and p value were calculated to assess the strength of the association with the risk of cancer using Comprehensive Meta-analysis software (Corporation, NJ, USA). The 127 studies including 38,757 cancer patients and 50,177 control subjects were analyzed for the meta-analysis.Our meta-analysis revealed that G allele of Ser326Cys polymorphism of the hOGG1 gene statistically increased the susceptibility of cancer (all population, OR = 1.092, 95% CI = 1.051-1.134, p < 0.001; in Asian, OR = 1.095, 95% CI = 1.048-1.145, p < 0.001; in Caucasian, OR = 1.097, 95% CI = 1.033-1.179, p = 0.002). Also, other genotype models showed significant association with cancer (p < 0.05, respectively).The present meta-analysis concluded that the G allele was associated with an increased risk of cancer. It suggested that the hOGG1 polymorphism may be a candidate marker of cancer.

Keywords: Ser326Cys; cancer; hOGG1; meta-analysis; polymorphism.

Figure 1. Flow chart illustrating the search strategy used for this meta-analysis to identify studies that examined the association between hOGG1 Ser326Cys polymorphism and risk of cancer

Figure 2. Begg's funnel plot for publication bias in selection of studies on the hOGG1 Ser326Cys polymorphism (C vs. G, C/C vs. C/G+G/G, and C/C+C/G vs. G/G in all population)