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http://dx.doi.org/10.7314/APJCP.2014.15.15.6131

Lack of Any Association of GST Genetic Polymorphisms with Susceptibility to Ovarian Cancer - a Meta-analysis  

Han, Li-Yuan (Department of Preventive Medicine, Zhejiang Provincial Key Laboratory of Pathological and Physiological Technology, Medical School of Ningbo University)
Liu, Kui (Department of Science Research and Information Management, Zhejiang Provincial Center for Disease Control and Prevention)
Lin, Xia-Lu (Department of Preventive Medicine, Zhejiang Provincial Key Laboratory of Pathological and Physiological Technology, Medical School of Ningbo University)
Zou, Bao-Bo (Department of Preventive Medicine, Zhejiang Provincial Key Laboratory of Pathological and Physiological Technology, Medical School of Ningbo University)
Zhao, Jin-Shun (Department of Preventive Medicine, Zhejiang Provincial Key Laboratory of Pathological and Physiological Technology, Medical School of Ningbo University)
Publication Information
Asian Pacific Journal of Cancer Prevention / v.15, no.15, 2014 , pp. 6131-6136 More about this Journal
Abstract
Objective: Epidemiology studies have reported conflicting results between glutathione S-transferase Mu-1 (GSTM1), glutathione S-transferase theta-1 (GSTT1) and glutathione S-transferase pi-1 (GSTP1) and ovarian cancer (OC) susceptibility. In this study, an updated meta-analysis was applied to determine whether the deletion of GSTM1, GSTT1 and GSTP1 has an influence on OC susceptibility. Methods: A published literature search was performed through PubMed, Embase, Cochrane Library, and Science Citation Index Expanded database for articles published in English. Pooled odds ratios (ORs) and 95% confidence intervals (95%CIs) were calculated using random or fixed effects models. Heterogeneity between studies was assessed using the Cochrane Q test and $I^2$ statistics. Sub-group analysis was conducted to explore the sources of heterogeneity. Sensitivity analysis was employed to evaluate the respective influence of each study on the overall estimate. Results: In total, 10 published studies were included in the final analysis. The combined analysis revealed that there was no significant association between GSTM1 null genotype and OC risk (OR=1.01, 95%CI: 0.91-1.12). Additionally, there was no significant association between GSTT1 genetic polymorphisms and OC risk (OR=0.98, 95% CI: 0.85-1.13). Similalry, no significant associations were found concerning the GSTP1 rs1695 locus and OC risk. Meanwhile, subgroup analysis did not show a significant increase in eligible studies with low heterogeneity. However, sensitivity analysis, publication bias and cumulative analysis demonstrated the reliability and stability of the current meta-analysis. Conclusions: These findings suggest that GSTs genetic polymorphisms may not contribute to OC susceptibility. Large epidemiological studies with the combination of GSTM1 null, GSTT1 null and GSTP1 Ile105Val polymorphisms and more specific histological subtypes of OC are needed to prove our findings.
Keywords
GSTM1; GSTT1; GSTP1; polymorphisms; ovarian cancer; meta; analysis;
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