ABSTRACT: BACKGROUND AND OBJECTIVES: The GSTM1, GSTT1 and GSTP1 polymorphisms might be involved in inactivation of procarcinogens that contribute to the genesis and progression of cancers. However, studies investigating the association between GSTM1, GSTT1 or GSTP1 polymorphisms and prostate cancer (PCa) risk report conflicting results, therefore, we conducted a meta-analysis to re-examine the controversy. METHODS: Published literature from PubMed, Embase, Google Scholar and China National Knowledge Infrastructure (CNKI) were searched (updated to June 2, 2012). According to our inclusion criteria, studies that observed the association between GSTM1, GSTT1 or GSTP1 polymorphisms and PCa risk were included. The principal outcome measure was the odds ratio (OR) with 95% confidence interval (CI) for the risk of PCa associated with GSTM1, GSTT1 and GSTP1 polymorphisms. RESULTS: Fifty-seven studies involving 11313 cases and 12934 controls were recruited. The overall OR, which was 1.2854 (95% CI?=?1.1405-1.4487), revealed a significant risk of PCa and GSTM1 null genotype, and the similar results were observed when stratified by ethnicity and control source. Further, the more important is that the present study first reported the high risks of PCa for people who with dual null genotype of GSTM1 and GSTT1 (OR?=?1.4353, 95% CI?=?1.0345-1.9913), or who with GSTT1 null genotype and GSTP1 A131G polymorphism (OR?=?1.7335, 95% CI?=?1.1067-2.7152). But no association was determined between GSTT1 null genotype (OR?=?1.102, 95% CI?=?0.9596-1.2655) or GSTP1 A131G polymorphism (OR?=?1.0845, 95% CI?=?0.96-1.2251) and the PCa risk. CONCLUSIONS: Our meta-analysis suggested that the people with GSTM1 null genotype, with dual null genotype of GSTM1 and GSTT1, or with GSTT1 null genotype and GSTP1 A131G polymorphism are associated with high risks of PCa, but no association was found between GSTT1 null genotype or GSTP1 A131G polymorphism and the risk of PCa. Further rigorous analytical studies are highly expected to confirm our conclusions and assess gene-environment interactions with PCa risk.
