Polymorphism in IGFBP3 gene is associated with prostate cancer risk: An updated meta-analysis

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Abstract

Objective: Insulin-like growth factor-binding protein-3 (IGFBP3) is the major protein that binds with insulin-like growth factor-1 (IGF-1) and is considered to be involved in the development and progression of various cancers. We aimed to examine the association between prostate cancer (PCa) and the IGFBP3 gene-202A/C polymorphism. Methods: A comprehensive search within PubMed, EMBASE, and Cochrane Library was conducted to identify all case-control studies up to October 30, 2015, for a meta-analysis. Pooled odds ratios (ORs) and the 95% confidence intervals (CIs) were calculated using the fixed or random effects model. Results: Eighteen studies including 10,538 cases and 10,078 controls were identified. Overall, the CC genotype of IGFBP3-202A/C polymorphism was associated with increased risk of PCa in homozygote comparison (CC vs AA-OR =1.16, 95% CI: 1.08-1.25) and in recessive model (CC vs AA+AC-OR =1.11, 95% CI: 1.04-1.17). In dominant model, the CC/AC genotypes also implicated an increased risk of PCa (CC+AC vs AA-OR =1.11, 95% CI: 1.05-1.19). The C allele of IGFBP3-202A/C polymorphism was the risk allele for PCa relative to the A allele (OR =1.09, 95% CI: 1.05-1.14). Further stratification analysis revealed that the association between-202A/C polymorphism and PCa risk among Caucasians, but not in other ethnicities, was statistically significant (recessive model, OR =1.10, 95% CI: 1.02-1.19). In addition, the IGFBP3-202A/C polymorphism was associated with PCa risk in both population-based and hospital-based studies in homozygote comparison, recessive model, and allele model. Conclusion: Our meta-analysis indicates that the IGFBP3-202A/C polymorphism is associated with the risk of PCa, particularly in Caucasians, with the C allele being the risk allele for PCa.

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Qie, Y., Nian, X., Liu, X., Hu, H., Zhang, C., Xie, L., … Xu, Y. (2016). Polymorphism in IGFBP3 gene is associated with prostate cancer risk: An updated meta-analysis. OncoTargets and Therapy, 9, 4163–4171. https://doi.org/10.2147/OTT.S102452

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