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      Menopausal Status Modifies Breast Cancer Risk Associated with ESR1 PvuII and XbaI Polymorphisms in Asian Women: a HuGE Review and Meta-analysis

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      https://www.riss.kr/link?id=A101654817

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      Background: Published data on the association between single nucleotide polymorphisms (SNPs) in the ESR1 gene and breast cancer susceptibility are inconclusive or controversial. The aim of this Human Genome Epidemiology (HuGE) review and meta-analysis...

      Background: Published data on the association between single nucleotide polymorphisms (SNPs) in the ESR1 gene and breast cancer susceptibility are inconclusive or controversial. The aim of this Human Genome Epidemiology (HuGE) review and meta-analysis was to derive a more precise estimation of this relationship. Methods: A literature search of Pubmed, Embase, Web of science and CBM databases was conducted from inception through September 1th, 2012. Crude odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the strength of association. Results: A total of five studies including 1,678 breast cancer cases and 1,678 general population controls in Asian populations were involved in this meta-analysis. When all the eligible studies were pooled into the meta-analysis, the higher transcriptional activity variant allele T of ESR1 PvuII (C>T) (rs2234693) in pre-menopausal breast cancer women showed a significant relation to increased risk (OR = 1.13, 95%CI: 1.01-1.28, P = 0.040) in contrast to their post-menopausal counterparts which showed non-significant increased risk (OR = 1.01, 95%CI: 0.87-1.18, P = 0.858). Nevertheless, no significant association between ESR1 XbaI (A>G) (rs9340799) polymorphism and the risk of breast cancer was observed in pre-menopausal and post-menopausal individuals. Conclusion: Based on a homogeneous Asian population, results from the current meta-analysis indicates that the ESR1 PvuII (C>T) polymorphism places pre-menopausal breast cancer women at risk for breast cancer, while ESR1 XbaI (A>G) polymorphism is not likely to predict the risk of breast cancer.

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