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Breast Cancer Research and Treatment

, Volume 122, Issue 2, pp 503–507 | Cite as

Lack of significant association between CYP1A1 T3801C polymorphism and breast cancer risk: a meta-analysis involving 25,087 subjects

  • Lei Yao
  • XiaoJia Yu
  • Long Yu
Epidemiology

Abstract

Breast cancer is the most prevalent cancer in the world, which is a major public health challenge. To date, many publications have evaluated the correlation between Cytochrome P450 1A1 (CYP1A1) T3801C polymorphism and breast cancer risk. However, the results remain inconclusive. In order to derive a more precise estimation of the association, a meta-analysis was performed in this study. By searching Medline, PubMed, and ISI Web of Knowledge databases, 23 studies including 10,520 cases and 14,567 controls were collected for CYP1A1 T3801C polymorphism. The strength of association between CYP1A1 T3801C polymorphism and breast cancer risk was assessed by calculating crude ORs with 95% CIs. The pooled ORs were performed for codominant model, dominant model, and recessive model, respectively. Overall, no significant associations between CYP1A1 T3801C polymorphism and breast cancer susceptibility were found for TT versus CC (OR = 0.93; 95% CI: 0.72–1.19), TC versus CC (OR = 0.95; 95% CI: 0.79–1.14), TT + TC versus CC (OR = 0.93; 95% CI: 0.75–1.15), and TT versus TC + CC (OR = 0.99; 95% CI: 0.87–1.13). In the stratified analysis by ethnicity, menopausal status, and source of controls, no significant associations were detected in all genetic models. In conclusion, this meta-analysis provides strong evidence that CYP1A1 T3801C polymorphism is not associated with breast cancer risk.

Keywords

CYP1A1 Polymorphism Breast cancer Meta-analysis 

Notes

Acknowledgments

This study was supported by national 973 programs of China grants 2004CB518605, the national 863 project of China grants 2006AA020501, and the national key sci-tech special project of China grants 2008ZX10002-020. We thank Li-Xin Qiu for revising the manuscript.

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Copyright information

© Springer Science+Business Media, LLC. 2010

Authors and Affiliations

  1. 1.State Key Laboratory of Genetic Engineering, Institute of Genetics, School of Life SciencesFudan UniversityShanghaiPeople’s Republic of China
  2. 2.Institutes of Biomedical SciencesFudan UniversityShanghaiPeople’s Republic of China

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