SNP-SNP interactions in breast cancer susceptibility.

Venüs Ümmiye Onay,Hilmi Ozcelik,Sean Wells,Julia A Knight,Hong Li,Yuanyuan Wang,Irene L Andrulis,Isaac Rajendram,Ellen Shi,Laurent Briollais

doi:10.1186/1471-2407-6-114

Abstract

BackgroundBreast cancer predisposition genes identified to date (e.g., BRCA1 and BRCA2) are responsible for less than 5% of all breast cancer cases. Many studies have shown that the cancer risks associated with individual commonly occurring single nucleotide polymorphisms (SNPs) are incremental. However, polygenic models suggest that multiple commonly occurring low to modestly penetrant SNPs of cancer related genes might have a greater effect on a disease when considered in combination.MethodsIn an attempt to identify the breast cancer risk conferred by SNP interactions, we have studied 19 SNPs from genes involved in major cancer related pathways. All SNPs were genotyped by TaqMan 5'nuclease assay. The association between the case-control status and each individual SNP, measured by the odds ratio and its corresponding 95% confidence interval, was estimated using unconditional logistic regression models. At the second stage, two-way interactions were investigated using multivariate logistic models. The robustness of the interactions, which were observed among SNPs with stronger functional evidence, was assessed using a bootstrap approach, and correction for multiple testing based on the false discovery rate (FDR) principle.ResultsNone of these SNPs contributed to breast cancer risk individually. However, we have demonstrated evidence for gene-gene (SNP-SNP) interaction among these SNPs, which were associated with increased breast cancer risk. Our study suggests cross talk between the SNPs of the DNA repair and immune system (XPD-[Lys751Gln] and IL10-[G(-1082)A]), cell cycle and estrogen metabolism (CCND1-[Pro241Pro] and COMT-[Met108/158Val]), cell cycle and DNA repair (BARD1-[Pro24Ser] and XPD-[Lys751Gln]), and within carcinogen metabolism (GSTP1-[Ile105Val] and COMT-[Met108/158Val]) pathways.ConclusionThe importance of these pathways and their communication in breast cancer predisposition has been emphasized previously, but their biological interactions through SNPs have not been described. The strategy used here has the potential to identify complex biological links among breast cancer genes and processes. This will provide novel biological information, which will ultimately improve breast cancer risk management.

Highlights

Breast cancer predisposition genes identified to date (e.g., BRCA1 and BRCA2) are responsible for less than 5% of all breast cancer cases
To estimate breast cancer risk conferred by individual single nucleotide polymorphisms (SNP), as well SNP-SNP interactions, we have studied 19 SNPs from 18 key cancer genes, involved in DNA repair (XPD, PTEN, GADD45), cell cycle (CCND1, p27, BARD1), carcinogen/estrogen metabolism (ESR1, CYP17, COMT, GSTP1, GSTM3, MTHFR), immune system (IL1a, IL10, IL13, TNFa, G-CSF) and others (MMP1) (Table 1)
Logistic regression analysis was performed for all SNPs in the context of recessive, dominant and co-dominant models after adjustment for age

Summary

Introduction

Breast cancer predisposition genes identified to date (e.g., BRCA1 and BRCA2) are responsible for less than 5% of all breast cancer cases. Many studies have shown that the cancer risks associated with individual commonly occurring single nucleotide polymorphisms (SNPs) are incremental. The functionally defective mutations of BRCA1 and BRCA2 are strongly associated with dramatically increased breast cancer risk, such mutations are found to be rare (

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Discussion

Conclusion