Dataset Information

SNP-SNP interactions between dNTP supply enzymes and mismatch DNA repair in breast cancer.

ABSTRACT: The dNTP supply system genes RRM1, DCTD, TYMS, TK1 and DCK balance dNTP pools to avoid incorrect insertions of bases (i.e. DNA mismatches) and the DNA mismatch repair system genes MLH1 and MSH2 are involved in removing such mismatches. The objective of this study is to explore the possibility of interactions between these two systems, since greater mismatch production rates are expected to be more detrimental in cells that also have compromised mismatch removal rates. This conjecture was explored here specifically with respect to the development of breast cancer. More than 2400 breast cancer cases and controls are included in the Cancer Genetic Markers of Susceptibility (CGEMS) single nucleotide polymorphism (SNP) dataset. For each of these individuals, a total of 99 SNPs (69 dNTP supply SNPs and 30 mismatch repair SNPs) and 2070 SNP-SNP interactions between these two groups were evaluated for their effect on breast cancer using logistic regression to compute odds ratios (ORs) and corresponding 95% confidence intervals (CIs). Of these, 12 SNPs had found statistically significant associations with breast cancer individually (Four of them to decrease risk and eight of them to increase risk) and 697 of 2070 two-way interactions were significant associated with the risk of breast cancer. Thus, our study suggests that mismatches contribute to the formation of breast cancer.

SUBMITTER: Feng IJ

PROVIDER: S-EPMC3091819 | biostudies-literature | 2009 Jun

REPOSITORIES: biostudies-literature

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SNP-SNP interactions between dNTP supply enzymes and mismatch DNA repair in breast cancer.

Feng I Jung IJ Radivoyevitch Tomas T

Proceedings. Ohio Collaborative Conference on Bioinformatics 20090601

The dNTP supply system genes RRM1, DCTD, TYMS, TK1 and DCK balance dNTP pools to avoid incorrect insertions of bases (i.e. DNA mismatches) and the DNA mismatch repair system genes MLH1 and MSH2 are involved in removing such mismatches. The objective of this study is to explore the possibility of interactions between these two systems, since greater mismatch production rates are expected to be more detrimental in cells that also have compromised mismatch removal rates. This conjecture was explore ...[more]

PMID: 21566726

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Project description:Genome-wide association studies (GWASs) have identified low-penetrance common variants (i.e., single nucleotide polymorphisms, SNPs) associated with breast cancer susceptibility. Although GWASs are primarily focused on single-locus effects, gene-gene interactions (i.e., epistasis) are also assumed to contribute to the genetic risks for complex diseases including breast cancer. While it has been hypothesized that moderately ranked (P value based) weak single-locus effects in GWASs could potentially harbor valuable information for evaluating epistasis, we lack systematic efforts to investigate SNPs showing consistent associations with weak statistical significance across independent discovery and replication stages. The objectives of this study were i) to select SNPs showing single-locus effects with weak statistical significance for breast cancer in a GWAS and/or candidate-gene studies; ii) to replicate these SNPs in an independent set of breast cancer cases and controls; and iii) to explore their potential SNP-SNP interactions contributing to breast cancer susceptibility. A total of 17 SNPs related to DNA repair, modification and metabolism pathway genes were selected since these pathways offer a priori knowledge for potential epistatic interactions and an overall role in breast carcinogenesis. The study design included predominantly Caucasian women (2,795 cases and 4,505 controls) from Alberta, Canada. We observed two two-way SNP-SNP interactions (APEX1-rs1130409 and RPAP1-rs2297381; MLH1-rs1799977 and MDM2-rs769412) in logistic regression that conferred elevated risks for breast cancer (P(interaction)<7.3 × 10(-3)). Logic regression identified an interaction involving four SNPs (MBD2-rs4041245, MLH1-rs1799977, MDM2-rs769412, BRCA2-rs1799943) (P(permutation) = 2.4 × 10(-3)). SNPs involved in SNP-SNP interactions also showed single-locus effects with weak statistical significance, while BRCA2-rs1799943 showed stronger statistical significance (P(correlation/trend) = 3.2 × 10(-4)) than the others. These single-locus effects were independent of body mass index. Our results provide a framework for evaluating SNPs showing statistically weak but reproducible single-locus effects for epistatic effects contributing to disease susceptibility.

Project description: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.

Dataset Information

SNP-SNP interactions between dNTP supply enzymes and mismatch DNA repair in breast cancer.

Publications

SNP-SNP interactions between dNTP supply enzymes and mismatch DNA repair in breast cancer.

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