Background: 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. 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.

The risk of colorectal cancer associated with smoking is unclear and may be influenced by genetic variation in enzymes that metabolize cigarette carcinogens. The authors examined the colorectal cancer risk associated with smoking and 26 variants in carcinogen metabolism genes in 1,174 colorectal cancer cases and 1,293 population-based controls recruited in Canada by the Ontario Familial Colorectal Cancer Registry from 1997 to 2001. Adjusted odds ratios were calculated by multivariable logistic regression. Smoking for >27 years was associated with a statistically significant increased colorectal cancer risk (adjusted odds ratio (AOR) = 1.25, 95% confidence interval (CI): 1.02, 1.53) in all subjects. Colorectal cancer risk associated with smoking was higher in males for smoking status, duration, and intensity. The CYP1A1-3801-CC (AOR = 0.47, 95% CI: 0.23, 0.94) and CYP2C9-430-CT (AOR = 0.82, 95% CI: 0.68, 0.99) genotypes were associated with decreased risk, and the GSTM1-K173N-CG (AOR = 1.99, 95% CI: 1.21, 3.25) genotype was associated with an increased risk of colorectal cancer. Statistical interactions between smoking and genetic variants were assessed by comparing logistic regression models with and without a multiplicative interaction term. Significant interactions were observed between smoking status and SULT1A1-638 (P = 0.02), NAT2-857 (P = 0.01), and CYP1B1-4390 (P = 0.04) variants and between smoking duration and NAT1-1088 (P = 0.02), SULT1A1-638 (P = 0.04), and NAT1-acetylator (P = 0.03) status. These findings support the hypothesis that prolonged cigarette smoking is associated with increased risk of colorectal cancer and that this risk may be modified by variation in carcinogen metabolism genes.

There are several genes that code for enzymes, including various forms of superoxide dismutase and glutathione peroxidase, that protect the cell against oxidative damage that, in turn, can lead to carcinogenesis. There are a few common genetic polymorphisms in these genes that lead to altered proteins. Three that have been identified are SOD2 Val-9Ala, GPX1 Pro198Leu, and the GPX1 GCG repeat (three alleles with four, five, or six repeats). The SOD2 variant has been associated with increased breast cancer risk in two studies. The GPX1 variants have not been studied with respect to breast cancer, but Pro198Leu has been associated with lung cancer. We conducted a case-control study of these three polymorphisms in incident, invasive breast cancer in Caucasian women under 55. There were 399 cases and 372 controls genotyped, of whom 488 were premenopausal, 208 postmenopausal, and 75 of unknown menopausal status. We were unable to replicate the previously observed association with SOD2 Val-9Ala and also found no association between breast cancer and GPX1 Pro198Leu. However, the allele of GPX1 containing four GCG repeats was significantly associated with breast cancer risk in premenopausal women (odds ratio, 1.55; 95% confidence interval, 1.04 -2.30 for carriers versus noncarriers). There is a significant trend of increasing risk with increasing number of alleles with four GCG repeats (P ‫؍‬ 0.03). This variant has not previously been reported to be associated with breast cancer.

Background: There is growing evidence that gene-gene interactions are ubiquitous in determining the susceptibility to common human diseases. The investigation of such gene-gene interactions presents new statistical challenges for studies with relatively small sample sizes as the number of potential interactions in the genome can be large. Breast cancer provides a useful paradigm to study genetically complex diseases because commonly occurring single nucleotide polymorphisms (SNPs) may additively or synergistically disturb the system-wide communication of the cellular processes leading to cancer development.