Breast cancer exhibits familial aggregation, consistent with variation in genetic susceptibility to the disease. Known susceptibility genes account for less than 25% of the familial risk of breast cancer, and the residual genetic variance is likely to be due to variants conferring more moderate risks. To identify further susceptibility alleles, we conducted a two-stage genome-wide association study in 4,398 breast cancer cases and 4,316 controls, followed by a third stage in which 30 single nucleotide polymorphisms (SNPs) were tested for confirmation in 21,860 cases and 22,578 controls from 22 studies. We used 227,876 SNPs that were estimated to correlate with 77% of known common SNPs in Europeans at r2 > 0.5. SNPs in five novel independent loci exhibited strong and consistent evidence of association with breast cancer (P < 10(-7)). Four of these contain plausible causative genes (FGFR2, TNRC9, MAP3K1 and LSP1). At the second stage, 1,792 SNPs were significant at the P < 0.05 level compared with an estimated 1,343 that would be expected by chance, indicating that many additional common susceptibility alleles may be identifiable by this approach.

Phytoestrogens are a group of polyphenolic plant metabolites that can induce biological responses. Their bioactivity is based on their similarity to 17beta-estradiol and their ability to bind to the beta-estrogen receptor. Although epidemiological data are inconclusive, phytoestrogens are considered to be beneficial for a variety of conditions, for example, hormone-related cancers like breast and prostate cancer. To investigate the biological effects of these compounds and to assess the exposure of larger cohorts or the general public, reliable data on the phytoestrogen content of food is necessary. Previously, food analysis for phytoestrogens was performed using either HPLC-UV or GC/MS. Here, we describe the development of the first generic method for the analysis of phytoestrogens in food, using automated solid-phase extraction and liquid chromatography-tandem mass spectrometry. The presented method shows a good reproducibility and can be easily adapted to other phytoestrogens if required.

Prospective phytoestrogen exposure was assessed using both biomarkers and estimates of intake in 89 British men recruited into the Norfolk arm of the European Prospective Investigation into Cancer and Nutrition study, men who subsequently developed prostate cancer. Results were compared with those from 178 healthy men matched by age and date of recruitment. Levels of seven phytoestrogens (daidzein, genistein, glycitein, O-desmethylangolensin, equol, enterodiol, and enterolactone) were measured in spot urine and serum samples. Five single-nucleotide polymorphisms in COMT, CYP19, ESR1, and SHBG genes were genotyped. Urinary levels of all phytoestrogens correlated strongly with serum levels. Correlation coefficients ranged from 0.63 (glycitein) to 0.88 (daidzein) (P < 0.001). Urinary and serum levels correlated significantly with isoflavone intake assessed from food diaries (R = 0.15-0.20; P < 0.05) but not with that from a food-frequency questionnaire. Odds ratios for phytoestrogen exposure, as assessed using the four methods, were not significantly associated with prostate cancer risk (P = 0.15-0.94). Men with the CC genotype for the ESRI PvuII polymorphism had significantly higher risk for prostate cancer compared with men with the TT genotype [adjusted odds ratio = 4.65 (1.60-13.49); P = 0.005]. Our results utilizing a combined prospective exposure provide no evidence that phytoestrogens alter prostate cancer risk in British men, whereas the C allele for the PvuII polymorphism may be associated with increased risk.