Modification of BRCA1-Associated Breast and Ovarian Cancer Risk by BRCA1-Interacting Genes.

Inherited BRCA1 mutations confer elevated cancer risk. Recent studies have identified genes that encode proteins that interact with BRCA1 as modifiers of BRCA1-associated breast cancer. We evaluated a comprehensive set of genes that encode most known BRCA1 interactors to evaluate the role of these genes as modifiers of cancer risk. A cohort of 2,825 BRCA1 mutation carriers was used to evaluate the association of haplotypes at ATM, BRCC36, BRCC45 (BRE), BRIP1 (BACH1/FANCJ), CTIP, ABRA1 (FAM175A), MERIT40, MRE11A, NBS1, PALB2 (FANCN), RAD50, RAD51, RAP80, and TOPBP1, and was associated with time to breast and ovarian cancer diagnosis. Statistically significant false discovery rate (FDR) adjusted P values for overall association of haplotypes (P(FDR)) with breast cancer were identified at ATM (P(FDR) = 0.029), BRCC45 (P(FDR) = 0.019), BRIP1 (P(FDR) = 0.008), CTIP (P(FDR) = 0.017), MERIT40 (P(FDR) = 0.019), NBS1 (P(FDR) = 0.003), RAD50 (P(FDR) = 0.014), and TOPBP1 (P(FDR) = 0.011). Haplotypes at ABRA1 (P(FDR) = 0.007), BRCC45 (P(FDR) = 0.016 and P(FDR) = 0.005 in two haplotype blocks), and RAP80 (P(FDR) < 0.001) were associated with ovarian cancer risk. Overall, the data suggest that genomic variation at multiple loci that encode proteins that interact biologically with BRCA1 are associated with modified breast cancer and ovarian cancer risk in women who carry BRCA1 mutations.

Context-dependent effects of genome-wide association study genotypes and macroenvironment on time to biochemical (prostate specific antigen) failure after prostatectomy.

BACKGROUND: Disparities in cancer defined by race, age, or gender are well established. However, demographic metrics are surrogates for the complex contributions of genotypes, exposures, health care, socioeconomic and sociocultural environment, and many other factors. Macroenvironmental factors represent novel surrogates for exposures, lifestyle, and other factors that are difficult to measure but might influence cancer outcomes. METHODS: We applied a "multilevel molecular epidemiology" approach using a prospective cohort of 444 White prostate cancer cases who underwent prostatectomy and were followed until biochemical failure (BF) or censoring without BF. We applied Cox regression models to test for joint effects of 86 genome-wide association study-identified genotypes and macroenvironment contextual effects after geocoding all cases to their residential census tracts. All analyses were adjusted for age at diagnosis and tumor aggressiveness. RESULTS: Residents living in census tracts with a high proportion of older single heads of household, high rates of vacant housing, or high unemployment had shorter time until BF postsurgery after adjustment for patient age and tumor aggressiveness. After correction for multiple testing, genotypes alone did not predict time to BF, but interactions predicting time to BF were observed for MSMB (rs10993994) and percentage of older single heads of households (P = 0.0004), and for HNF1B/TCF2 (rs4430796) and census tract per capita income (P = 0.0002). CONCLUSIONS: The context-specific macroenvironmental effects of genotype might improve the ability to identify groups that might experience poor prostate cancer outcomes. IMPACT: Risk estimation and clinical translation of genotype information might require an understanding of both individual- and macroenvironment-level context.

Effect of hormone metabolism genotypes on steroid hormone levels and menopausal symptoms in a prospective population-based cohort of women experiencing the menopausal transition.

OBJECTIVE: This study evaluated whether genes involved in the metabolism of steroid hormones are associated with hormone levels or menopausal symptoms. METHODS: We used a population-based prospective sample of 436 African American (AA) and European American (EA) women who were premenopausal at enrollment and were followed longitudinally through menopause. We evaluated the relationship between steroid hormone metabolism genotypes at COMT, CYP1A2, CYP1B1, CYP3A4, CYP19, SULT1A1, and SULT1E1 with hormone levels and menopausal features. RESULTS: In EA women, SULT1E1 variant carriers had lower levels of dehydroepiandrosterone sulfate, and SULT1A1 variant carriers had lower levels of estradiol, dehydroepiandrosterone sulfate, and testosterone compared with women who did not carry these variant alleles. In AA women, CYP1B1*3 genotypes were associated with hot flashes (odds ratio [OR], 0.62; 95% CI, 0.40-0.95). Interactions of CYP1A2 genotypes were associated with hot flashes across menopausal stage (P = 0.006). Interactions of CYP1B1*3 (P = 0.02) and CYP1B1*4 (P = 0.03) with menopausal stage were associated with depressive symptoms. In EA women, SULT1A1*3 was associated with depressive symptoms (OR, 0.53; 95% CI, 0.41-0.68) and hot flashes (OR, 2.08; 95% CI, 1.64-2.63). There were significant interactions between SULT1A1*3 and hot flashes (P < 0.001) and between SULT1A1*2 and depressive symptoms (P = 0.007) on menopausal stage, and there were race-specific effects of SULT1A1*2, SULT1A1*3, CYP1B1*3, and CYP3A4*1B on menopause. CONCLUSIONS: Our results suggest that genotypes are associated with the occurrence of menopause-related symptoms or the timing of the menopausal transition.

Hormone-dependent effects of FGFR2 and MAP3K1 in breast cancer susceptibility in a population-based sample of post-menopausal African-American and European-American women.

FGFR2 and MAP3K1 are members of the RAS/RAF/MEK/ERK-signaling pathway and have been identified from genome-wide association studies to be breast cancer susceptibility genes. Potential interactions of these genes and their role with respect to tumor markers, hormonal factors and race on breast cancer risk have not been explored. We examined FGFR2 and MAP3K1 variants, breast tumor characteristics and hormone exposures in a population-based case-control sample of 1225 European-American (EA) and 584 African-American (AA) women. FGFR2 rs1219648 and rs2981582 genotypes were significantly associated with breast cancer in EA only in estrogen receptor-positive (ER+), progesterone receptor-positive (PR+) and HER2/Neu-negative (HER2-) tumors. MAP3K1 was not associated with breast cancer in EA women, but it was associated with breast cancer in AA women, again limited to ER+, PR+ and HER2- tumors. An interaction was observed between combined hormone replacement therapy use and FGFR2 rs1219648 genotypes on breast cancer risk in EA women (P = 0.010). Finally, we observed a significant interaction between MAP3K1 rs889312 and FGFR2 rs2981582 (P = 0.022) in AA but not EA women. These results confirm that FGFR2 and MAP3K1 are involved in breast cancer susceptibility and confer their effects primarily in ER+ and PR+ tumors. We further report that these genes confer their effects in HER2- tumors, interact with one another to confer breast cancer susceptibility in AA women and interact with hormone exposures in AA and EA women.