A. H. Wu

Common Breast Cancer Susceptibility Variants in LSP1 and RAD51L1 Are Associated with Mammographic Density Measures that Predict Breast Cancer Risk

Background: Mammographic density adjusted for age and body mass index (BMI) is a heritable marker of breast cancer susceptibility. Little is known about the biologic mechanisms underlying the association between mammographic density and breast cancer risk. We examined whether common low-penetrance breast cancer susceptibility variants contribute to interindividual differences in mammographic density measures. Methods: We established an international consortium (DENSNP) of 19 studies from 10 countries, comprising 16,895 Caucasian women, to conduct a pooled cross-sectional analysis of common breast cancer susceptibility variants in 14 independent loci and mammographic density measures. Dense and nondense areas, and percent density, were measured using interactive-thresholding techniques. Mixed linear models were used to assess the association between genetic variants and the square roots of mammographic density measures adjusted for study, age, case status, BMI, and menopausal status. Results: Consistent with their breast cancer associations, the C-allele of rs3817198 in LSP1 was positively associated with both adjusted dense area (P = 0.00005) and adjusted percent density (P = 0.001), whereas the A-allele of rs10483813 in RAD51L1 was inversely associated with adjusted percent density (P = 0.003), but not with adjusted dense area (P = 0.07). Conclusion: We identified two common breast cancer susceptibility variants associated with mammographic measures of radiodense tissue in the breast gland. Impact: We examined the association of 14 established breast cancer susceptibility loci with mammographic density phenotypes within a large genetic consortium and identified two breast cancer susceptibility variants, LSP1-rs3817198 and RAD51L1-rs10483813, associated with mammographic measures and in the same direction as the breast cancer association. Cancer Epidemiol Biomarkers Prev; 21(7); 1156–. ©2012 AACR.

Progesterone receptor variation and risk of ovarian cancer is limited to the invasive endometrioid subtype: Results from the ovarian cancer association consortium pooled analysis

There is evidence that progesterone plays a role in the aetiology of invasive epithelial ovarian cancer. Therefore, genes involved in pathways that regulate progesterone may be candidates for susceptibility to this disease. Previous studies have suggested that genetic variants in the progesterone receptor gene (PGR) may be associated with ovarian cancer risk, although results have been inconsistent. We have established an international consortium to pool resources and data from many ovarian cancer case–control studies in an effort to identify variants that influence risk. In this study, three PGR single nucleotide polymorphisms (SNPs), for which previous data have suggested they affect ovarian cancer risk, were examined. These were +331 C/T (rs10895068), PROGINS (rs1042838), and a 3′ variant (rs608995). A total of 4788 ovarian cancer cases and 7614 controls from 12 case–control studies were included in this analysis. Unconditional logistic regression was used to model the association between each SNP and ovarian cancer risk and two-sided P-values are reported. Overall, risk of ovarian cancer was not associated with any of the three variants studied. However, in histopathological subtype analyses, we found a statistically significant association between risk of endometrioid ovarian cancer and the PROGINS allele (n=651, OR=1.17, 95% CI=1.01–1.36, P=0.036). We also observed borderline evidence of an association between risk of endometrioid ovarian cancer and the +331C/T variant (n=725 cases; OR=0.80, 95% CI 0.62–1.04, P=0.100). These data suggest that while these three variants in the PGR are not associated with ovarian cancer overall, the PROGINS variant may play a modest role in risk of endometrioid ovarian cancer.

Validating genetic risk associations for ovarian cancer through the international Ovarian Cancer Association Consortium

The search for genetic variants associated with ovarian cancer risk has focused on pathways including sex steroid hormones, DNA repair, and cell cycle control. The Ovarian Cancer Association Consortium (OCAC) identified 10 single-nucleotide polymorphisms (SNPs) in genes in these pathways, which had been genotyped by Consortium members and a pooled analysis of these data was conducted. Three of the 10 SNPs showed evidence of an association with ovarian cancer at P⩽0.10 in a log-additive model: rs2740574 in CYP3A4 (P=0.011), rs1805386 in LIG4 (P=0.007), and rs3218536 in XRCC2 (P=0.095). Additional genotyping in other OCAC studies was undertaken and only the variant in CYP3A4, rs2740574, continued to show an association in the replication data among homozygous carriers: ORhomozygous(hom)=2.50 (95% CI 0.54-11.57, P=0.24) with 1406 cases and 2827 controls. Overall, in the combined data the odds ratio was 2.81 among carriers of two copies of the minor allele (95% CI 1.20–6.56, P=0.017, phet across studies=0.42) with 1969 cases and 3491 controls. There was no association among heterozygous carriers. CYP3A4 encodes a key enzyme in oestrogen metabolism and our finding between rs2740574 and risk of ovarian cancer suggests that this pathway may be involved in ovarian carcinogenesis. Additional follow-up is warranted.

Tagging single-nucleotide polymorphisms in candidate oncogenes and susceptibility to ovarian cancer.

Low–moderate risk alleles that are relatively common in the population may explain a significant proportion of the excess familial risk of ovarian cancer (OC) not attributed to highly penetrant genes. In this study, we evaluated the risks of OC associated with common germline variants in five oncogenes (BRAF, ERBB2, KRAS, NMI and PIK3CA) known to be involved in OC development. Thirty-four tagging SNPs in these genes were genotyped in ∼1800 invasive OC cases and 3000 controls from population-based studies in Denmark, the United Kingdom and the United States. We found no evidence of disease association for SNPs in BRAF, KRAS, ERBB2 and PIK3CA when OC was considered as a single disease phenotype; but after stratification by histological subtype, we found borderline evidence of association for SNPs in KRAS and BRAF with mucinous OC and in ERBB2 and PIK3CA with endometrioid OC. For NMI, we identified a SNP (rs11683487) that was associated with a decreased risk of OC (unadjusted Pdominant=0.004). We then genotyped rs11683487 in another 1097 cases and 1792 controls from an additional three case–control studies from the United States. The combined odds ratio was 0.89 (95% confidence interval (CI): 0.80–0.99) and remained statistically significant (Pdominant=0.032). We also identified two haplotypes in ERBB2 associated with an increased OC risk (Pglobal=0.034) and a haplotype in BRAF that had a protective effect (Pglobal=0.005). In conclusion, these data provide borderline evidence of association for common allelic variation in the NMI with risk of epithelial OC.

Estrogens, Progestins, and Risk of Breast Cancer

Obesity is associated with a decreased risk of breast cancer in premenopausal women but an increased risk in postmenopausal women, an effect that increases with time since menopause. Analysis of these effects of obesity shows that there is a ceiling to the carcinogenic effect of estrogen on the breast; increases in nonsex hormone-binding globulin-bound estradiol (non-SHBG bound E2) exceeding approximately 10.2 pg/ml have no further effect on breast cancer risk; this ceiling is lower than the lowest level seen during the menstrual cycle. This suggests that the effects of menopausal estrogen therapy (ET) and menopausal estrogen-progestin therapy (EPT) on a womans breast cancer risk will greatly depend on her body mass index (BMI; weight in kilograms/height in meters squared, kg/m2) with the largest effects being in slender women. Epidemiological studies confirm this prediction. Our best estimates, per 5 years of use, of the effects of ET on breast cancer risk is a 30% increase in a woman with a BMI of 20 kg/m2 decreasing to an 8% increase in a woman with a BMI of 30 kg/m2; the equivalent figures for EPT are 50% and 26%. The analysis of the effects of estrogen also shows that even reducing the dose of estrogen in ET and EPT by as much as a half will have little or no effect on these risks. Reducing the progestin dose is likely to significantly reduce the risk of EPT: this is possible with an endometrial route of administration.

Explaining Disparities in Ovarian Cancer Incidence Rates between Women of African and European Ancestry: The Role of Genetic Factors

Non-Hispanic White (NHW) women are at higher risk of ovarian cancer than African-American (AA) women. Approximately 30% of the difference in age-adjusted invasive epithelial ovarian cancer incidence rates (AAIR) between the two groups can be explained by differing oophorectomy rates and the prevalence of non-genetic risk and protective factors. Our purpose was to determine how much of the remaining difference in AAIRs could be explained by varying allele frequencies between NHWs and AAs for 18 genome-wide significant common susceptibility variants for ovarian cancer. Using data on 13,385 cases and 24,875 controls from the Ovarian Cancer Association Consortium, a genetic risk score (GRS) was created from 18 single nucleotide polymorphisms (SNPs) associated with ovarian cancer risk following the Collaborative Oncological Gene-environment Study (COGS) effort. Relative risks for each GRS quintile were estimated using conditional logistic regression, adjusting for genetic ancestry and conditioning on study site, age, and race. The population attributable risk percent (PAR) for GRS above the lowest quintile was calculated using the Bruzzi method. Previously reported oophorectomy and non-genetic risk factor (talc, oral contraceptive use, family history of ovarian cancer, endometriosis, parity and tubal ligation) adjusted incidence rates for ovarian cancer in NHWs and AAs were 7.2 and 5.8 per 100,000 respectively. These incidence rates were further adjusted for the contribution of the GRS from this analysis. The subsequent genetic PAR adjusted rate was 5.1 per 100,000 for the European ancestry group and 4.9 for the African ancestry group, after taking into account the different oophorectomy rates and prevalence of non-genetic risk factors. These incidence rates show the unexplained difference in incidence rates between NHWs and AAs is only 3.9%. Future efforts should focus on incorporating novel non-genetic and genetic factors into this analysis to determine whether essentially all of the difference in incidence between these groups can be explained.

Erratum: Validating genetic risk associations for ovarian cancer through the International Ovarian Cancer Association Consortium (British Journal of Cancer (2009) 100 (412-420) DOI: 10.1038/sj.bjc.6604820 www.bjcancer.com)

CL Pearce, AM Near, DJ Van Den Berg, SJ Ramus, A Gentry-Maharaj, U Menon, SA Gayther, AR Anderson, CK Edlund, AH Wu, X Chen, J Beesley, PM Webb, SK Holt, C Chen, JA Doherty, MA Rossing, AS Whittemore, V McGuire, RA DiCioccio, MT Goodman, G Lurie, ME Carney, LR Wilkens, RB Ness, KB Moysich, R Edwards, E Jennison, SK Kjaer, E Hogdall, CK Hogdall, EL Goode, TA Sellers, RA Vierkant, JM Cunningham, JM Schildkraut, A Berchuck, PG Moorman, ES Iversen, DW Cramer, KL Terry, AF Vitonis, L Titus-Ernstoff, H Song, PDP Pharoah, AB Spurdle, H Anton-Culver, A Ziogas, W Brewster, V Galitovskiy and G Chenevix-Trench, Australian Cancer Study (Ovarian Cancer) Australian Ovarian Cancer Study Group on behalf of the Ovarian Cancer Association Consortium