Couch, Fergus J.

Background: Endometriosis affects an estimated 10% of reproductive-aged women and is associated with increased ovarian cancer risk. While BRCA1/2 mutations are established risk factors for ovarian cancer, their association with endometriosis remains unclear. This study aimed to characterize the prevalence and clinical features of endometriosis within a large cohort of BRCA mutation carriers. Methods: A descriptive analysis was conducted using data from a multi-center longitudinal cohort of women with pathogenic BRCA variants. Reproductive history and related factors were collected through self-reported questionnaires and compared. Results: Among 16,950 BRCA carriers, the prevalence of endometriosis was 2.4%. Compared to BRCA carriers without endometriosis, those with endometriosis were more likely to carry a BRCA2 mutation, have post-secondary education, and experience earlier menarche. BRCA carriers with endometriosis had a lower ovarian cancer prevalence than those without (10% vs. 15%, p < 0.001). Conclusions: This is the first study of this scale to report the prevalence of endometriosis among BRCA mutation carriers, which was lower than previously reported in the general population. The association between endometriosis and ovarian cancer does not appear to be generalizable to this population. Further prospective studies are warranted to clarify this association among BRCA mutation carriers.

10510 Background: The impact of germline pathogenic or likely pathogenic variants (PVs) in cancer predisposition genes on overall survival (OS) after breast cancer diagnosis is not well defined. In particular, unbiased OS estimates from population-based studies accounting for clinical subtypes of breast cancer (based on ER, PR, and HER2 status) and for genes other than BRCA1/2 are lacking. Methods: The study included 25,168 prospectively followed women with locoregional invasive breast cancer within the population-based CARRIERS study. Germline sequencing using a custom multigene amplicon-based panel was performed to identify PVs. OS was compared between germline PV carriers in ATM, BRCA1, BRCA2, CHEK2 and PALB2 and non-carriers (negative for germline PVs in 13 known breast cancer predisposition genes) for each clinical subtype of breast cancer from the time of breast cancer diagnosis to death or last follow up in a multivariable Cox proportional hazard regression analysis adjusting for age at diagnosis, race/ethnicity, histology, TNM stage, type of surgery, use of adjuvant radiation, chemotherapy and endocrine agents. Results: Among 25,168 women with breast cancer, germline PVs in one of the five breast cancer predisposition genes were detected in 5.8% of the women [ ATM : 0.8%, BRCA1 : 1.3%, BRCA2: 1.6%, CHEK2 : 1.5%, and PALB2 : 0.6%]. Among women with ER+ breast cancer, compared to non-carriers, a significantly worse OS was noted for BRCA1 (Hazard Ratio (HR): 1.8, 95% Confidence Interval (CI): 1.1 – 3.0, p=0.02) and BRCA2 (HR: 1.8, 95%CI: 1.4 – 2.4, p<0.001), but not for ATM (HR: 1.2, 95%CI: 0.8 – 1.7, p=0.40) or CHEK2 (HR:1.0, 95%CI: 0.8 – 1.3, p=1.0) PV carriers. Worse OS was noted in PALB2 PV carriers with ER+ breast cancer (HR:1.5, 95%CI: 0.9 – 2.2, p=0.09), although it did not reach statistical significance. Similar HR estimates for OS as with ER+ breast cancer were observed in women with ER+/HER2- breast cancer for BRCA1 , BRCA2 and PALB2 PV carriers, but only BRCA2 results were statistically significant. Among women with ER-negative breast cancer, compared to non-carriers, a significant difference in OS was not observed for PV carriers in ATM (HR:0.8, 95%CI: 0.4 – 1.8, p=0.63), BRCA1 (HR:1.2, 95%CI: 0.8 – 1.7, p=0.35), BRCA2 (HR: 0.8, 95%CI: 0.5 – 1.2, p=0.29), CHEK2 (HR: 0.7, 95%CI: 0.3 – 1.4), or PALB2 (HR: 0.9, 95%CI: 0.5 -1.7, p=0.78). Conclusions: The suggestive differences in OS by ER status of the tumor in BRCA1 and BRCA2 PV carriers warrant further investigation of underlying tumor biology and assessment of endocrine sensitivity of breast cancer in germline PV carriers.

Abstract Introduction: Genome-wide association studies over the past 10 years have identified over 100 common variants associated with breast cancer risk. The association of these polymorphisms varies according to estrogen receptor status of the tumor, with some associated primarily with ER+ or ER- disease, or both subtypes. However, ER expression in breast cancer cells is continuous. The aim of this study was to establish whether the association between polygenic risk scores and ER expression in breast cancer is continuous in nature. Methods: Data were taken from the international Breast Cancer Association Consortium (BCAC). Germline genotype data for 75 SNPs previously reported to be associated with breast cancer were available for 4,999 breast cancer cases for which ER expression data were also available. Automated ER expression on a continuous scale was measured using two image analysis algorithms: Astrogrid and Ariol. A third form of ER expression score, the manual Allred ordinal, was used. Genotype data were used to calculate polygenic risk scores using the equation: PRS = ∑ βx where β is the log-odds of the odds ratio (OR) of breast cancer associated with that single nucleotide polymorphism (SNP), and x is the number of variant alleles at a SNP locus. Five different PRSs were calculated: i) SNPs associated with both ER+ and ER- disease (PRS-A, n= 74) ii) SNPs associated with ER+ disease at P&lt;0.01 (PRS-B, n= 65) iii) SNPs associated with ER- disease at P&lt;0.01 (PRS-C, n= 43) iv) SNPs associated with ER+ but not ER- disease (PRS-D, n= 30) v) SNPs associated with ER- but not ER+ disease (PRS-E, n = 8) The ER-specific weights for the PRS were taken from previous OR estimates. Linear regression models adjusted for study were used to test for a relationship between the five PRSs and ER expression measured on the Ariol, Astrogrid and Allred scales. Results: There was a strong positive correlation found between PRS-B against Astrogrid (β=0.0176, P=4.06x10-4), a weak negative correlation found with PRS-C (β=-0.012, P=0.019) and a weak positive correlation for PRS-A (β=0.012, P=0.0144). PRS-D and E showed far stronger association with Astrogrid than PRS-B and C, respectively (β=0.0186 and -0.017, P=1.97x10-4 and 8.1x10-4). There was a qualitatively similar association when the PRSs were correlated with Ariol and Allred, apart from the stronger correlations with PRS-B (β=91.2 and 0.0853, P=5.52x10-4 and 1.33x10-3). Conclusion: We have shown a robust association between PRS and ER expression in the directions we predicted. This suggests that the continuous variation in ER expression is biologically plausible and linked to genetic polymorphism. The weakening of association with PRS-A and the stronger associations with PRS-D and E show that having SNPs that are associated with both ER subtypes in the same PRS weakens significance, and suggests that subtype-specific PRSs may be improved on by using SNPs exclusive to the respective subtype. Citation Format: Anamay H. Shetty, Raza Ali, Fiona Blows, Carlos Caldas, Nicholas Inard, Javier Benítez, Jenny Chang-Claude, Georgia Chenevix-Trench, Fergus Couch, Angela Cox, Peter Devilee, Douglas Easton, Montserrat Garcia-Closas, Arto Mannermaa, Heli Nevanlinna, Marjanka Schmidt, Paul Pharoah. Patient level polygenic risk scores and continuous estrogen receptor expression in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2211.

A large genotyping project within the Breast Cancer Association Consortium (BCAC) recently identified 41 associations between single nucleotide polymorphisms (SNPs) and overall breast cancer (BC) risk. We investigated whether the effects of these 41 SNPs, as well as six SNPs associated with estrogen receptor (ER) negative BC risk are modified by 13 environmental risk factors for BC. Data from 22 studies participating in BCAC were pooled, comprising up to 26,633 cases and 30,119 controls. Interactions between SNPs and environmental factors were evaluated using an empirical Bayes‐type shrinkage estimator. Six SNPs showed interactions with associated p ‐values ( p int ) <1.1 × 10 −3 . None of the observed interactions was significant after accounting for multiple testing. The Bayesian False Discovery Probability was used to rank the findings, which indicated three interactions as being noteworthy at 1% prior probability of interaction. SNP rs6828523 was associated with increased ER‐negative BC risk in women ≥170 cm (OR = 1.22, p = 0.017), but inversely associated with ER‐negative BC risk in women <160 cm (OR = 0.83, p = 0.039, p int = 1.9 × 10 −4 ). The inverse association between rs4808801 and overall BC risk was stronger for women who had had four or more pregnancies (OR = 0.85, p = 2.0 × 10 −4 ), and absent in women who had had just one (OR = 0.96, p = 0.19, p int = 6.1 × 10 −4 ). SNP rs11242675 was inversely associated with overall BC risk in never/former smokers (OR = 0.93, p = 2.8 × 10 −5 ), but no association was observed in current smokers (OR = 1.07, p = 0.14, p int = 3.4 × 10 −4 ). In conclusion, recently identified BC susceptibility loci are not strongly modified by established risk factors and the observed potential interactions require confirmation in independent studies.

Abstract Triple-negative breast cancers (TNBC), defined by the absence of estrogen receptor, progesterone receptor, and HER-2 expression, account for 12% to 24% of all breast cancers. TNBC is associated with early recurrence of disease and poor outcome. Germline mutations in the BRCA1 and BRCA2 breast cancer susceptibility genes have been associated with up to 15% of TNBC, and TNBC accounts for 70% of breast tumors arising in BRCA1 mutation carriers and 16% to 23% of breast tumors in BRCA2 carriers. Whether germline mutations in other breast cancer susceptibility genes also predispose to TNBC remains to be determined. Common variation in a subset of the 72 known breast cancer susceptibility loci identified through genome-wide association studies and other large-scale genotyping efforts have also been associated with risk of TNBC (TOX3, ESR1, RAD51L1, TERT, 19p13.1, 20q11, MDM4, 2p24.1, and FTO). Furthermore, variation in the 19p13.1 locus and the MDM4 locus has been associated with TNBC, but not other forms of breast cancer, suggesting that these are TNBC-specific loci. Thus, TNBC can be distinguished from other breast cancer subtypes by a unique pattern of common and rare germline predisposition alleles. Additional efforts to combine genetic and epidemiologic data are needed to better understand the etiology of this aggressive form of breast cancer, to identify prevention and therapeutic targets, and to impact clinical practice through the development of risk prediction models. Cancer Res; 73(7); 2025–30. ©2012 AACR.

AbstractBackground: A number of susceptibility genes are common to breast and pancreatic cancer. Recently, several breast cancer susceptibility loci have been identified through genome-wide association studies. Here we evaluated possible associations between these single nucleotide polymorphisms (SNP) and pancreatic cancer risk.Methods: Ten SNPs from FGFR2, TOX3, MAP3K1, H19, LSP1, chromosome 8q24, CASP8, and LUM were investigated for associations with pancreatic cancer risk following genotyping in 1,143 Caucasian individuals with pancreatic adenocarcinoma and 1,097 unaffected controls from a clinic-based pancreatic cancer case-control study.Results: CASP8 rs1045485 [odds ratio (OR), 0.78; 95% confidence interval (95% CI), 0.65-0.9; P = 0.005] and MAP3K1 rs889312 (OR, 0.85; 95% CI, 0.74-0.97; P = 0.017) showed evidence of association with risk of pancreatic cancer. The CASP8 rs1045485 association was evident in ever smokers (P = 0.002), but not in nonsmokers (P = 0.55), and the effect was strongest in heavy smokers (OR, 0.52; 95% CI, 0.29-0.93; P = 0.03). In contrast the MAP3K1 rs889312 association was only evident in nonsmokers (OR, 0.78; 95% CI, 0.64-0.95; P = 0.01). In addition, evaluation of the influence of the 10 SNPs on survival detected significant associations between outcome for locally advanced pancreatic cancer cases and both 8q rs6983561 (P = 0.045) and LUM rs2268578 (P = 0.02).Conclusion: Association studies in a large pancreatic case-control study indicate that SNPs associated with breast cancer may also be associated with pancreatic cancer susceptibility and survival. (Cancer Epidemiol Biomarkers Prev 2009;18(11):3044–8)

Abstract Background: Gene amplification leading to overexpression is a common event in breast tumors that is linked to tumor development and progression. The 17q23 region is amplified in &gt;40% of breast tumors and contains several candidate oncogenes. Because common genetic variation in several oncogenes has been associated with cancer risk, we assessed the relevance of common variants in the 17q23 candidate oncogenes to breast cancer. Methods: We investigated 60 polymorphisms in the TUBD1, SEPT4, PRKCA, TBX2, TBX4, TEX14, TLK2, YPEL2, and PPM1E genes from this amplicon for association with breast cancer risk among 798 Caucasian breast cancer cases and 843 unaffected Caucasian controls from the Mayo Clinic. Results: Eight polymorphisms in PRKCA, TBX4, TLK2, and YPEL2 displayed significant dose-response associations with breast cancer risk (Ptrend &lt; 0.05). Of these, PRKCA rs7342847 and TLK2 rs2245092 and rs733025 were also associated with hormone receptor–positive breast cancer: PRKCA rs7342847 (odds ratio, 0.7; 95% confidence interval, 0.6-0.9; Ptrend = 0.002) and TLK2 rs733025 and rs2245092 (both: odds ratio, 0.8; 95% confidence interval, 0.7-1.0; Ptrend = 0.03). Interactions between SEPT4 rs758377 and TEX14 rs302864 (Pinteraction = 0.0003) and between TLK2 rs733025 and YPEL2 rs16943468 (Pinteraction = 0.05) for risk of breast cancer were also observed. Conclusion: These findings suggest that single polymorphisms and combinations of polymorphisms within candidate oncogenes from the 17q23 amplicon may influence risk of breast cancer overall and possibly specific molecular subtypes of breast tumors. The findings are discussed within the context of the results from two independent data sets. (Cancer Epidemiol Biomarkers Prev 2009;18(6):1864–8)