Haeberle, Lothar

Abstract Studies have identified genetic and epidemiologic factors associated with mammographic density (MD) phenotypes. However, MD-associated genetic variants only account for a small proportion of the total estimated heritability. Interrogating interactions between genetic and epidemiologic factors could potentially identify additional MD-associated loci, expand our understanding of the genetic basis of MD phenotypes, and clarify how epidemiologic factors modulate relationships between genetic variants and MD. We conducted six separate genome-wide, gene–environment (GxE) interaction analyses, applying 2 degrees of freedom (df) and 1df interaction tests, for each of three MD phenotypes (percent density, dense area (DA), and nondense area (NDA)). The six epidemiologic factors considered were height, ever parous, parity, ever menopausal hormone therapy, ever breastfeeding, and months of breastfeeding. We included European ancestry participants from multiple studies within the Markers of Density consortium and the Breast Cancer Association Consortium (n = 4895-16 218 depending on specific analyses). We identified 11 loci with genome-wide significant (P < 5 × 10−8) interaction tests including two novel common genetic signals interacting with parity (8p21.2) and ever breastfeeding (19p13.2) for NDA. Our results suggest that epidemiologic risk factors might influence relationships between common genetic variants and MD phenotypes at particular genomic loci.

Abstract We evaluated the joint associations between a new 313-variant PRS (PRS313) and questionnaire-based breast cancer risk factors for women of European ancestry, using 72 284 cases and 80 354 controls from the Breast Cancer Association Consortium. Interactions were evaluated using standard logistic regression and a newly developed case-only method for breast cancer risk overall and by estrogen receptor status. After accounting for multiple testing, we did not find evidence that per-standard deviation PRS313 odds ratio differed across strata defined by individual risk factors. Goodness-of-fit tests did not reject the assumption of a multiplicative model between PRS313 and each risk factor. Variation in projected absolute lifetime risk of breast cancer associated with classical risk factors was greater for women with higher genetic risk (PRS313 and family history) and, on average, 17.5% higher in the highest vs lowest deciles of genetic risk. These findings have implications for risk prevention for women at increased risk of breast cancer.

1048 Background: Germline BRCA1/2 ( gBRCA) mutations (mt) are some of the few actionable alterations in mBC patients. The PARP inhibitors olaparib/talazoparib are more effective than chemotherapy (ctx) in patients with a gBRCAmt and HER2 negative(-) mBC. In mBC patients the TNT-study suggested a better progression-free survival (PFS) for g BRCA-mt compared to patients with a gBRCA1/2 wildtype (wt) when treated with platinum and not with a taxane. Otherwise little is known about the prognostic effect of g BRCA1/2mt in mBC patients. Methods: PRAEGNANT (NCT02338167) is a prospective mBC registry with a focus on molecular biomarkers. Patients were eligible for this analysis if their mBC was HER2- and treated with ctx for the first time (referred to as first-line ctx). Hormone receptor (HR) positive patients had to have all hormone therapies exhausted. Mutation frequencies and their association with patient and tumor characteristics were analyzed. Multivariable Cox regression models were built with commonly established prognostic factors and g BRCA mutation status as predictors of PFS and overall survival (OS) from first-line ctx. Results: Out of 2932 PRAEGNANT patients, 576 were HER2- and received first-line ctx. Of those 529 patients with g BRCA genotype results and follow up information could be analyzed. 24 patients (4.5%) had a g BRCAmt (11 BRCA1, 13 BRCA2). Mutation rate in HR positive patients was 3.9% (17/432) and 7.2% (7/97) in HR negative patients. Most patients received ctx either as the first treatment in the metastatic setting or after one line of hormone therapy (n=382; 72.2%). Multivariable Cox regression models showed an adjusted hazard ratio for gBRCAmt vs. gBRCAwt patients of 0.70 (95% CI: 0.43-1.15) for PFS and of 0.41 (95% CI: 0.18-0.93) for OS. Most frequent ctx treatments were taxane (52%) or capecitabine based (21%). Additionally, the prevalence of somatic BRCA1/2 mutations in this population will be presented. Conclusions: In this HER2- mBC population under ctx g BRCA mutation rates were within the expected range of about 5%. Within the analyzed population patients with a g BRCA mutation seemed to have a better OS than patients without a mutation. PFS results pointed in the same direction without statistical significance. However, with only 24 mutations replication of these results in additional cohorts is warranted. Clinical trial information: NCT02338167.

Abstract Background New treatment strategies for metastatic breast cancer (mBC) are mainly driven by therapies against specific targets. BRCA mutations are one of the few established actionable targets, with PARP-Inhibitors and Platinum showing high efficacy in mBC. Hereditary cancer testing panels are now broadly used for identification of individuals with BRCA1/2 mutations who may benefit from these therapies. Many of these panels also contain other predisposition genes involved in BRCA-related DNA repair pathways, but the clinical relevance of mutations in these genes remain unclear. The aim of this study was to describe the mutation rates of BRCA1/2 and panel-based predisposition genes, and the associated clinical characteristics of individuals with these mutations, in a prospective cohort of mBC patients. Methods The PRAEGNANT mBC registry (NCT02338167) is a prospective registry for metastatic breast cancer patients with a focus on molecular biomarkers. Patients receiving any therapeutic regimen are eligible for this registry. Germline DNA was collected at study entry and genotyped for 37 cancer predisposition genes including BRCA1 and BRCA2. The frequency of mutations in each gene was determined, and associations between mutations and patient and tumor characteristics, metastatic pattern, and overall survival were assessed. Results Mutations in established high (odds ratio (OR)>5.0) and moderate risk (OR>2.0) breast cancer genes (BRCA1/2, PALB2, CHEK2, ATM, RAD51D, BARD1, and MSH6) were seen in 123 of 1462 tested patients with mBC (8.4%). BRCA1 and BRCA2 mutations were seen in 1.4% and 2.9% of patients respectively. Most frequently mutated non-BRCA panel genes were CHEK2, PALB2 and ATM with 2.8%, 0.8% and 0.6% of patients. Mutation frequency varied with regard to patients who developed brain metastases, visceral metastases or bone only metastases. BRCA1 or BRCA2 mutations were seen frequently in patients with brain (5.3%) or visceral metastases (5.2%), but were present in only 2.5% patients with bone only metastases and 1.5% of patients with lesions in other locations. Panel genes were equally distributed among all metastatic patients. PALB2 mutations (n=11) were only seen in patients with brain (1.9%) and visceral metastases (0.9%), but not in patients with bone metastases or other locations. 36.4% (N=4) of all patients with PALB2 mutations developing a brain metastasis. When adjusted for other mBC prognostic factors, a mutation (all genes) was associated with an unfavorable prognosis (HR: 1.50; 95%CI: 1.04 to 2.30, p=0.03). Mutation frequencies were similar according to therapy lines. All other associations with molecular subtypes and risk factors were similar to primary breast cancer cases. Conclusion Mutations in high and moderate risk breast cancer genes were frequent in metastatic breast cancer patients. The frequency was substantially higher than the 4 to 5% mutation frequency observed among unselected primary breast cancer patients, but is consistent with recent results from studies of metastatic prostate cancer patients. Patients with brain and visceral metastases had the highest BRCA mutation rates. Results suggested that PALB2 mutations may be more frequent in patients with brain metastases. Citation Format: Fasching PA, Hu C, Hart SN, Polley EC, Lee KY, Gnanolivu RD, Lilyquist J, Hartkopf AD, Taran FA, Janni W, Hadji P, Tesch H, Haeberle L, Ettl J, Lux MP, Lueftner D, Wallwiener M, Mueller V, Beckmann MW, Belleville E, Wimberger P, Untch M, Kolberg H-C, Fehm TN, Overkamp F, Wallwiener D, Brucker SY, Schneeweiss A, Couch F. Cancer predisposition genes in metastatic breast cancer – Association with metastatic pattern, prognosis, patient and tumor characteristics [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr PD1-02.

Background The rarity of mutations in PALB2, CHEK2 and ATM make it difficult to estimate precisely associated cancer risks. Population-based family studies have provided evidence that at least some of these mutations are associated with breast cancer risk as high as those associated with rare BRCA2 mutations. We aimed to estimate the relative risks associated with specific rare variants in PALB2, CHEK2 and ATM via a multicentre case-control study. Methods We genotyped 10 rare mutations using the custom iCOGS array: PALB2 c.1592delT, c.2816T>G and c.3113G>A, CHEK2 c.349A>G, c.538C>T, c.715G>A, c.1036C>T, c.1312G>T, and c.1343T>G and ATM c.7271T>G. We assessed associations with breast cancer risk (42 671 cases and 42 164 controls), as well as prostate (22 301 cases and 22 320 controls) and ovarian (14 542 cases and 23 491 controls) cancer risk, for each variant. Results For European women, strong evidence of association with breast cancer risk was observed for PALB2 c.1592delT OR 3.44 (95% CI 1.39 to 8.52, p=7.1×10−5), PALB2 c.3113G>A OR 4.21 (95% CI 1.84 to 9.60, p=6.9×10−8) and ATM c.7271T>G OR 11.0 (95% CI 1.42 to 85.7, p=0.0012). We also found evidence of association with breast cancer risk for three variants in CHEK2, c.349A>G OR 2.26 (95% CI 1.29 to 3.95), c.1036C>T OR 5.06 (95% CI 1.09 to 23.5) and c.538C>T OR 1.33 (95% CI 1.05 to 1.67) (p≤0.017). Evidence for prostate cancer risk was observed for CHEK2 c.1343T>G OR 3.03 (95% CI 1.53 to 6.03, p=0.0006) for African men and CHEK2 c.1312G>T OR 2.21 (95% CI 1.06 to 4.63, p=0.030) for European men. No evidence of association with ovarian cancer was found for any of these variants. Conclusions This report adds to accumulating evidence that at least some variants in these genes are associated with an increased risk of breast cancer that is clinically important.

Abstract Background: Chemotherapy-related amenorrhea (CRA) impacts quality of life and reproductive options, and may play a role in treatment decision-making for young breast cancer patients. Although age, increasing doses of alkylating agents, and tamoxifen are known to increase the risk of chemotherapy-related amenorrhea (CRA), it is difficult to predict which women will develop CRA in order to inform fertility preservation and treatment decisions. We sought to investigate whether single nucleotide polymorphisms (SNPs) that have been associated with a younger age at natural menopause and ovarian reserve in non-oncologic populations were predictive of CRA in two large German clinical trials that administered gonadotoxic chemotherapy. Methods: A total of 1322 premenopausal participants under age 50 who enrolled in SUCCESS B (a phase 3 trial of FEC-docetaxel-trastuzumab +/- gemcitabine for high risk early stage breast cancer) or SUCCESS C (a phase 3 trial of FEC-docetaxel-cyclophosphamide vs. docetaxel-cyclophosphamide that also tested the efficacy of a weight loss intervention in early stage breast cancer patients) were eligible for this study. We excluded patients who were receiving ovarian suppression. On these trials, menstrual status was self-reported as amenorrheic or not every three months after chemotherapy. Bloods were stored and patients provided consent for DNA analysis. We genotyped nine candidate SNPs in six genes (rs2002555 and rs11170547 in AMHR2, rs6166 in FSHR, rs10852344 <60kb from TNFRSF17/RUNDC2A/ GSPT1, rs12461110 in NLRP11, rs1801133 in MTHFR, rs2066470 in MTHRF, rs3810682 in BMP15, and rs615942 in COASY), and examined their association with CRA at 12-month and 24-month time points using logistic regression adjusted for age, BMI, and tamoxifen. Results: Of the 554 eligible women with SNP data and menstrual data at 12 months, 70% reported CRA; of the 458 eligible women with SNP data and menstrual data at 24 months, 69% reported CRA. The two SNPs in AMHR2 showed suggestive associations with CRA at 12 and 24 months. [Final results pending]. Conclusions: Genetic variation in AMHR2 may be associated with CRA. Additional research will be needed to validate these findings in other breast cancer survivors and to identify additional SNPs that may be associated with CRA. Together with other clinical factors, genetic variation may improve our ability to predict who will experience CRA, and may inform reproductive and treatment decision-making in cancer patients. Citation Format: Ruddy KJ, Rack B, Schwitulla J, Lambrechts D, Haeberle L, Schramm A, Trapp E, Scholz C, Beutler AS, Ginsburg E, Couch F, Partridge AH, Wang L, Weinshilboum RM, Janni W, Vachon C, Fasching P. Genetic predictors of chemotherapy-related amenorrhea. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P4-10-07.

Abstract Purpose: Mammographic breast density is an established and strong risk factor for breast cancer. Recently, a number of common genetic susceptibility loci have been identified as risk factors for breast cancer. We present the first report on the relative contribution of 76 validated breast cancer susceptibility loci, in the context of a polygenic risk score (PRS), to the breast density and breast cancer association. We also examine whether the PRS improves prediction of the Breast Cancer Surveillance Consortium (BCSC) 5-year risk model above and beyond breast density and clinical factors included in the model. Methods: The study population included 1643 cases and 2397 controls from three independent epidemiologic studies: the Mayo Mammography Health Study (MMHS), the Mayo Clinic Breast Cancer Study (MCBCS), and the Bavarian Breast Cancer Cases and Control Study (BBCC). Data collected on patients in each of the studies included clinical risk factor, BI-RADS breast density [a) almost entirely fat; b) scattered fibroglandular densities; c) heterogeneously dense; and d) extremely dense] and genotypes for the 76 breast cancer susceptibility loci known at the time of the study. We formed a PRS from the reported per-SNP odds ratios (OR) for 76 known breast cancer susceptibility loci, and evaluated whether BI-RADS density and the PRS were independent risk factors for breast cancer, when adjusted for age, 1/BMI and study. We also incorporated the PRS (OR) into the BCSC 5-year risk model and estimated 5-year risk for the MMHS nested case-control study of 339 invasive cases, 765 controls. Results: BI-RADS density (p<0.0001) and PRS (p<0.0001) were independent risk factors for breast cancer that together showed greater discrimination of risk (AUC=0.69) than density (AUC=0.66; ΔAUC=0.029) or PRS score alone (AUC=0.68; ΔAUC=0.013; p<0.001). Relative to those with scattered fibroglandular densities and average (2nd quartile) PRS, women with extremely dense breasts and in the highest PRS quartile, had a 2.7 fold (95%CI: 1.7-4.1) increased risk of breast cancer, while those with fatty breasts and in the lowest PRS quartile had a reduced risk (OR=0.30, 95%CI: 0.18-0.51). Incorporation of the PRS into the BCSC risk model improved discrimination (ΔAUC=0.031, p=0.001), for a net reclassification improvement of 20% (95%CI: 11%-28%), split equally among cases (9%) and controls (11%). Conclusion: BI-RADS density and the PRS are both important risk factors for breast cancer that can be included in breast cancer risk models to improve prediction of this disease. Using these models to identify high and low-risk risk groups will facilitate improved tailored screening and primary prevention interventions. Citation Format: Celine M. Vachon, V. Shane Pankratz, Christopher G. Scott, Lothar Haeberle, Elad Ziv, Matthew R. Jensen, Kathleen R. Brandt, Dana H. Whaley, Janet E. Olson, Katharina Heusinger, Carolin C. Hack, Sebastian M. Jud, Matthias W. Beckmann, Jeffrey A. Tice, Kristen S. Purrington, Thomas A. Sellers, Karla Kerlikowske, Peter A. Fasching, Fergus J. Couch. The contribution of common breast cancer susceptibility loci to the breast density and breast cancer association and the Breast Cancer Surveillance Consortium (BCSC) risk model. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 940. doi:10.1158/1538-7445.AM2014-940