Goldgar, DE

Abstract Background: Clinical germline genetic testing of cancer predisposition gene panels is used to identify women at increased risk for breast cancer. The identification of pathogenic mutations in established high and moderate predisposition genes may result in improved risk management of breast cancer for tested patients and their family members through tailored screening, prophylactic surgeries, or chemoprevention. However, the risks of breast cancer associated with mutations in these genes have likely been overestimated for many women in the general population because previous studies have focused on individuals with a family history of breast and/or ovarian cancer, early onset disease, or triple negative breast cancer. The goal of the “CAnceR RIsk Estimates Related to Susceptibility” (CARRIERS) study is to estimate breast cancer risks associated with mutations in hereditary cancer panel genes in the general population. Methods: Germline DNA samples from blood or saliva were obtained from 39,439 breast cancer patients and matched unaffected controls from six US-based cohorts (BWHS, CPSII, CTS, MEC, NHS1, NHS2, WHI). DNA was subjected to dual bar-coded QIAseq multiplex PCR-based amplification of 1733 target regions covering all coding regions of 37 cancer predisposition genes and sequenced. Mutation calling was conducted with Haplotype Caller and Vardict. Results: High quality sequence data was obtained for 38,990 of 39,439 samples (98.9%) and for 99.3% of target regions. Pathogenic mutations in 12 known breast cancer predisposition genes were identified 4.5% of all breast cancer cases and 2.1% of controls; and in 6.7% of African American breast cancer cases and 1.8% of controls. Differences in mutation frequencies were observed by age with mutations in 7.8% of cases diagnosed £50 years of age and 4.0% of cases diagnosed over age 50. Mutations in ATM, BRCA1, BRCA2, and PALB2 were enriched 2 to 3-fold in cases diagnosed under age 50 relative to older cases. No change in frequency of CHEK2 mutations by age was observed. In case-control analyses mutations in BRCA1, BRCA2 and PALB2 were significantly associated with a high risk of breast cancer (odds ratio (OR)>4.0). Of these, BRCA1 and BRCA2 displayed ORs of 13.5 and 16.6 in the £50 age group, but only 5.7 and 3.2 in the >50 age group. Only minor age-specific effects were observed for PALB2. Mutations in ATM and CHEK2 were associated with moderate risks of breast cancer (OR=2.0 to 4.0) in the younger age group, but not in the older age group. Conclusions: Results from the CARRIERS cohort-based study establish that mutations in known breast cancer predisposition genes are associated with only moderate risks of breast cancer in the general population. However, risks are substantially increased for BRCA1 and BRCA2 but not ATM, CHEK2 or PALB2 mutations in those £50 years of age. The age-related estimates of breast cancer risk for each of the hereditary cancer panel genes in this study may inform selection of individuals in the general population who may benefit from genetic testing and associated risk management strategies. Citation Format: Couch FJ, Hu C, Hart SN, Gnanaolivu RD, Lilyquist J, Lee KY, Gao C, Eckloff B, Samara R, Klebba J, Auer P, Bernstein L, Gaudet M, Haiman C, Palmer JR, Yao S, Domchek SM, Weitzel JN, Goldgar DE, Nathanson KL, Kraft P, Polley EC. Age-related breast cancer risk estimates for the general population based on sequencing of cancer predisposition genes in 19,228 breast cancer patients and 20,211 matched unaffected controls from US based cohorts in the CARRIERS study [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr GS2-01.

Abstract Clinical genetic testing panels are broadly used to gather information about cancer predisposition in individuals with personal and/or family history of breast cancer. However, the involvement of several of the genes on clinical testing panels in predisposition to breast cancer, such as MRE11A and RAD50, has recently come into question. In addition, accurate risk estimates for breast and other cancer are not well defined for the majority of genes on testing panels. We studied 60,000 women diagnosed with breast cancer who were tested for germline cancer predisposing mutations using hereditary cancer gene panels. Information on personal and family cancer history, age of diagnosis, and ethnicity of patients was obtained from test requisition forms. Greater than 90% met National Comprehensive Cancer Network HBOC testing criteria. To estimate gene-specific risks for breast cancer, case-control analyses were performed comparing the frequencies of pathogenic mutations from Caucasian cancer cases with frequencies from Caucasian, non-Finnish, non-TCGA controls from the Exome Aggregation Consortium (ExAC) database. Mutations were detected in 9% of breast cancer patients. Twelve genes displayed a significant association (p<0.05) with breast cancer. Nine of these genes, including ATM, RAD51D, NF1, and MSH6, were associated with moderate risk (RR>2.0) of breast cancer and three genes (BRCA1, BRCA2, PALB2) were associated with high risk (RR>5.0) of breast cancer. Cumulative age-dependent risk models were developed for each gene. This large clinical testing dataset of 60,000 women with breast cancer provides useful data for many predisposition genes previously lacking risk estimates, and should prove useful for clinical risk management of patients with inherited mutations in these genes. Citation Format: Couch FJ, Hu C, Lilyquist J, Shimelis H, Akinhanmi M, Na J, Polley EC, Hart SN, McFarland R, LaDuca H, Huether R, Goldgar DE, Dolinsky JS. Breast cancer risks associated with mutations in cancer predisposition genes identified by clinical genetic testing of 60,000 breast cancer patients [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr S2-01.

Abstract Clinical genetic testing of individuals with a personal or family history of breast and ovarian cancer using panels for BRCA1/2 and other candidate cancer predisposition genes has become routine clinical practice. Several of the genes on hereditary cancer testing panels have been strongly associated with specific subtypes of breast cancer. In particular, individuals with germline mutations in BRCA1 predominantly develop estrogen receptor (ER)-negative and triple negative (TN) (estrogen receptor negative, progesterone receptor negative, HER2 negative) breast tumors. In contrast, CHEK2 and ATM mutations have been associated with ER-positive breast cancer. In this study, associations between mutations in panel genes and breast cancer subtypes were evaluated. A cohort of 60,000 breast cancer patients tested for germline cancer predisposing mutations using hereditary cancer gene panels was utilized. Information on personal and family cancer history, age of diagnosis, tumor pathology, and ethnicity of patients was obtained from test requisition forms or by follow up with ordering health care providers. Mutations in each gene were combined into four histological subtypes (triple negative; HER2 positive; ER-positive,HER2-positive; and ER-positive,HER2 negative). Associations for each subtype were estimated by case-control analyses comparing the frequencies of pathogenic mutations in each subtype with frequencies from non-TCGA controls from the Exome Aggregation Consortium (ExAC) database. In addition, case-case analyses were conducted to assess enrichment of gene mutations in specific breast cancer subtypes. Among the observed associations between genes and breast cancer subtypes, mutations in CHEK2 and ATM were highly enriched in luminal breast cancers and BARD1 was specifically associated with TN breast cancer. Refining the spectrum of pathological correlates with mutations in hereditary breast cancer genes will aid gene specific cancer risk management, and may accelerate the development of novel gene-specific therapeutic interventions. Citation Format: Couch FJ, Lilyquist J, Na J, Hu C, Polley EC, Shimelis H, Akinhanmi M, McFarland R, LaDuca H, Goldgar DE, Dolinsky JS. Associations between breast cancer subtypes and mutations in cancer predisposition genes identified by clinical genetic testing of breast cancer patients [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P5-09-03.

Abstract Approximately 15% of genetic screens for mutations in BRCA1 and BRCA2 identify Variants of Uncertain Significance (VUS). Primarily missense mutations, VUS are often difficult to interpret, leading to either uncertainty in how to properly counsel a patient or an unnecessary prophylactic surgery. Given the paucity of data for which missenses are classified as truly pathogenic, computational deleterious missense prediction (DMP) algorithms are used to predict whether a mutation is likely deleterious or neutral. Accuracy of DMPs can vary considerably and have only been calibrated on a relatively small number of missense mutations of demonstrable effect on protein function. In this study, the performance of 41 different DMPs was compared to functional data from 455 functionally characterized missense variants in BRCA1 and BRCA2. New optimized thresholds for classifying missense mutations as deleterious are presented for several existing models as well as a newly derived naïve voting method (NVM). The areas under the curve estimates for the NVM approach are between 0.889-0.922, much higher than previous methods. We estimate that the overall pathogenic potential of missense variants to be 6.8% for BRCA1 and 3.2% of BRCA2, but can be as high as 50% depending on protein location. Overall these results provide key insights into how to predict deleterious missense mutations in BRCA1 and BRCA2. Citation Format: Hart SN, Hoskin T, Shimelis H, Feng B, Lindor NM, Monteiro A, Iversen E, Goldgar DE, Suman V, Couch FJ. Optimized prediction of deleterious missense mutations in BRCA1 and BRCA2 genes [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P2-02-03.