Couch, FJ

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.

Abstract Women with one or more first-degree female relatives with a history of breast cancer have a two-fold increased risk of developing breast cancer. This risk increases with the number of affected family members, particularly for those diagnosed at a young age or with bilateral disease. Segregation analyses of breast cancer families led to the identification of inactivating mutations in the BRCA1 and BRCA2 breast cancer susceptibility genes. Pathogenic variants resulting in truncation of these proteins, along with a small number of pathogenic missense variants, have been associated with 55% to 65% lifetime risk of breast cancer in the general population and up to 85% lifetime risks among women with a strong family history of the disease. In contrast, the influence on cancer risk of many rare variants of uncertain significance (VUS) is not known. Mutations in several genes in addition to BRCA1 and BRCA2 have been implicated in predisposition to breast cancer through family segregation studies. These include moderate risk mutations (relative risk between 2.0 and 5.0) in CHEK2 and ATM, high-risk mutations (relative risk greater than 5.0) in PALB2, and high-risk mutations in CDH1, PTEN, STK11, and TP53 that are associated with hereditary diffuse gastric cancer, Cowden, Peutz-Jeghers, and Li-Fraumeni syndromes. However, risks of breast and other cancers associated with mutations in these and other genes that have been suggested to predispose to cancer have not been established or have very broad confidence intervals. Despite the absence of accurate risk estimates clinical testing with gene panels for hereditary cancer gene mutations has become an integral component of medical management for high-risk families and individuals with triple negative breast cancer. To estimate breast cancer risks several large studies of breast cancer patients from the general population and from high-risk families are underway. These studies are expected to identify the subset of panel genes that are associated with increased risk of breast cancer or breast cancer subtypes and to establish more accurate risks of breast and other cancers. In addition, classification of the clinical relevance of VUS in BRCA1, BRCA2, and other predisposition genes remains a significant problem, with patients unable to benefit from enhanced risk assessment, prevention, and clinical management. Thousands of VUS in BRCA1 and BRCA2 have already been identified through clinical testing and many more in BRCA1, BRCA2, and other predisposition genes are being identified through panel-based genetic testing and tumor sequencing studies. Efforts to classify VUS as neutral or pathogenic have focused on large case-control studies and quantitative multifactorial models based on family history of cancer and pathology. However, more recent studies have established the utility of validated functional assays for VUS assessment. Hundreds of BRCA1 and BRCA2 VUS have been reclassified by commercial testing laboratories or by the ENIGMA consortium that serves as the expert review panel for variants in these genes for the ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/) and BRCA Exchange (http://brcaexchange.org) publically accessible websites. Common genetic variants associated with breast cancer risk have also been identified through genome-wide association studies (GWAS). The magnitude of these associations have ranged from 1.03 to 1.29 in women of European ancestry. While the majority of the 179 known breast cancer variants are associated with estrogen receptor (ER) positive breast cancer, 21 of these show specific associations with ER negative or triple negative (ER negative, PR negative, HER2 negative) breast cancer. The variants in risk loci account for approximately 19% of the familial relative risk of breast cancer. Several studies have recently established that polygenic risk scores derived from these risk variants improve personalized risk assessment by identifying women at increased or reduced risk of breast cancer in the general population and by modifying risks of breast cancer among BRCA1 and BRCA2 mutation carriers. In summary, germline genetic studies have substantially changed the landscape of breast cancer, identifying mutations associated with moderate and high risks of breast cancer in up to 5% of population-based breast cancer cases and 35% of high-risk families and providing personalization of underlying breast cancer risk for all women. Citation Format: Couch FJ. OI-1 Decoding breast cancer predisposition 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 OI-1.

Abstract Background: The BRCA1 tumour suppressor gene is mutated in the germline of women who are predisposed to developing breast cancer. Gene expression profiling has identified at least five different breast cancer subtypes with BRCA- mutated breast tumours clustering with triple negative breast cancers. The majority of BRCA1-mutated breast tumours are characterised as being negative for the estrogen receptor-α (ER-α), however, the underlying molecular biology of these tumours has not yet been fully determined. The aim of this study is to identify and characterise novel proliferation-associated BRCA1 target genes that are activated in BRCA1 mutated estrogen receptor negative (ER-ve) breast tumours. Methods: Gene expression profiling and data analysis was performed on a cohort of 46 FFPE (Formalin Fixed Paraffin Embedded) derived BRCA1 mutated (ER-ve) breast tumours and matched sporadic controls using the Almac Diagnostics Breast DSA research tool. Profiling was also performed on a panel of 15 breast cancer cell lines. Bioinformatics analysis was performed using Oncomine, DAVID and Metacore. High throughput siRNA screens using HiPerFect were performed on the Qiagen Flexiplate siRNA. Validation of gene targets was performed by qRT-PCR and ChIP assay. Clonogenic assays were performed to independently validate the effect of selected target genes on cell survival. Results: A list of differentially expressed transcripts was derived from the comparison of 23 (ER-ve) BRCA1 mutated breast tumours and 23 matched sporadic controls. A genome-wide ChIP-Chip promoter analysis was also performed in MCF7 breast cancer cells. By overlapping these two datasets, a list of tumour derived BRCA1 promoter bound target genes was identified. Functional analysis of this gene list has identified the main pathways and processes that are deregulated in BRCA1 mutated (ER-ve) breast cancer including: (1) immune response (2) induction of the epithelial to mesenchymal transition (EMT) (3) cell cycle regulation and (4) apoptosis and survival. Hierarchical clustering of these 46 breast tumours and 15 breast cancer cell lines was performed and the BRCA1 mutated (ER-ve) breast cancer cell lines (MDA436 and SUM149) were identified as those that best reflect the biology BRCA1 mutated (ER-ve) tumours. High throughput siRNA screening in these cell lines has identified a set of transcripts that when inhibited have a negative impact on cellular proliferation. Independent validation by qRT-PCR, ChIP assay, western blotting and clonogenic assays have confirmed HE4 (WFDC2) as a novel BRCA1 target gene that provides a growth advantage in BRCA1 mutated (ER-ve) breast cancer cells. Conclusions: Gene expression profiling of an extensive cohort of BRCA1 mutated (ER-ve) breast tumours and matched sporadic controls has identified a profile of BRCA1 mutated (ER-ve) breast cancer. This list has been further refined to generate a list of BRCA1 promoter bound transcriptional target genes. High throughout siRNA screening has revealed a panel of genes that are implicated in the proliferation of BRCA1 mutated (ER-ve) breast cancer. HE4 has been identified as a novel BRCA1 transcriptional target gene that promotes the survival of BRCA1 mutated (ER-ve) breast tumours. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr PD10-05.

Abstract Background: Approximately 5-10% of all breast cancers are hereditary and the majority of these arise due to germline mutations in the BRCA1 and BRCA2 tumour suppressor genes. BRCA1 is involved in multiple cellular pathways including DNA damage signalling, DNA repair, cell cycle regulation, protein ubiquitination, chromatin remodelling, transcriptional regulation and apoptosis. Several distinct pathological features can be used to estimate the likelihood of the presence of a BRCA1 mutation, however, it is not yet possible to fully categorise a BRCA1 mutated tumour. BRCA1-associated breast cancers are generally defined as being ER (Estrogen Receptor) negative and indeed triple negative for ER, PR and HER2. However, approximately 10-36% of BRCA1 mutated breast cancers are, in fact, ER positive. These tumours less frequently demonstrate the characteristics more commonly associated with BRCA 1 -associated breast cancers. Initial molecular evidence also suggests that there is heterogeneity within BRCA1-associated breast tumours and this is dependent on the presence or absence of the estrogen receptor. The aims of this study are to investigate the underlying biology of BRCA1-mutated (ER positive) and BRCA1-mutated (ER negative) breast tumours. Methods: Extensive gene expression profiling and data analysis was performed on a cohort of 70 FFPE (Formalin Fixed Paraffin Embedded) derived BRCA1 mutated breast tumours and matched sporadic controls using the ALMAC Breast Cancer DSA™ research tool. Within this dataset we have generated molecular profiles of: (1) BRCA 1 -mutated ER positive and (2) BRCA1-mutated ER negative breast cancer. Functional analysis was performed using DAVID and METACORE. Validation of gene targets was performed by qRT-PCR and Western blotting. Results: A list of differentially expressed transcripts was derived from the comparison of 35 BRCA1 mutant breast tumours and 35 matched sporadic controls. Further analysis based on the presence and absence of ER identified a set of transcripts defining BRCA1-mutated (ER positive) and BRCA1-mutated (ER negative) breast cancer. Functional analysis of these two datasets has identified the main pathways and processes that are deregulated. Specifically, BRCA1-deficiency in the absence of ER was associated with deregulation of pathways implicated in immune response whereas BRCA 1 deficiency in the presence of ER was associated with pathways implicated in cell adhesion and cytoskeletal remodelling. Validation of the key genes underlying these two BRCA1-deficient breast cancer subtypes has been performed. Discussion: This approach has revealed significant heterogeneity within BRCA1 mutated breast cancer based on the presence or absence of ER. Significant differences in the transcripts and molecular processes underlying BRCA1-mutated (ER positive) and BRCA1-mutated (ER negative) breast tumours have been identified. The ability to identify BRCA 1 -deficiency by gene expression profiling from FFPE derived breast tissue may also have significant clinical application. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P6-04-14.