Breast cancer is one of the most common cancers in the US. Approximately 15% to 20% of cases exhibit a family history of the disease suggesting a strong heritable component. Susceptibility to breast cancer is associated with high-penetrance germline mutations in BRCA1, BRCA2, PTEN, STK11, CDH1, and TP53. In addition, inherited inactivating mutations in several other genes have been associated with familial breast cancer. These include ATM, CHEK2, PALB2, BRIP1, BARD1, RAD51C, RAD51D, XRCC2, NBN, RAD50, and MRE11A. While inactivating mutations in ATM and CHEK2 have been associated with moderate 3 to 7-fold increased risk of breast cancer with lifetime risks of between 20% and 50%, these risk estimates are imprecise and little is known about the risk of breast and other cancers associated with inactivating mutations in the other predisposition genes. Clinical genetic testing for all of these high and moderate risk predisposition genes is now available. Many women, with personal and family history of breast, ovarian or other cancers, are pursuing testing for mutations with these panels, which has seen an upsurge in demand in response to 'Angelina's story'. Initial data suggest that ~10% of panel tests identify truncating mutations and 20% yield variants of uncertain significance (VUS) in the form of missense and intronic changes of undefined clinical relevance in the known predisposition genes. Although potentially useful for establishing the etiology of breast cancer in a patient's family, there remain significant limitatins in the clinical interpretation of the results from the panel testing. In particular, the age-relate risk of breast and other cancers associated with mutations in the genes are largely undefined. Furthermore, clear medical management recommendations for mutation carriers have not been developed. Thus, the results of these tests can lead to confusion and uninformed medical decisions that can result in significant harm. We propose to use high-throughput mutation screening of known breast cancer predisposition genes in breast cancer case-control studies and high-risk breast cancer families to establish the risks of breast and other cancers associated with deleterious mutations in these genes as follows:
Aim 1) Establish the risk of breast cancer in the general population associated with mutations in known predisposition genes using large cohort-based case-control studies;
Aim 2) Define the penetrance of cancers associated with inactivating mutations in panel-based predisposition genes through breast cancer family studies;
Aim 3) Determine the clinical relevance of VUS in the known predisposition genes. At the conclusion of the study, we expect to establish risk estimates associated with deleterious mutations in the genes for the general population and breast cancer families, leading to much improved risk assessment for mutation carriers. In addition, we expect to establish the clinical relevance of many VUS in the known predisposition genes. The results of this study will also provide the necessary data to establish standard of care medical management recommendations for carriers of deleterious mutations in moderate penetrance genes, a critical unmet need.

Public Health Relevance

This highly translational project will result in defined risk estimates associated with deleterious mutations in known moderate risk breast cancer predisposition genes. Functional assays will also be used to classify the clinical relevance of numerous VUS in these genes. Overall, the significant advances from the study will lead to improved risk assessment and clinical management of women found to carry mutations in moderate risk breast cancer susceptibility genes.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA192393-02
Application #
8934075
Study Section
Special Emphasis Panel (ZRG1-PSE-K (90))
Program Officer
Rotunno, Melissa
Project Start
2014-09-25
Project End
2019-08-31
Budget Start
2015-09-01
Budget End
2016-08-31
Support Year
2
Fiscal Year
2015
Total Cost
$1,319,364
Indirect Cost
$248,882
Name
Mayo Clinic, Rochester
Department
Type
DUNS #
006471700
City
Rochester
State
MN
Country
United States
Zip Code
55905
Weigelt, Britta; Bi, Rui; Kumar, Rahul et al. (2018) The Landscape of Somatic Genetic Alterations in Breast Cancers From ATM Germline Mutation Carriers. J Natl Cancer Inst 110:1030-1034
Fasching, Peter A; Loibl, Sibylle; Hu, Chunling et al. (2018) BRCA1/2 Mutations and Bevacizumab in the Neoadjuvant Treatment of Breast Cancer: Response and Prognosis Results in Patients With Triple-Negative Breast Cancer From the GeparQuinto Study. J Clin Oncol 36:2281-2287
Colombo, Mara; Lòpez-Perolio, Irene; Meeks, Huong D et al. (2018) The BRCA2 c.68-7T > A variant is not pathogenic: A model for clinical calibration of spliceogenicity. Hum Mutat 39:729-741
Hu, Chunling; Hart, Steven N; Polley, Eric C et al. (2018) Association Between Inherited Germline Mutations in Cancer Predisposition Genes and Risk of Pancreatic Cancer. JAMA 319:2401-2409
Leon-Ferre, Roberto A; Polley, Mei-Yin; Liu, Heshan et al. (2018) Impact of histopathology, tumor-infiltrating lymphocytes, and adjuvant chemotherapy on prognosis of triple-negative breast cancer. Breast Cancer Res Treat 167:89-99
Horne, Hisani N; Oh, Hannah; Sherman, Mark E et al. (2018) E-cadherin breast tumor expression, risk factors and survival: Pooled analysis of 5,933 cases from 12 studies in the Breast Cancer Association Consortium. Sci Rep 8:6574
Rudolph, Anja; Song, Minsun; Brook, Mark N et al. (2018) Joint associations of a polygenic risk score and environmental risk factors for breast cancer in the Breast Cancer Association Consortium. Int J Epidemiol 47:526-536
Lilyquist, Jenna; Ruddy, Kathryn J; Vachon, Celine M et al. (2018) Common Genetic Variation and Breast Cancer Risk-Past, Present, and Future. Cancer Epidemiol Biomarkers Prev 27:380-394
Guidugli, Lucia; Shimelis, Hermela; Masica, David L et al. (2018) Assessment of the Clinical Relevance of BRCA2 Missense Variants by Functional and Computational Approaches. Am J Hum Genet 102:233-248
Hart, Steven N; Hoskin, Tanya; Shimelis, Hermela et al. (2018) Comprehensive annotation of BRCA1 and BRCA2 missense variants by functionally validated sequence-based computational prediction models. Genet Med :

Showing the most recent 10 out of 41 publications