Australian Breast Cancer Family Study

Project Details

The ABCFS is a part of the international Breast Cancer Family Registry involving five other research groups across USA and Canada.

This collaboration provides a global research infrastructure to facilitate large-scale studies of breast cancer aetiology, risk and survival. Together these registries have recruited thousands of population-based and clinic-based breast cancer families as well as population-based control families.

The ABCFS currently comprises data and biospecimens for 8,700 participants from 2,200 Australian families. Our researchers have undertaken analyses of epidemiological, cancer history, and genetic and pathology data collected at baseline and during twenty years of follow-up. Recently the project has added digital mammograms to their resources and is recruiting women under the age of 45 diagnosed with breast cancer (but before they commence treatment) for a new study.

Much of our research shows we can better understand environmental and lifestyle factors by recognising the enormous genetic heterogeneity of breast cancer risk. More recently, we have initiated studies which draw on complex statistical analyses of genome-wide association studies, twin studies, and studies of mammographic density, a heritable risk factor for the disease.

Our completed analyses include:

• Validation of breast cancer risk-prediction models
• Survival in affected women
• Using genetic data to improve breast cancer risk prediction models
• Calculating cancer risks for relatives of affected women
• Identifying gene–environment interactions

Researchers

Professor Mary Beth Terry, Lead Principal Investigator, Colombia University

The Late Professor John Hopper, Former Co-Principal Investigator, University of Melbourne

Professor Melissa Southey. Co-Principal Investigator, Monash University

Dr Adrian Bickerstaffe

Associate Professor Shuai Li , Co-Investigator, University of Melbourne

Dr Robert MacInnis, Co-Investigator, Cancer Council Victoria

Ms Samantha Fox, Data Manager

Hannah Murchie, Data Manager

Ms Prue Weideman, Study Coordinator

Dr Zhoufeng Ye, researcher

Collaborators

• Centre for Epidemiology and Biostatistics, University of Melbourne, Monash University
• New York Breast Cancer Family Registry, Columbia University
• Northern California Breast Cancer Family Registry, Stanford university
• Ontario Breast Cancer Family Registry, Lunenfeld-Tanenbaum Research Institute
• Philadelphia Breast Cancer Family Registry, Fox Chase Cancer Centre
• Utah Cooperative Breast Cancer Registry, Huntsman Cancer Institute University of Utah

Funding

Funded by the National Institutes of Health (USA) since1995
Previously funded by NHMRC and Cancer Australia

Research Publications

https://www.bcfamilyregistry.org/publications

MacInnis RJ, Bickerstaffe A, Apicella C, Dite GS, Dowty JG, Aujard K, et al. Prospective validation of the breast cancer risk prediction model BOADICEA and a batch-mode version BOADICEACentre. British Journal of Cancer 2013; 109: 1296–1301.

Dite GS, Mahmoodi M, Bickerstaffe A, Hammett F, Macinnis RJ, Tsimiklis H, et al. Using SNP genotypes to improve the discrimination of a simple breast cancer risk prediction model. Breast Cancer Research and Treatment 2013; 139: 887–896.

Li S, Nguyen-Dumont T, Southey MC, Hopper JL. RE: Heterozygous BRCA1 and BRCA2 and mismatch repair gene pathogenic variants in children and adolescents with cancer. J Natl Cancer Inst. 2023;115(6):757-9. doi: 10.1093/jnci/djad056.

Li S, Silvestri V, Leslie G, et al. Cancer Risks Associated With BRCA1 and BRCA2 Pathogenic Variants. J Clin Oncol. 2022;40(14):1529-1541. doi:10.1200/JCO.21.02112

MacInnis RJ, Knight JA, Chung WK, et al. Comparing 5-Year and Lifetime Risks of Breast Cancer using the Prospective Family Study Cohort. J Natl Cancer Inst. 2021;113(6):785-791. doi:10.1093/jnci/djaa178

Nguyen TL, Schmidt DF, Makalic E, et al. Novel mammogram-based measures improve breast cancer risk prediction beyond an established mammographic density measure. Int J Cancer. 2021;148(9):2193-2202. doi:10.1002/ijc.33396

Renault, A. L., J. G. Dowty, J. A. Steen, S. Li, I. M. Winship, ..., G. G. Giles, T. Nguyen-Dumont (2022). "Population-based estimates of age-specific cumulative risk of breast cancer for pathogenic variants in ATM." Breast Cancer Res 24(1): 24.

Ye Z, Li S, Dite GS, et al. Weight is More Informative than Body Mass Index for Predicting Postmenopausal Breast Cancer Risk: Prospective Family Study Cohort (ProF-SC). Cancer Prev Res (Phila). 2022;15(3):185-191. doi:10.1158/1940-6207.CAPR-21-0164