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Grant Details

Grant Number: 5R01CA159868-05 Interpret this number
Primary Investigator: Terry, Mary Beth
Organization: Columbia University Health Sciences
Project Title: Genes, Environment and Breast Cancer Risk: the 15 Year Follow-Up of the Prof-SC
Fiscal Year: 2015
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Abstract

DESCRIPTION (provided by applicant): The discovery of BRCA1 and BRCA2 has resulted in more appropriate targeting of preventive and screening strategies for breast cancer. The on-going discovery of genes with moderate-risk mutations, and of multiple loci with common low-risk associated variants, means that more women at substantial genetic risk will be identified. Despite these advances in genomic medicine, there remain major unanswered questions for high risk women, the majority of whom do not carry mutations in any currently identified susceptibility genes: 1) What is my absolute risk of breast cancer?; 2) Are there modifiable factors that might lower my risk?; and, for women with prior breast cancer, 3) Can I do anything to lower my risk of a new cancer? Answers to these questions are fundamental to improving clinical care, and are long overdue. We lack answers to these important questions because many studies fail to capture the complexity of family history and lack long-term follow-up data to measure risk. Breast cancer risk prediction models commonly used at non-specialist clinics often capture risk based on only first-degree family history. No breast cancer prediction models have been based on, nor validated with, large prospective cohorts of high risk women. Studies that have examined potential modifiers of risk for BRCA1 and BRCA2 mutation carriers have used a retrospective design and included prevalent cancers over-sampled for disease survivors. To address these gaps, we propose to conduct active follow-up of 30,563 women of whom 2,597 are BRCA1 and BRCA2 mutation carriers. These women come from 9,739 families recruited and followed since 1995 in the U.S., Canada, and Australia. We collected the same extensive baseline epidemiologic, multigenerational pedigree, and genetic data for these women. Our prospective family study is enriched with women at increased susceptibility for breast cancer who vary widely in underlying Familial Risk Profile (FRP), which can be estimated using multigenerational pedigree and genetic data. We will estimate age-specific absolute, and relative, risks of breast cancer using two separate cohorts (18,530 women unaffected and 12,033 women affected at baseline), as a function of their estimated FRP, modifiable risk factors, and by BRCA1 and BRCA2 mutation status. By the end of follow-up, we estimate 1,427 of the women unaffected and 1,359 women affected at baseline will be diagnosed with a new breast cancer. 15-17% of these new cases will be in BRCA1 or BRCA2 mutation carriers. We will use our findings to enhance prediction models by incorporating information from multigenerational family history, measured gene variants, and risk factors. Clinical practice has been conservative in advising high risk women, particularly mutation carriers, about potential lifestyle modifications to reduce risk, basing this advice on studies of average-risk women. Instead, we propose to build more accurate prediction models for women across the spectrum of risk that can be used to tailor more effective prevention strategies.

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Publications

Benign breast disease increases breast cancer risk independent of underlying familial risk profile: Findings from a Prospective Family Study Cohort.
Authors: Zeinomar N. , Phillips K.A. , Daly M.B. , Milne R.L. , Dite G.S. , MacInnis R.J. , Liao Y. , Kehm R.D. , Knight J.A. , Southey M.C. , et al. .
Source: International journal of cancer, 2019-07-15; 145(2), p. 370-379.
EPub date: 2019-02-20.
PMID: 30725480
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Regular use of aspirin and other non-steroidal anti-inflammatory drugs and breast cancer risk for women at familial or genetic risk: a cohort study.
Authors: Kehm R.D. , Hopper J.L. , John E.M. , Phillips K.A. , MacInnis R.J. , Dite G.S. , Milne R.L. , Liao Y. , Zeinomar N. , Knight J.A. , et al. .
Source: Breast cancer research : BCR, 2019-04-18; 21(1), p. 52.
EPub date: 2019-04-18.
PMID: 30999962
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Age-specific breast cancer risk by body mass index and familial risk: prospective family study cohort (ProF-SC).
Authors: Hopper J.L. , Dite G.S. , MacInnis R.J. , Liao Y. , Zeinomar N. , Knight J.A. , Southey M.C. , Milne R.L. , Chung W.K. , Giles G.G. , et al. .
Source: Breast cancer research : BCR, 2018-11-03; 20(1), p. 132.
EPub date: 2018-11-03.
PMID: 30390716
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Association analysis identifies 65 new breast cancer risk loci.
Authors: Michailidou K. , Lindström S. , Dennis J. , Beesley J. , Hui S. , Kar S. , Lemaçon A. , Soucy P. , Glubb D. , Rostamianfar A. , et al. .
Source: Nature, 2017-11-02; 551(7678), p. 92-94.
EPub date: 2017-10-23.
PMID: 29059683
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Risk of uterine cancer for BRCA1 and BRCA2 mutation carriers.
Authors: Lee Y.C. , Milne R.L. , Lheureux S. , Friedlander M. , McLachlan S.A. , Martin K.L. , Bernardini M.Q. , Smith C. , Picken S. , Nesci S. , et al. .
Source: European journal of cancer (Oxford, England : 1990), 2017 10; 84, p. 114-120.
EPub date: 2017-08-10.
PMID: 28802188
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Risks of Breast, Ovarian, and Contralateral Breast Cancer for BRCA1 and BRCA2 Mutation Carriers.
Authors: Kuchenbaecker K.B. , Hopper J.L. , Barnes D.R. , Phillips K.A. , Mooij T.M. , Roos-Blom M.J. , Jervis S. , van Leeuwen F.E. , Milne R.L. , Andrieu N. , et al. .
Source: JAMA, 2017-06-20; 317(23), p. 2402-2416.
PMID: 28632866
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Dependence of cancer risk from environmental exposures on underlying genetic susceptibility: an illustration with polycyclic aromatic hydrocarbons and breast cancer.
Authors: Shen J. , Liao Y. , Hopper J.L. , Goldberg M. , Santella R.M. , Terry M.B. .
Source: British journal of cancer, 2017-04-25; 116(9), p. 1229-1233.
EPub date: 2017-03-28.
PMID: 28350789
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DNA Repair Gene Expression Levels as Indicators of Breast Cancer in the Breast Cancer Family Registry.
Authors: Kappil M.A. , Liao Y. , Terry M.B. , Santella R.M. .
Source: Anticancer research, 2016 Aug; 36(8), p. 4039-44.
PMID: 27466510
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Breast cancer risk prediction using a polygenic risk score in the familial setting: a prospective study from the Breast Cancer Family Registry and kConFab.
Authors: Li H. , Feng B. , Miron A. , Chen X. , Beesley J. , Bimeh E. , Barrowdale D. , John E.M. , Daly M.B. , Andrulis I.L. , et al. .
Source: Genetics in medicine : official journal of the American College of Medical Genetics, 2017 01; 19(1), p. 30-35.
EPub date: 2016-05-12.
PMID: 27171545
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Breast Cancer Risk Prediction Using Clinical Models and 77 Independent Risk-Associated SNPs for Women Aged Under 50 Years: Australian Breast Cancer Family Registry.
Authors: Dite G.S. , MacInnis R.J. , Bickerstaffe A. , Dowty J.G. , Allman R. , Apicella C. , Milne R.L. , Tsimiklis H. , Phillips K.A. , Giles G.G. , et al. .
Source: Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2016 Feb; 25(2), p. 359-65.
EPub date: 2015-12-16.
PMID: 26677205
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Odds per adjusted standard deviation: comparing strengths of associations for risk factors measured on different scales and across diseases and populations.
Authors: Hopper J.L. .
Source: American journal of epidemiology, 2015-11-15; 182(10), p. 863-7.
EPub date: 2015-10-31.
PMID: 26520360
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Cohort Profile: The Breast Cancer Prospective Family Study Cohort (ProF-SC).
Authors: Terry M.B. , Phillips K.A. , Daly M.B. , John E.M. , Andrulis I.L. , Buys S.S. , Goldgar D.E. , Knight J.A. , Whittemore A.S. , Chung W.K. , et al. .
Source: International journal of epidemiology, 2016 06; 45(3), p. 683-92.
EPub date: 2015-07-13.
PMID: 26174520
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microRNA Expression in Prospectively Collected Blood as a Potential Biomarker of Breast Cancer Risk in the BCFR.
Authors: Chang C.W. , Wu H.C. , Terry M.B. , Santella R.M. .
Source: Anticancer research, 2015 Jul; 35(7), p. 3969-77.
PMID: 26124344
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Practical problems with clinical guidelines for breast cancer prevention based on remaining lifetime risk.
Authors: Quante A.S. , Whittemore A.S. , Shriver T. , Hopper J.L. , Strauch K. , Terry M.B. .
Source: Journal of the National Cancer Institute, 2015 Jul; 107(7), .
EPub date: 2015-05-08.
PMID: 25956172
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Differences in DNA methylation by extent of breast cancer family history in unaffected women.
Authors: Delgado-Cruzata L. , Wu H.C. , Liao Y. , Santella R.M. , Terry M.B. .
Source: Epigenetics, 2014 Feb; 9(2), p. 243-8.
EPub date: 2013-10-29.
PMID: 24172832
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Prospective validation of the breast cancer risk prediction model BOADICEA and a batch-mode version BOADICEACentre.
Authors: MacInnis R.J. , Bickerstaffe A. , Apicella C. , Dite G.S. , Dowty J.G. , Aujard K. , Phillips K.A. , Weideman P. , Lee A. , Terry M.B. , et al. .
Source: British journal of cancer, 2013-09-03; 109(5), p. 1296-301.
EPub date: 2013-08-13.
PMID: 23942072
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Breast cancer risk assessment across the risk continuum: genetic and nongenetic risk factors contributing to differential model performance.
Authors: Quante A.S. , Whittemore A.S. , Shriver T. , Strauch K. , Terry M.B. .
Source: Breast cancer research : BCR, 2012-11-05; 14(6), p. R144.
EPub date: 2012-11-05.
PMID: 23127309
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