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Grant Details

Grant Number: 5R01CA155767-04 Interpret this number
Primary Investigator: Goldgar, David
Organization: University Of Utah
Project Title: A Comprehensive Approach to Breast Cancer Susceptibility Across the Risk Spectrum
Fiscal Year: 2014
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Abstract

DESCRIPTION (provided by applicant): Based on data from 2002-2006, SEER estimated that in 2009, 192,370 American women were diagnosed with breast cancer and 40,170 died of the disease (Horner 2009). Although familial and/or early onset breast cancer does not represent the majority of the disease, these cases are often associated with poor prognosis. Further, because of their early age at diagnosis, these cases have a disproportionately large impact in terms of years of life lost to the disease. The high-risk breast cancer susceptibility genes BRCA1, BRCA2, PTEN, and TP53 were all discovered more than a decade ago. Currently, mutation screening of these genes plays an important role in the clinical management of women with a strong family history of the disease or syndromic evidence for the presence of a gene mutation. At the other end of the risk spectrum, genome-wide association studies have identified a number of common alleles with very modest effects on breast cancer; their clinical utility has yet to be established. However, taken together, the known spectrum of genetic effects only explain about a third of the overall familial excess of breast cancer. It should be emphasized that, at present, the vast majority of women seen at familial cancer clinics are counseled on the basis of their family history alone because they do not have mutations in the known susceptibility genes. Accordingly, the long-term objective of this project is to identify the majority of genes responsible for the unexplained component of inherited breast cancer risk. Over the last few years, new DNA sequencing technologies - often referred to as "next generation" or "massively parallel" sequencing - have been maturing rapidly. They are now ripe for application to research questions in genetic susceptibility, for which linkage analysis is confounded by extensive genetic heterogeneity and candidate gene studies technologically limited to small numbers of genes. Taking advantage of breast cancer genetics resources that have been gathered by international consortia over the last 15-plus years, two massively parallel sequencing strategies will be used to pursue the long term objective of this project: 1) resequencing all of the gene exons in the human genome from a series of breast cancer cases who have strong family history that is not explained by one of the currently known high-risk susceptibility genes; and 2) resequencing the gene exons of all of the genes in biochemical pathways that have been implicated in breast cancer susceptibility from a series of 2,400 early onset breast cancer cases and frequency-matched controls. The collaborative team assembled for this project has collected the largest breast cancer family resource extant, has unique expertise in breast cancer genetics, has the statistical and bioinformatic skills required to analyze massive resequencing data, and has the experience required to build wider consortia as necessary. Thus this team and project are poised to meet their long-term breast cancer susceptibility gene identification objective and thereby solve the "problem of missing heritability" in breast cancer genetics.

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Publications

Is RNASEL:p.Glu265* a modifier of early-onset breast cancer risk for carriers of high-risk mutations?
Authors: Nguyen-Dumont T. , Teo Z.L. , Hammet F. , Roberge A. , Mahmoodi M. , Tsimiklis H. , Park D.J. , Pope B.J. , Lonie A. , Kapuscinski M.K. , et al. .
Source: BMC cancer, 2018-02-08; 18(1), p. 165.
EPub date: 2018-02-08.
PMID: 29422015
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Panel sequencing of 264 candidate susceptibility genes and segregation analysis in a cohort of non-BRCA1, non-BRCA2 breast cancer families.
Authors: Li J. , Li H. , Makunin I. , kConFab Investigators , Thompson B.A. , Tao K. , Young E.L. , Lopez J. , Camp N.J. , Tavtigian S.V. , et al. .
Source: Breast cancer research and treatment, 2017 Dec; 166(3), p. 937-949.
EPub date: 2017-08-24.
PMID: 28840378
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PERCH: A Unified Framework for Disease Gene Prioritization.
Authors: Feng B.J. .
Source: Human mutation, 2017 03; 38(3), p. 243-251.
EPub date: 2017-01-28.
PMID: 27995669
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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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UNDR ROVER - a fast and accurate variant caller for targeted DNA sequencing.
Authors: Park D.J. , Li R. , Lau E. , Georgeson P. , Nguyen-Dumont T. , Pope B.J. .
Source: BMC bioinformatics, 2016-04-16; 17, p. 165.
EPub date: 2016-04-16.
PMID: 27083325
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Multigene testing of moderate-risk genes: be mindful of the missense.
Authors: Young E.L. , Feng B.J. , Stark A.W. , Damiola F. , Durand G. , Forey N. , Francy T.C. , Gammon A. , Kohlmann W.K. , Kaphingst K.A. , et al. .
Source: Journal of medical genetics, 2016 06; 53(6), p. 366-76.
EPub date: 2016-01-19.
PMID: 26787654
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Targeted massively parallel sequencing of a panel of putative breast cancer susceptibility genes in a large cohort of multiple-case breast and ovarian cancer families.
Authors: Li J. , Meeks H. , Feng B.J. , Healey S. , Thorne H. , Makunin I. , Ellis J. , kConFab Investigators , Campbell I. , Southey M. , et al. .
Source: Journal of medical genetics, 2016 Jan; 53(1), p. 34-42.
EPub date: 2015-11-03.
PMID: 26534844
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Hi-Plex targeted sequencing is effective using DNA derived from archival dried blood spots.
Authors: Nguyen-Dumont T. , Mahmoodi M. , Hammet F. , Tran T. , Tsimiklis H. , Kathleen Cuningham Foundation Consortium for Research into Familial Breast Cancer (kConFab) , Giles G.G. , Hopper J.L. , Australian Breast Cancer Family Registry , Southey M.C. , et al. .
Source: Analytical biochemistry, 2015-02-01; 470, p. 48-51.
EPub date: 2014-10-30.
PMID: 25447460
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Abridged adapter primers increase the target scope of Hi-Plex.
Authors: Nguyen-Dumont T. , Hammet F. , Mahmoodi M. , Pope B.J. , Giles G.G. , Hopper J.L. , Southey M.C. , Park D.J. .
Source: BioTechniques, 2015 Jan; 58(1), p. 33-6.
EPub date: 2015-01-01.
PMID: 25605578
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Rare mutations in RINT1 predispose carriers to breast and Lynch syndrome-spectrum cancers.
Authors: Park D.J. , Tao K. , Le Calvez-Kelm F. , Nguyen-Dumont T. , Robinot N. , Hammet F. , Odefrey F. , Tsimiklis H. , Teo Z.L. , Thingholm L.B. , et al. .
Source: Cancer discovery, 2014 Jul; 4(7), p. 804-15.
EPub date: 2014-05-02.
PMID: 25050558
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Cross-platform compatibility of Hi-Plex, a streamlined approach for targeted massively parallel sequencing.
Authors: Nguyen-Dumont T. , Pope B.J. , Hammet F. , Mahmoodi M. , Tsimiklis H. , Southey M.C. , Park D.J. .
Source: Analytical biochemistry, 2013-11-15; 442(2), p. 127-9.
EPub date: 2013-08-08.
PMID: 23933242
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Hi-Plex for high-throughput mutation screening: application to the breast cancer susceptibility gene PALB2.
Authors: Nguyen-Dumont T. , Teo Z.L. , Pope B.J. , Hammet F. , Mahmoodi M. , Tsimiklis H. , Sabbaghian N. , Tischkowitz M. , Foulkes W.D. , Kathleen Cuningham Foundation Consortium for research into Familial Breast cancer (kConFab) , et al. .
Source: BMC medical genomics, 2013-11-08; 6, p. 48.
EPub date: 2013-11-08.
PMID: 24206657
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COMPLEXO: identifying the missing heritability of breast cancer via next generation collaboration.
Authors: COMPLEXO , Southey M.C. , Park D.J. , Nguyen-Dumont T. , Campbell I. , Thompson E. , Trainer A.H. , Chenevix-Trench G. , Simard J. , Dumont M. , et al. .
Source: Breast cancer research : BCR, 2013-06-21; 15(3), p. 402.
EPub date: 2013-06-21.
PMID: 23809231
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Risk of pancreatic cancer in breast cancer families from the breast cancer family registry.
Authors: Mocci E. , Milne R.L. , Méndez-Villamil E.Y. , Hopper J.L. , John E.M. , Andrulis I.L. , Chung W.K. , Daly M. , Buys S.S. , Malats N. , et al. .
Source: Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2013 May; 22(5), p. 803-11.
EPub date: 2013-03-01.
PMID: 23456555
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FAVR (Filtering and Annotation of Variants that are Rare): methods to facilitate the analysis of rare germline genetic variants from massively parallel sequencing datasets.
Authors: Pope B.J. , Nguyen-Dumont T. , Odefrey F. , Hammet F. , Bell R. , Tao K. , Tavtigian S.V. , Goldgar D.E. , Lonie A. , Southey M.C. , et al. .
Source: BMC bioinformatics, 2013-02-25; 14, p. 65.
EPub date: 2013-02-25.
PMID: 23441864
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Rare mutations in XRCC2 increase the risk of breast cancer.
Authors: Park D.J. , Lesueur F. , Nguyen-Dumont T. , Pertesi M. , Odefrey F. , Hammet F. , Neuhausen S.L. , John E.M. , Andrulis I.L. , Terry M.B. , et al. .
Source: American journal of human genetics, 2012-04-06; 90(4), p. 734-9.
EPub date: 2012-03-29.
PMID: 22464251
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Design considerations for massively parallel sequencing studies of complex human disease.
Authors: Feng B.J. , Tavtigian S.V. , Southey M.C. , Goldgar D.E. .
Source: PloS one, 2011; 6(8), p. e23221.
EPub date: 2011-08-05.
PMID: 21850262
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