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Grant Details

Grant Number: 5R01CA121245-10 Interpret this number
Primary Investigator: Tavtigian, Sean
Organization: University Of Utah
Project Title: Common and Rare Sequence Variants in Breast Cancer Risk
Fiscal Year: 2021


Abstract The research proposed here is in the area of cancer predisposition genetics, and its focus is on the moderate- risk cancer susceptibility genes (ATM, CHEK2, etc.) in the biochemical pathway responsible for DNA double strand break homologous recombination repair (HRR). Most of the genes in the HRR pathway are breast cancer susceptibility genes, with several also being ovarian cancer susceptibility genes and/or pancreatic cancer susceptibility genes. ¶ In the first funding cycle, we discovered that the majority of pathogenic alleles in the moderate-risk HRR genes are individually rare missense substitutions (rather than the individually rare protein truncating variants that dominate the mutation spectrum of BRCA1 and BRCA2). From a clinical cancer genetics and patient counseling point of view, this observation creates a serious problem: the clinical testing labs typically report these rare missense substitutions as Variants of Unclear Significance (VUS). Because the VUS are not used for patient counseling, this means that the majority of the bona fide genetic risk detectable in the moderate-risk HRR genes by the panel tests is not used for patient counseling and risk management! ¶ Over the last 12 years, we played a central role in development of methods for clinical classification of VUS in BRCA1 and BRCA2, and are currently developing corresponding methods for the colorectal (and other cancer) susceptibility genes MLH1, MSH2, PMS2, and MSH6. Here, we hypothesize that combining improved computational methods for rare missense substitution evaluation with comprehensive high-throughput functional assays will dramatically accelerate the process of evaluation and classification of clinically observed VUS. Thus the first Aim of the project focuses on confirming and then improving the accuracy of computational methods for evaluation of rare missense substitution. The second Aim is directed towards development of medium-to-high throughput assays of missense substitution functionality. In terms of genes, we will begin these studies with the RING domain of BRCA1 (which lacks a properly calibrated functional assay), and then progress to ATM and then CHEK2. In the third Aim, we re-calibrate the outputs from the computational methods of Aim 1 and the functional assays of Aim 2 into probabilities (or odds) in favor of pathogenicity, the key variables required for clinical-quality classification of sequence variants observed in people. We then combine these data to obtain posterior probabilities in favor of pathogenicity and pass those posterior probabilities through a well-recognized categorical classifier (the IARC standards) to generate classification recommendations for clinicians and patients. Progress across the three Aims of this study will dramatically accelerate variant classification while simultaneously improving the sensitivity and precision of the clinical testing process.


Structural insights into DNA double-strand break signaling.
Authors: Panigrahi R. , Glover J.N.M. .
Source: The Biochemical journal, 2021-01-15; 478(1), p. 135-156.
PMID: 33439989
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Fitting a naturally scaled point system to the ACMG/AMP variant classification guidelines.
Authors: Tavtigian S.V. , Harrison S.M. , Boucher K.M. , Biesecker L.G. .
Source: Human mutation, 2020 Oct; 41(10), p. 1734-1737.
EPub date: 2020-08-30.
PMID: 32720330
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Two integrated and highly predictive functional analysis-based procedures for the classification of MSH6 variants in Lynch syndrome.
Authors: Drost M. , Tiersma Y. , Glubb D. , Kathe S. , van Hees S. , Calléja F. , Zonneveld J.B.M. , Boucher K.M. , Ramlal R.P.E. , Thompson B.A. , et al. .
Source: Genetics in medicine : official journal of the American College of Medical Genetics, 2020 May; 22(5), p. 847-856.
EPub date: 2020-01-22.
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Recommendations for application of the functional evidence PS3/BS3 criterion using the ACMG/AMP sequence variant interpretation framework.
Authors: Brnich S.E. , Abou Tayoun A.N. , Couch F.J. , Cutting G.R. , Greenblatt M.S. , Heinen C.D. , Kanavy D.M. , Luo X. , McNulty S.M. , Starita L.M. , et al. .
Source: Genome medicine, 2019-12-31; 12(1), p. 3.
EPub date: 2019-12-31.
PMID: 31892348
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Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification.
Authors: Parsons M.T. , Tudini E. , Li H. , Hahnen E. , Wappenschmidt B. , Feliubadaló L. , Aalfs C.M. , Agata S. , Aittomäki K. , Alducci E. , et al. .
Source: Human mutation, 2019 Sep; 40(9), p. 1557-1578.
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A functional assay-based procedure to classify mismatch repair gene variants in Lynch syndrome.
Authors: Drost M. , Tiersma Y. , Thompson B.A. , Frederiksen J.H. , Keijzers G. , Glubb D. , Kathe S. , Osinga J. , Westers H. , Pappas L. , et al. .
Source: Genetics in medicine : official journal of the American College of Medical Genetics, 2019 Jul; 21(7), p. 1486-1496.
EPub date: 2018-12-03.
PMID: 30504929
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Modeling the ACMG/AMP variant classification guidelines as a Bayesian classification framework.
Authors: Tavtigian S.V. , Greenblatt M.S. , Harrison S.M. , Nussbaum R.L. , Prabhu S.A. , Boucher K.M. , Biesecker L.G. , ClinGen Sequence Variant Interpretation Working Group (ClinGen SVI) .
Source: Genetics in medicine : official journal of the American College of Medical Genetics, 2018 Sep; 20(9), p. 1054-1060.
EPub date: 2018-01-04.
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Improved, ACMG-compliant, in silico prediction of pathogenicity for missense substitutions encoded by TP53 variants.
Authors: Fortuno C. , James P.A. , Young E.L. , Feng B. , Olivier M. , Pesaran T. , Tavtigian S.V. , Spurdle A.B. .
Source: Human mutation, 2018 Aug; 39(8), p. 1061-1069.
EPub date: 2018-06-05.
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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 Jun; 53(6), p. 366-76.
EPub date: 2016-01-19.
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No evidence that protein truncating variants in BRIP1 are associated with breast cancer risk: implications for gene panel testing.
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Source: Journal of medical genetics, 2016 May; 53(5), p. 298-309.
EPub date: 2016-02-26.
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ABRAXAS (FAM175A) and Breast Cancer Susceptibility: No Evidence of Association in the Breast Cancer Family Registry.
Authors: Renault A.L. , Lesueur F. , Coulombe Y. , Gobeil S. , Soucy P. , Hamdi Y. , Desjardins S. , Le Calvez-Kelm F. , Vallée M. , Voegele C. , et al. .
Source: PloS one, 2016; 11(6), p. e0156820.
EPub date: 2016-06-07.
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Rare mutations in RINT1 predispose carriers to breast and Lynch syndrome-spectrum cancers.
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Rare key functional domain missense substitutions in MRE11A, RAD50, and NBN contribute to breast cancer susceptibility: results from a Breast Cancer Family Registry case-control mutation-screening study.
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Source: Breast cancer research : BCR, 2014-06-03; 16(3), p. R58.
EPub date: 2014-06-03.
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Growing recognition of the role for rare missense substitutions in breast cancer susceptibility.
Authors: Tavtigian S.V. , Chenevix-Trench G. .
Source: Biomarkers in medicine, 2014; 8(4), p. 589-603.
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Rare mutations in XRCC2 increase the risk of breast cancer.
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Source: American journal of human genetics, 2012-04-06; 90(4), p. 734-9.
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RAD51 and breast cancer susceptibility: no evidence for rare variant association in the Breast Cancer Family Registry study.
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Source: PloS one, 2012; 7(12), p. e52374.
EPub date: 2012-12-27.
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Rare variants in the ATM gene and risk of breast cancer.
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Detecting differential allelic expression using high-resolution melting curve analysis: application to the breast cancer susceptibility gene CHEK2.
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Tests of association for rare variants: case control mutation screening.
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Association of ESR1 gene tagging SNPs with breast cancer risk.
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Classification of rare missense substitutions, using risk surfaces, with genetic- and molecular-epidemiology applications.
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