Literature DB >> 25085752

Development and validation of a new algorithm for the reclassification of genetic variants identified in the BRCA1 and BRCA2 genes.

Dmitry Pruss1, Brian Morris, Elisha Hughes, Julie M Eggington, Lisa Esterling, Brandon S Robinson, Aric van Kan, Priscilla H Fernandes, Benjamin B Roa, Alexander Gutin, Richard J Wenstrup, Karla R Bowles.   

Abstract

BRCA1 and BRCA2 sequencing analysis detects variants of uncertain clinical significance in approximately 2 % of patients undergoing clinical diagnostic testing in our laboratory. The reclassification of these variants into either a pathogenic or benign clinical interpretation is critical for improved patient management. We developed a statistical variant reclassification tool based on the premise that probands with disease-causing mutations are expected to have more severe personal and family histories than those having benign variants. The algorithm was validated using simulated variants based on approximately 145,000 probands, as well as 286 BRCA1 and 303 BRCA2 true variants. Positive and negative predictive values of ≥99 % were obtained for each gene. Although the history weighting algorithm was not designed to detect alleles of lower penetrance, analysis of the hypomorphic mutations c.5096G>A (p.Arg1699Gln; BRCA1) and c.7878G>C (p.Trp2626Cys; BRCA2) indicated that the history weighting algorithm is able to identify some lower penetrance alleles. The history weighting algorithm is a powerful tool that accurately assigns actionable clinical classifications to variants of uncertain clinical significance. While being developed for reclassification of BRCA1 and BRCA2 variants, the history weighting algorithm is expected to be applicable to other cancer- and non-cancer-related genes.

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Year:  2014        PMID: 25085752     DOI: 10.1007/s10549-014-3065-9

Source DB:  PubMed          Journal:  Breast Cancer Res Treat        ISSN: 0167-6806            Impact factor:   4.872


  20 in total

1.  Clinical Variant Classification: A Comparison of Public Databases and a Commercial Testing Laboratory.

Authors:  William Gradishar; KariAnne Johnson; Krystal Brown; Erin Mundt; Susan Manley
Journal:  Oncologist       Date:  2017-04-13

2.  Exploring the effect of ascertainment bias on genetic studies that use clinical pedigrees.

Authors:  John Michael O Ranola; Ginger J Tsai; Brian H Shirts
Journal:  Eur J Hum Genet       Date:  2019-07-11       Impact factor: 4.246

3.  Physician interpretation of variants of uncertain significance.

Authors:  Sarah K Macklin; Jessica L Jackson; Paldeep S Atwal; Stephanie L Hines
Journal:  Fam Cancer       Date:  2019-01       Impact factor: 2.375

Review 4.  New targeted therapies for breast cancer: A focus on tumor microenvironmental signals and chemoresistant breast cancers.

Authors:  Armel Hervé Nwabo Kamdje; Paul Faustin Seke Etet; Lorella Vecchio; Richard Simo Tagne; Jeremie Mbo Amvene; Jean-Marc Muller; Mauro Krampera; Kiven Erique Lukong
Journal:  World J Clin Cases       Date:  2014-12-16       Impact factor: 1.337

5.  Frequency of Germline Mutations in 25 Cancer Susceptibility Genes in a Sequential Series of Patients With Breast Cancer.

Authors:  Nadine Tung; Nancy U Lin; John Kidd; Brian A Allen; Nanda Singh; Richard J Wenstrup; Anne-Renee Hartman; Eric P Winer; Judy E Garber
Journal:  J Clin Oncol       Date:  2016-03-14       Impact factor: 44.544

6.  Comparison of locus-specific databases for BRCA1 and BRCA2 variants reveals disparity in variant classification within and among databases.

Authors:  Paris J Vail; Brian Morris; Aric van Kan; Brianna C Burdett; Kelsey Moyes; Aaron Theisen; Iain D Kerr; Richard J Wenstrup; Julie M Eggington
Journal:  J Community Genet       Date:  2015-03-18

7.  Distributing the future: The weak justifications for keeping human genomic databases secret and the challenges and opportunities in reverse engineering them.

Authors:  Misha Angrist; Robert Cook-Deegan
Journal:  Appl Transl Genom       Date:  2014-12-01

8.  Assessing biases of information contained in pedigrees for the classification of BRCA-genetic variants: a study arising from the ENIGMA analytical working group.

Authors:  C H H Kerkhofs; A B Spurdle; P J Lindsey; D E Goldgar; E B Gómez-García
Journal:  Hered Cancer Clin Pract       Date:  2016-04-30       Impact factor: 2.857

9.  Classification of genetic variants in genes associated with Lynch syndrome using a clinical history weighting algorithm.

Authors:  Brian Morris; Elisha Hughes; Eric Rosenthal; Alexander Gutin; Karla R Bowles
Journal:  BMC Genet       Date:  2016-07-01       Impact factor: 2.797

10.  Multicenter Prospective Cohort Study of the Diagnostic Yield and Patient Experience of Multiplex Gene Panel Testing For Hereditary Cancer Risk.

Authors:  Gregory E Idos; Allison W Kurian; Charité Ricker; Duveen Sturgeon; Julie O Culver; Kerry E Kingham; Rachel Koff; Nicolette M Chun; Courtney Rowe-Teeter; Alexandra P Lebensohn; Peter Levonian; Katrina Lowstuter; Katlyn Partynski; Christine Hong; Meredith A Mills; Iva Petrovchich; Cindy S Ma; Anne-Renee Hartman; Brian Allen; Richard J Wenstrup; Johnathan M Lancaster; Krystal Brown; John Kidd; Brent Evans; Bhramar Mukherjee; Kevin J McDonnell; Uri Ladabaum; James M Ford; Stephen B Gruber
Journal:  JCO Precis Oncol       Date:  2019-03-28
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