Literature DB >> 34793697

Closing the gap: Systematic integration of multiplexed functional data resolves variants of uncertain significance in BRCA1, TP53, and PTEN.

Shawn Fayer1, Carrie Horton2, Jennifer N Dines1, Alan F Rubin3, Marcy E Richardson2, Kelly McGoldrick2, Felicia Hernandez2, Tina Pesaran2, Rachid Karam2, Brian H Shirts4, Douglas M Fowler5, Lea M Starita6.   

Abstract

Clinical interpretation of missense variants is challenging because the majority identified by genetic testing are rare and their functional effects are unknown. Consequently, most variants are of uncertain significance and cannot be used for clinical diagnosis or management. Although not much can be done to ameliorate variant rarity, multiplexed assays of variant effect (MAVEs), where thousands of single-nucleotide variant effects are simultaneously measured experimentally, provide functional evidence that can help resolve variants of unknown significance (VUSs). However, a rigorous assessment of the clinical value of multiplexed functional data for variant interpretation is lacking. Thus, we systematically combined previously published BRCA1, TP53, and PTEN multiplexed functional data with phenotype and family history data for 324 VUSs identified by a single diagnostic testing laboratory. We curated 49,281 variant functional scores from MAVEs for these three genes and integrated four different TP53 multiplexed functional datasets into a single functional prediction for each variant by using machine learning. We then determined the strength of evidence provided by each multiplexed functional dataset and reevaluated 324 VUSs. Multiplexed functional data were effective in driving variant reclassification when combined with clinical data, eliminating 49% of VUSs for BRCA1, 69% for TP53, and 15% for PTEN. Thus, multiplexed functional data, which are being generated for numerous genes, are poised to have a major impact on clinical variant interpretation.
Copyright © 2021 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  BRCA1; MAVE; PTEN; TP53; functional data; variant interpretation

Mesh:

Substances:

Year:  2021        PMID: 34793697      PMCID: PMC8715144          DOI: 10.1016/j.ajhg.2021.11.001

Source DB:  PubMed          Journal:  Am J Hum Genet        ISSN: 0002-9297            Impact factor:   11.043


  38 in total

1.  Quantifying the potential of functional evidence to reclassify variants of uncertain significance in the categorical and Bayesian interpretation frameworks.

Authors:  Sarah E Brnich; Edgar A Rivera-Muñoz; Jonathan S Berg
Journal:  Hum Mutat       Date:  2018-09-05       Impact factor: 4.878

2.  Variant Interpretation: Functional Assays to the Rescue.

Authors:  Lea M Starita; Nadav Ahituv; Maitreya J Dunham; Jacob O Kitzman; Frederick P Roth; Georg Seelig; Jay Shendure; Douglas M Fowler
Journal:  Am J Hum Genet       Date:  2017-09-07       Impact factor: 11.025

3.  Evaluation of ACMG-Guideline-Based Variant Classification of Cancer Susceptibility and Non-Cancer-Associated Genes in Families Affected by Breast Cancer.

Authors:  Kara N Maxwell; Steven N Hart; Joseph Vijai; Kasmintan A Schrader; Thomas P Slavin; Tinu Thomas; Bradley Wubbenhorst; Vignesh Ravichandran; Raymond M Moore; Chunling Hu; Lucia Guidugli; Brandon Wenz; Susan M Domchek; Mark E Robson; Csilla Szabo; Susan L Neuhausen; Jeffrey N Weitzel; Kenneth Offit; Fergus J Couch; Katherine L Nathanson
Journal:  Am J Hum Genet       Date:  2016-05-05       Impact factor: 11.025

4.  A dominant-negative effect drives selection of TP53 missense mutations in myeloid malignancies.

Authors:  Steffen Boettcher; Peter G Miller; Rohan Sharma; Marie McConkey; Matthew Leventhal; Andrei V Krivtsov; Andrew O Giacomelli; Waihay Wong; Jesi Kim; Sherry Chao; Kari J Kurppa; Xiaoping Yang; Kirsten Milenkowic; Federica Piccioni; David E Root; Frank G Rücker; Yael Flamand; Donna Neuberg; R Coleman Lindsley; Pasi A Jänne; William C Hahn; Tyler Jacks; Hartmut Döhner; Scott A Armstrong; Benjamin L Ebert
Journal:  Science       Date:  2019-08-09       Impact factor: 47.728

5.  PERCH: A Unified Framework for Disease Gene Prioritization.

Authors:  Bing-Jian Feng
Journal:  Hum Mutat       Date:  2017-01-28       Impact factor: 4.878

6.  ACMG SF v3.0 list for reporting of secondary findings in clinical exome and genome sequencing: a policy statement of the American College of Medical Genetics and Genomics (ACMG).

Authors:  David T Miller; Kristy Lee; Wendy K Chung; Adam S Gordon; Gail E Herman; Teri E Klein; Douglas R Stewart; Laura M Amendola; Kathy Adelman; Sherri J Bale; Michael H Gollob; Steven M Harrison; Ray E Hershberger; Kent McKelvey; C Sue Richards; Christopher N Vlangos; Michael S Watson; Christa Lese Martin
Journal:  Genet Med       Date:  2021-05-20       Impact factor: 8.822

7.  Specifications of the ACMG/AMP variant interpretation guidelines for germline TP53 variants.

Authors:  Cristina Fortuno; Kristy Lee; Magali Olivier; Tina Pesaran; Phuong L Mai; Kelvin C de Andrade; Laura D Attardi; Stephanie Crowley; D Gareth Evans; Bing-Jian Feng; Ann K M Foreman; Megan N Frone; Robert Huether; Paul A James; Kelly McGoldrick; Jessica Mester; Bryce A Seifert; Thomas P Slavin; Leora Witkowski; Liying Zhang; Sharon E Plon; Amanda B Spurdle; Sharon A Savage
Journal:  Hum Mutat       Date:  2020-12-25       Impact factor: 4.700

Review 8.  Beyond DNA: An Integrated and Functional Approach for Classifying Germline Variants in Breast Cancer Genes.

Authors:  T Pesaran; R Karam; R Huether; S Li; S Farber-Katz; A Chamberlin; H Chong; H LaDuca; A Elliott
Journal:  Int J Breast Cancer       Date:  2016-10-16

9.  Multiplex assessment of protein variant abundance by massively parallel sequencing.

Authors:  Kenneth A Matreyek; Lea M Starita; Jason J Stephany; Beth Martin; Melissa A Chiasson; Vanessa E Gray; Martin Kircher; Arineh Khechaduri; Jennifer N Dines; Ronald J Hause; Smita Bhatia; William E Evans; Mary V Relling; Wenjian Yang; Jay Shendure; Douglas M Fowler
Journal:  Nat Genet       Date:  2018-05-21       Impact factor: 38.330

10.  Recommendations for application of the functional evidence PS3/BS3 criterion using the ACMG/AMP sequence variant interpretation framework.

Authors:  Sarah E Brnich; Ahmad N Abou Tayoun; Fergus J Couch; Garry R Cutting; Marc S Greenblatt; Christopher D Heinen; Dona M Kanavy; Xi Luo; Shannon M McNulty; Lea M Starita; Sean V Tavtigian; Matt W Wright; Steven M Harrison; Leslie G Biesecker; Jonathan S Berg
Journal:  Genome Med       Date:  2019-12-31       Impact factor: 11.117

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  3 in total

1.  A calibrated functional patch-clamp assay to enhance clinical variant interpretation in KCNH2-related long QT syndrome.

Authors:  Connie Jiang; Ebony Richardson; Jessica Farr; Adam P Hill; Rizwan Ullah; Brett M Kroncke; Steven M Harrison; Kate L Thomson; Jodie Ingles; Jamie I Vandenberg; Chai-Ann Ng
Journal:  Am J Hum Genet       Date:  2022-06-09       Impact factor: 11.043

2.  Comprehensive evaluation and efficient classification of BRCA1 RING domain missense substitutions.

Authors:  Kathleen A Clark; Andrew Paquette; Kayoko Tao; Russell Bell; Julie L Boyle; Judith Rosenthal; Angela K Snow; Alex W Stark; Bryony A Thompson; Joshua Unger; Jason Gertz; Katherine E Varley; Kenneth M Boucher; David E Goldgar; William D Foulkes; Alun Thomas; Sean V Tavtigian
Journal:  Am J Hum Genet       Date:  2022-06-02       Impact factor: 11.043

3.  The functional impact of BRCA1 BRCT domain variants using multiplexed DNA double-strand break repair assays.

Authors:  Aleksandra I Adamovich; Mariame Diabate; Tapahsama Banerjee; Gregory Nagy; Nahum Smith; Kathryn Duncan; Erika Mendoza Mendoza; Gisselle Prida; Michael A Freitas; Lea M Starita; Jeffrey D Parvin
Journal:  Am J Hum Genet       Date:  2022-02-22       Impact factor: 11.043

  3 in total

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