Literature DB >> 29260485

Managing Variant Interpretation Discrepancies in Hereditary Cancer: Clinical Practice, Concerns, and Desired Resources.

Ellen Zirkelbach1,2, Syed Hashmi3, Aarti Ramdaney4, Leslie Dunnington5, Myla Ashfaq5, Elizabeth K Nugent6, Kate Wilson7.   

Abstract

Variant interpretation is a complex process, and classification may vary between sources. This study aimed to determine the practice of cancer genetic counselors regarding discrepancies in variant interpretation and to identify concerns when counseling these discrepancies. An electronic survey was sent to genetic counselors in the NSGC Cancer Special Interest Group. The vast majority of counselors (93%) had seen a variant interpretation discrepancy in practice. A large majority (96%) of respondents indicated that they conducted their own research on reported variants. Most respondents cited variant databases as the most common resource utilized in researching variants. Approximately 33% of counselors spent 45 min or more of extra time researching a discrepancy compared to researching a variant with a single classification. When asked how they approached counseling sessions involving variant interpretation discrepancies, the free responses emphasized that counselors considered family history, clinical information, and psychosocial concerns, showing that genetic counselors tailored the session to each individual. Discrepancies in variant interpretation are an ongoing concern for clinical cancer genetic counselors, as demonstrated by the fact that counselors desired further resources to aid in addressing these discrepancies, including a centralized database (89%), guidelines from a major organization (88%), continuing education about the issue (74%), and functional studies (58%). Additionally, most respondents reported that the ideal database would be owned by a non-profit organization (59%) and obtain information directly from laboratories (91%). This investigation was the first to address these discrepancies from a clinical point of view. The study demonstrates that discrepancies in variant interpretation are a concern for clinical cancer genetic counselors and outlines the need for additional support.

Entities:  

Keywords:  Cancer; Clinic; Concerns; Database; Discrepancy; Functional studies; Interpretation; Resources; Variant

Mesh:

Year:  2017        PMID: 29260485     DOI: 10.1007/s10897-017-0184-6

Source DB:  PubMed          Journal:  J Genet Couns        ISSN: 1059-7700            Impact factor:   2.537


  12 in total

1.  Getting Data Sharing Right to Help Fulfill the Promise of Cancer Genomics.

Authors:  Neil Savage
Journal:  Cell       Date:  2017-02-09       Impact factor: 41.582

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 Systematic Comparison of Traditional and Multigene Panel Testing for Hereditary Breast and Ovarian Cancer Genes in More Than 1000 Patients.

Authors:  Stephen E Lincoln; Yuya Kobayashi; Michael J Anderson; Shan Yang; Andrea J Desmond; Meredith A Mills; Geoffrey B Nilsen; Kevin B Jacobs; Federico A Monzon; Allison W Kurian; James M Ford; Leif W Ellisen
Journal:  J Mol Diagn       Date:  2015-07-22       Impact factor: 5.568

Review 5.  Searching for cancer-associated gene polymorphisms: promises and obstacles.

Authors:  Evgeny N Imyanitov; Alexandr V Togo; Kaido P Hanson
Journal:  Cancer Lett       Date:  2004-02-10       Impact factor: 8.679

6.  Laboratory and clinical genomic data sharing is crucial to improving genetic health care: a position statement of the American College of Medical Genetics and Genomics.

Authors: 
Journal:  Genet Med       Date:  2017-01-05       Impact factor: 8.822

7.  Actionable exomic incidental findings in 6503 participants: challenges of variant classification.

Authors:  Laura M Amendola; Michael O Dorschner; Peggy D Robertson; Joseph S Salama; Ragan Hart; Brian H Shirts; Mitzi L Murray; Mari J Tokita; Carlos J Gallego; Daniel Seung Kim; James T Bennett; David R Crosslin; Jane Ranchalis; Kelly L Jones; Elisabeth A Rosenthal; Ella R Jarvik; Andy Itsara; Emily H Turner; Daniel S Herman; Jennifer Schleit; Amber Burt; Seema M Jamal; Jenica L Abrudan; Andrew D Johnson; Laura K Conlin; Matthew C Dulik; Avni Santani; Danielle R Metterville; Melissa Kelly; Ann Katherine M Foreman; Kristy Lee; Kent D Taylor; Xiuqing Guo; Kristy Crooks; Lesli A Kiedrowski; Leslie J Raffel; Ora Gordon; Kalotina Machini; Robert J Desnick; Leslie G Biesecker; Steven A Lubitz; Surabhi Mulchandani; Greg M Cooper; Steven Joffe; C Sue Richards; Yaoping Yang; Jerome I Rotter; Stephen S Rich; Christopher J O'Donnell; Jonathan S Berg; Nancy B Spinner; James P Evans; Stephanie M Fullerton; Kathleen A Leppig; Robin L Bennett; Thomas Bird; Virginia P Sybert; William M Grady; Holly K Tabor; Jerry H Kim; Michael J Bamshad; Benjamin Wilfond; Arno G Motulsky; C Ronald Scott; Colin C Pritchard; Tom D Walsh; Wylie Burke; Wendy H Raskind; Peter Byers; Fuki M Hisama; Heidi Rehm; Debbie A Nickerson; Gail P Jarvik
Journal:  Genome Res       Date:  2015-01-30       Impact factor: 9.043

8.  Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology.

Authors:  Sue Richards; Nazneen Aziz; Sherri Bale; David Bick; Soma Das; Julie Gastier-Foster; Wayne W Grody; Madhuri Hegde; Elaine Lyon; Elaine Spector; Karl Voelkerding; Heidi L Rehm
Journal:  Genet Med       Date:  2015-03-05       Impact factor: 8.822

9.  Knocking down the obstacles to functional genomics data sharing.

Authors:  Kaylene J Simpson; Jennifer A Smith
Journal:  Sci Data       Date:  2017-03-01       Impact factor: 6.444

10.  Clinical laboratories collaborate to resolve differences in variant interpretations submitted to ClinVar.

Authors:  Steven M Harrison; Jill S Dolinsky; Amy E Knight Johnson; Tina Pesaran; Danielle R Azzariti; Sherri Bale; Elizabeth C Chao; Soma Das; Lisa Vincent; Heidi L Rehm
Journal:  Genet Med       Date:  2017-03-16       Impact factor: 8.822

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  2 in total

1.  The value of genomic variant ClinVar submissions from clinical providers: Beyond the addition of novel variants.

Authors:  Karen E Wain; Emily Palen; Juliann M Savatt; Devin Shuman; Brenda Finucane; Andrea Seeley; Thomas D Challman; Scott M Myers; Christa Lese Martin
Journal:  Hum Mutat       Date:  2018-11       Impact factor: 4.878

2.  A Commentary on Opportunities for the Genetic Counseling Profession through Genomic Variant Interpretation: Reflections from an Ex-Lab Rat.

Authors:  Karen Wain
Journal:  J Genet Couns       Date:  2018-03-10       Impact factor: 2.537

  2 in total

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