Combining evidence for and against pathogenicity for variants in cancer susceptibility genes: CanVIG-UK consensus recommendations
- PMID: 33208383
- PMCID: PMC8086256
- DOI: 10.1136/jmedgenet-2020-107248
Combining evidence for and against pathogenicity for variants in cancer susceptibility genes: CanVIG-UK consensus recommendations
Abstract
Accurate classification of variants in cancer susceptibility genes (CSGs) is key for correct estimation of cancer risk and management of patients. Consistency in the weighting assigned to individual elements of evidence has been much improved by the American College of Medical Genetics (ACMG) 2015 framework for variant classification, UK Association for Clinical Genomic Science (UK-ACGS) Best Practice Guidelines and subsequent Cancer Variant Interpretation Group UK (CanVIG-UK) consensus specification for CSGs. However, considerable inconsistency persists regarding practice in the combination of evidence elements. CanVIG-UK is a national subspecialist multidisciplinary network for cancer susceptibility genomic variant interpretation, comprising clinical scientist and clinical geneticist representation from each of the 25 diagnostic laboratories/clinical genetic units across the UK and Republic of Ireland. Here, we summarise the aggregated evidence elements and combinations possible within different variant classification schemata currently employed for CSGs (ACMG, UK-ACGS, CanVIG-UK and ClinGen gene-specific guidance for PTEN, TP53 and CDH1). We present consensus recommendations from CanVIG-UK regarding (1) consistent scoring for combinations of evidence elements using a validated numerical 'exponent score' (2) new combinations of evidence elements constituting likely pathogenic' and 'pathogenic' classification categories, (3) which evidence elements can and cannot be used in combination for specific variant types and (4) classification of variants for which there are evidence elements for both pathogenicity and benignity.
Keywords: genetic testing; genetic variation; genetics; genomics; medical.
© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.
Conflict of interest statement
Competing interests: None declared.
References
-
- Plon SE, Eccles DM, Easton D, Foulkes WD, Genuardi M, Greenblatt MS, Hogervorst FBL, Hoogerbrugge N, Spurdle AB, Tavtigian SV, IARC Unclassified Genetic Variants Working Group . Sequence variant classification and reporting: recommendations for improving the interpretation of cancer susceptibility genetic test results. Hum Mutat 2008;29:1282–91. 10.1002/humu.20880 - DOI - PMC - PubMed
-
- Eccles DM, Mitchell G, Monteiro ANA, Schmutzler R, Couch FJ, Spurdle AB, Gómez-García EB, Driessen R, Lindor NM, Blok MJ, Moller P, de la Hoya M, Pal T, Domchek S, Nathanson K, Van Asperen C, Diez O, Rheim K, Stoppa-Lyonnet D, Parsons M, Goldgar D. Brca1 and BRCA2 genetic testing—pitfalls and recommendations for managing variants of uncertain clinical significance. Ann Oncol 2015;26:2057–65. 10.1093/annonc/mdv278 - DOI - PMC - PubMed
-
- Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, Grody WW, Hegde M, Lyon E, Spector E, Voelkerding K, Rehm HL, ACMG Laboratory Quality Assurance Committee . 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. Genet Med 2015;17:405–23. 10.1038/gim.2015.30 - DOI - PMC - PubMed
-
- Ellard S, Baple EL, Berry I, Forrester N, Turnbull C, Owens M, Eccles DM, Abbs S, Scott R, Deans Z, Lester T, Campbell J, Newman W, McMullan D. ACGS best practice guidelines for variant classification 2020: association for clinical genetics science (ACGS), 2020. Available: https://www.acgs.uk.com/quality/best-practice-guidelines/#VariantGuidelines
-
- Garrett A, Callaway A, Durkie M, Cubuk C, Alikian M, Burghel GJ, Robinson R, Izatt L, Talukdar S, Side L, Cranston T, Palmer-Smith S, Baralle D, Berry IR, Drummond J, Wallace AJ, Norbury G, Eccles DM, Ellard S, Lalloo F, Evans DG, Woodward E, Tischkowitz M, Hanson H, Turnbull C, CanVIG-UK . Cancer variant interpretation group UK (CanVIG-UK): an exemplar national subspecialty multidisciplinary network. J Med Genet 2020;57:829–34. 10.1136/jmedgenet-2019-106759 - DOI - PMC - PubMed
Publication types
MeSH terms
Grants and funding
LinkOut - more resources
Full Text Sources
Medical
Research Materials
Miscellaneous