Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, London, UK.
Sheffield Diagnostic Genetics Service, Sheffield Children's NHS Foundation Trust, Sheffield, UK.
J Med Genet. 2021 May;58(5):297-304. doi: 10.1136/jmedgenet-2020-107248. Epub 2020 Nov 18.
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.
准确分类癌症易感性基因 (CSG) 的变异体对于正确估计癌症风险和管理患者至关重要。美国医学遗传学学院 (ACMG) 2015 年变异分类框架、英国临床基因组科学协会 (UK-ACGS) 最佳实践指南以及随后的英国癌症变异解释小组 (CanVIG-UK) CSG 共识规范,极大地提高了对证据要素个体权重的一致性。然而,在综合证据要素方面仍然存在相当大的不一致。CanVIG-UK 是一个全国性的专科多学科癌症易感性基因组变异解释网络,由英国和爱尔兰共和国的 25 个诊断实验室/临床遗传单位的临床科学家和临床遗传学家代表组成。在这里,我们总结了当前用于 CSG 的不同变异分类方案 (ACMG、UK-ACGS、CanVIG-UK 和 ClinGen 针对 PTEN、TP53 和 CDH1 的基因特异性指南) 中可能存在的聚合证据要素和组合。CanVIG-UK 就以下内容提出了共识建议:(1) 使用经过验证的数值“指数评分”对证据要素组合进行一致评分;(2) 构成“可能致病性”和“致病性”分类类别的新证据要素组合;(3) 哪些证据要素可以和不能用于特定变异类型的组合;(4) 对于同时存在致病性和良性证据要素的变异进行分类。