Department of Clinical Genetics, Odense University Hospital, Odence C, Denmark.
Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands.
Hum Mutat. 2022 Dec;43(12):1921-1944. doi: 10.1002/humu.24449. Epub 2022 Oct 23.
Skipping of BRCA2 exon 3 (∆E3) is a naturally occurring splicing event, complicating clinical classification of variants that may alter ∆E3 expression. This study used multiple evidence types to assess pathogenicity of 85 variants in/near BRCA2 exon 3. Bioinformatically predicted spliceogenic variants underwent mRNA splicing analysis using minigenes and/or patient samples. ∆E3 was measured using quantitative analysis. A mouse embryonic stem cell (mESC) based assay was used to determine the impact of 18 variants on mRNA splicing and protein function. For each variant, population frequency, bioinformatic predictions, clinical data, and existing mRNA splicing and functional results were collated. Variant class was assigned using a gene-specific adaptation of ACMG/AMP guidelines, following a recently proposed points-based system. mRNA and mESC analysis combined identified six variants with transcript and/or functional profiles interpreted as loss of function. Cryptic splice site use for acceptor site variants generated a transcript encoding a shorter protein that retains activity. Overall, 69/85 (81%) variants were classified using the points-based approach. Our analysis shows the value of applying gene-specific ACMG/AMP guidelines using a points-based approach and highlights the consideration of cryptic splice site usage to appropriately assign PVS1 code strength.
BRCA2 外显子 3(∆E3)的跳跃是一种自然发生的剪接事件,使可能改变 ∆E3 表达的变体的临床分类复杂化。本研究使用多种证据类型来评估 85 个 BRCA2 外显子 3 内/附近变体的致病性。生物信息学预测的剪接变体使用微基因和/或患者样本进行 mRNA 剪接分析。使用定量分析测量 ∆E3。使用基于小鼠胚胎干细胞(mESC)的测定来确定 18 个变体对 mRNA 剪接和蛋白功能的影响。对于每个变体,都整理了群体频率、生物信息学预测、临床数据以及现有的 mRNA 剪接和功能结果。使用 ACMG/AMP 指南的基因特异性适应性,并遵循最近提出的基于点数的系统,为每个变体分配变体类别。mRNA 和 mESC 分析联合鉴定了六个具有转录和/或功能特征的变体,这些特征被解释为功能丧失。供体位点变体的隐蔽剪接位点使用产生编码保留活性的较短蛋白的转录本。总体而言,使用基于点数的方法对 85 个变体中的 69 个(81%)进行了分类。我们的分析表明,使用基于点数的方法应用基因特异性 ACMG/AMP 指南的价值,并强调考虑隐蔽剪接位点的使用,以正确分配 PVS1 代码强度。