PDF(Pubmed)
Abstract：
Despite recent efforts to issue clinical guidelines outlining strategies to define the pathogenicity of genomic variants, there is currently no standardized framework for which to make these assertions. This review does not present a step-by-step methodology, but rather takes a holistic approach to discuss many aspects which should be taken into consideration when determining variant pathogenicity. Categorization should be curated to reflect relevant findings within the scope of the specific medical context. Functional characterization should evaluate all available information, including results from literature reviews, different classes of genomic data repositories, and applicable computational predictive algorithms. This article further proposes a multidimensional view to infer pathogenic status from many genomic measurements across multiple axes. Notably, tumor suppressors and oncogenes exhibit fundamentally different biology which helps refine the importance of effects on splicing, mutation interactions, copy number thresholds, rearrangement annotations, germline status, and genome-wide signatures. Understanding these relevant datapoints with thoughtful perspective could aid in the reclassification of variants of unknown significance (VUS), which are ambiguously understood and currently have uncertain clinical implications. Ongoing assessments of VUS examining these relevant biological axes could lead to more accurate classification of variant pathogenicity interpretation in diagnostic oncology.
摘要：
尽管最近努力发布临床指南概述了定义基因组变异致病性的策略，目前没有标准化的框架来做出这些断言。这篇综述没有提出循序渐进的方法，而是采取整体的方法来讨论确定变异致病性时应考虑的许多方面。应进行分类，以反映特定医学背景范围内的相关发现。功能表征应评估所有可用信息，包括文献综述的结果，不同类别的基因组数据存储库，和适用的计算预测算法。这篇文章进一步提出了一个多维视图，从多个轴的许多基因组测量中推断致病状态。值得注意的是,肿瘤抑制基因和癌基因表现出根本不同的生物学，这有助于提高剪接效应的重要性，突变相互作用，副本数量阈值，重排注释,种系状态,和全基因组特征。以深思熟虑的视角理解这些相关数据点可以帮助重新分类未知意义的变体(VUS)，这是模糊的理解，目前具有不确定的临床意义。对VUS检查这些相关生物学轴的持续评估可以导致诊断肿瘤学中变异致病性解释的更准确分类。
