Sukhai Mahadeo A, Craddock Kenneth J, Thomas Mariam, Hansen Aaron R, Zhang Tong, Siu Lillian, Bedard Philippe, Stockley Tracy L, Kamel-Reid Suzanne
Laboratory Medicine Program, Advanced Molecular Diagnostics Laboratory, Department of Pathology, University Health Network, Toronto, Ontario, Canada.
Cancer Genomics Program, Princess Margaret Cancer Centre, The University Health Network, Toronto, Ontario, Canada.
Genet Med. 2016 Feb;18(2):128-36. doi: 10.1038/gim.2015.47. Epub 2015 Apr 16.
Interpretation systems for clinical laboratory reporting of genetic variants for inherited conditions have been widely published. By contrast, there are no existing systems for interpretation and classification of somatic variants found from molecular testing of cancer.
We designed an assessment protocol and classification system for somatic variants identified through next-generation sequencing molecular profiling of tumor-derived samples and applied these to a pilot dataset of somatic variants found by next-generation sequencing profiling of 158 tumor samples derived from advanced cancer patients examined at the Princess Margaret Cancer Centre.
We present a classification system to interpret the significance of genetic variants in molecular analysis of cancer, including the following key factors: (i) known or predicted pathogenicity of the variant; (ii) primary site and tumor histology in which the variant is found; (iii) recurrence of the variant; and (iv) evidence of clinical actionability. We used these factors to develop a five-category somatic variant classification for simplified reporting of variant interpretations to treating oncologists.
Our somatic variant classification can be of practical value to other clinical molecular laboratories performing cancer genetic profiling by promoting consistent reporting of somatic variants and permitting harmonization of variant data among laboratories and clinical studies.
关于遗传性疾病基因变异临床实验室报告的解读系统已广泛发表。相比之下，目前尚无用于解读和分类癌症分子检测中发现的体细胞变异的系统。
我们设计了一种评估方案和分类系统，用于解读通过肿瘤来源样本的下一代测序分子谱分析鉴定出的体细胞变异，并将其应用于一个试点数据集，该数据集包含通过对玛格丽特公主癌症中心检测的158例晚期癌症患者的肿瘤样本进行下一代测序谱分析发现的体细胞变异。
我们提出了一个分类系统，用于解读癌症分子分析中基因变异的意义，包括以下关键因素：（i）变异的已知或预测致病性；（ii）发现变异的主要部位和肿瘤组织学类型；（iii）变异的复发情况；（iv）临床可操作性证据。我们利用这些因素开发了一个五类体细胞变异分类系统，以便向肿瘤治疗医生简化报告变异解读。
我们的体细胞变异分类对于其他进行癌症基因谱分析的临床分子实验室具有实际价值，它可促进体细胞变异报告的一致性，并允许实验室和临床研究之间的变异数据协调统一。
