Department of Genetics, Quest Diagnostics Nichols Institute, San Juan Capistrano, CA 92675, USA.
Athena/Quest Diagnostics, Marlborough, MA 01752, USA.
Biomed Res Int. 2020 Jan 22;2020:3289023. doi: 10.1155/2020/3289023. eCollection 2020.
The use of genetic testing to identify individuals with hereditary cancer syndromes has been widely adopted by clinicians for management of inherited cancer risk. The objective of this study was to develop and validate a 34-gene inherited cancer predisposition panel using targeted capture-based next-generation sequencing (NGS). The panel incorporates genes underlying well-characterized cancer syndromes, such as and (), along with more recently discovered genes associated with increased cancer risk. We performed a validation study on 133 unique specimens, including 33 with known variant status; known variants included single nucleotide variants (SNVs) and small insertions and deletions (Indels), as well as copy-number variants (CNVs). The analytical validation study achieved 100% sensitivity and specificity for SNVs and small Indels, with 100% sensitivity and 98.0% specificity for CNVs using in-house developed CNV flagging algorithm. We employed a microarray comparative genomic hybridization (aCGH) method for all specimens that the algorithm flags as CNV-positive for confirmation. In combination with aCGH confirmation, CNV detection specificity improved to 100%. We additionally report results of the first 500 consecutive specimens submitted for clinical testing with the 34-gene panel, identifying 53 deleterious variants in 13 genes in 49 individuals. Half of the detected pathogenic/likely pathogenic variants were found in (23%), (23%), or the Lynch syndrome-associated genes (4%) and (2%). The other half were detected in 9 other genes: (17%) (15%), (4%), (4%), (2%), (2%), (2%), (2%), and (2%). Our validation studies and initial clinical data demonstrate that a 34-gene inherited cancer predisposition panel can provide clinically significant information for cancer risk assessment.
利用基因检测来识别遗传性癌症综合征患者,已被临床医生广泛用于管理遗传性癌症风险。本研究的目的是开发和验证一种基于靶向捕获的下一代测序(NGS)的 34 基因遗传性癌症易感性panel。该 panel 纳入了一些明确的癌症综合征相关基因,如 和 (), 以及最近发现的与癌症风险增加相关的基因。我们对 133 个独特的样本进行了验证研究,其中包括 33 个具有已知变异状态的样本;已知变异包括单核苷酸变异(SNVs)和小插入/缺失(Indels),以及拷贝数变异(CNVs)。分析验证研究实现了 SNVs 和小 Indels 的 100%敏感性和特异性,使用内部开发的 CNV 标记算法,CNVs 的敏感性为 100%,特异性为 98.0%。我们对算法标记为 CNV 阳性的所有样本都采用微阵列比较基因组杂交(aCGH)方法进行确认。与 aCGH 确认相结合,CNV 检测特异性提高到 100%。我们还报告了 34 基因 panel 首次进行的 500 例连续临床检测结果,在 49 名个体的 13 个基因中发现了 53 个有害变异。在检测到的致病性/可能致病性变异中,有一半(53%)位于 (23%)、 (23%)、或与 Lynch 综合征相关的基因 (4%)和 (2%)。另一半分布在另外 9 个基因中: (17%)(15%)、 (4%)、 (4%)、 (2%)、 (2%)、 (2%)、 (2%)、 (2%)和 (2%)。我们的验证研究和初步临床数据表明,34 基因遗传性癌症易感性 panel 可为癌症风险评估提供具有临床意义的信息。