Shen Wei, Paxton Christian N, Szankasi Philippe, Longhurst Maria, Schumacher Jonathan A, Frizzell Kimberly A, Sorrells Shelly M, Clayton Adam L, Jattani Rakhi P, Patel Jay L, Toydemir Reha, Kelley Todd W, Xu Xinjie
ARUP Laboratories, Salt Lake City, Utah, USA.
Department of Pathology, University of Utah School of Medicine, Salt Lake City, Utah, USA.
J Clin Pathol. 2018 Apr;71(4):372-378. doi: 10.1136/jclinpath-2017-204823. Epub 2017 Dec 2.
Genetic abnormalities, including copy number variants (CNV), copy number neutral loss of heterozygosity (CN-LOH) and gene mutations, underlie the pathogenesis of myeloid malignancies and serve as important diagnostic, prognostic and/or therapeutic markers. Currently, multiple testing strategies are required for comprehensive genetic testing in myeloid malignancies. The aim of this proof-of-principle study was to investigate the feasibility of combining detection of genome-wide large CNVs, CN-LOH and targeted gene mutations into a single assay using next-generation sequencing (NGS).
For genome-wide CNV detection, we designed a single nucleotide polymorphism (SNP) sequencing backbone with 22 762 SNP regions evenly distributed across the entire genome. For targeted mutation detection, 62 frequently mutated genes in myeloid malignancies were targeted. We combined this SNP sequencing backbone with a targeted mutation panel, and sequenced 9 healthy individuals and 16 patients with myeloid malignancies using NGS.
We detected 52 somatic CNVs, 11 instances of CN-LOH and 39 oncogenic mutations in the 16 patients with myeloid malignancies, and none in the 9 healthy individuals. All CNVs and CN-LOH were confirmed by SNP microarray analysis.
We describe a genome-wide SNP sequencing backbone which allows for sensitive detection of genome-wide CNVs and CN-LOH using NGS. This proof-of-principle study has demonstrated that this strategy can provide more comprehensive genetic profiling for patients with myeloid malignancies using a single assay.
包括拷贝数变异（CNV）、拷贝数中性杂合性缺失（CN-LOH）和基因突变在内的基因异常是髓系恶性肿瘤发病机制的基础，并且可作为重要的诊断、预后和/或治疗标志物。目前，髓系恶性肿瘤的全面基因检测需要多种检测策略。本原理验证研究的目的是探讨使用下一代测序（NGS）将全基因组大CNV、CN-LOH和靶向基因突变的检测整合到单一检测中的可行性。
对于全基因组CNV检测，我们设计了一个单核苷酸多态性（SNP）测序框架，其中22762个SNP区域均匀分布于整个基因组。对于靶向突变检测，靶向髓系恶性肿瘤中62个频繁突变的基因。我们将这个SNP测序框架与一个靶向突变panel相结合，并使用NGS对9名健康个体和16例髓系恶性肿瘤患者进行测序。
我们在16例髓系恶性肿瘤患者中检测到52个体细胞CNV、11例CN-LOH和39个致癌突变，而在9名健康个体中未检测到。所有CNV和CN-LOH均通过SNP微阵列分析得到证实。
我们描述了一种全基因组SNP测序框架，其可使用NGS灵敏检测全基因组CNV和CN-LOH。本原理验证研究表明，该策略可通过单一检测为髓系恶性肿瘤患者提供更全面的基因图谱。
