Zhao Xiaobei, Wang Anyou, Walter Vonn, Patel Nirali M, Eberhard David A, Hayward Michele C, Salazar Ashley H, Jo Heejoon, Soloway Matthew G, Wilkerson Matthew D, Parker Joel S, Yin Xiaoying, Zhang Guosheng, Siegel Marni B, Rosson Gary B, Earp H Shelton, Sharpless Norman E, Gulley Margaret L, Weck Karen E, Hayes D Neil, Moschos Stergios J
Lineberger Comprehensive Cancer Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, United States of America.
Lineberger Comprehensive Cancer Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, United States of America; Department of Pathology and Laboratory Medicine, the University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, United States of America.
PLoS One. 2015 Jun 15;10(6):e0129280. doi: 10.1371/journal.pone.0129280. eCollection 2015.
The recent FDA approval of the MiSeqDx platform provides a unique opportunity to develop targeted next generation sequencing (NGS) panels for human disease, including cancer. We have developed a scalable, targeted panel-based assay termed UNCseq, which involves a NGS panel of over 200 cancer-associated genes and a standardized downstream bioinformatics pipeline for detection of single nucleotide variations (SNV) as well as small insertions and deletions (indel). In addition, we developed a novel algorithm, NGScopy, designed for samples with sparse sequencing coverage to detect large-scale copy number variations (CNV), similar to human SNP Array 6.0 as well as small-scale intragenic CNV. Overall, we applied this assay to 100 snap-frozen lung cancer specimens lacking same-patient germline DNA (07-0120 tissue cohort) and validated our results against Sanger sequencing, SNP Array, and our recently published integrated DNA-seq/RNA-seq assay, UNCqeR, where RNA-seq of same-patient tumor specimens confirmed SNV detected by DNA-seq, if RNA-seq coverage depth was adequate. In addition, we applied the UNCseq assay on an independent lung cancer tumor tissue collection with available same-patient germline DNA (11-1115 tissue cohort) and confirmed mutations using assays performed in a CLIA-certified laboratory. We conclude that UNCseq can identify SNV, indel, and CNV in tumor specimens lacking germline DNA in a cost-efficient fashion.
美国食品药品监督管理局（FDA）近期对MiSeqDx平台的批准，为开发针对人类疾病（包括癌症）的靶向新一代测序（NGS）面板提供了独特机遇。我们开发了一种可扩展的、基于靶向面板的检测方法，称为UNCseq，它涉及一个包含200多个癌症相关基因的NGS面板以及一个标准化的下游生物信息学流程，用于检测单核苷酸变异（SNV）以及小的插入和缺失（indel）。此外，我们开发了一种新颖的算法NGScopy，专为测序覆盖度稀疏的样本设计，用于检测大规模拷贝数变异（CNV），类似于人类SNP Array 6.0以及小规模基因内CNV。总体而言，我们将该检测方法应用于100份缺乏同患者种系DNA的冰冻肺癌标本（07 - 0120组织队列），并通过桑格测序、SNP Array以及我们最近发表的整合DNA测序/RNA测序检测方法UNCqeR验证了结果，在RNA测序覆盖深度足够的情况下，同患者肿瘤标本的RNA测序证实了DNA测序检测到的SNV。此外，我们将UNCseq检测方法应用于一个具有可用同患者种系DNA的独立肺癌肿瘤组织样本集（11 - 1115组织队列），并使用在CLIA认证实验室进行的检测方法确认了突变。我们得出结论，UNCseq能够以经济高效的方式识别缺乏种系DNA的肿瘤标本中的SNV、indel和CNV。
