Development and validation of an ultra-high sensitive next-generation sequencing assay for molecular diagnosis of clinical oncology.
Dramatic improvements in the understanding of oncogenes have spurred the development of molecular target therapies, which created an exigent need for comprehensive and rapid clinical genotyping. Next-generation sequencing (NGS) assay with increased performance and decreased cost is becoming more widely used in clinical diagnosis. However, the optimization and validation of NGS assay remain a challenge, especially for the detection of somatic variants at low mutant allele fraction (MAF). In the present study, we developed and validated the Novogene Comprehensive Panel (NCP) based on targeted capture for NGS analysis. Due to the high correlation between SNV/INDEL detection performance and target coverage, here we focused on these two types of variants for our deep sequencing strategy. To validate the capability of NCP in single-nucleotide variant (SNV) and small insert and deletion (INDEL) detection, we implemented a practical validation strategy with pooled cell lines, deep sequencing of pooled samples (>2000X average unique coverage across target region) achieving >99% sensitivity and high specificity (positive predictive value, PPV >99%) for all types of variations with expected MAF >5%. Furthermore, given the high sensitivity and that false positive may exist in this assay, we confirmed its accuracy of variants with MAF <5% using 35 formalin-fixed and paraffin-embedded (FFPE) tumor specimens by Quantstudio 3D Digital PCR (dPCR; Life Technologies) and obtained a high consistency (32 of 35 mutations detected by NGS were verified). We also used the amplification refractory mutation system (ARMS) to verify the variants with a MAF in a broad range of 2-63% detected in 33 FFPE samples and reached a 100% PPV for this assay. As a potential clinical diagnosis tool, NCP can robustly and comprehensively analyze clinical-related genes with high sensitivity and low cost.
State Key Laboratory of Biomembrane and Membrane Biotechnology, School of Medicine, National Engineering Laboratory for Anti-tumor Therapeutics, Tsinghua University, Beijing 100084, P.R. China.
Jiao
J
Liang
Department of General Surgery, Chinese PLA General Hospital, Beijing 100853, P.R. China.
Yaoguang
Y
She
Novogene Bioinformatics Institute, Beijing 100083, P.R. China.
Jiaqi
J
Zhu
Novogene Bioinformatics Institute, Beijing 100083, P.R. China.
Longgang
L
Wei
Novogene Bioinformatics Institute, Beijing 100083, P.R. China.
Lanying
L
Zhang
Novogene Bioinformatics Institute, Beijing 100083, P.R. China.
Lianju
L
Gao
Novogene Bioinformatics Institute, Beijing 100083, P.R. China.
Yan
Y
Wang
Novogene Bioinformatics Institute, Beijing 100083, P.R. China.
Jing
J
Xing
Novogene Bioinformatics Institute, Beijing 100083, P.R. China.
Yang
Y
Guo
Novogene Bioinformatics Institute, Beijing 100083, P.R. China.
Xuehong
X
Meng
Department of General Surgery, Chinese PLA General Hospital, Beijing 100853, P.R. China.
Peiyu
P
Li
D014408:Biomarkers, Tumor / Q000235:genetics*; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000235:genetics*; D005260:Female; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D008175:Lung Neoplasms / Q000175:diagnosis* / Q000235:genetics*; D009154:Mutation / Q000235:genetics*; D016612:Paraffin Embedding; D060888:Real-Time Polymerase Chain Reaction; D014407:Tumor Cells, Cultured
D014408:Biomarkers, Tumor