Development and Analytical Validation of a Targeted Next-Generation Sequencing Panel to Detect Actionable Mutations for Targeted Therapy
Received 27 December 2020
Accepted for publication 18 March 2021
Published 7 April 2021 Volume 2021:14 Pages 2423—2431
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Arseniy Yuzhalin
Dandan Wang,1,2,* Kai Ma,3,* Wei Deng,4,* Jingyu Li,1 Shaohua Xiang,1 Yang Zhang,2 Ying Fu,2 Heng Dai,2 Bingding Huang1,2
1College of Big Data and Internet, Shenzhen Technology University, Shenzhen, Guangdong, 518118, People’s Republic of China; 2Department of Research and Development, Sinotech Genomics Inc., Shanghai, 230001, People’s Republic of China; 3Department of Thoracic Surgery, National Cancer Center, Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, Guangdong, 518116, People’s Republic of China; 4Department of General Surgery, Beijing Friendship Hospital, Capital Medical University & National Clinical Research Center for Digestive Disease, Beijing, 100050, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Bingding Huang
College of Big Data and Internet, Shenzhen Technology University, Shenzhen, Guangdong, 518118, People’s Republic of China
Email [email protected]
Background: The ability to rapidly, inexpensively, and accurately identify cancer patients based on actionable genomic mutations in tumour specimens is becoming critically important in routine clinical diagnostics. Targeted panel sequencing is becoming popular because it enables comprehensive and cost-effective diagnosis. However, the implementation of a next-generation sequencing (NGS) assay in clinical settings requires careful analytical validation to demonstrate its ability to detect multiple genomic variants.
Materials and Methods: Here, we developed a custom-targeted NGS panel to identify actionable variants, including single nucleotide variants, insertions, and deletions; copy number variants; and gene fusions, across 73 genes for targeted cancer therapy. We implemented a practical validation strategy with diluted samples and reference standard samples that modelled key determinants of accuracy, including mutant allele frequency, insertion/deletion length, amplitude of copy number, and hotspot gene fusions.
Results: The analytical validation results demonstrated that our panel can identify different types of genomic alterations in these test samples with high levels of accuracy, sensitivity, and reproducibility.
Conclusion: Our panel could be deployed as a routine clinical test to comprehensively detect actionable variants in cancer patients to guide targeted therapy decisions.
Keywords: next-generation sequencing, actionable mutations, targeted therapy
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