Establishment and application of a method of next generation sequencing of 285 genes in lung cancer based on Ion-Proton platform

BACKGROUND: The development of “precision medicine” needs a novel genetic screening and diagnostic technique for clinical detection. This study aims to establish a method for highly parallel multiplexed detection of genetic mutations in Chinese lung cancer samples through testing 285 genes by customized next generation sequencing (NGS) on Ion-Proton platform. METHODS: We reviewed the related literature and collected data of genomic alteration that occurred in lung cancer. We identified 285 target genes closely related to the pathogenesis, drug resistance, and metastasis of lung cancer. Targeted hybridization probes were designed using SureDesign software. The detection method was established by analyzing four cell lines and 13 lung cancer specimens which had been validated through Sanger sequencing. The sensitivity and specificity of the proposed method were preliminarily evaluated by comparisons with the Sanger sequencing and a LungCarta mutation-detection method. RESULTS: The proposed method was able to detect mutations of 285 genes in lung cancer cell lines and clinical lung cancer specimens. The reads, mapped reads, on target, mean depth and uniformity were 14.90±4.37 (×10(6)), 98.68%±0.61%, 60.49%±10.72%, 714.42±264.13 and 90.51%±6.91%, respectively. The detected mutation result of cell lines was consistent with the observations on previously reported mutations, and the congruence rate was 100%. The proposed method can detect single nucleotide polymorphism (SNP), InDel, Fusion and copy number variation (CNV). The complete congruence rate of detected result of specimens between the proposed method and Sanger sequencing, LungCarta mutation-detection method, immunohistochemistry (IHC), real-time polymerase chain reaction (RT-PCR) method were all 100% regarding mutations in common genes like EGFR, KRAS, or fusions of ALK, RET, etc. In addition, NFE2L3_p.Ser511_Pro513del, ERBB2_E770delinsEAYVM, MET_S701N, PDGFRA_T674I, TP53_G245V, TP53_V274A, TP53_A276F, TP53_G334L, TP53_R337L and TP53_Y220C mutations were detected only through the proposed method. The proposed method can detect mutations from blood, this detection result was consistent with the cancer tissues of the same clinical lung cancer patient. CONCLUSIONS: The proposed Ion-Proton technology-based NGS method can detect genetic mutations in Chinese lung cancer patients. Therefore, the proposed method could be used to detect mutations in other cancer tissues and plasma, which needs further validation.