Analysis of common mutations in non-small cell lung cancer by high-throughput sequencing
10.3760/cma.j.issn.1009-8158.2019.04.013
- VernacularTitle:基于高通量测序技术的非小细胞肺癌常见基因位点突变分析
- Author:
Lutao DU
1
;
Yao ZHAN
;
Juan LI
;
Lishui WANG
;
Zhao DU
;
Li YANG
;
Chuanxin WANG
Author Information
1. 山东大学第二医院检验医学中心
- Keywords:
Carcinoma;
non-small-cell lung;
Lung neoplasms;
High-throughput nucleotide sequencing;
Mutation
- From:
Chinese Journal of Laboratory Medicine
2019;42(4):297-305
- CountryChina
- Language:Chinese
-
Abstract:
Objective Next Generation Sequencing(NGS) platform was used to study the characteristics of hot gene mutations in non-small cell lung cancer (NSCLC). The distribution, type and frequency of mutation sites were systematically analyzed to evaluate the pathogenicity of mutation sites . Methods A total of 94 NSCLC tissue samples were included in this study including paraffin-embedded (FFPE) samples and fresh tissue samples, which were collected from July 2015 to April 2017 at the Qilu Hospital of Shandong University. The patient's age ranged from 35 to 82 years with a median age of 61 years. There were 63 males and 31 females. 22 hot genes in NSCLC were selected as the detection panel, including KRAS, EGFR, BRAF, PIK3CA, AKT1, ERBB2, PTEN, NRAS, STK11, MAP2K1, ALK, DDR2, CTNNB1, MET, TP53, SMAD4, FBXW7, NOTCH1, ERBB4, FGFR1 and FGFR2. Mutation detection was performed using the Ion AmpliSeq Colon and Lung Cancer Panel of the Thermo fisher's Ion Torrent sequencing platform. The sequencing data was analyzed using Ion Torrent suite v4.4.2 software. Results Among the 22 mutant genes commonly found in NSCLC, the mutation frequency of TP53 was the highest, accounting for 46.9％ of all mutations, followed by the EGFR mutation (28.1％); A total of 89 mutations were detected, including 63 hot spot mutations (reported mutations) and 26 new mutations (unreported mutations). The most frequently detected mutation was the frameshift deletion of exon 19 of EGFR, followed by the mutation of exon L858R;Analysis of the mutation in targeted drug sites of EGFR showed that the frameshift deletion of exon 19 of EGFR was the most frequently detected, followed by the mutation of exon L858R on chromosome 21. Bioinformatics software was used to analyze the pathogenicity of 26 new mutation sites. Results showed that in addition to ATK1:c. 47-12G>A and TP53: c. 214 C>G, the remaining 24 new mutation sites had at least one major impact on the gene function in three aspects, including gene conservation, amino acid sequence change and protein structure influence. Conclusion In this study, NGS was used to conduct combined detection of mutation sites of multiple hot genes, which might cover more comprehensively genetic variation and provide a basis for screening the most suitable targeted therapy groups. The pathogenicity prediction of new mutations and the changes in tumor-related signaling pathways involved provide a reference for further study of the pathogenesis of NSCLC.
