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. 2020 Sep;8(9):e1398.
doi: 10.1002/mgg3.1398. Epub 2020 Jul 12.

Genetic profile of non-small cell lung cancer (NSCLC): A hospital-based survey in Jinhua

Xianguo Chen  1 , Bo Xu  1 , Qiang Li  2 , Xiaoyi Xu  1 , Xianshuai Li  1 , Xia You  2 , Zhaonan Yu  2
Affiliations

Genetic profile of non-small cell lung cancer (NSCLC): A hospital-based survey in Jinhua

Xianguo Chen et al. Mol Genet Genomic Med. 2020 Sep.

Abstract

Background: We describe the clinical features, genetic profile, and their correlation in NSCLC patients.

Methods: A total of 256 Chinese patients with NSCLC were enrolled in this study. NGS-based genomic profiling of major lung cancer-related genes was performed on formalin-fixed paraffin-embedded tumor samples.

Results: Of 256 patients with NSCLC, 219 were adenocarcinoma and most of them were in the early stage. Among patients, 63.3% patients have more than two gene mutations. By analyzing variant allele frequency (VAF), we found that the median VAF has significant differences between squamous cell carcinoma and adenocarcinoma, as well as early stage and advanced stage. The frequency of mutations in EGFR, MET, and RET were significantly higher in nonsmokers than in smokers. Besides, Pearson correlation analysis found that ALK, BRAF, and MET mutations had a strong correlation with age. Notably, higher frequencies of ALK and BRAF alterations were associated with younger age, while more frequent MET mutations appear in the patients at age 55 or older.

Conclusion: More unique features of cancer driver genes in Chinese NSCLC were identified by next-generation sequencing. These findings highlighted that it is necessary to carry out targeted detection according to different clinical features for NSCLC.

Keywords: clinical characteristics; genetic profile; nonsmall cell lung cancer; targeted sequencing.

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Conflict of interest statement

The authors have declared no conflicts of interest.

Figures

Figure 1
Figure 1
The genetic profile of nonsmall cell lung cancer (a) For 244 patients (each column), altered genes (rows) with mutations are shown. The percentage of samples with a mutation is noted at the left. The type of genetic mutation is presented in the middle. Clinical information is presented at the bottom. (b) Distribution of altered gene numbers in 256 patients with nonsmall cell lung cancer. (c) Bar chart showing the frequency of EGFR mutation in different subtypes of all NSCLC
Figure 2
Figure 2
Comparison of variant allele frequencies in tumor type and tumor stage (a) Comparison of variant allele frequencies of LUAD and LUSC with uncorrected data. (b) Comparison of variant allele frequencies of patients with stage I and stage II‐IV with uncorrected data. (c) Comparison of variant allele frequencies of LUAD and LUSC with corrected data. (d) Comparison of variant allele frequencies of patients with stage I and stage II‐IV with corrected data. LUAD: Lung adenocarcinoma. LUSC: Lung squamous cell carcinoma. S1: patients with stage I. S2: patients with stage II‐IV. Statistical significance was defined as p＜0.05
Figure 3
Figure 3
Comparison of variant allele frequencies in tumor type and tumor stage (a) Comparison of variant allele frequencies of LUAD and LUSC with uncorrected data. (b) Comparison of variant allele frequencies of patients with stage I and stage II‐IV with uncorrected data. (c) Comparison of variant allele frequencies of LUAD and LUSC with corrected data. (d) Comparison of variant allele frequencies of patients with stage I and stage II‐IV with corrected data. LUAD: Lung adenocarcinoma. LUSC: Lung squamous cell carcinoma. S1: patients with stage I. S2: patients with stage II‐IV. Statistical significance was defined as p＜0.05
Figure 4
Figure 4
The distribution of representative targeted genetic alterations between the younger and older patients with lung adenocarcinoma (a) The genetic profiles in different age groups of patients with nonsmall‐cell lung cancer. 246 patients with NSCLC patients were enrolled, and tissue sample were analyzed by NGS assays. (b‐f) The distribution of representative targeted genetic alterations between the younger and older patients. (b) ALK arrangements, (c) BRAF mutations, (d)EGFR mutations, (e) KRAS mutations, (f) MET mutations. Statistical significance was defined as p＜0.05. WT: wide type
Figure 5
Figure 5
Pearson correlation analysis between gene mutations and clinical features. Positive number indicates positive correlation. Negative number indicates negative correlation. Correlation coefficients range from −1 to + 1
See this image and copyright information in PMC

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