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. 2021 Mar 25:9:661792.
doi: 10.3389/fcell.2021.661792. eCollection 2021.

Comprehensive Analysis of the Prognostic Role and Mutational Characteristics of m6A-Related Genes in Lung Squamous Cell Carcinoma

Chang Gu  1   2 , Xin Shi  3 , Wenli Qiu  4 , Zhenyu Huang  5   6 , Yan Yu  7 , Feng Shen  7 , Yumei Chen  8 , Xufeng Pan  1
Affiliations

Comprehensive Analysis of the Prognostic Role and Mutational Characteristics of m6A-Related Genes in Lung Squamous Cell Carcinoma

Chang Gu et al. Front Cell Dev Biol. .

Abstract

Background: There have been limited treatment therapies for lung squamous cell carcinoma (LUSC). M6A-related genes may be the next therapeutic targets for LUSC. In this study, we explored the prognostic role and mutational characteristics of m6A-related genes in LUSC.

Methods: LUSC gene expression data, mutational data, and corresponding clinical information were extracted from The Cancer Genome Atlas database. Differentially expressed genes (DEGs) were identified, and the mutation characteristics of LUSC patients were explored. Then, m6A-related genes were extracted and the correlations among the genes were detected. Finally, the prognostic roles of the genes were investigated and the nomogram model was developed. Besides, the protein-protein interaction (PPI) network was used to explore the potential interactions among the genes.

Results: In total, there are 551 LUSC samples enrolled in our study, containing 502 LUSC tumor samples and 49 adjacent normal LUSC samples, respectively. There were 2970 upregulated DEGs and 1806 downregulated DEGs were further explored. IGF2BP1 and RBM15 had significant co-occurrence frequency (p < 0.05). Besides, METTL14 and ZC3H13 or YTHDF3 also had significant co-occurrence frequency (p < 0.05). All the m6A-related genes represent the positive correlation. WTAP was identified as a prognostic gene in the TCGA database while YTHDC1 and YTHDF1 were identified as prognostic genes. In multivariate Cox analysis, YTHDF1, age, pN stage, pTNM stage, and smoking were all identified as significant prognostic factors for OS.

Conclusion: We investigated the expression patterns and mutational characteristics of LUSC patients and identified three potential independent prognostic m6A-related genes (WTAP, YTHDC1, and YTHDF1) for OS in LUSC patients.

Keywords: RNA methylation; lung squamous cell carcinoma; m6A; nomogram; prognosis.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Differentially expressed genes (DEGs) in patients with lung squamous cell carcinoma (LUSC). (A) Principal component analysis (PCA) for tumor and normal tissues. (B) DEGs between tumor and normal tissues. (C) Heat map for DEGs in paired samples. (D) The expression of m6A-related genes in total LUSC patients in TCGA database.
FIGURE 2
FIGURE 2
Mutation patterns of LUSC patients. (A) Oncoplot displays the mutational patterns of m6A-related genes in 89 LUSC patients. (B) The co-expression patterns of m6A-related genes in LUSC patients. (C) The SNP patterns of LUSC patients. (D) Rainfall plot shows hypermutated genomic regions. *p < 0.05.
FIGURE 3
FIGURE 3
Correlation analysis among m6A related genes. (A) The distributions of each sample and the correlation coefficients were calculated. (B) The correlation coefficients were drawn by pie charts.
FIGURE 4
FIGURE 4
Identification of consensus clusters according to the expression similarity of m6A-related genes. (A) Cumulative distribution function (CDF) (k = 2–6). (B) Relative change in area under the CDF curve (k = 2–6). (C) The matrix of consensus clustering (k = 3). (D) Heat map of m6A-related gene expression in different subgroups; red represents high expression while blue represents low expression.
FIGURE 5
FIGURE 5
Survival curves according to the expression of (A) WTAP; (B) YTHDC1; and (C) YTHDF1.
FIGURE 6
FIGURE 6
The identification of prognostic factor for OS and the development of the nomogram. (A) Univariate Cox analysis. (B) Multivariate Cox analysis. (C) Nomogram for OS in LUSC patients. (D) The calibration curves for each year.
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