Identification of a N6-Methyladenosine (m6A)-Related lncRNA Signature for Predicting the Prognosis and Immune Landscape of Lung Squamous Cell Carcinoma

Abstract

Background: m6A-related lncRNAs emerged as potential targets for tumor diagnosis and treatment. This study aimed to identify m6A-regulated lncRNAs in lung squamous cell carcinoma (LUSC) patients.

Materials and methods: RNA sequencing and the clinical data of LUSC patients were downloaded from The Cancer Genome Atlas (TCGA) database. The m6A-related lncRNAs were identified by using Pearson correlation assay. Univariate and multivariate Cox regression analyses were utilized to construct a risk model. The performance of the risk model was validated using Kaplan-Meier survival analysis and receiver operating characteristics (ROC). Immune estimation of LUSC was downloaded from TIMER, and the correlations between the risk score and various immune cells infiltration were analyzed using various methods. Differences in immune functions and expression of immune checkpoint inhibitors and m6A regulators between high-risk and low-risk groups were further explored. Finally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were utilized to explore the biological functions of AL122125.1.

Results: A total of 351 m6A-related lncRNAs were obtained from TCGA. Seven lncRNAs demonstrated prognostic values. A further multivariate Cox regression assay constructed a risk model consisting of two lncRNAs (AL122125.1 and HORMAD2-AS1). The Kaplan-Meier analysis and area under the curve indicated that this risk model could be used to predict the prognosis of LUSC patients. The m6A-related lncRNAs were immune-associated. There were significant correlations between risk score and immune cell infiltration, immune functions, and expression of immune checkpoint inhibitors. Meanwhile, there were significant differences in the expression of m6A regulators between the high- and low-risk groups. Moreover, GO and KEGG analyses revealed that the upregulated expression of AL122125.1 was tumor-related.

Conclusion: In this study, we constructed an m6A-related lncRNA risk model to predict the survival of LUSC patients. This study could provide a novel insight to the prognosis and treatment of LUSC patients.

Keywords: immune microenvironment; long noncoding RNA; lung squamous cell carcinoma (LSCC); m6A (N6-methyladenosine); prognosis.

Figure 1

Expression profiles of m6A regulators in lung squamous cell carcinoma (LUSC). The data was retrieved from The Cancer Genome Atlas database. The expression of 23 m6A regulators between LUSC tumor tissues and normal tissues was compared. Eighteen out of 23 m6A regulators demonstrated significant differences in expression.

Figure 2

m6A-related lncRNAs. Graphs summarizing the m6A-related lncRNAs.

Figure 3

Construction of an m6A-related lncRNA risk model. (A) Univariate Cox regression was used to identify m6A-related lncRNAs with prognostic value. (B) Expression of m6A-related lncRNAs identified from univariate Cox regression analysis. (C) Multivariate Cox regression assay was used to identify m6A-related lncRNAs with an independent prognostic value. **P < 0.01; ***P < 0.001.

Figure 4

Validation of the risk model. Patients were divided into high- and low-risk groups based on the risk score. (A) Kaplan–Meier survival curve of the risk model. (B) Distribution of the risk scores. (C) Distribution of the survival status. (D) Receiver operating curve (ROC) of the risk score and conventional clinical factors. (E) ROC curves of the risk score in predicting 1-, 2-, and 3-year survival. (F) A heat map of the differential expression of AL122125.1 and HORMAD2-AS1 the between high- and low- risk groups.

Figure 5

Immune cell infiltration features in the high- and low- risk groups. A heat map of the differences of immune cell infiltrations between the high- and low-risk groups.

Figure 6

Immune functions (A) and expression of immune checkpoint inhibitors (B) between the high- and low-risk groups. *P < 0.05; **P < 0.01; ***P < 0.001.

Figure 7

Differences in the expression of m6A regulators between the high- and low-risk groups. **P < 0.01; ***P < 0.001. ns, no significance.

Figure 8

Expression and prognosis value of AL122125.1. The differential expression of AL122125.1 was retrieved from The Cancer Genome Atlas (TCGA) (A) and Gene Expression Profiling Interactive Analysis (B). (C) Kaplan–Meier survival curve of AL122125.1. Data was retrieved from TCGA database.

Figure 9

Functional analysis of AL122125.1. (A) Gene Ontology enrichment analysis of AL122125.1. (B) Kyoto Encyclopedia of Genes and Genomes enrichment analysis of AL122125.1.