Abstract
Background Despite increasing understanding of m6A-related lncRNAs in lung cancer, the role of m6A-related lncRNAs in the prognosis and treatment of lung squamous cell carcinoma is poorly understood to date. Thus, the current study aims to elucidate its role and build a model to predict the prognosis of LUSC patients. Materials and Methods The data of the current study were accessed from the TCGA database. Pearson correlation analysis was performed to identify lncRNAs correlated to m6A. Next, an m6A-related lncRNAs risk model was built using a single factor, least absolute association, selection operator, and multivariate Cox regression analysis. Results The relevance between 23 m6A genes and 14,056 lncRNAs is shown by Pearson correlation analysis by Sankey diagram. Multivariate Cox regression analysis determined that 11 m6A-lncRNAs show predictive potential in prognosis, which is confirmed by the consistency index, Kaplan–Meier analysis, principal component analysis, and ROC curve. Additionally, the immune analysis showed that the enrichment of immune cells, major histocompatibility complex molecules, and immune checkpoints in the high and low-risk subgroups were markedly disparate, with the high-risk group showing a stronger immune escape ability and a worse response to immunotherapy. Conclusion In conclusion, the risk model based on m6A-related lncRNAs showed great promise in predicting the prognosis and the efficacy of immunotherapy.
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