Construction of an m6A-related lncRNA model for predicting prognosis and immunotherapy in patients with lung adenocarcinoma

Abstract

N6-methyladenosine (m6A)-related lncRNAs could be involved in the development of multiple tumors with an unknown role in lung adenocarcinoma (LUAD). Hence, gene expression data and clinical data of LUAD patients were acquired from The Cancer Genome Atlas Database. The prognostic m6A-related lncRNAs were identified through differential lncRNA expression analysis and Spearman’s correlation analysis. The least absolute shrinkage and selection operator regression was used to establish the prognostic risk model, so as to evaluate and validate the predictive performance with survival analysis and receiver operating characteristic curve analysis. The expression of immune checkpoints, immune cell infiltration and drug sensitivity of patients in different risk groups were analyzed separately. A total of 19 prognostic m6A-related lncRNAs were identified to set up the prognostic risk model. The patients were divided into high- and low-risk groups based on the median value of the risk scores. Compared with the patients in the low-risk group, the prognosis of the patients in the high-risk group was relatively worse. The receiver operating characteristic curves indicated that this model had excellent sensitivity and specificity. Multivariate Cox regression analysis demonstrated that the risk score could be supposed as an independent prognostic risk factor. We highlighted that the risk scores were correlated with immune cell infiltration and drug sensitivity for constructing a prognostic risk model in LUAD patients based on m6A-related lncRNAs.