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

Abstract Purpose: This study aimed to explore the role of N6-methyladenosine (m6A)-related lncRNAs in lung adenocarcinoma (LUAD). Methods: Gene expression data and clinical data of LUAD patients were acquired from The Cancer Genome Atlas (TCGA) Database. Combined with clinical information, the prognostic m6A-related lncRNAs were identified through differential lncRNA expression analysis and Spearman correlation analysis. Next, the least absolute shrinkage and selection operator (LASSO) regression was used to establish the prognostic risk model. We evaluated and validated the predictive performance of this model via survival analysis and receiver operating characteristic (ROC) curve analysis. The expression of immune checkpoints, immune cell infiltration and drug sensitivity of patients in different risk groups were analyzed separately. Results: A total of 19 prognostic m6A-related lncRNAs were identified and then the prognostic risk model was well established. The patients were divided into high- and low-risk group 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 poor. The ROC curves showed that this model had excellent sensitivity and specificity. Multivariate Cox regression analysis indicated that the risk score could be used as an independent prognostic risk factor. The expression levels of immune checkpoint CD276, PVR, and VTCN1 were significantly increased in the high-risk group. Finally, we found that the risk scores were correlated with immune cell infiltration and drug sensitivity. Conclusion: We constructed a prognostic risk model in LUAD patients based on m6A-related lncRNAs. This model was also associated with the expression of immune checkpoints, immune cell infiltration and drug sensitivity, which will provide new insights into immunotherapy for LUAD patients in the future.