Construction of a Prognostic Immune-Related LncRNA Risk Model for Lung Adenocarcinoma

摘要

Growing evidence suggests that immune-related genes and long non-coding RNAs (lncRNAs) can serve as prognostic markers of overall survival (OS) in patients with lung adenocarcinoma (LUAD). This study aimed to identify an immune-related lncRNA signature for the prospective assessment of prognosis in these patients. Gene expression and clinical data of LUAD patients were downloaded from The Cancer Genome Atlas (TCGA). Immune-related lncRNAs were identified by a correlation analysis between lncRNAs and immune-related genes. In total, 497 samples were divided into a training set and a testing set. Univariate and multivariate Cox regression analyses identified an immune-related ten-lncRNA signature closely related to OS in LUAD patients in the training set. A risk score formula involving ten immune-related lncRNAs was developed to evaluate the prognostic value of the lncRNA signature in the training set. LUAD patients with a high risk score had poorer OS than those with a low risk score. Univariate and multivariate Cox regression analyses confirmed that the immune-related ten-lncRNA signature could be an independent prognostic factor in LUAD patients. The results were further confirmed in the testing set and the TCGA dataset. Furthermore, Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis may be helpful in formulating clinical strategies and understanding the underlying mechanisms. In order to explain the internal mechanism of the risk model in predicting the efficacy of immunotherapy, we analyzed the differentially expressed genes related to Epithelial-mesenchymal transition(EMT) between two risk groups. A quantitative real-time polymerase chain reaction(qRT-PCR) assay found that the model lncRNAs were significantly differentially expressed in LUAD cell lines. The AUC of ROC of 5 years in the independent validation dataset showed that this model had superior accuracy.Western blot analysis verified the change of EMT-related marker in protein level.The results of this study indicate that this signature has important clinical implications for improving predictive outcomes and guiding individualized treatment in lung cancer patients. These lncRNAs could be potential biomarkers affecting the prognosis of LUAD.