Lung cancer is the world's highest morbidity and mortality of malignant tumors, with lung adenocarcinoma (LUAD) as a major subtype. The competitive endogenous RNA (ceRNA) regulative network provides opportunities to understand the relationships among different molecules, as well as the regulative mechanisms among them in order to investigate the whole transcriptome landscape in cancer pathology. We designed this work to explore the role of a key oncogene, MYC, in the pathogenesis of LUAD, and this study aims to identify important long noncoding RNA (lncRNA)-microRNA (miRNA)- transcription factor (TF) interactions in non-small cell lung cancer (NSCLC) using a bioinformatics analysis. The Cancer Genome Atlas (TCGA) database, containing mRNA expression data of NSCLC, was used to determine the deferentially expressed genes (DEGs), and the ceRNA network was composed of WT1-AS, miR-206, and nicotinamide phosphoribosyltransferase (NAMPT) bashing on the MYC expression level. The Kaplan-Meier univariate survival analysis showed that these components may be closely related prognostic biomarkers and will become new ideas for NSCLC treatment. Moreover, the high expression of WT1-AS and NAMPT and low expression of miR-206 were associated with a shortened survival in NSCLC patients, which provided a survival advantage. In summary, the current study constructing a ceRNA-based WT1-AS/miR-206/NAMPT axis might be a novel important prognostic factor associated with the diagnosis and prognosis of LUAD.
Keywords: LUAD; WT1-AS/miR-206/NAMPT axis; ceRNA network; prognosis.