A mRNA-miRNA-lncRNA regulatory network related to potential pathogenesis and prognostic markers of Non- small cell lung cancer

Non-small cell lung cancer (NSCLC) is one of the most malignant tumors with the fastest increasing incidence and mortality rate, but the etiology of NSCLC is still not clear. Most of lncRNAs have some structural similarities with mRNAs, suggesting that miRNAs negatively regulate the expression of lncRNAs to affect the occurrence and development of tumor. Therefore, system bioinformatics was used to explore the potential biomarkers and possible pathogenesis of NSCLC in this study. Firstly, all the clinical information and transcriptome data were downloaded from GEO and TCGA databases. R language was used to analyze the differentially expressed genes (DEGs) in NSCLC and normal lung tissues. Then, 50 overlapped DEGs were obtained via Venn database, including 10 down-regulated mRNAs and 40 down-regulated mRNAs. Secondly, the top 20 DEGs were selected for KEGG pathway and GO enrichment analysis. After screening 4 HUB genes related to the survival and prognosis of NSCLC patients, their prognosis models were established. Meanwhile, HUB genes related miRNAs and lncRNAs were screened. Finally, a mRNA-miRNA-lncRNA network related to the survival and prognosis of NSCLC patients was established, including 4 up-regulated mRNAs, 3 up-regulated miRNAs, 10 down-regulated miRNAs, 6 up-regulated lncRNAs and 19 down-regulated lncRNAs. Subject terms Non-small cell lung cancer, mRNA-miRNA-lncRNA, pathogenesis, prognostic biomarkers.