Identification of key genes and construction of microRNA-mRNA regulatory networks in non-small cell lung cancer

Abstract

Non-small cell lung cancer (NSCLC) is the most common type of lung tumor. Deregulation of microRNA may be involved in the occurrence of NSCLC and we aimed to find the potential prognostic biomarkers for NSCLC. The microRNA microarray expression profiles were downloaded from GEO dataset and then generated by applying robust multi-array average (RMA). The normalized data was analyzed with a Bioconductor package linear model for microarray data and an independent dataset was used to inspect the results. Then, the differentially expressed genes were identified using the limma package. Besides, in order to investigate the function of the differentially expressed microRNA in NSCLC, the GO and KEGG functional enrichment analysis were applied, and the GSEA analysis was performed for mining the therapeutic candidates. A total of 160 differentially expressed microRNAs were identified, among which 37 microRNAs showed significant expression changes (up-regulated and down-regulated) with the same method in the validation dataset GSE74190. Multiple cancer-related pathways, such as AMPK signaling pathway, AMPK signaling pathway, non-small cell lung cancer signaling pathway, were determined by performing the functional enrichment analysis. Besides, the results of GSEA analysis showed that the CCND1 was mostly enriched in lung cancer group. In conclusion, a set of differentially expressed microRNAs in NSCLC was identified and the CCND1 gene was determined as the potential prognostic biomarkers for NSCLC, providing useful information for discovery of future therapeutic targets and candidates in the clinical management of NSCLC.