Regulatory Network Analysis to Reveal Important miRNAs and Genes in Non-Small Cell Lung Cancer

Objective Lung cancer has high incidence and mortality rate, and non-small cell lung cancer (NSCLC) takes up approximately 85% of lung cancer cases. This study is aimed to reveal miRNAs and genes involved in the mechanisms of NSCLC. Materials and Methods In this retrospective study, GSE21933 (21 NSCLC samples and 21 normal samples), GSE27262 (25 NSCLC samples and 25 normal samples), GSE43458 (40 NSCLC samples and 30 normal samples) and GSE74706 (18 NSCLC samples and 18 normal samples) were searched from gene expression omnibus (GEO) database. The differentially expressed genes (DEGs) were screened from the four microarray datasets using MetaDE package, and then conducted with functional annotation using DAVID tool. Afterwards, protein-protein interaction (PPI) network and module analyses were carried out using Cytoscape software. Based on miR2Disease and Mirwalk2 databases, microRNAs (miRNAs)-DEG pairs were selected. Finally, Cytoscape software was applied to construct miRNA-DEG regulatory network. Results Totally, 727 DEGs (382 up-regulated and 345 down-regulated) had the same expression trends in all of the four microarray datasets. In the PPI network, TP53 and FOS could interact with each other and they were among the top 10 nodes. Besides, five network modules were found. After construction of the miRNA-gene network, top 10 miRNAs (such as hsa-miR-16-5p, hsa-let-7b-5p, hsa-miR-15a-5p, hsa-miR-15b-5p, hsa-let-7a-5p and hsa-miR-34a- 5p) and genes (such as HMGA1, BTG2, SOD2 and TP53) were selected. Conclusion These miRNAs and genes might contribute to the pathogenesis of NSCLC.