Regulatory Network Analysis to Reveal Important miRNAs and Genes in NonSmall Cell Lung Cancer

Objective Lung cancer has high incidence and mortality rate, and nonsmall 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, proteinprotein 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 miRNADEG regulatory network. Results Totally, 727 DEGs (382 upregulated and 345 downregulated) 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 miRNAgene network, top 10 miRNAs (such as hsamiR165p, hsalet7b5p, hsamiR15a5p, hsamiR15b5p, hsalet7a5p and hsamiR34a 5p) and genes (such as HMGA1, BTG2, SOD2 and TP53) were selected. ConclusionThese miRNAs and genes might contribute to the pathogenesis of NSCLC.