Prognostic Values and Prospective Pathway Signaling of miR-25 in Non-Small Cell Lung Cancer: A Bioinformatics Analysis Based on Gene Expression Omnibus

Abstract

MicroRNAs (MiRNAs) are believed to significantly influence the occurrence and development of Non-small cell lung cancer (NSCLC). This study aims to clarify the action of hsa-miR-25-5p (miR-25) in NSCLC. Public datasets related to miR-25 expression from Gene Expression Omnibus (GEO) were retrieved. MiR-25 expression in the retrieved datasets were calculated using a fix-effects model (REM). Statistical analysis was performed using Stata 15.0, with standard mean difference (SMD) as the effect size. Downloaded from GEO database, two mRNA datasets, GSE18842 and GSE101929, was used to obtain differentially expressed genes (DEGs) using R 4.2.1 software. TargetScan and miRwalk 3.0 were used to predict hsa-miR-25-5p target genes. Subsequently, Gene Ontology (GO) enrichment analysis were conducted. We constructed protein–protein interaction (PPI) network using String and Cytoscape. The prognostic values of top 10 HUB genes were analyzed. Four datasets related to miR-25 expression were retrieved from GEO, including GSE27705, GSE29248, GSE63805 and GSE102286. The results of REM suggested that miR-25 expression was obviously increased in NSCLC versus adjacent noncancerous lung tissues (SMD = 0.06, 95% CI: 0.36–0.84, P <0.001). 244 DEGs associated with both NSCLC and hsa-miR-25-5p were identified. Numerous DEGs were significantly enriched in the locus of cell membranes, playing the roles of protein binding, and biological regulation. Based on PPI analysis, among the top 10 HUB genes, the high expressions of eight genes significantly reduced overall survival in NSCLC (CCNB1, RAD51AP1, MELK, NCAPH, MCM10, NUSAP, PRC1, BRCA). miR-25 displays an critical role in the biological process by binding target genes, influencing prognosis in patients with NSCLC.