Down-regulation of microRNA-144-3p and its clinical value in non-small cell lung cancer: A comprehensive analysis based on microarray, miRNA-sequencing, and quantitative real-time PCR data

Abstract

Background: Previous studies have shown that miR-144-3p might be a potential biomarker in non-small cell lung cancer (NSCLC). Nevertheless, the comprehensive mechanism behind the effects of miR-144-3p on the origin, differentiation, and apoptosis of NSCLC, as well as the relationship between miR-144-3p and clinical parameters, has been rarely reported. Methods: We investigated the correlations between miR-144-3p expression and clinical characteristics through data collected from Gene Expression Omnibus (GEO) microarrays, the relevant literature, The Cancer Genome Atlas (TCGA), and real-time quantitative real-time PCR (RT-qPCR) analyses to determine the clinical role of miR-144-3p in NSCLC. Furthermore, we investigated the biological function of miR-144-3p by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Protein-protein interaction (PPI) network was created to identify the hub genes. Results: From the comprehensive meta-analysis, the combined SMD of miR-144-3p was - 0.95 with 95% CI of (- 1.37, - 0.52), indicating that less miR-144-3p was expressed in the NSCLC tissue than in the normal tissue. MiR-144-3p expression was significantly correlated with stage, lymph node metastasis and vascular invasion (all P < 0.05). As for the bioinformatics analyses, a total of 37 genes were chosen as the potential targets of miR-144-3p in NSCLC. These promising target genes were highly enriched in various key pathways such as the protein digestion and absorption and the thyroid hormone signaling pathways. Additionally, PPI revealed five genes - C12orf5, CEP55, E2F8, STIL, and TOP2A - as hub genes with the threshold value of 6. Conclusions: The current study validated that miR-144-3p was lowly expressed in NSCLC. More importantly, miR-144-3p might function as a latent tumor biomarker in the prognosis prediction for NSCLC. The results of bioinformatics analyses may present a new method for investigating the pathogenesis of NSCLC.