Identification of crucial miRNAs and genes in esophageal squamous cell carcinoma by miRNA-mRNA integrated analysis - Zhong, Xiaowu (Medicine (Baltimore), 2019)
Esophageal squamous cell carcinoma (ESCC) is a malignancy that severely threatens human health and carries a high incidence rate and a low 5-year survival rate. MicroRNAs (miRNAs) are commonly accepted as a key regulatory function in human cancer, but the potential regulatory mechanisms of miRNA-mRNA related to ESCC remain poorly understood. The GSE55857, GSE43732, and GSE6188 miRNA microarray datasets and the gene expression microarray datasets GSE70409, GSE29001, and GSE20347 were downloaded from Gene Expression Omnibus databases. The differentially expressed miRNAs (DEMs) and differentially expressed genes (DEGs) were obtained using GEO2R. Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for DEGs were performed by Database for Annotation, Visualization and Integrated Discovery (DAVID). A protein–protein interaction (PPI) network and functional modules were established using the STRING database and were visualized by Cytoscape. Kaplan-Meier analysis was constructed based on The Cancer Genome Atlas (TCGA) database. In total, 26 DEMs and 280 DEGs that consisted of 96 upregulated and 184 downregulated genes were screened out. A functional enrichment analysis showed that the DEGs were mainly enriched in the ECM-receptor interaction and cytochrome P450 metabolic pathways. In addition, MMP9, PCNA, TOP2A, MMP1, AURKA, MCM2, IVL, CYP2E1, SPRR3, FOS, FLG, TGM1, and CYP2C9 were considered to be hub genes owing to high degrees in the PPI network. MiR-183-5p was with the highest connectivity target genes in hub genes. FOS was predicted to be a common target gene of the significant DEMs. Hsa-miR-9-3p, hsa-miR-34c-3p and FOS were related to patient prognosis and higher expression of the transcripts were associated with a poor OS in patients with ESCC. Our study revealed the miRNA-mediated hub genes regulatory network as a model for predicting the molecular mechanism of ESCC. This may provide novel insights for unraveling the pathogenesis of ESCC.