Abstract:AIM: To identify metastatic genes and miRNAs and to investigate the metastatic mechanism of uveal melanoma (UVM). METHODS: GSE27831, GSE39717, and GSE73652 gene expression profiles were downloaded from the Gene Expression Omnibus (GEO) database, and the limma R package was used to identify differentially expressed genes (DEGs). Gene Ontology (GO) term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed using the DAVID online tool. A comprehensive list of interacting DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes (STRING) database and Cytoscape software. The Cytoscape MCODE plug-in was used to identify clustered sub-networks and modules of hub genes from the protein-protein interaction network. GEPIA online software was used for survival analysis of UVM patients (n=80) from the The Cancer Genome Atlas (TCGA) cohort. OncomiR online software was used to find that the miRNAs were associated with UVM prognosis from the TCGA cohort. TargetScan Human 7.2 software was then used to identify the miRNAs targeting the genes. RESULTS: There were 1600 up-regulated genes and 1399 down-regulated genes. The up-regulated genes were mainly involved in protein translation in the cytosol, whereas the down-regulated genes were correlated with extracellular matrix organization and cell adhesion in the extracellular space. Among the 2999 DEGs, five genes, Znf391, Mrps11, Htra3, Sulf2, and Smarcd3 were potential predictors of UVM prognosis. Otherwise, three miRNAs, hsa-miR-509-3-5p, hsa-miR-513a-5p, and hsa-miR-1269a were associated with UVM prognosis. CONCLUSION: After analyzing the metastasis-related enriched terms and signaling pathways, the up-regulated DEGs are mainly involved in protein synthesis and cell proliferation by ribosome and mitogen-activated protein kinase (MAPK) pathways. However, the down-regulated DEGs are mainly involved in processes that reduced cell-cell adhesion and promoted cell migration in the extracellular matrix through PI3K-Akt signaling pathway, focal adhesion, and extracellular matrix-receptor interactions. Bioinformatics and interaction analysis may provide new insights on the events leading up to the development and progression of UVM.
