Identification of key genes and pathways in Ewing's sarcoma using bioinformatics analysis

Purpose: Ewing's sarcoma (ES) is a highly aggressive malignant bone and soft tissue neoplasm. The purpose of our study was to identify candidate biomarkers of ES and uncover their potential molecular mechanisms. Methods: The gene expression profiles of GSE45544 and GSE73I66 were downloaded from Gene Expression Omnibus (GEO) database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed based on the Database for Annotation, Visualization and Integrated Discovery (DAVID) database, protein-protein interaction (PPI) network was constructed, and hub genes of the differentially expressed genes (DEGs) were identified by Cytoscape software. Results: 586 DEGs in total were identified in ES, and the top up-regulated genes were extremely potent as ES biomarkers. GO function analysis data showed that these DEGs were significantly enriched in DNA translation, nucleus, and protein binding. KEGG pathway analysis revealed that DEGs were enriched in the pathways involved in cancer, HTLV-I infection, viral carcinogenesis, ribosome, and cell cycle. PPI network showed that most of the hub genes were for ribosomal proteins, associated in some way with the biological process of ES. Conclusions: In conclusion, we identified the DEGs and hub genes which could promote our comprehension of detailed mechanisms involved in the development of ES.