Bioinformatics analysis of Ewing's sarcoma: Seeking key candidate genes and pathways

• Published in: Oncology letters Vol. 18; no. 6; pp. 6008 - 6016
• Main Authors: Zhang, Jinming, Zhang, Yao, Li, Ze, Wu, Hongzeng, Xun, Jianjun, Feng, Helin
• Format: Journal Article
• Language: English
• Published: Athens D.A. Spandidos 01.12.2019; Spandidos Publications; Spandidos Publications UK Ltd
• Subjects: Annotations; Bioinformatics; Biological markers; Cancer; Cancer therapies; Carcinogenesis; Cell adhesion & migration; Cell growth; Cell membranes; Chromatin; Computational biology; Datasets; Deoxyribonucleic acid; differentially expressed genes; DNA; Ewing's sarcoma; Ewings sarcoma; Gene expression; Genes; Genomes; Interdisciplinary subjects; Medical prognosis; Oncology; Ontology; pathways; Protein-protein interactions; RNA; RNA polymerase; Sarcoma; Studies; Survival analysis; Transcription (Genetics); Tumorigenesis; Tumors; Vincristine; Youth
• ISSN: 1792-1074; 1792-1082; 1792-1082
• DOI: 10.3892/ol.2019.10936

Ewing's sarcoma (ES) is the second most common bone tumor among children and adolescents worldwide. However, the genes and signaling pathways involved in ES tumorigenesis and progression remain unclear. The present study used two gene-expression profile datasets (GSE17674 and GSE31215) to elucidate key potential candidate genes and pathways in ES. Differentially expressed genes (DEGs) were identified and a functional enrichment analysis was performed. A protein-protein interaction (PPI) network was constructed, and the most significant module in the PPI network was selected from the Search Tool for the Retrieval of Interacting Genes/Proteins database. A total of 278 genes were identified by comparing the tumor samples with non-cancerous samples; these included 272 upregulated and 6 downregulated genes. The pathway analysis demonstrated significant enrichment in the positive regulation of transcription in the DEGs coding for RNA polymerase II promoter, plasma membrane and chromatin binding pathways in cancer in general. There were 269 nodes and 292 edges in the PPI network. Finally, MYC, IGF1, OAS1, EZH2 and ISG15 were identified as the hub genes according to the degree levels. The survival analysis revealed that EZH2 is associated with a poor prognosis in patients with ES. In conclusion, the DEGs, associated pathways and hub genes identified in the present study help elucidate the underlying molecular mechanisms of ES carcinogenesis and progression, and provide potential molecular targets and biomarkers for ES.