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Identification of Prognostic Biomarkers of Ewing Sarcoma using Bioinformatics Analysis and Experiments


 Background. Ewing sarcoma (EWS) is the second most familiar bone or soft-tissue sarcoma, making the identification of EWS biomarkers critically important. This study aimed to explore and validate potential prognostic biomarkers in EWS by bioinformatics analysis and experiments. Methods The microarray dataset GSE119546 was downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between EWS cells treated with and without Cyclin-dependent kinase 9 (CDK9) inhibitors were analyzed using R package limma. Next, we performed gene enrichment analysis and constructed a protein-protein interaction (PPI) network. The expression level of the top18 hub genes and the overall survival (OS) in patients with sarcoma were validated using the Oncomine and Gene Expression Profiling Interactive Analysis 2 (GEPIA2) databases. Furthermore, the mRNA expression of Bystin Like (BYSL), Nucleolar Protein 11 (NOL11), and P21-activated protein kinase-interacting protein 1 (PAK1IP1) was detected by RT-PCR in the EWS cell line (A-673), and the protein expression in EWS tissue was verified by immunohistochemistry (IHC).Results Our study identified 343 DEGs, which were associated with various cancer-related functions and pathways. A total of three DEGs, including BYSL, NOL11, and PAK1IP1, were identified as hub genes with prognostic values using GEPAI2 and Oncomine. Finally, RT-PCR results showed the mRNA expression level of BYSL, NOL11, and PAK1IP1 in A-673 cells was higher than that in human mesenchymal stem cells. IHC staining revealed a positive expression ratio of NOL11, BYSL, and PAK1IP1 was 63.6% (14/22), 31.9% (7/22), and 0% (0/22), respectively. Cox regression analysis confirmed NOL11 was a significant prognostic factor for OS. Conclusions. Our findings revealed that NOL11 may be a potential biomarker for EWS prognosis and treatment.