Ewing sarcoma (ES) is a common primary malignancy in children and adolescents. Progression of treatment methods hasn't contributed a lot to the imrovement of prognosis. To identify potential prognostic biomarkers, a meta-analysis pipeline of multi-gene expression datasets for ES from the Gene Expression Omnibus (GEO) was performed. Three datasets were screened and differential expression genes (DEGs) in ES samples compared with normal tissues were identified through limma package and subjected to network analysis. As a result, 1,470 DEGs were obtained which were mainly involved in biological processes associated with immune response and transcription regulation. Network analysis obtained 22 core genes with high network degree and fold change. Kaplan-Meier analysis based on ES datasets from The Cancer Genome Atlas identified five genes, including glycogen phosphorylase, muscle-associated, myocyte-specific enhancer factor 2C, tripartite motif containing 63, budding uninhibited by benzimidazoses1 and Ras GTPase-activating protein 1, whose altered expression profiles are significantly associated with survival. Changes of their expression values were further confirmed through RT-qPCR in ES cell and normal cell lines. Those genes may be considered as potential prognostic biomarkers of ES and should be helpful for its early diagnosis and treatment.