Construction of a Prognostic Signature in Ewing’s Sarcoma: Based On Metabolism-Related Genes

Abstract

Objective: By combining the expression profiles of metabolism-related genes (MRGS) with clinical information, the expression quantities of MRGS and the influence on development and prognosis were systematically analyzed, so as to provide a theoretical basis for the clinical study on the prognosis of Ewing's sarcoma.Methods: MRGs expression profiles of 64 patients with Ewing's sarcoma were obtained from the GEO dataset. Univariate Cox regression analysis was used to identify metabolization-related differentially expressed genes (DEGs) related with prognosis in Ewing's sarcoma patients. Then, multivariate Cox analysis was used to calculate novel prognostic markers based on metabolism-related DEGs. Finally, the new prognostic index was verified on the basis of the prognostic models.Results: Univariate Cox regression analysis identified 20 metabolization-related DEGs, 9 of which were significantly associated with Ewing's sarcoma patients' overall survival. Subsequently, we used nine metabolism-related DEGs to construct metabolism-related prognostic signature for patients with Ewing's sarcoma. Based on the 9 DEGs regression coefficient, we put forward the formula of each patient's risk score, and then divided the patients into high-risk group and low-risk group. The results indicated that the survival rate and survival time were higher in the low-risk group and lower in the high-risk group. Multivariate Cox analysis showed that risk score index was indeed an independent prognostic factor for Ewing's sarcoma. In addition, the area under the receiver operating characteristic (ROC) curve for overall survival was 0.985. And a nomogram model was established.Conclusion: The experimental results suggest that the 9 metabolism-related DEGs marker may be effective in predicting the prognosis of Ewing's sarcoma to some extent, helping to individualize treatment of patients at different risks.