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 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. Besides, We validate the model using ICGC datasets. Finally, the new prognostic index was verified on the basis of the prognostic models.

Results

Multivariate Cox regression analysis identified 74 metabolization-related DEGs, 25 of which were associated with Ewing's sarcoma patients' overall survival. Subsequently, we used 25 DEGs to construct metabolism-related prognostic signature for patients with Ewing's sarcoma. Based on the 18 DEGs regression coefficient, we propose 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 an independent prognostic factor for Ewing's sarcoma.

Conclusion

The experimental results suggest that the 18 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.

中文翻译：

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尤文肉瘤预后特征的构建：基于代谢相关基因

客观的

结合代谢相关基因（MRGS）的表达谱与临床信息，系统分析MRGS的表达量及其对发展和预后的影响，为尤文肉瘤预后的临床研究提供理论依据。 .

方法

从 GEO 数据集获得 64 例尤文肉瘤患者的 MRGs 表达谱。单变量Cox回归分析用于鉴定与尤文氏肉瘤患者预后相关的代谢相关差异表达基因（DEG）。然后，多变量 Cox 分析用于计算基于代谢相关 DEG 的新预后标志物。此外，我们使用 ICGC 数据集验证模型。最后，在预后模型的基础上对新的预后指标进行验证。

结果

多变量 Cox 回归分析确定了 74 个与代谢相关的 DEG，其中 25 个与尤文肉瘤患者的总生存期相关。随后，我们使用 25 DEG 构建了尤文肉瘤患者的代谢相关预后特征。基于18DEGs回归系数，我们提出了每个患者的风险评分公式，然后将患者分为高危组和低危组。结果表明，低危组的存活率和存活时间较高，高危组的存活率较低。多变量Cox分析显示风险评分指数是尤文肉瘤的独立预后因素。

结论

实验结果表明，18个代谢相关的DEGs标志物可能在一定程度上有效预测尤文肉瘤的预后，有助于不同风险患者的个体化治疗。