■角化是铜诱导的细胞死亡。铜代谢相关基因(CMRGs)被证明可用于评估肿瘤的预后。在研究中,检测CMRG对尤文氏肉瘤(ES)中TME细胞浸润的影响。
■GEO和ICGC数据库提供了mRNA表达谱和临床特征以供下载。在GSE17674数据集中,通过单变量回归分析鉴定了22个预后相关的铜代谢相关基因(PR-CMRGs)。随后,为了比较这些PR-CMRGs高表达和低表达组的生存率,实施Kaplan-Meier分析。此外,检查了它们之间的相关性。该研究采用功能富集分析来调查可能的潜在途径,而GSVA用于评估ES(表达集)中的富集途径。通过无监督聚类算法,样本被分为两个集群,揭示了存活率和免疫浸润水平的显著差异。
■使用Lasso和逐步回归方法,五个基因(TFRC,SORD,选择SLC11A2、FKBP4和AANAT)作为风险特征。根据Kaplan-Meier生存分析,高危组的生存率明显低于低危组(p=6.013e-09).受试者工作特征(ROC)曲线的曲线下面积(AUC)值分别为1年、3年和5年的0.876、0.883和0.979,分别。在其他数据集中进一步验证了风险模型,即GSE63155、GSE63156和ICGC数据集。为了帮助预测结果,建立了纳入风险水平和临床特征的列线图.此列线图的性能通过校准曲线得到有效验证。此外,该研究评估了不同风险组之间免疫浸润的差异,以及高表达和低表达组。重要的是,确定了几种显示敏感性的药物,为ES提供潜在的治疗选择。
■上述发现强烈表明,CMRGs在预测ES的预后和免疫状态中起着至关重要的作用。
UNASSIGNED: Cuproptosis is copper-induced cell death. Copper metabolism related genes (CMRGs) were demonstrated that used to assess the prognosis out of tumors. In the study, CMRGs were tested for their effect on TME cell infiltration in Ewing\'s sarcoma (ES).
UNASSIGNED: The GEO and ICGC databases provided the mRNA expression profiles and clinical features for downloading. In the GSE17674 dataset, 22prognostic-related copper metabolism related genes (PR-CMRGs) was identified by using univariate regression analysis. Subsequently, in order to compare the survival rates of groups with high and low expression of these PR-CMRGs,Kaplan-Meier analysis was implemented. Additionally, correlations among them were examined. The study employed functional enrichment analysis to investigate probable underlying pathways, while GSVA was applied to evaluate enriched pathways in the ES (Expression Set). Through an unsupervised clustering algorithm, samples were classified into two clusters, revealing significant differences in survival rates and levels of immune infiltration.
UNASSIGNED: Using Lasso and step regression methods, five genes (TFRC, SORD, SLC11A2, FKBP4, and AANAT) were selected as risk signatures. According to the Kaplan-Meier survival analysis, the high-risk group had considerably lower survival rates than the low-risk group(p=6.013e-09). The area under the curve (AUC) values for the receiver operating characteristic (ROC) curve were 0.876, 0.883, and 0.979 for 1, 3, and 5 years, respectively. The risk model was further validated in additional datasets, namely GSE63155, GSE63156, and the ICGC datasets. To aid in outcome prediction, a nomogram was developed that incorporated risk levels and clinical features. This nomogram\'s performance was effectively validated through calibration curves.Additionally, the study evaluated the variations in immune infiltration across different risk groups, as well as high-expression and low-expression groups. Importantly, several drugs were identified that displayed sensitivity, offering potential therapeutic options for ES.
UNASSIGNED: The findings above strongly indicate that CMRGs play crucial roles in predicting prognosis and immune status in ES.