Metabolic abnormalities have recently been widely studied in various cancer types. This study aims to explore the expression profiles of metabolism-related genes (MRGs) in endometrial cancer (EC). We analyzed the expression of MRGs using The Cancer Genome Atlas (TCGA) data to screen differentially expressed MRGs (DE-MRGs) significantly correlated with EC patient prognosis. Functional pathway enrichment analysis of the DE-MRGs was performed. LASSO and Cox regression analyses were performed to select MRGs closely related to EC patient outcomes. A prognostic signature was developed, and the efficacy was validated in part of and the entire TCGA EC cohort. Moreover, we developed a comprehensive nomogram including the risk model and clinical features to predict EC patients’ survival probability. Forty-seven DE-MRGs were significantly correlated with EC patient prognosis. Functional enrichment analysis showed that these MRGs were highly enriched in amino acid, glycolysis, and glycerophospholipid metabolism. Nine MRGs were found to be closely related to EC patient outcomes: CYP4F3, CEL, GPAT3, LYPLA2, HNMT, PHGDH, CKM, UCK2 and ACACB. Based on these nine DE-MRGs, we developed a prognostic signature, and its efficacy in part of and the entire TCGA EC cohort was validated. The nine-MRG signature was independent of other clinical features, and could effectively distinguish high- and low-risk EC patients and predict patient OS. The nomogram showed excellent consistency between the predictions and actual survival observations. The MRG prognostic model and the comprehensive nomogram could guide precise outcome prediction and rational therapy selection in clinical practice.

中文翻译：

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子宫内膜癌患者代谢相关基因表达预后模型的鉴定。

近年来，已在各种癌症类型中广泛研究了代谢异常。这项研究旨在探讨子宫内膜癌（EC）中代谢相关基因（MRG）的表达特征。我们使用癌症基因组图谱（TCGA）数据分析了MRGs的表达，以筛选与EC患者预后显着相关的差异表达的MRGs（DE-MRGs）。进行了DE-MRG的功能途径富集分析。进行LASSO和Cox回归分析以选择与EC患者预后密切相关的MRG。开发了预后标志，并在部分TCGA EC队列和整个TCGA EC队列中验证了疗效。此外，我们开发了包括风险模型和临床特征在内的综合列线图，以预测EC患者的生存概率。47例DE-MRG与EC患者的预后显着相关。功能富集分析表明，这些MRGs在氨基酸，糖酵解和甘油磷脂代谢中高度富集。发现9个MRG与EC患者的预后密切相关：CYP4F3，CEL，GPAT3，LYPLA2，HNMT，PHGDH，CKM，UCK2和ACACB。基于这九种DE-MRG，我们开发了一种预后标志，并验证了其在部分TCGA EC队列和整个TCGA EC队列中的功效。九个MRG信号与其他临床特征无关，可以有效地区分高风险和低风险的EC患者并预测患者的OS。列线图显示了预测和实际生存观察之间极好的一致性。