Department of Gynecology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, Jiangsu Province, China.
BMC Cancer. 2020 Sep 7;20(1):864. doi: 10.1186/s12885-020-07345-8.
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.
代谢异常最近在多种癌症类型中得到了广泛研究。本研究旨在探索子宫内膜癌（EC）中与代谢相关的基因（MRGs）的表达谱。
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 患者预后显著相关的差异表达 MRGs（DE-MRGs）。对 DE-MRGs 进行功能途径富集分析。使用 LASSO 和 Cox 回归分析选择与 EC 患者结局密切相关的 MRGs。构建预后标志物，并在 TCGA 部分和整个 EC 队列中进行验证。此外，我们开发了一个包含风险模型和临床特征的综合列线图，以预测 EC 患者的生存概率。
47 个 DE-MRGs 与 EC 患者的预后显著相关。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 MRGs 与 EC 患者的结局密切相关：CYP4F3、CEL、GPAT3、LYPLA2、HNMT、PHGDH、CKM、UCK2 和 ACACB。基于这 9 个 DE-MRGs，我们构建了一个预后标志物，并在 TCGA 部分和整个 EC 队列中验证了其疗效。该 9-MRG 标志物与其他临床特征独立，能够有效区分高风险和低风险的 EC 患者，并预测患者的 OS。列线图显示预测与实际生存观察之间具有极好的一致性。
MRG 预后模型和综合列线图可以指导临床实践中精确的预后预测和合理的治疗选择。
