Pietkiewicz Dagmara, Zaborowski Mikołaj Piotr, Plewa Szymon, Potograbski Michał, Miedziarek Cezary, Kluz Tomasz, Nowak-Markwitz Ewa, Matysiak Jan
Doctoral School, Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 3 Rokietnicka Street, 60-806 Poznan, Poland.
Gynecologic Oncology Department, Poznan University of Medical Sciences, 33 Polna Street, 60-535 Poznan, Poland.
Metabolites. 2025 Jun 20;15(7):422. doi: 10.3390/metabo15070422.
Endometrial cancer is among the most prevalent gynecological malignancies, with increasing mortality primarily due to initially advanced disease with lymph node metastasis or tumor recurrence. Current risk stratification models show limited accuracy, highlighting the need for more accurate biomarkers. This study aimed to identify metabolic compounds that can serve as predictors of recurrence risk and lymph node status in endometrial cancer.
Targeted metabolomic profiling of preoperative serum samples from 123 patients with endometrial cancer, stratified into high- or low-risk and lymph node-positive or -negative groups, was conducted using the AbsoluteIDQ p180 Kit and high-performance liquid chromatography-mass spectrometry.
Analysis revealed significant differences in metabolites related to lipid and amino acid metabolism between groups. High-risk and lymph node-positive patients presented significantly lower concentrations of phosphatidylcholines, lysophosphatidylcholines, medium-chain acylcarnitines, and specific amino acids such as alanine, histidine, and tryptophan compared to low-risk and lymph node-negative patients. Receiver operating characteristic curve analyses highlighted the diagnostic potential of these metabolites, particularly alanine and taurine, in distinguishing patient groups.
The findings indicate complex metabolic reprogramming associated with aggressive endometrial cancer phenotypes, involving enhanced lipid utilization and amino acid metabolism alterations, potentially supporting tumor proliferation and metastatic progression. Thus, targeted metabolomic serum profiling might be a powerful tool for improving risk assessment, enabling more personalized therapeutic approaches and management strategies in endometrial cancer.
子宫内膜癌是最常见的妇科恶性肿瘤之一，死亡率上升主要归因于疾病初发时即为晚期且伴有淋巴结转移或肿瘤复发。目前的风险分层模型准确性有限，凸显了对更准确生物标志物的需求。本研究旨在识别可作为子宫内膜癌复发风险和淋巴结状态预测指标的代谢化合物。
使用AbsoluteIDQ p180试剂盒和高效液相色谱 - 质谱联用技术，对123例子宫内膜癌患者术前血清样本进行靶向代谢组学分析，这些患者被分为高风险或低风险组以及淋巴结阳性或阴性组。
分析显示，各组之间与脂质和氨基酸代谢相关的代谢物存在显著差异。与低风险和淋巴结阴性患者相比，高风险和淋巴结阳性患者的磷脂酰胆碱、溶血磷脂酰胆碱、中链酰基肉碱以及特定氨基酸（如丙氨酸、组氨酸和色氨酸）浓度显著降低。受试者工作特征曲线分析突出了这些代谢物，尤其是丙氨酸和牛磺酸，在区分患者组方面的诊断潜力。
研究结果表明，侵袭性子宫内膜癌表型与复杂的代谢重编程有关，涉及脂质利用增强和氨基酸代谢改变，这可能支持肿瘤增殖和转移进展。因此，靶向代谢组学血清分析可能是改善风险评估的有力工具，能够在子宫内膜癌中实现更个性化的治疗方法和管理策略。
