Wang Xinyang, Zhao Xinshu, Zhao Jinhui, Yang Tongshu, Zhang Fengmin, Liu Liyan
Department of Microbiology, Harbin Medical University, Harbin, PR China; Wu Lien-Teh Institute, Harbin Medical University, Harbin, PR China.
The Affiliated Tumor Hospital of Harbin Medical University, Harbin, PR China.
Clin Chim Acta. 2021 Jul;518:59-69. doi: 10.1016/j.cca.2021.03.012. Epub 2021 Mar 18.
Epithelial ovarian cancer (EOC) is a common gynecological cancer with high mortality rates. The main objective of this study was to investigate the serum amino acid and organic acid profiles to distinguish key metabolites for screening EOC patients.
In total, 39 patients with EOC and 31 healthy controls were selected as the training set. Serum amino acid and organic acid profiles were determined using the targeted metabolomics approach. Metabolite profiles were processed via multivariate analysis to identify potential metabolites and construct a metabolic network. Finally, a test dataset derived from 29 patients and 28 healthy controls was constructed to validate the potential metabolites.
Distinct amino acid and organic acid profiles were obtained between EOC and healthy control groups. Methionine, glutamine, asparagine, glutamic acid and glycolic acid were identified as potential metabolites to distinguish EOC from control samples. The areas under the curve for methionine, glutamine, asparagine, glutamic acid and glycolic acid were 0.775, 0 778, 0.955, 0.874 and 0.897, respectively, in the validation study. Metabolic network analysis of the training set indicated key roles of alanine, aspartate and glutamate metabolism as well as D-glutamine and D-glutamate metabolism in the pathogenesis of EOC.
Amino acid and organic acid profiles may serve as potential screening tools for EOC. Data from this study provide useful information to bridge gaps in the understanding of the amino acid and organic acid alterations associated with epithelial ovarian cancer.
上皮性卵巢癌（EOC）是一种常见的妇科癌症，死亡率很高。本研究的主要目的是调查血清氨基酸和有机酸谱，以鉴别用于筛查EOC患者的关键代谢物。
总共选取39例EOC患者和31例健康对照作为训练集。采用靶向代谢组学方法测定血清氨基酸和有机酸谱。通过多变量分析处理代谢物谱，以识别潜在的代谢物并构建代谢网络。最后，构建一个来自29例患者和28例健康对照的测试数据集，以验证潜在的代谢物。
EOC组和健康对照组之间获得了不同的氨基酸和有机酸谱。蛋氨酸、谷氨酰胺、天冬酰胺、谷氨酸和乙醇酸被鉴定为区分EOC和对照样本的潜在代谢物。在验证研究中，蛋氨酸、谷氨酰胺、天冬酰胺、谷氨酸和乙醇酸的曲线下面积分别为0.775、0.778、0.955、0.874和0.897。训练集的代谢网络分析表明丙氨酸、天冬氨酸和谷氨酸代谢以及D-谷氨酰胺和D-谷氨酸代谢在EOC发病机制中起关键作用。
氨基酸和有机酸谱可能作为EOC的潜在筛查工具。本研究的数据为填补对与上皮性卵巢癌相关的氨基酸和有机酸改变的理解空白提供了有用信息。
