Department of Gastrointestinal Surgery, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, 518020 Guangdong, China.
Department of General Surgery, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, 518020 Guangdong, China.
Dis Markers. 2022 Apr 26;2022:1758113. doi: 10.1155/2022/1758113. eCollection 2022.
Colorectal cancer (CRC) is one of the most commonly diagnosed cancers with high mortality rate due to its poor diagnosis in the early stage. Here, we report a urinary metabolomic study on a cohort of CRC patients ( =67) and healthy controls ( =21) using ultraperformance liquid chromatography triple quadrupole mass spectrometry. Pathway analysis showed that a series of pathways that belong to amino acid metabolism, carbohydrate metabolism, and lipid metabolism were dysregulated, for instance the glycine, serine and threonine metabolism, alanine, aspartate and glutamate metabolism, glyoxylate and dicarboxylate metabolism, glycolysis, and TCA cycle. A total of 48 differential metabolites were identified in CRC compared to controls. A panel of 12 biomarkers composed of chenodeoxycholic acid, vanillic acid, adenosine monophosphate, glycolic acid, histidine, azelaic acid, hydroxypropionic acid, glycine, 3,4-dihydroxymandelic acid, 4-hydroxybenzoic acid, oxoglutaric acid, and homocitrulline were identified by Random Forest (RF), Support Vector Machine (SVM), and Boruta analysis classification model and validated by Gradient Boosting (GB), Logistic Regression (LR), and Random Forest diagnostic model, which were able to discriminate CRC subjects from healthy controls. These urinary metabolic biomarkers provided a novel and promising molecular approach for the early diagnosis of CRC.
结直肠癌（CRC）是最常见的癌症之一，由于其早期诊断不佳，死亡率很高。在这里，我们报告了一项使用超高效液相色谱三重四极杆质谱对 CRC 患者（ =67）和健康对照（ =21）进行的尿液代谢组学研究。途径分析显示，一系列属于氨基酸代谢、碳水化合物代谢和脂质代谢的途径发生了失调，例如甘氨酸、丝氨酸和苏氨酸代谢、丙氨酸、天冬氨酸和谷氨酸代谢、乙醛酸和二羧酸代谢、糖酵解和 TCA 循环。与对照组相比，CRC 中总共鉴定出 48 种差异代谢物。通过随机森林（RF）、支持向量机（SVM）和 Boruta 分析分类模型，确定了由鹅去氧胆酸、香草酸、单磷酸腺苷、乙二醇酸、组氨酸、壬二酸、羟基丙酸、甘氨酸、3,4-二羟苯乙酸、4-羟基苯甲酸、草酰乙酸和同型瓜氨酸组成的 12 个生物标志物面板，通过梯度提升（GB）、逻辑回归（LR）和随机森林诊断模型进行验证，这些模型能够区分 CRC 患者和健康对照者。这些尿液代谢生物标志物为 CRC 的早期诊断提供了一种新颖且有前途的分子方法。
