Abstract：
BACKGROUND: Early identification and therapy can significantly improve the outcome for gastric cancer. However, there is still no perfect biomarker available for the detection of early gastric cancer. This study aimed to investigate the alterations in the plasma metabolites of early gastric cancer using metabolomics and lipidomics based on high-performance liquid chromatography-mass spectrometry (HPLC-MS), which detected potential biomarkers that could be used for clinical diagnosis.
METHODS: To investigate the changes in metabolomics and lipidomics, a total of 30 plasma samples were collected, consisting of 15 patients with early gastric cancer and 15 healthy controls. Extensive HPLC-MS-based untargeted metabolomic and lipidomic investigations were conducted. Differential metabolites and metabolic pathways were uncovered through the utilization of statistical analysis and bioinformatics analysis. Candidate biomarker screening was performed using support vector machine-based multivariate receiver operating characteristic analysis.
RESULTS: A disturbance was observed in a combined total of 19 metabolites and 67 lipids of the early gastric cancer patients. The analysis of KEGG pathways showed that the early gastric cancer patients experienced disruptions in the arginine biosynthesis pathway, the pathway for alanine, aspartate, and glutamate metabolism, as well as the pathway for glyoxylate and dicarboxylate metabolism. Plasma metabolomics and lipidomics have identified multiple biomarker panels that can effectively differentiate early gastric cancer patients from healthy controls, exhibiting an area under the curve exceeding 0.9.
CONCLUSIONS: These metabolites and lipids could potentially serve as biomarkers for the screening of early gastric cancer, thereby optimizing the strategy for the detection of early gastric cancer. The disrupted pathways implicated in early gastric cancer provide new clues for additional understanding of gastric cancer\'s pathogenesis. Nonetheless, large-scale clinical data are required to prove our findings.
METHODS: To investigate the changes in metabolomics and lipidomics, a total of 30 plasma samples were collected, consisting of 15 patients with early gastric cancer and 15 healthy controls. Extensive HPLC-MS-based untargeted metabolomic and lipidomic investigations were conducted. Differential metabolites and metabolic pathways were uncovered through the utilization of statistical analysis and bioinformatics analysis. Candidate biomarker screening was performed using support vector machine-based multivariate receiver operating characteristic analysis.
RESULTS: A disturbance was observed in a combined total of 19 metabolites and 67 lipids of the early gastric cancer patients. The analysis of KEGG pathways showed that the early gastric cancer patients experienced disruptions in the arginine biosynthesis pathway, the pathway for alanine, aspartate, and glutamate metabolism, as well as the pathway for glyoxylate and dicarboxylate metabolism. Plasma metabolomics and lipidomics have identified multiple biomarker panels that can effectively differentiate early gastric cancer patients from healthy controls, exhibiting an area under the curve exceeding 0.9.
CONCLUSIONS: These metabolites and lipids could potentially serve as biomarkers for the screening of early gastric cancer, thereby optimizing the strategy for the detection of early gastric cancer. The disrupted pathways implicated in early gastric cancer provide new clues for additional understanding of gastric cancer\'s pathogenesis. Nonetheless, large-scale clinical data are required to prove our findings.
摘要：
背景：早期识别和治疗可以显著改善胃癌的预后。然而,目前还没有完美的生物标志物可用于早期胃癌的检测。本研究采用基于高效液相色谱-质谱(HPLC-MS)的代谢组学和脂质组学研究早期胃癌血浆代谢产物的改变,检测到可用于临床诊断的潜在生物标志物。
方法：为了研究代谢组学和脂质组学的变化，共收集了30份血浆样本，由15例早期胃癌患者和15例健康对照组成。进行了广泛的基于HPLC-MS的非靶向代谢组学和脂质组学研究。通过统计分析和生物信息学分析发现了差异代谢物和代谢途径。使用基于支持向量机的多变量接受者操作特征分析进行候选生物标志物筛选。
结果：在早期胃癌患者的19种代谢物和67种脂质的组合中观察到了紊乱。对KEGG通路的分析显示,早期胃癌患者的精氨酸生物合成通路发生了中断,丙氨酸的途径，天冬氨酸,和谷氨酸代谢，以及乙醛酸和二羧酸代谢的途径。血浆代谢组学和脂质组学已经确定了多个生物标志物小组，可以有效区分早期胃癌患者和健康对照，曲线下面积超过0.9。
结论：这些代谢物和脂质可能作为早期胃癌筛查的生物标志物，从而优化早期胃癌的检测策略。这些与早期胃癌相关的通路为进一步了解胃癌的发病机制提供了新的线索。尽管如此，需要大规模的临床数据来证明我们的发现.
方法：为了研究代谢组学和脂质组学的变化，共收集了30份血浆样本，由15例早期胃癌患者和15例健康对照组成。进行了广泛的基于HPLC-MS的非靶向代谢组学和脂质组学研究。通过统计分析和生物信息学分析发现了差异代谢物和代谢途径。使用基于支持向量机的多变量接受者操作特征分析进行候选生物标志物筛选。
结果：在早期胃癌患者的19种代谢物和67种脂质的组合中观察到了紊乱。对KEGG通路的分析显示,早期胃癌患者的精氨酸生物合成通路发生了中断,丙氨酸的途径，天冬氨酸,和谷氨酸代谢，以及乙醛酸和二羧酸代谢的途径。血浆代谢组学和脂质组学已经确定了多个生物标志物小组，可以有效区分早期胃癌患者和健康对照，曲线下面积超过0.9。
结论：这些代谢物和脂质可能作为早期胃癌筛查的生物标志物，从而优化早期胃癌的检测策略。这些与早期胃癌相关的通路为进一步了解胃癌的发病机制提供了新的线索。尽管如此，需要大规模的临床数据来证明我们的发现.
