Department of Gastrointestinal Surgery, the Sixth Affiliated Hospital (Gastrointestinal and Anal Hospital), Sun Yat-sen University, Guangzhou, Guangdong, China.
Braz J Med Biol Res. 2012 Jan;45(1):78-85. doi: 10.1590/s0100-879x2011007500158. Epub 2011 Nov 25.
Research on molecular mechanisms of carcinogenesis plays an important role in diagnosing and treating gastric cancer. Metabolic profiling may offer the opportunity to understand the molecular mechanism of carcinogenesis and help to non-invasively identify the potential biomarkers for the early diagnosis of human gastric cancer. The aims of this study were to explore the underlying metabolic mechanisms of gastric cancer and to identify biomarkers associated with morbidity. Gas chromatography/mass spectrometry (GC/MS) was used to analyze the serum metabolites of 30 Chinese gastric cancer patients and 30 healthy controls. Diagnostic models for gastric cancer were constructed using orthogonal partial least squares discriminant analysis (OPLS-DA). Acquired metabolomic data were analyzed by the nonparametric Wilcoxon test to find serum metabolic biomarkers for gastric cancer. The OPLS-DA model showed adequate discrimination between cancer and non-cancer cohorts while the model failed to discriminate different pathological stages (I-IV) of gastric cancer patients. A total of 44 endogenous metabolites such as amino acids, organic acids, carbohydrates, fatty acids, and steroids were detected, of which 18 differential metabolites were identified with significant differences. A total of 13 variables were obtained for their greatest contribution in the discriminating OPLS-DA model [variable importance in the projection (VIP) value >1.0], among which 11 metabolites were identified using both VIP values (VIP >1) and the Wilcoxon test. These metabolites potentially revealed perturbations of glycolysis and of amino acid, fatty acid, cholesterol, and nucleotide metabolism of gastric cancer patients. These results suggest that gastric cancer serum metabolic profiling has great potential in detecting this disease and helping to understand its metabolic mechanisms.
致癌分子机制的研究在胃癌的诊断和治疗中起着重要作用。代谢组学分析可能提供了理解致癌分子机制的机会，并有助于非侵入性地识别人类胃癌早期诊断的潜在生物标志物。本研究旨在探讨胃癌的潜在代谢机制，并确定与发病相关的生物标志物。采用气相色谱/质谱联用（GC/MS）分析 30 例中国胃癌患者和 30 例健康对照者的血清代谢物。采用正交偏最小二乘判别分析（OPLS-DA）构建胃癌诊断模型。采用非参数 Wilcoxon 检验对获得的代谢组学数据进行分析，以寻找胃癌的血清代谢标志物。OPLS-DA 模型显示癌症和非癌症队列之间有足够的区分，而该模型未能区分胃癌患者的不同病理阶段（I-IV）。共检测到 44 种内源性代谢物，如氨基酸、有机酸、碳水化合物、脂肪酸和类固醇，其中 18 种差异代谢物具有显著差异。在判别 OPLS-DA 模型中，共有 13 个变量因其最大贡献而获得（投影变量重要性（VIP）值>1.0），其中 11 种代谢物同时通过 VIP 值（VIP>1）和 Wilcoxon 检验确定。这些代谢物可能揭示了胃癌患者糖酵解以及氨基酸、脂肪酸、胆固醇和核苷酸代谢的紊乱。这些结果表明，胃癌血清代谢组学在检测该疾病和帮助理解其代谢机制方面具有很大的潜力。
