Department of Gastrointestinal Surgery, Xuzhou Central Hospital, Affiliated Hospital of Medical College of Southeast University, Xuzhou, Jiangsu 221009, China.
Chin Med J (Engl). 2012 Mar;125(5):757-63.
Gastric cancer (GC) is one of the most common types of cancer in the world. A change in the metabolism of lipids in tumor cells could lead to the pathogenesis of cancer. In this study, we investigated fatty acid and fatty acid amide metabolic perturbations associated with GC morbidity.
Gas chromatography/mass spectrometry (GC/MS) was utilized to analyze fatty acids (FAs) and fatty acid amides (FAAs) of GC tissues and matched normal mucosae from 30 GC patients. Acquired lipid data was analyzed using non parametric Wilcoxon rank sum test to find the differential biomarkers for GC and diagnostic models for GC were established by using orthogonal partial least squares discriminant analysis (OPLS-DA).
A total of 13 FAs and 4 FAAs were detected using GC/MS and 5 differential FAs as well as oleamide were identified with significant difference (P<0.05). The OPLS-DA model generated from lipid profile showed adequate discrimination of GC tissues from normal mucosae while the OPLS-DA model failed to separate GC specimens of different TNM stages. A total of 8 variables were obtained for their most contribution in the discriminating model (Variable importance in the projection (VIP) value>1.0), five of which were detected with significant difference (P<0.05).
FA and FAA metabolic profiles have great potential in detecting GC and helping understand perturbations of lipid metabolism associated with GC morbidity.
胃癌（GC）是世界上最常见的癌症类型之一。肿瘤细胞中脂质代谢的改变可能导致癌症的发病机制。在这项研究中，我们研究了与 GC 发病率相关的脂肪酸（FAs）和脂肪酸酰胺（FAAs）代谢紊乱。
气相色谱/质谱（GC/MS）用于分析 30 名 GC 患者的 GC 组织和匹配的正常黏膜中的脂肪酸（FAs）和脂肪酸酰胺（FAAs）。使用非参数 Wilcoxon 秩和检验分析获得的脂质数据，以找到 GC 的差异生物标志物，并通过正交偏最小二乘判别分析（OPLS-DA）建立 GC 的诊断模型。
GC/MS 共检测到 13 种 FAs 和 4 种 FAAs，其中 5 种差异 FAs 和油酸酰胺具有显著差异（P<0.05）。来自脂质谱的 OPLS-DA 模型显示 GC 组织与正常黏膜具有足够的区分能力，而 OPLS-DA 模型未能区分不同 TNM 阶段的 GC 标本。在判别模型中，共有 8 个变量因其对区分模型的最大贡献而获得（投影变量重要性（VIP）值>1.0），其中 5 个变量具有显著差异（P<0.05）。
FA 和 FAA 代谢谱在检测 GC 方面具有很大的潜力，并有助于了解与 GC 发病率相关的脂质代谢紊乱。
