Background: 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.
Methods: 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).
Results: 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).
Conclusions: FA and FAA metabolic profiles have great potential in detecting GC and helping understand perturbations of lipid metabolism associated with GC morbidity.