Background/Objectives: Gastric cancer (GC) is a prevalent malignant tumor worldwide, with its pathological mechanisms largely unknown. Understanding the metabolic reprogramming associated with GC is crucial for the prevention and treatment of this disease. This study aims to identify significant alterations in metabolites and pathways related to the development of GC. Methods: A liquid chromatography–mass spectrometry-based non-targeted metabolomics data acquisition was performed on paired tissues from 80 GC patients. Differences in metabolic profiles between tumor and adjacent normal tissues were first investigated through univariate and multivariate statistical analyses. Additionally, differential correlation network analysis and a newly proposed network analysis method (NAM) were employed to explore significant metabolite pathways and subnetworks related to tumorigenesis and various TNM stages of GC. Results: Over half of the annotated metabolites exhibited significant alterations. Phosphatidylcholine (PC)_30_0 and fatty acid C20_3 demonstrated strong diagnostic performance for GC, with AUCs of 0.911 and 0.934 in the discovery and validation sets, respectively. Differential correlation network analysis revealed significant fatty acid-related metabolic reprogramming in GC with elevated levels of medium-chain acylcarnitines and increased activity of medium-chain acyl-CoA dehydrogenase, firstly observed in clinical GC tissues. Of note, using NAM, two correlation subnetworks were identified as having significant alterations across different TNM stages, centered with choline and carnitine C4_0-OH, respectively. Conclusions: The identified significant alterations in fatty acid metabolism and TNM-related metabolic subnetworks in GC tissues will facilitate future investigations into the metabolic reprogramming associated with gastric cancer.