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Gastric cancer (GC) is one of the most common causes of cancer-related deaths worldwide, and chemotherapy is still a standard strategy for treating patients with advanced GC. Lipid metabolism has been reported to play an important role in the carcinogenesis and development of GC. However, the potential values of lipid-metabolism-related genes (LMRGs) concerning prognostic value and the prediction of chemotherapy responsiveness in GC remains unclear. A total of 714 stomach adenocarcinoma patients were enrolled from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Using univariate Cox and LASSO regression analyses, we developed a risk signature based on LMRGs that can distinguish high-GC-risk patients from low-risk patients with significant differences in overall survival. We further validated this signature prognostic value using the GEO database. The R package "pRRophetic" was applied to calculate the sensitivity of each sample from high- and low-risk groups to chemotherapy drugs. The expression of two LMRGs, AGT and ENPP7, can predict the prognosis and response to chemotherapy in GC. Furthermore, AGT significantly promoted GC growth and migration, and the downregulation of AGT enhanced the chemotherapy response of GC both in vitro and in vivo. Mechanistically, AGT induced significant levels of epithelial-mesenchymal transition (EMT) through the PI3K/AKT pathway. The PI3K/AKT pathway agonist 740 Y-P can restore the EMT of GC cells impaired by AGT knockdown and treatment with 5-fluorouracil. Our findings suggest that AGT plays a key role in the development of GC, and targeting AGT may help to improve the chemotherapy response of GC patients.

System Analysis Based on Lipid-Metabolism-Related Genes Identifies AGT as a Novel Therapy Target for Gastric Cancer with Neoadjuvant Chemotherapy