The important metabolic characteristics of cancer cells include increased fat production and changes in amino acid metabolism. Based on the category of tumor, tumor cells are capable of synthesizing as much as 95% of saturated and monounsaturated fatty acids through de novo synthesis, even in the presence of sufficient dietary lipid intake. This fat transformation starts early when cell cancerization and further spread along with the tumor cells grow more malignant. In addition, local catabolism of tryptophan, a common feature, can weaken anti-tumor immunity in primary tumor lesions and TDLN. Arginine catabolism is likewise related with the inhibition of anti-tumor immunity. Due to the crucial role of amino acids in tumor growth, increasing tryptophan along with arginine catabolism will promote tumor growth. However, immune cells also require amino acids to expand and distinguish into effector cells that can kill tumor cells. Therefore, it is necessary to have a deeper understanding of the metabolism of amino acids and fatty acids within cells. In this study, we established a method for the simultaneous analysis of 64 metabolites consisting of fatty acids and amino acids, covering biosynthesis of unsaturated fatty acids, aminoacyl-tRNA biosynthesis, and fatty acid biosynthesis using the Agilent GC-MS system. We selected linoleic acid, linolenic acid, sodium acetate, and sodium butyrate to treat H460 cells to validate the current method. The differential metabolites observed in the four fatty acid groups in comparison with the control group indicate the metabolic effects of various fatty acids on H460 cells. These differential metabolites could potentially become biomarkers for the early diagnosis of lung cancer.
Keywords: GC-MS; H460 lung cancer cell; amino acids; fatty acids; targeted metabolomics.