Amino acids not only play a vital role in the synthesis of biological molecules such as proteins in cancer malignant cells, they are also essential metabolites for immune cell activation and antitumor effects in the tumor microenvironment. The abnormal changes in amino acid metabolism are closely related to the occurrence and development of tumors and immunity. Intestinal microorganisms play an essential role in amino acid metabolism, and tryptophan and its intestinal microbial metabolites are typical representatives. However, it is known that the cyclic amino acid profile is affected by specific cancer types, so relevant studies mainly focus on one type of cancer and rarely study different cancer forms at the same time. The objective of this study was to examine the PFAA profile of five cancer patients and the characteristics of tryptophan intestinal microbial metabolites to determine whether there are general amino acid changes across tumors. Plasma samples were collected from esophageal (n = 53), lung (n = 73), colorectal (n = 94), gastric (n = 55), breast cancer (n = 25), and healthy control (HC) (n = 139) subjects. PFAA profile and tryptophan metabolites were measured, and their perioperative changes were examined using high-performance liquid chromatography. Univariate analysis revealed significant differences between cancer patients and HC. Furthermore, multivariate analysis discriminated cancer patients from HC. Regression diagnosis models were established for each cancer group using differential amino acids from univariate analysis. Receiver-operating characteristic analysis was applied to evaluate these diagnosis models. Finally, GABA, arginine, tryptophan, taurine, glutamic acid, and melatonin showed common alterations across all types of cancer patients. Metabolic pathway analysis shows that the most significant enrichment pathways were tryptophan, arginine, and proline metabolism. This study provides evidence that common alterations of the metabolites mentioned above suggest their role in the pathogenesis of each cancer patient. It was suggested that multivariate models based on PFAA profiles and tryptophan metabolites might be applicable in the screening of cancer patients.
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