Non-targeted metabolomics analysis of indoleamine 2,3-dioxygenase inhibitor treatment in a mouse model of early-stage lung adenocarcinoma

Background: Lung adenocarcinoma is a common malignant tumor, and its early diagnosis and treatment are key to improving patient survival rates. However, due to the non-specific early symptoms, many patients are already at an advanced stage when diagnosed. Non -targeted metabolomics analysis, as a method for comprehensive analysis of metabolites in the body, has been shown to have potential in the early diagnosis of cancer. This study aims to identify early -stage lung adenocarcinoma-specific biomarkers using non -targeted metabolomics analysis in an established mouse model. The intervention mechanism of indoleamine 2,3-dioxygenase (IDO) inhibitor in early -stage lung adenocarcinoma is explored to provide evidence for clinical disease treatment. Methods: Twenty specific -pathogen -free -grade female Kunming mice were divided into control group, experimental group, Epacadostatlow group, and Epacadostathigh group. After modeling, immune therapy intervention (epacadostat) was administered to the mice, and plasma and urine samples were collected from all mice on day 7 and day 28. Ultra -high-performance liquid chromatography -quadrupole time -offlight mass spectrometry (UPLC-QTOF-MS) analysis was performed to identify potential biomarkers for diagnosing early -stage lung adenocarcinoma. Cluster analysis and correlation analysis were used to explore the differential expression patterns of metabolites in different samples. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was used to identify enriched pathways of differentially expressed metabolites. Results: A total of 348 metabolites were identified after merging the positive and negative ion modes. Among them, organic acids and derivatives (16.954%) and lipids and lipid -like molecules (15.517%) were the two major classes of metabolites in the early -stage lung adenocarcinoma mice. Anthranilic acid (vitamin L1), 1-methylhistidine, 12(R)-HETE, and hippuric acid were the major differentially expressed metabolites on both day 7 and day 28, and they showed correlations with each other. Metabolic pathway analysis revealed multiple dysregulated pathways in lung adenocarcinoma mice. Conclusions: UPLC-QTOF-MS analysis is a feasible method for identifying biomarkers of lung adenocarcinoma. Epacadostat, a novel and promising IDO inhibitor, may exert its therapeutic effect by modulating 1-methylhistidine and anthranilic acid (vitamin L1).