Integrated Transcriptomic and Metabolomic Analysis Revealed That Tryptophan Metabolism-Related Metabolites Are Biomarkers of Trastuzumab Resistance.

BACKGROUND: Trastuzumab resistance strongly affects the prognosis of HER2-positive breast cancer patients, and tryptophan metabolism plays a key role in cancer progression and cancer prognosis. However, the relationship between trastuzumab resistance and tryptophan metabolism in HER2-positive breast cancer remains unclear. METHODS: Four HER2-positive breast cancer cell lines (TS: BT-474, SK-BR-3; TR: HCC1954, JIMT-1) were cultured in specific media. Metabolites from cells, tissues, and serum were extracted via pretreatment, centrifugation, drying, and redissolution. UPLC-MS/MS was used for metabolite detection, while tryptophan metabolism-related gene expression was measured using qRT-PCR. T-test was used to calculate statistical differences. Data visualization, machine learning models construction (RF, LASSO logistic regression), and nomogram were achieved through R language. RESULTS: PLS-DA showed distinct separation between TS and TR breast cancer cell lines in tryptophan metabolism-related gene expression (four differentially expressed genes: HAAO, KYNU, KMO, AFMID) and metabolite abundance (five differentially abundant metabolites). Integration analysis identified 3-hydroxyanthranilic acid, cinnabarinic acid, kynurenine, and kynurenic acid as potential metabolic biomarkers. These four metabolites differed significantly in serum of HCs, TS and TR patients. Four predictors were selected by LASSO, and a nomogram was constructed based on logistic regression. Finally, biomarkers and related genes were validated in tissues. CONCLUSION: Our explored the changes induced by trastuzumab resistance in terms of metabolite abundance and gene transcription levels associated with tryptophan metabolism. Furthermore, this work provided new insights into novel diagnostic biomarkers and prediction models of trastuzumab resistance in HER2-positive breast cancer patients.