A study on bile from patients with recurrent common bile duct stones and cholangiocarcinoma following ERCP using...

This study aimed to analyze bile samples from patients with common bile duct stones and cholangiocarcinoma using non-targeted liquid chromatography-mass spectrometry (LC-MS)-based metabolomics, in order to identify disease-associated differential metabolites and metabolic pathways, and to establish metabolite-based models for predicting bile duct stone recurrence and facilitating diagnosis of cholangiocarcinoma.

Bile samples and clinical data were collected from 50 patients who underwent ERCP with nasobiliary drainage tube placement at the Second Affiliated Hospital of Zhengzhou University between January and June 2025. Among them, 20 cases were primary choledocholithiasis (PDS), 15 cases were recurrent choledocholithiasis (RDS) (with ≥6 months since previous choledocholithiasis detection), and 15 with cholangiocarcinoma (CCA). LC-MS was used to detect small-molecule metabolites in bile. Principal Component Analysis (PCA) and Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) were performed on the results. Differential metabolites were identified using metabolomics databases. The screening criteria were set at p < 0.05 and fold change <0.67 or >1.50, combined with variable importance projection >1.00. Pathway enrichment analysis was performed. Based on the selected differential metabolites, predictive models for common bile duct stone recurrence and cholangiocarcinoma were established, and preliminary model evaluation was conducted using receiver operating characteristic (ROC) curves.

LC-MS identified a total of 174 metabolites with secondary match names. Based on screening criteria, 32 differentially expressed metabolites were selected, including 17 between the PDS and RDS groups, 8 between the PDS and CCA groups, and 7 between the RDS and CCA groups. Significant enrichment was observed in the unsaturated fatty acid, amino acid, and sphingolipid metabolic pathways. Among the 17 differential metabolites in the PDS and RDS groups, four metabolites with consistent trend changes and AUC values exceeding 0.7 were selected to construct a common bile duct stone recurrence model. The area under the ROC curve reached 0.92, with a sensitivity of 86.7% and a specificity of 90.2%. Additionally, in both the stone group and cholangiocarcinoma group, the diagnostic efficacy of the novel tumor marker combination of arachidonic acid and dimethyl phosphate surpassed that of the traditional tumor marker combination of CA19-9 and CEA.

Recurrent common bile duct stones and cholangiocarcinoma patients exhibit distinct alterations in bile metabolic profiles. Specific combinations of bile metabolites hold promise as potential biomarkers for diagnosing recurrent common bile duct stones and cholangiocarcinoma.