UPLC-Q-TOF-MS-based unbiased serum metabolomics investigation of cholangiocarcinoma - Wang, Xiaowei; Xu, Xuefeng; Jia, Ran; Xu, Yuanhong; Hu, Ping (Frontiers in Molecular Biosciences, 2025)
ObjectiveCholangiocarcinoma (CCA) is a highly aggressive malignancy, and early diagnosis remains challenging. Metabolic biomarkers are increasingly recognized as promising tools for the early detection of cancer. However, a comprehensive exploration of metabolic alterations in CCA, especially from a global metabolic perspective, has yet to be fully realized. To identify reliable metabolic markers for the early diagnosis of CCA and to explore its potential pathogenesis through an in-depth analysis of global metabolism.MethodsSerum samples from 30 CCA patients and 31 healthy individuals were analyzed using an unbiased UPLC-Q-TOF-MS based metabolomics approach. Principal component analysis (PCA) and orthogonal projections to latent structures discriminant analysis (OPLS-DA) were applied to identify potential biomarkers. High-resolution MS/MS and available standards were used to further confirm the identified metabolites. A systematic metabolic pathway analysis was conducted to interpret the biological roles of these biomarkers and explore their relevance to CCA progression.ResultsA total of 25 marker metabolites were identified, including lysophosphatidylcholines (LysoPCs), phosphatidylcholines (PCs), organic acids, sphinganine, and ketoleucine. These metabolites effectively distinguished CCA patients from healthy controls, with an AUC of 0.995 for increased biomarkers and 0.992 for decreased biomarkers in positive mode. In negative mode, the AUC for increased and decreased biomarkers was 0.899 and 0.976, respectively. The metabolic pathway analysis revealed critical biological functions linked to these biomarkers, offering insights into the molecular mechanisms underlying CCA initiation and progression.ConclusionThis study identifies novel metabolic biomarkers for the early diagnosis of CCA and provides a deeper understanding of the metabolic alterations associated with the disease. These findings could contribute to the development of diagnostic strategies and therapeutic interventions for CCA.