Machine learning-empowered cis-diol metabolic fingerprinting enables precise diagnosis of primary liver cancer.

ABSTRACT: Cis-diol metabolic reprogramming evolves during primary liver cancer (PLC) initiation and progression. However, owing to the low concentrations and highly structural heterogeneity of cis-diols in vivo, severe interference from complex biofluids and limited profiling coverage of existing methods, in-depth profiling of cis-diol metabolites and linking their specific changes with PLC remain challenging. Besides, due to the low specificity of widely used protein biomarkers, accurate classification of PLC from hepatitis still represents an unmet need in clinical diagnostics. Herein, to high-coverage profile cis-diols and explore the translational potential of them as biomarkers, a machine learning-empowered boronate affinity extraction-solvent evaporation assi

SUBMITTER: Li P 

PROVIDER: S-EPMC9993839 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature