Diagnosis of liver cancer using HPLC-based metabonomics avoiding false-positive result from hepatitis and hepatocirrhosis diseases.

Metabonomics, the study of metabolites and their roles in various disease states, is a novel methodology arising from the post-genomics era. This methodology has been applied in many fields. Current metabonomics practice has relied on mass spectrometry (MS), gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) to analyze metabolites. In this study, a novel approach of using high-performance liquid chromatography (HPLC) in conjunction with developed software was employed. Using the principal components analysis method (PCA), all (113) peaks of urinary metabolites with a cis-diol structure from patients with hepatitis and hepatocirrhosis were compared to those from liver cancer patients. The results showed that the metabonomics-PCA method might be useful to differentiate between patients with hepatocirrhosis and hepatitis from patients with liver cancer while lowering false-positive rate. These findings also suggest that a subset of the urinary nucleosides identified with metabonomics correlate better with cancer diagnosis than the traditional single tumor marker alpha-fetoprotein (AFP).