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).