Establishment of a pattern recognition metabolomics model for the diagnosis of hepatocellular carcinoma

Abstract

BACKGROUND Early diagnosis of hepatocellular carcinoma may help to ensure that patients have a chance for long-term survival; however, currently available biomarkers lack sensitivity and specificity. AIM To characterize the serum metabolome of hepatocellular carcinoma in order to develop a new metabolomics diagnostic model and identifying novel biomarkers for screening hepatocellular carcinoma based on the pattern recognition method. METHODS Ultra-performance liquid chromatography-mass spectroscopy was used to