Related Experiment Video For Hepatocellular carcinoma
Updated: Jul 9, 2025

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry UPLC-MS
Published on: March 14, 2013
Non-targeted metabolomics study for discovery of hepatocellular carcinoma serum diagnostic biomarker
Shufeng Wang1, Tingting He2, Hongxia Wang3
1Keystonobel Biotechnologies and Pharmaceuticals (Beijing) Co., Ltd, Beijing 100176, PR China.
Abstract:
Hepatocellular carcinoma (HCC) is one of the most prevalent malignant cancers worldwide. Due to the asymptomatic features of HCC at early stages, patients are often diagnosed at advanced stages and missed effective treatment. Thus, there is an urgent need to identify sensitive and specific biomarkers for HCC early diagnosis. In the present study, an ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) approach was used to profile serum metabolites from HCC patients, liver cirrhosis (LC) patients, and normal controls (NC). Univariate and multivariate statistical analyses were performed to obtain the metabolomic differences of the three groups and select significantly changed metabolites that can be used as diagnostic biomarkers. In total, 757 differential metabolites were quantified among the three groups, and pathway enrichment analysis of these metabolites indicated that glycerophospholipid metabolism, pentose and glucuronate interconversions, phenylalanine, tyrosine and tryptophan biosynthesis, and linoleic acid metabolism were the most altered pathways involved in HCC development. Receiver operating characteristic (ROC) curve analysis was performed to select and evaluate the diagnostic biomarker performance. Seven metabolites were identified as potential biomarkers that can differentiate HCC from LC and NC, and LC from NC with the good diagnostic performance of area under the curve (AUC) from 0.890 to 0.990. In summary, our findings provide highly effective biomarker candidates to differentiate HCC from LC and NC, LC, and NC, which shed insight into HCC pathological mechanisms and will be helpful in better understanding and managing HCC.

