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Πέμπτη 28 Σεπτεμβρίου 2017

A large-scale, multi-center serum metabolite biomarkers identification study for the early detection of hepatocellular carcinoma

Abstract

Hepatocellular carcinoma (HCC) is the third most lethal cancer worldwide. The lack of effective biomarkers for the early detection of HCC results in unsatisfactory curative treatments. Here, metabolite biomarkers were identified and validated for HCC diagnosis. A total of 1448 subjects, mainly including normal controls and patients with chronic hepatitis B virus infection, liver cirrhosis, and HCC were recruited from multi-center in China. Liquid chromatography-mass spectrometry (LC-MS)-based metabolomics methods were used to characterize the subjects' serum metabolic profiles and to screen and validate the HCC biomarkers. A serum metabolite biomarker panel including phenylalanyl-tryptophan and glycocholate, was defined. This panel had a higher diagnostic performance than did α-fetoprotein (AFP) in differentiating HCC from a high-risk population of cirrhosis, such as area under the receiver-operating characteristic curve (AUC) of 0.930, 0.892, 0.807 for panel versus 0.657, 0.725, 0.650 for AFP in the discovery, test and cohort 1 of the validation set, respectively. In the nested case-control study, this panel had high sensitivity (rang 80.0-70.3%) to detect preclinical HCC, and its combination with AFP provided better risk prediction of preclinical HCC before clinical diagnosis. Besides, this panel showed a larger AUC than did AFP (0.866 versus 0.682) to distinguish small-HCC, and 80.6% of the AFP false-negative patients with HCC were correctly diagnosed using this panel in the test set, which was corroborated by the validation set. The specificity and biological relevance of the identified biomarkers were further evaluated using sera from other two cancers and HCC tissue specimens, respectively. Conclusions: The discovered and validated serum metabolite biomarker panel exhibits good diagnostic performance for the early detection of HCC from at-risk populations. This article is protected by copyright. All rights reserved.



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