title: Metabolomics study of stepwise hepatocarcinogenesis from the model rats to patients: potential biomarkers effective for small hepatocellular carcinoma diagnosis.
abstract: The aim of this study is to find the potential biomarkers from the rat hepatocellular carcinoma (HCC) disease model by using a non-target metabolomics method, and test their usefulness in early human HCC diagnosis. The serum metabolic profiling of the diethylnitrosamine-induced rat HCC model, which presents a stepwise histopathological progression that is similar to human HCC, was performed using liquid chromatography-mass spectrometry. Multivariate data analysis methods were utilized to identify the potential biomarkers. Three metabolites, taurocholic acid, lysophosphoethanolamine 16:0, and lysophosphatidylcholine 22:5, were defined as "marker metabolites," which can be used to distinguish the different stages of chemical hepatocarcinogenesis. These metabolites represented the abnormal metabolism during the progress of hepatocarcinogenesis, which could also be found in patients. To test their diagnosis potential 412 sera from 262 patients with HCC, 76 patients with cirrhosis and 74 patients with chronic hepatitis B were collected and studied, it was found that 3 marker metabolites were effective for the discrimination of small liver tumor (solitary nodules of less than 2 cm in diameter) patients, achieved a sensitivity of 80.5% and a specificity of 80.1%,which is better than those of α-fetoprotein (53 and 64%, respectively). Moreover, they were also effective for the discrimination of all HCCs and chronic liver disease patients, which could achieve a sensitivity of 87.5% and a specificity of 72.3%, better than those of α-fetoprotein (61.2 and 64%). These results indicate metabolomics method has the potential of finding biomarkers for the early diagnosis of HCC.
authors.affiliation: International Cooperation Laboratory on Signal Transduction, Eastern Hepatobiliary Surgery Institute, the Second Military Medical University, Shanghai, China.
authors.forename: Yexiong
authors.initials: Y
authors.lastname: Tan
authors.forename: Peiyuan
authors.initials: P
authors.lastname: Yin
authors.forename: Liang
authors.initials: L
authors.lastname: Tang
authors.forename: Wenbin
authors.initials: W
authors.lastname: Xing
authors.forename: Qiang
authors.initials: Q
authors.lastname: Huang
authors.forename: Dan
authors.initials: D
authors.lastname: Cao
authors.forename: Xinjie
authors.initials: X
authors.lastname: Zhao
authors.forename: Wenzhao
authors.initials: W
authors.lastname: Wang
authors.forename: Xin
authors.initials: X
authors.lastname: Lu
authors.forename: Zhiliang
authors.initials: Z
authors.lastname: Xu
authors.forename: Hongyang
authors.initials: H
authors.lastname: Wang
authors.forename: Guowang
authors.initials: G
authors.lastname: Xu
mesh_terms: D000328:Adult; D000368:Aged; D000818:Animals; D014408:Biomarkers, Tumor / Q000097:blood*; D006528:Carcinoma, Hepatocellular / Q000097:blood / Q000175:diagnosis*; D018288:Carcinoma, Small Cell / Q000097:blood / Q000175:diagnosis*; D002853:Chromatography, Liquid; D004195:Disease Models, Animal; D005260:Female; D006801:Humans; D008113:Liver Neoplasms / Q000097:blood / Q000175:diagnosis*; D008297:Male; D055442:Metabolome; D055432:Metabolomics; D008875:Middle Aged; D051381:Rats; D017207:Rats, Sprague-Dawley; D012680:Sensitivity and Specificity; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization; D055815:Young Adult
chemical_list: D014408:Biomarkers, Tumor
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