A Serum Metabonomics Study On HBV Induced Liver Cirrhosis And Hepatocellular Carcinoma

Background: Hepatocellular carcinoma(HCC) is one of the most common malignant tumors in our country, with the high malignant degree and poor prognosis, and it often secondary to the chronic hepatitis B and liver cirrhosis. HCC has a concealed onset and lack of typical symptoms in the early stage. Most patients have developed into the middle-late stage when diagnosed, and usually lead to miss the best time to treat. Importantly, about 80 percent of HCC patients in our country were developed from hepatitis B viral induced liver cirrhosis(HBV-LC), so LC patients had a higher risk of developing to HCC. Several methods including AFP, ultrasound, CT, MRI and pathological biopsy, were applied to distinguish HCC and LC, but it still difficult to identify HCC in the early stage. Given the metabonomics mainly focus on studying low molecular weight metabolites within the cell or organism by qualitative and quantitative analysis, to monitor the metabolic changes in the organisms or living cells. It had made a great achievement in searching for the disease molecular diagnostic biomarkers. Thus, our study utilized the nuclear magnetic resonance to analysis the serum metabolites among the HBV-LC, HCC and healthy controls, and made possible to screen the most significant difference’s metabolites, explore the feasibility of them as the molecular diagnostic markers to identify HBV-LC and HCC.Methods: The morning empty stomach blood of 16 HBV-LC patients, 29 HCC patients and 20 healthy controls were collected, NMR technology was utilized to analyze the serum metabolomics between groups, and its signal were converted into the NMR spectra. Input the normalized 1H-nmr spectral data into SIMCA-p to conduct the Principal Component Analysis(PCA) and Orthogonal Partial least Squares discriminant Analysis(OPLS-DA), built models respectively. According to the variable importance projection(VIP) and load value to primary screen for the metabolic markers, at last conduct the paired sample t test for the obtained variable by SPSS 17.0 software. Eliminate the variables with P > 0.05, and search for the metabolic markers which can distinguish between HBV-LC and HCC, and discuss their metabolic features.Results: Based on the serum metabolomics analysis for the HBV-LC, HCC and healthy controls by NMR technology, PCA model shown the aggregate distribution of controls can distinguish with experimental group, but the distribution of HBV-LC overlapped with HCC group, suggesting that some common metabolic changes maybe existed two groups. Further OPLS-DA model shown HBV-LC, HCC groups can be well distinguished with controls, suggesting PCA and OPLS-DA models can be used to identify HBV-LC and HCC. The higher VIP value of small molecule metabolites show serum lactic acid, choline and formic acid increased in HBV-LC and HCC patients compared with controls; Taurine increased in HBV-LC patients, whereas decreased in HCC patients. Compared with the HBV-LC group, lactic acid, alanine, leucine, choline, glycine increased in the HCC patients, but taurine and formic acids decreased.Conclusions: Our study explored the serum metabolomics among the HBV-LC, HCC and healthy controls by the NMR technology. The PCA and OPLS-DA models can distinguished HBV-LC, HCC and healthy controls. HBV-LC and HCC patients share significant differences in serum level of lactic acid, choline, taurine, formic acid compared with control group, this results could provide theoretical basis for metabonomics used to distingish HBV-LC and HCC.