Serum and urine metabolite profiling reveals potential biomarkers of human hepatocellular carcinoma - PubMed (original) (raw)

. 2011 Jul;10(7):M110.004945.

doi: 10.1074/mcp.M110.004945. Epub 2011 Apr 25.

Guoxiang Xie, Xiaoying Wang, Jia Fan, Yunping Qiu, Xiaojiao Zheng, Xin Qi, Yu Cao, Mingming Su, Xiaoyan Wang, Lisa X Xu, Yun Yen, Ping Liu, Wei Jia

Affiliations

Serum and urine metabolite profiling reveals potential biomarkers of human hepatocellular carcinoma

Tianlu Chen et al. Mol Cell Proteomics. 2011 Jul.

Erratum in

Abstract

Hepatocellular carcinoma (HCC) is a common malignancy in the world with high morbidity and mortality rate. Identification of novel biomarkers in HCC remains impeded primarily because of the heterogeneity of the disease in clinical presentations as well as the pathophysiological variations derived from underlying conditions such as cirrhosis and steatohepatitis. The aim of this study is to search for potential metabolite biomarkers of human HCC using serum and urine metabolomics approach. Sera and urine samples were collected from patients with HCC (n = 82), benign liver tumor patients (n = 24), and healthy controls (n = 71). Metabolite profiling was performed by gas chromatography time-of-flight mass spectrometry and ultra performance liquid chromatography-quadrupole time of flight mass spectrometry in conjunction with univariate and multivariate statistical analyses. Forty three serum metabolites and 31 urinary metabolites were identified in HCC patients involving several key metabolic pathways such as bile acids, free fatty acids, glycolysis, urea cycle, and methionine metabolism. Differentially expressed metabolites in HCC subjects, such as bile acids, histidine, and inosine are of great statistical significance and high fold changes, which warrant further validation as potential biomarkers for HCC. However, alterations of several bile acids seem to be affected by the condition of liver cirrhosis and hepatitis. Quantitative measurement and comparison of seven bile acids among benign liver tumor patients with liver cirrhosis and hepatitis, HCC patients with liver cirrhosis and hepatitis, HCC patients without liver cirrhosis and hepatitis, and healthy controls revealed that the abnormal levels of glycochenodeoxycholic acid, glycocholic acid, taurocholic acid, and chenodeoxycholic acid are associated with liver cirrhosis and hepatitis. HCC patients with alpha fetoprotein values lower than 20 ng/ml was successfully differentiated from healthy controls with an accuracy of 100% using a panel of metabolite markers. Our work shows that metabolomic profiling approach is a promising screening tool for the diagnosis and stratification of HCC patients.

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Figures

Fig. 1.

Fig. 1.

OPLS-DA scores plots and loadings plots of 55 HCC patients (red dots) and 47 healthy controls (blue squares) based on serum spectral data of (A) GC-TOFMS; (B) UPLC-QTOFMS positive ion mode; and (C) UPLC-QTOFMS negative ion mode. On the right side of the three scores plots, three representative chromatograms of a HCC (red) and a healthy control sample (blue) derived from GC-TOFMS, UPLC-QTOFMS positive ion mode, and negative ion mode, respectively.

Fig. 2.

Fig. 2.

Bar charts of quantitative analysis results of bile acids in serum and urine samples (Mean ± S. E., μg/ml) (* p < 0.05; **, p < 0.01). (1. HCC patients; 2. HCC patients with cirrhosis and hepatitis; 3. liver cirrhosis and hepatitis patients; 4. Healthy controls).

Fig. 3.

Fig. 3.

The OPLS-DA prediction model of HCC. An OPLS-DA model was constructed using data from 47 healthy controls (blue squares) and 55 HCC patients (red dots) (the “training set”), this model was then used to predict HCC of a further 51 samples including 24 healthy controls (black stars) and 27 HCC patients (green triangles) that were not used in the construction of the model (the “testing set”). (A) scores plot; (B) magnified scores plot of HCC, the labled numbers are AFP values; (C) loadings plot with identified compounds.

Fig. 4.

Fig. 4.

Bar charts showing fluctuations in integrated intensities of six representative serum differential metabolites and three urine metabolites among five phenotypic states; healthy, HCC stage I, II, III, and IV. (*, p < 0.05; **, p < 0.01, compared with healthy control).

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