Oncotarget

Research Papers:

Plasma metabolomic analysis of human hepatocellular carcinoma: Diagnostic and therapeutic study

Yang Chen, Jianyin Zhou, Jinquan Li, Jianghua Feng _, Zhong Chen and Xiaomin Wang

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Oncotarget. 2016; 7:47332-47342. https://doi.org/10.18632/oncotarget.10119

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Abstract

Yang Chen1,*, Jianyin Zhou2,*, Jinquan Li1, Jianghua Feng1, Zhong Chen1, Xiaomin Wang2

1Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, 361005, China

2Department of Hepatobiliary and Pancreatic Surgery, Zhongshan Hospital, Xiamen University, Xiamen, 361004, China

*These authors contributed equally to this work

Correspondence to:

Jianghua Feng, email: [email protected]

Xiaomin Wang, email: [email protected]

Keywords: hepatocellular carcinoma, metabolic profiling, 1H-NMR spectroscopy, transcatheter arterial chemoembolization, surgery

Received: March 28, 2016     Accepted: May 23, 2016     Published: June 17, 2016

ABSTRACT

Many hepatocellular carcinoma (HCC) patients suffer from late stages when diagnosed, leading to dismal prospects for cure. Improving the diagnosis and treatment of HCC remains a challenge. In this work, NMR-based metabolomic techniques were used to investigate the metabolic alterations of HCC patients from different pathological backgrounds. Metabolic improvement of clinical surgical treatments or transcatheter arterial chemoembolization (TACE) for recurrent or metastatic HCC was also evaluated. HCC was characterized by enhanced lipid metabolism and high consumption in response to liver injury. Expectedly, higher consumption of glucose and lactate production in TACE group confirmed that recurrent or metastatic HCC is more active in citric acid cycle and oxidative phosphorylation. However, TACE or surgical treatments did not immediately improve the metabolic profiles of HCC patients. Combining multivariate statistical analyses with univariate t-test, a series of characteristic metabolites were identified and served as biomarkers for discrimination of HCC patients in different pathological backgrounds. The relative metabolic pathway analyses help to get insight into the underlying biochemical mechanism and extend clinical relevance. Furthermore, algorithm of support vector classification was used to identify HCC and control subjects, and diagnostic sensitivity and specificity reached to 100% and 81.08% respectively by receiver operating characteristic analysis. It is concluded that NMR-based metabolomic analysis of plasma can provide a powerful approach to discover diagnostic and therapeutic biomarkers, and subsequently contribute to clinical disease management.


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