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基于氢核磁共振的肿瘤组织代谢组学用于大鼠肝细胞癌形成和转移的代谢特征分析

(1)H-NMR-based metabolomics of tumor tissue for the metabolic characterization of rat hepatocellular carcinoma formation and metastasis.

作者信息

Wang Juan, Zhang Shu, Li Zongfang, Yang Jun, Huang Chen, Liang Rongrui, Liu Zhongwei, Zhou Rui

机构信息

Department of General Surgery, The Second Affiliated Hospital, School of Medicine, Xi'an Jiaotong University, No. 157, West 5th Road, Xi'an 710004, Shaanxi, China.

出版信息

Tumour Biol. 2011 Feb;32(1):223-31. doi: 10.1007/s13277-010-0116-7. Epub 2010 Oct 4.

Abstract

The high mortality figures for hepatocellular carcinoma (HCC) are mostly due to high recurrence and metastasis rates. However, the metabolic characteristics of HCC metastasis have not been studied extensively. In this study, we attempted to elucidate the metabolite profile of HCC formation and metastasis through proton nuclear magnetic resonance ((1)H-NMR)-based metabolomics. We first established a hepatocellular carcinoma with lung metastasis (HLM) rat model by exposure to diethylnitrosamine. Fifteen rats were then divided into three groups based on pathologic changes: HCC, HLM, and controls. The metabolite profiles of extracts from tumor tissue were obtained using high-resolution (1)H-NMR. One-way ANOVA was used to compare the metabolite levels among the three groups. Multivariate statistical analysis (specifically, unsupervised principal components analysis and supervised partial least squares discriminant analysis (PLS-DA)) were used for HCC and HLM metabolite profiling and data interpretation. PLS-DA models could discern HCC or HLM rats from normal (control) rats. Tumor tissue from HLM showed changes in glucose, lactate, choline, lipids, and some amino acids such as glycine. The results of this pilot study suggest that alterations in glycolysis and the metabolism of glycine and choline occur during HCC invasion and metastasis.

摘要

肝细胞癌(HCC)的高死亡率主要归因于高复发率和转移率。然而,HCC转移的代谢特征尚未得到广泛研究。在本研究中,我们试图通过基于质子核磁共振((1)H-NMR)的代谢组学来阐明HCC形成和转移的代谢物谱。我们首先通过暴露于二乙基亚硝胺建立了具有肺转移的肝细胞癌(HLM)大鼠模型。然后根据病理变化将15只大鼠分为三组:HCC组、HLM组和对照组。使用高分辨率(1)H-NMR获得肿瘤组织提取物的代谢物谱。采用单因素方差分析比较三组之间的代谢物水平。多变量统计分析(具体而言,无监督主成分分析和有监督偏最小二乘判别分析(PLS-DA))用于HCC和HLM代谢物谱分析及数据解释。PLS-DA模型能够区分HCC或HLM大鼠与正常(对照)大鼠。HLM的肿瘤组织显示葡萄糖、乳酸、胆碱、脂质以及一些氨基酸(如甘氨酸)发生了变化。这项初步研究的结果表明,在HCC侵袭和转移过程中发生了糖酵解以及甘氨酸和胆碱代谢的改变。

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