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肝细胞癌的代谢组学研究:利用毛细管电泳-质谱法发现并验证血清潜在生物标志物

Metabolomics study of hepatocellular carcinoma: discovery and validation of serum potential biomarkers by using capillary electrophoresis-mass spectrometry.

作者信息

Zeng Jun, Yin Peiyuan, Tan Yexiong, Dong Liwei, Hu Chunxiu, Huang Qiang, Lu Xin, Wang Hongyang, Xu Guowang

机构信息

Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences , 457 Zhongshan Road, Dalian 116023, China.

出版信息

J Proteome Res. 2014 Jul 3;13(7):3420-31. doi: 10.1021/pr500390y. Epub 2014 Jun 2.

Abstract

Hepatocellular carcinoma (HCC) is one of the most lethal malignancies. The lack of effective screening methods for early diagnosis has been a longstanding bottleneck to improve the survival rate. In the present study, a capillary electrophoresis-time-of-flight mass spectrometry (CE-TOF/MS)-based metabolomics method was employed to discover novel biomarkers for HCC. A total of 183 human serum specimens (77 sera in discovery set and 106 sera in external validation set) were enrolled in this study, and a "serum biomarker model" including tryptophan, glutamine, and 2-hydroxybutyric acid was finally established based on the comprehensive screening and validation workflow. This model was evaluated as an effective tool in that area under the receiver operating characteristic curve reached 0.969 in the discovery set and 0.99 in the validation set for diagnosing HCC from non-HCC (health and cirrhosis). Furthermore, this model enabled the discrimination of small HCC from precancer cirrhosis with an AUC of 0.976, highlighting the potential of early diagnosis. The biomarker model is effective for those a-fetoprotein (AFP) false-negative and false-postive subjects, indicating the complementary function to conventional tumor marker AFP. This study demonstrates the promising potential of CE-MS-based metabolomics approach in finding biomarkers for disease diagnosis and providing special insights into tumor metabolism.

摘要

肝细胞癌(HCC)是最致命的恶性肿瘤之一。缺乏用于早期诊断的有效筛查方法一直是提高生存率的长期瓶颈。在本研究中,采用基于毛细管电泳-飞行时间质谱(CE-TOF/MS)的代谢组学方法来发现HCC的新型生物标志物。本研究共纳入183份人类血清标本(发现集77份血清,外部验证集106份血清),并基于全面的筛查和验证流程最终建立了一个包括色氨酸、谷氨酰胺和2-羟基丁酸的“血清生物标志物模型”。该模型被评估为该领域的有效工具,因为在发现集中,用于区分HCC与非HCC(健康和肝硬化)的受试者工作特征曲线下面积达到0.969;在验证集中达到0.99。此外,该模型能够以0.976的曲线下面积区分小肝癌与癌前肝硬化,凸显了早期诊断的潜力。该生物标志物模型对甲胎蛋白(AFP)假阴性和假阳性受试者有效,表明其对传统肿瘤标志物AFP具有互补作用。本研究证明了基于CE-MS的代谢组学方法在寻找疾病诊断生物标志物以及深入了解肿瘤代谢方面具有广阔的潜力。

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