4.7 Article

Metabolomics Study of Hepatocellular Carcinoma: Discovery and Validation of Serum Potential Biomarkers by Using Capillary Electrophoresis-Mass Spectrometry

Journal

JOURNAL OF PROTEOME RESEARCH
Volume 13, Issue 7, Pages 3420-3431

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/pr500390y

Keywords

hepatocellular carcinoma; HCC; metabolomics; serum; biomarkers; capillary electrophoresis; mass spectrometry

Funding

  1. State Key Science & Technology Project for Infectious Diseases [2012ZX10002-011, 2012ZX10002-009]
  2. creative research group project from National Natural Science Foundation of China [21321064]
  3. Program of Shanghai Municipal Commision of Health [XBR2013090]
  4. [21175132]

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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.

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