4.6 Article

Serum Metabolomics of Burkitt Lymphoma Mouse Models

Journal

PLOS ONE
Volume 12, Issue 1, Pages -

Publisher

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0170896

Keywords

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Funding

  1. General Program of the National Natural Science Foundation of China [21472197]
  2. Major National Basic Research Projects (973) [2013CB733701]
  3. National Natural Science Foundation of China [21305145]
  4. Strategic Priority Research Program of the Chinese Academy of Sciences [XDA09030307]

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Burkitt lymphoma (BL) is a rare and highly aggressive type of non-Hodgkin lymphoma. The mortality rate of BL patients is very high due to the rapid growth rate and frequent systemic spread of the disease. A better understanding of the pathogenesis, more sensitive diagnostic tools and effective treatment methods for BL are essential. Metabolomics, an important aspect of systems biology, allows the comprehensive analysis of global, dynamic and endogenous biological metabolites based on their nuclear magnetic resonance (NMR) and mass spectrometry (MS). It has already been used to investigate the pathogenesis and discover new biomarkers for disease diagnosis and prognosis. In this study, we analyzed differences of serum metabolites in BL mice and normal mice by NMR-based metabolomics. We found that metabolites associated with energy metabolism, amino acid metabolism, fatty acid metabolism and choline phospholipid metabolism were altered in BL mice. The diagnostic potential of the metabolite differences was investigated in this study. Glutamate, glycerol and choline had a high diagnostic accuracy; in contrast, isoleucine, leucine, pyruvate, lysine, a-ketoglutarate, betaine, glycine, creatine, serine, lactate, tyrosine, phenylalanine, histidine and formate enabled the accurate differentiation of BL mice from normal mice. The discovery of abnormal metabolism and relevant differential metabolites may provide useful clues for developing novel, noninvasive approaches for the diagnosis and prognosis of BL based on these potential biomarkers.

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