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학술저널
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Wen, He (Department of Biochemistry, Inha University Hospital and Center for Advanced Medical Education by BK21 Project, College of Medicine, Inha University) Yang, Hye-Ji (Department of Biochemistry, Inha University Hospital and Center for Advanced Medical Education by BK21 Project, College of Medicine, Inha University) Choi, Myung-Joo (Department of Biomedical Sciences, Inha University Hospital and Center for Advanced Medical Education by BK21 Project, College of Medicine, Inha University) Kwon, Hyuk-Nam (Department of Biochemistry, Inha University Hospital and Center for Advanced Medical Education by BK21 Project, College of Medicine, Inha University) Kim, Min-Ah (Department of Biomedical Sciences, Inha University Hospital and Center for Advanced Medical Education by BK21 Project, College of Medicine, Inha University) Hong, Soon-Sun (Department of Biomedical Sciences, Inha University Hospital and Center for Advanced Medical Education by BK21 Project, College of Medicine, Inha University) Park, Sung-Hyouk (Department of Biochemistry, Inha University Hospital and Center for Advan)
저널정보
한국응용약물학회 Biomolecules & Therapeutics(구 응용약물학회지) Biomolecules & therapeutics 제19권 제1호
발행연도
2011.1
수록면
38 - 44 (7page)

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Cisplatin is widely used for various types of cancers. However, its side effects, most notably, renal toxicity often limit its clinical utility. Although previous metabolomic studies reported possible toxicity markers, they used small number of animals and statistical approaches that may not perform best in the presence of intra-group variation. Here, we identified urinary biomarkers associated with renal toxicity induced by cisplatin using NMR-based metabolomics combined with Orthogonal Projections to Latent Structures-Discriminant Analysis (OPLS-DA). Male Sprague-Dawley rats (n=22) were treated with cisplatin (10 mg/kg single dose), and the urines obtained before and after treatment were analyzed by NMR. Multivariable analysis of NMR data presented clear separation between non-treated and treated groups. The OPLS-DA statistical results revealed that 1,3-dimethylurate, taurine, glucose, glycine and branched-chain amino acid (isoleucine, leucine and valine) were significantly elevated in the treated group and that phenylacetylglycine and sarcosine levels were decreased in the treated group. To test the robustness of the approach, we built a prediction model for the toxicity and were able to predict all the unknown samples (n=14) correctly. We believe the proposed NMR-based metabolomics with OPLS-DA approach and the resulting urine markers can be used to augment the currently available blood markers.

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