Biomolecules & Therapeutics

The Korean Society of Applied Pharmacology (한국응용약물학회)
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Identification of Urinary Biomarkers Related to Cisplatin-Induced Acute Renal Toxicity Using NMR-Based Metabolomics

  • 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 Advanced Medical Education by BK21 Project, College of Medicine, Inha University)
  • Received : 2010.09.15
  • Accepted : 2010.10.11
  • Published : 2011.01.31
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Abstract

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.

Keywords

References

  1. Arany, I. and Safi rstein, R. L. (2003) Cisplatin nephrotoxicity. Semin. Nephrol. 23, 460-464. https://doi.org/10.1016/S0270-9295(03)00089-5
  2. Boudonck, K. J., Mitchell, M. W., Nemet, L., Keresztes, L., Nyska, A., Shinar, D. and Rosenstock, M. (2009) Discovery of metabolomics biomarkers for early detection of nephrotoxicity. Toxicol. Pathol. 37, 280-292. https://doi.org/10.1177/0192623309332992
  3. Bylesjo, M., Rantalainen, M., Cloarec, O., Nicholson, J., Holmes, E. and Trygg, J. (2006) OPLS discriminant analysis: combining the strengths of PLS-DA and SIMCA classifi cation. J. Chemom. 20, 341-351. https://doi.org/10.1002/cem.1006
  4. Clayton, T. A., Baker, D., Lindon, J. C., Everett, J. R. and Nicholson, J. K. (2009) Pharmacometabonomic identifi cation of a signifi cant host-microbiome metabolic interaction affecting human drug metabolism. Proc. Natl. Acad. Sci. USA. 106, 14728-14733. https://doi.org/10.1073/pnas.0904489106
  5. Clayton, T. A., Lindon, J. C., Cloarec, O., Antti, H., Charuel, C., Hanton, G., Provost, J. P., Le Net, J. L., Baker, D., Walley, R. J., Everett, J. R. and Nicholson, J. K. (2006) Pharmaco-metabonomic phenotyping and personalized drug treatment. Nature 440, 1073-1077. https://doi.org/10.1038/nature04648
  6. Cloarec, O., Dumas, M. E., Craig, A., Barton, R. H., Trygg, J., Hudson, J., Blancher, C., Gauguier, D., Lindon, J. C., Holmes, E. and Nicholson, J. (2005) Statistical total correlation spectroscopy: an exploratory approach for latent biomarker identifi cation from metabolic 1H NMR data sets. Anal. Chem. 77, 1282-1289. https://doi.org/10.1021/ac048630x
  7. Crino, L., Calandri, C., Maestri, A. and Marrocolo, F. (2001) Gemcitabine and cisplatin combination in early-stage non-small-cell lung cancer. Oncology (Williston Park) 15, 40-42.
  8. Davis, J. W. and Kramer, J. A. (2006) Genomic-based biomarkers of drug-induced nephrotoxicity. Expert Opin. Drug Metab. Toxicol. 2, 95-101. https://doi.org/10.1517/17425255.2.1.95
  9. Ebbels, T. M., Keun, H. C., Beckonert, O. P., Bollard, M. E., Lindon, J. C., Holmes, E. and Nicholson, J. K. (2007) Prediction and classification of drug toxicity using probabilistic modeling of temporal metabolic data: the consortium on metabonomic toxicology screening approach. J. Proteome. Res. 6, 4407-4422. https://doi.org/10.1021/pr0703021
  10. Gong, J. G., Costanzo, A., Yang, H. Q., Melino, G., Kaelin, W. G. Jr., Levrero, M. and Wang, J. Y. (1999) The tyrosine kinase c-Abl regulates p73 in apoptotic response to cisplatin-induced DNA damage. Nature 399, 806-809. https://doi.org/10.1038/21690
  11. Hewitt, S. M., Dear, J. and Star, R. A. (2004) Discovery of protein biomarkers for renal diseases. J. Am. Soc. Nephrol. 15, 1677-1689. https://doi.org/10.1097/01.ASN.0000129114.92265.32
  12. Kang, J., Choi, M. Y., Kang, S., Kwon, H. N., Wen, H., Lee, C. H., Park, M., Wiklund, S., Kim, H. J., Kwon, S. W. and Park, S. (2008a) Application of a 1H nuclear magnetic resonance (NMR) metabolomics approach combined with orthogonal projections to latent structure-discriminant analysis as an effi cient tool for discriminating between Korean and Chinese herbal medicines. J. Agric. Food Chem. 56, 11589-11595. https://doi.org/10.1021/jf802088a
  13. Kang, J., Lee, S., Kang, S., Kwon, H. N., Park, J. H., Kwon, S. W. and Park, S. (2008b) NMR-based metabolomics approach for the differentiation of ginseng (Panax ginseng) roots from different origins. Arch. Pharm. Res. 31, 330-336. https://doi.org/10.1007/s12272-001-1160-2
  14. Loehrer, P. J. and Einhorn, L. H. (1984) Drugs five years later. Cisplatin. Ann. Intern. Med. 100, 704-713. https://doi.org/10.7326/0003-4819-100-5-704
  15. Maher, A. D., Cloarec, O., Patki, P., Craggs, M., Holmes, E., Lindon, J. C. and Nicholson, J. K. (2009) Dynamic biochemical information recovery in spontaneous human seminal fl uid reactions via 1H NMR kinetic statistical total correlation spectroscopy. Anal. Chem. 81, 288-295. https://doi.org/10.1021/ac801993m
  16. Maxuitenko, Y. Y., North, W. G. and Roebuck, B. D. (1997) Urinary taurine as a non-invasive marker of afl atoxin B1-induced hepatotoxicity: success and failure. Toxicology 118, 159-169. https://doi.org/10.1016/S0300-483X(96)03610-4
  17. Muggia, F. (2009) Platinum compounds 30 years after the introduction of cisplatin: implications for the treatment of ovarian cancer. Gynecol. Oncol. 112, 275-281. https://doi.org/10.1016/j.ygyno.2008.09.034
  18. Nicholson, J. K., Connelly, J., Lindon, J. C. and Holmes, E. (2002) Metabonomics: a platform for studying drug toxicity and gene function. Nat. Rev. Drug Discov. 1, 153-161. https://doi.org/10.1038/nrd728
  19. Nicholson, J. K., Lindon, J. C. and Holmes, E. (1999) 'Metabonomics': understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica. 29, 1181-1189. https://doi.org/10.1080/004982599238047
  20. Portilla, D., Li, S., Nagothu, K. K., Megyesi, J., Kaissling, B., Schnackenberg, L., Safi rstein, R. L. and Beger, R. D. (2006) Metabolomic study of cisplatin-induced nephrotoxicity. Kidney International 69, 2194-2204. https://doi.org/10.1038/sj.ki.5000433
  21. Pruefer, F. G., Lizarraga, F., Maldonado, V. and Melendez-Zajgla, J. (2008) Participation of Omi Htra2 serine-protease activity in the apoptosis induced by cisplatin on SW480 colon cancer cells. J. Chemother. 20, 348-354. https://doi.org/10.1179/joc.2008.20.3.348
  22. Rozen, R., Tenenhouse, H. S. and Scriver, C. R. (1979). Taurine transport in renal brush-border-membrane vesicles. Biochem. J. 180, 245-248.
  23. Sands, C. J., Coen, M., Maher, A. D., Ebbels, T. M., Holmes, E., Lindon, J. C. and Nicholson, J. K. (2009) Statistical total correlation spectroscopy editing of 1H NMR spectra of biofl uids: application to drug metabolite profi le identifi cation and enhanced information recovery. Anal. Chem. 81, 6458-6466. https://doi.org/10.1021/ac900828p
  24. Smith, I. E. and Talbot, D. C. (1992) Cisplatin and its analogues in the treatment of advanced breast cancer: a review. Br. J. Cancer 65, 787-793. https://doi.org/10.1038/bjc.1992.169
  25. Sreekumar, A., Poisson, L. M., Rajendiran, T. M., Khan, A. P., Cao, Q., Yu, J., Laxman, B., Mehra, R., Lonigro, R. J., Li, Y., Nyati, M. K., Ahsan, A., Kalyana-Sundaram, S., Han, B., Cao, X., Byun, J., Omenn, G. S., Ghosh, D., Pennathur, S., Alexander, D. C., Berger, A., Shuster, J. R., Wei, J. T., Varambally, S., Beecher, C. and Chinnaiyan, A. M. (2009) Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression. Nature. 457, 910-914. https://doi.org/10.1038/nature07762
  26. Trygg, J. and Wold, S. (2002) Orthogonal projections to latent structures (O-PLS). J. Chemom. 16, 119-128. https://doi.org/10.1002/cem.695
  27. von der Maase, H., Hansen, S. W., Roberts, J. T., Dogliotti, L., Oliver, T., Moore, M. J., Bodrogi, I., Albers, P., Knuth, A., Lippert, C. M., Kerbrat, P., Sanchez Rovira, P., Wersall, P., Cleall, S. P., Roychowdhury, D. F., Tomlin, I., Visseren-Grul, C. M. and Conte, P. F. (2000) Gemcitabine and cisplatin versus methotrexate, vinblastine, doxorubicin, and cisplatin in advanced or metastatic bladder cancer: results of a large, randomized, multinational, multicenter, phase III study. J. Clin. Oncol. 18, 3068-3077.
  28. Wen, H., Kang, S., Song, Y., Sung, S. H. and Park, S. (2010a) Differentiation of cultivation sources of Ganoderma lucidum by NMR-based metabolomics approach. Phytochem. Anal. 21, 73-79. https://doi.org/10.1002/pca.1166
  29. Wen, H., Yoo, S. S., Kang, J., Kim, H. G., Park, J. S., Jeong, S., Lee, J. I., Kwon, H. N., Kang, S., Lee, D. H. and Park, S. (2010b) A new NMR-based metabolomics approach for the diagnosis of biliary tract cancer. J. Hepatol. 52, 228-233. https://doi.org/10.1016/j.jhep.2009.11.002
  30. Wiklund, S., Johansson, E., Sjostrom, L., Mellerowicz, E. J., Edlund, U., Shockcor, J. P., Gottfries, J., Moritz, T. and Trygg, J. (2008) Visualization of GC/TOF-MS-based metabolomics data for identification of biochemically interesting compounds using OPLS class Models. Anal. Chem. 80, 115-122. https://doi.org/10.1021/ac0713510
  31. Wishart, D. S. (2005) Metabolomics: the principles and potential applications to transplantation. Am. J. Transplant. 5, 2814-2820. https://doi.org/10.1111/j.1600-6143.2005.01119.x
  32. Yao, X., Panichpisal, K., Kurtzman, N. and Nugent, K. (2007) Cisplatin nephrotoxicity: a review. Am. J. Med. Sci. 334, 115-124. https://doi.org/10.1097/MAJ.0b013e31812dfe1e

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