Skip to main content

Metabonomics of Hepatocellular Carcinoma

  • Chapter
  • 1294 Accesses

Abstract

Hepatocellular carcinoma (HCC) is the third most frequent cause of cancer death. Its lethal impact is unlikely to change significantly in the coming years due to a limited understanding of disease pathogenesis on the molecular, cellular and environmental levels. Any new knowledge on preventive, diagnostic and therapeutic approaches of HCC will be helpful for reducing the mortality rate.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   189.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Gish R G. Hepatocellular carcinoma: overcoming challenges in disease management. Clin Gastroenterol Hepatol, 2006, 4: 252–261.

    Article  PubMed  Google Scholar 

  2. Nicholson J K, Lindon J C, Holmes E. “Metabonomics”: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica, 1999, 29: 1181–1189.

    Article  PubMed  CAS  Google Scholar 

  3. Oliver S G. Yeast as a navigational aid in genome analysis. Microbiology-UK, 1997, 143: 1483–1487.

    Article  CAS  Google Scholar 

  4. Nicholson J K, Connelly J, Lindon J C, et al. Metabonomics: a platform for studying drug toxicity and gene function. Nat Rev Drug Discov, 2002, 1: 153–161.

    Article  PubMed  CAS  Google Scholar 

  5. Nicholson J K, Wilson I D. Understanding “global” systems biology: metabonomics and the continuum of metabolism. Nat Rev Drug Discovery, 2003, 2: 668–676.

    Article  CAS  Google Scholar 

  6. Odunsi K, Wollman R M, Ambrosone C B, et al. Detection of epithelial ovarian cancer using H-1-NMR-based metabonomics. Int J Cancer, 2005, 113: 782–788.

    Article  PubMed  CAS  Google Scholar 

  7. Gowda G A N, Zhang S, Gu H, et al. Metabolomics-based methods for early disease diagnostics. Expert Rev Mol Diagn, 2008, 8: 617–633.

    Article  PubMed  CAS  Google Scholar 

  8. Keun H C, Sidhu J, Pchejetski D, et al. Serum molecular signatures of weight change during early breast cancer chemotherapy. Clin Cancer Res, 2009, 15: 6716–6723.

    Article  PubMed  CAS  Google Scholar 

  9. Robertson D G, Reily M D, Baker J D. Metabonomics in pharmaceutical discovery and development. J Proteome Res, 2007, 6: 526–539.

    Article  PubMed  CAS  Google Scholar 

  10. Spratlin J L, Serkova N J, Eckhardt S G. Clinical applications of metabolomics in oncology: a review. Clin Cancer Res, 2009, 15: 431–440.

    Article  PubMed  CAS  Google Scholar 

  11. Williams R E, Lenz E A, Evans J A, et al. A combined H-1 NMR and HPLC-MS-based metabonomic study of urine from obese (fa/fa) Zucker and normal Wistar-derived rats. J Pharm Biomed Anal, 2005, 38: 465–471.

    Article  PubMed  CAS  Google Scholar 

  12. Griffin J L, Nicholls A W. Metabolomics as a functional genomic tool for understanding lipid dysfunction in diabetes, obesity and related disorders. Pharmacogenomics, 2006, 7: 1095–1107.

    Article  PubMed  CAS  Google Scholar 

  13. T Kuhara. Gas chromatographic—mass spectrometric urinary metabolome analysis to study mutations of inborn errors of metabolism. Mass Spectrom Rev, 2005, 24: 814–827.

    Article  PubMed  CAS  Google Scholar 

  14. Mao Y, Huang X, Yu K, et al. Metabonomic analysis of hepatitis B virus-induced liver failure: identification of potential diagnostic biomarkers by fuzzy support vector machine. J Zhejiang Univ Sci B, 2008, 9: 474–481.

    Article  PubMed  CAS  Google Scholar 

  15. Jia L W, C Wang, Kong H W, et al. Plasma phospholipid metabolic profiling and biomarkers of mouse IgA nephropathy. Metabolomics, 2006, 2: 95–104.

    Article  CAS  Google Scholar 

  16. Brindle J T, Antti H, Holmes E, et al. Rapid and noninvasive diagnosis of the presence and severity of coronary heart disease using 1H-NMR-based metabonomics. Nat Med, 2002, 8: 1439–1444.

    Article  PubMed  CAS  Google Scholar 

  17. Gu J, Cao X. Conceptual consideration of cancer, challenges and opportunities for cancer biotherapy. Chinese J Cancer Biotherapy, 2008, 15: 2.

    Google Scholar 

  18. Holmes E, Tsang T M, Huang J T J, et al. Metabolic profiling of CSF: evidence that early intervention may impact on disease progression and outcome in schizophrenia. PLoS Med, 2006, 3: 1420–1428.

    CAS  Google Scholar 

  19. Grootveld M, Silwood C J L. H-1 NMR analysis as a diagnostic probe for human saliva. Biochem Biophys Res Commun, 2005, 329: 1–5.

    Article  PubMed  CAS  Google Scholar 

  20. Gowda G A, Shanaiah N, Cooper A, et al. Visualization of bile homeostasis using H-1-NMR spectroscopy as a route for assessing liver cancer. Lipids, 2009, 44: 27–35.

    Article  CAS  Google Scholar 

  21. Tse G M K, Cheung H S, Pang L M, et al. Characterization of lesions of the breast with proton MR spectroscopy: Comparison of carcinomas, benign lesions, and phyllodes tumors. Am J Roentgenol, 2003, 181: 1267–1272.

    Google Scholar 

  22. Tugnoli V, Reggiani A, Beghelli R, et al. Magnetic resonance spectroscopy and high performance liquid chromatography of neoplastic human renal tissues. Anticancer Res, 2003, 23: 1541–1548.

    PubMed  CAS  Google Scholar 

  23. Gika H G, Macpherson E, Theodoridis G A, et al. Evaluation of the repeatability of ultra-performance liquid chromatography-TOF-MS for global metabolic profiling of human urine samples. Journal of Chromatography B-Analytical Technologies in the Biomedical and Life Sciences, 2008, 871: 299–305.

    Article  CAS  Google Scholar 

  24. Teahan O, Gamble S, Holmes E, et al. Impact of analytical bias in metabonomic studies of human blood serum and plasma. Anal Chem, 2006, 78: 4307–4318.

    Article  PubMed  CAS  Google Scholar 

  25. Boyanton B L Jr., Blick K E. Stability studies of twenty-four analytes in human plasma and serum. Clin Chem, 2002, 48: 2242–2247.

    PubMed  CAS  Google Scholar 

  26. Deprez S, Sweatman B C, Connor S C, et al. Optimization of collection, storage and preparation of rat plasma for 1H NMR spectroscopic analysis in toxicology studies to determine inherent variation in biochemical profiles. J Pharm Biomed Anal, 2002, 30: 1297–1310.

    Article  PubMed  CAS  Google Scholar 

  27. Pelczer I. High-resolution NMR for metabomics. Curr Opin Drug Discovery Dev, 2005, 8: 127–133.

    CAS  Google Scholar 

  28. Tian J, Sang P, Gao P, et al. Optimization of a GC-MS metabolic fingerprint method and its application in characterizing engineered bacterial metabolic shift. J Sep Sci, 2009, 32: 2281–2288.

    Article  PubMed  CAS  Google Scholar 

  29. Myint K T, Aoshima K, Tanaka S, et al. Quantitative profiling of polar cationic metabolites in human cerebrospinal fluid by reversed-phase nanoliquid chromatography/mass spectrometry. Analytical Chemistry, 2009, 81: 1121–1129.

    Article  PubMed  CAS  Google Scholar 

  30. Plumb R S, Johnson K A, Rainville P, et al. The detection of phenotypic differences in the metabolic plasma profile of three strains of Zucker rats at 20 weeks of age using ultra-performance liquid chromatography/orthogonal acceleration time-of-flight mass spectrometry. Rapid Commun Mass Spectrom, 2006, 20: 2800–2806.

    Article  PubMed  CAS  Google Scholar 

  31. Novakova L, Solichova D, Solich P. Advantages of ultra performance liquid chromatography over high-performance liquid chromatography: Comparison of different analytical 2 approaches during analysis of diclofenac gel. J Sep Sci, 2006, 29: 2433–2443.

    Article  PubMed  CAS  Google Scholar 

  32. Trygg J, Holmes E, Lundstedt T. Chemometrics in metabonomics. J Proteome Res, 2007, 6: 469–479.

    Article  PubMed  CAS  Google Scholar 

  33. Nordstrom A, O’Maille G, Qin C, et al. Nonlinear data alignment for UPLC-MS and HPLC-MS based metabolomics: Quantitative analysis of endogenous and exogenous metabolites in human serum. Anal Chem, 2006, 78: 3289–3295.

    Article  PubMed  Google Scholar 

  34. Craig A, Cloareo O, Holmes E, et al. Scaling and normalization effects in NMR spectroscopic metabonomic data sets. Anal Chem, 2006, 78: 2262–2267.

    Article  PubMed  CAS  Google Scholar 

  35. Martin F P, Rezzi S, Philippe D, et al. Metabolic assessment of gradual development of moderate experimental colitis in IL-10 deficient mice. J Proteome Res, 2009, 8: 2376–2387.

    Article  PubMed  CAS  Google Scholar 

  36. Holmes E, Nicholls A W, Lindon J C, et al. Chemometric models for toxicity classification based on NMR spectra of biofluids. Chem Res Toxicol, 2000, 13: 471–478.

    Article  PubMed  CAS  Google Scholar 

  37. Bollard M E, Keun H C, Beckonert O, et al. Comparative metabonomics of differential hydrazine toxicity in the rat and mouse. Toxicol Appl Pharmacol, 2005, 204: 135–151.

    Article  PubMed  CAS  Google Scholar 

  38. Jansen J J, Hoefsloot H C J, van der Greef J, et al. ASCA: analysis of multivariate data obtained from an experimental design. J Chemom, 2005, 19: 469–481.

    Article  CAS  Google Scholar 

  39. Chen J, Shan Y, Yan Q, et al. Science in China Series B: chemistry, 2009, 39: 1268–1276.

    Google Scholar 

  40. Chen J, Zhao X, Fritsche J, et al. Practical approach for the identification and isomer elucidation of biomarkers detected in a metabonomic study for the discovery of individuals at risk of diabetes by integrating the chromatographic and mass spectrometric information. Anal Chem, 2008, 80: 1280–1289.

    Article  PubMed  CAS  Google Scholar 

  41. Xue R, Dong L, Zhang S, et al. Investigation of volatile biomarkers in liver cancer blood using solid-phase microextraction and gas chromatography/mass spectrometry. Rapid Commun Mass Spectrom, 2008, 22: 1181–1186.

    Article  PubMed  CAS  Google Scholar 

  42. Xue R, Lin Z, Deng C, et al. A serum metabolomic investigation on hepatocellular carcinoma patients by chemical derivatization followed by gas chromatography/mass spectrometry. Rapid Commun Mass Spectrom, 2008, 22: 3061–3068.

    Article  PubMed  CAS  Google Scholar 

  43. Chen J, Wang W, Lv S, et al. Metabonomics study of liver cancer based on ultra performance liquid chromatography coupled to mass spectrometry with HILIC and RPLC separations. Anal Chim Acta, 2009, 650: 3–9.

    Article  PubMed  CAS  Google Scholar 

  44. Wu H, Xue R, Dong L, et al. Metabolomic profiling of human urine in hepatocellular carcinoma patients using gas chromatography/mass spectrometry. Anal Chim Acta, 2009, 648: 98–104.

    Article  PubMed  CAS  Google Scholar 

  45. Yin P, Wan D, Zhao C, et al. A metabonomic study of hepatitis B-induced liver cirrhosis and hepatocellular carcinoma by using RP-LC and HILIC coupled with mass spectrometry. Mol BioSyst, 2009, 5: 868–876.

    Article  PubMed  CAS  Google Scholar 

  46. Wiklund S, Johansson E, Sjostrom L, et al. Visualization of GC/TOF-MS-based metabolomics data for identification of biochemically interesting compounds using OPLS class models. Anal Chem, 2008, 80: 115–122.

    Article  PubMed  CAS  Google Scholar 

  47. Chmura S J, Nodzenski E, Beckett M A, et al. Loss of ceramide production confers resistance to radiation-induced apoptosis. Cancer Res, 1997, 57: 1270–1275.

    PubMed  CAS  Google Scholar 

  48. Ockner R K, Kaikaus R M, Bass N M. Fatty-acid metabolism and the pathogenesis of hepatocellular carcinoma: review and hypothesis. Hepatology, 1993, 18: 669–676.

    Article  PubMed  CAS  Google Scholar 

  49. Roth E. Immune and cell modulation by amino acids. Clinical Nutrition, 2007, 26: 535–544.

    Article  PubMed  CAS  Google Scholar 

  50. Limbach P A, Crain P F, McCloskey J A. Summary: the modified nucleosides of RNA. Nucleic Acids Res, 1994, 22: 2183–2196.

    Article  PubMed  CAS  Google Scholar 

  51. Borek E, Baliga B S, Gehrke C W, et al. High turnover rate of transfer RNA in tumor tissue. Cancer Res, 1977, 37: 3362–3366.

    PubMed  CAS  Google Scholar 

  52. Langridge J I, McClure T D, el-Shakawi S, et al. Gas chromatography/mass spectrometric analysis of urinary nucleosides in cancer patients; potential of modified nucleosides as tumor markers. Rapid Commun. Mass Spectrom, 1993, 7: 427–434.

    Article  PubMed  CAS  Google Scholar 

  53. Rasmuson T, Bjork G R. Urinary excretion of pseudouridine and prognosis of patients with malignant lymphoma. Acta Oncol, 1995, 34: 61–67.

    Article  PubMed  CAS  Google Scholar 

  54. Frickenschmidt A, Frohlich H, Bullinger D, et al. Metabonomics in cancer diagnosis: mass spectrometry-based profiling of urinary nucleosides from breast cancer patients. Biomarkers, 2008, 13: 435–449.

    Article  PubMed  CAS  Google Scholar 

  55. Vold B S, Kraus L E, Rimer V G, et al. Use of a monoclonal antibody to detect elevated levels of a modified nucleoside, N-[9-(beta-D-ribofuranosyl) purin-6-ylcarbamoyl]-L-threonine, in the urine of breast cancer patients. Cancer Research, 1986, 46: 3164–3167.

    PubMed  CAS  Google Scholar 

  56. Liebich H M, Lehmann R, Xu G, et al. Application of capillary electrophoresis in clinical chemistry: the clinical value of urinary modified nucleosides. Journal of Chromatography, 2000, 745: 189–196.

    Article  PubMed  CAS  Google Scholar 

  57. Liebich H M, Xu G, Di Stefano C, et al. Capillary electrophoresis of urinary normal and modified nucleosides of cancer patients. J Chromatogr A, 1998, 793: 341–347.

    Article  PubMed  CAS  Google Scholar 

  58. Xu G, Liebich H M, Lehmann R, et al. Capillary electrophoresis of urinary normal and modified nucleosides of cancer patients. Methods Mol Biol, 2001, 162: 459–474.

    PubMed  CAS  Google Scholar 

  59. Nakano K, Nakao T, Schram K H, et al. Urinary excretion of modified nucleosides as biological marker of RNA turnover in patients with cancer and AIDS. Clinica Chimica Acta; International Journal of Clinical Chemistry, 1993, 218: 169–183.

    Article  PubMed  CAS  Google Scholar 

  60. Fischbein A, Sharma O K, Valciukas J A, et al. Urinary excretion of modified nucleosides in patients with acquired immune deficiency syndrome (AIDS) and individuals at high risk of AIDS. Cancer Detect Prev, 1985, 8: 271–277.

    PubMed  CAS  Google Scholar 

  61. Borek E, Sharma O K, Buschman F L, et al. Altered excretion of modified nucleosides and beta-aminoisobutyric acid in subjects with acquired immunodeficiency syndrome or at risk for acquired immunodeficiency syndrome. Cancer Res, 1986, 46: 2557–2561.

    PubMed  CAS  Google Scholar 

  62. Koshida K, Harmenberg J, Stendahl U, et al. Urinary modified nucleosides as tumor markers in cancer of the urinary organs or female genital tract. Urol Res, 1985, 13: 213–218.

    Article  PubMed  CAS  Google Scholar 

  63. Nakano K, Shindo K, Yasaka T, et al. Reversed-phase high-performance liquid chromatographic investigation of mucosal nucleosides and bases and urinary modified nucleosides of gastrointestinal cancer patients. J Chromatogr, 1985, 343: 21–33.

    Article  PubMed  CAS  Google Scholar 

  64. Nakano K, Yasaka T, Schram K H, et al. Isolation and identification of urinary nucleosides. Applications of high-performance liquid chromatographic methods to the synthesis of 5′-deoxyxanthosine and the simultaneous determination of 5,6-dihydrouridine and pseudouridine. J Chromatogr, 1990, 515: 537–546.

    Article  PubMed  CAS  Google Scholar 

  65. Trewyn R W, Glaser R, Kelly D R, et al. Elevated nucleoside excretion by patients with nasopharyngeal carcinoma. Preliminary diagnostic/prognostic evaluations. Cancer, 1982, 49: 2513–2517.

    Article  PubMed  CAS  Google Scholar 

  66. Cho S H, Choi M H, Lee W Y, et al. Evaluation of urinary nucleosides in breast cancer patients before and after tumor removal. Clin Biochem, 2009, 42: 540–543.

    Article  PubMed  CAS  Google Scholar 

  67. Zheng Y, Xu G, Yang J, et al. Determination of urinary nucleosides by direct injection and coupled-column high-performance liquid chromatography. J Chromatogr B Analyt Technol Biomed Life Sci, 2005, 819: 85–90.

    Article  PubMed  CAS  Google Scholar 

  68. Jeng L B, Lo W Y, Hsu W Y, et al. Analysis of urinary nucleosides as helper tumor markers in hepatocellular carcinoma diagnosis. Rapid Commun Mass Spectrom, 2009, 23: 1543–1549.

    Article  PubMed  CAS  Google Scholar 

  69. Seidel A, Brunner S, Seidel P, et al. Modified nucleosides: an accurate tumor marker for clinical diagnosis of cancer, early detection and therapy control. British Journal of Cancer, 2006, 94: 1726–1733.

    PubMed  CAS  Google Scholar 

  70. Clark I, MacKenzie J W, McCoy J R, et al. Comparison of urinary modified nucleosides and bases in rats with hepatomas and nephroblastomas. Recent Results Cancer Res, 1983, 84: 388–400.

    PubMed  CAS  Google Scholar 

  71. Yang J, Xu G W, Zheng Y F, et al. Diagnosis of liver cancer using HPLC-based metabonomics avoiding false-positive result from hepatitis and hepatocirrhosis diseases. J Chromatogr B Analyt Technol Biomed Life Sci, 2004, 813: 59–65.

    Article  PubMed  CAS  Google Scholar 

  72. El-Serag H B, Rudolph K L. Hepatocellular carcinoma: epidemiology and molecular carcinogenesis. Gastroenterology, 2007, 132: 2557–2576.

    Article  PubMed  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Zhejiang University Press, Hangzhou and Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Yin, P., Xu, G. (2012). Metabonomics of Hepatocellular Carcinoma. In: Primary Liver Cancer. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28702-2_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-28702-2_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28701-5

  • Online ISBN: 978-3-642-28702-2

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics