Advertisement

Metabolomics of Cancer

Protocol
First Online:
Part of the Methods in Molecular Biology book series (MIMB, volume 520)

Summary

Metabolomics, one of the “omic” sciences in systems biology, is the global assessment and validation of endogenous small-molecule biochemicals (metabolites) within a biologic system. Initially, putative quantitative metabolic biomarkers for cancer detection and/or assessment of efficacy of anticancer treatment are usually discovered in a preclinical setting (using animal and human cell cultures), followed by translational validation of these biomarkers in biofluid or tumor tissue. Based on the tumor origin, various biofluids, such as blood, urine, and expressed prostatic secretions, can be used for validating metabolic biomarkers noninvasively in cancer patients. Metabolite detection and quantification is usually carried out by nuclear magnetic resonance (NMR) spectroscopy, while mass spectrometry (MS) provides another highly sensitive metabolomics technology. Usually, sophisticated statistical analyses are carried out either on spectroscopic or on quantitative metabolic data sets to provide meaningful information about the metabolic makeup of the sample. Various metabolic biomarkers, related to glycolysis, mitochondrial citric cycle acid, choline and fatty acid metabolism, were recently reported to play important roles in cancer development and responsiveness to anticancer treatment using NMR-based metabolic profiling.

Carefully designed and validated protocols for sample handling and sample extraction followed by appropriate NMR techniques and statistical analyses, which are required to establish quantitative 1H-NMR-based metabolomics as a reliable analytical tool in the area of cancer biomarker discovery, are discussed in the present chapter.

Keywords

Endogenous metabolites Blood extraction Magic angle spinning NMR Principal component analysis Glycolysis Choline metabolism Quantitative metabolomics 
This is a preview of subscription content, log in to check access.

Notes

Acknowledgments

The authors would like to thank Jaimi L. Brown, B.S., for her continuous help in developing and validating sample preparation protocols, as well as Dr. Eduard J. Gamito for his help with statistical methods. This work was supported by the National Institutes of Health grants R21 CA112216 (KG), P50 CA103175 (JHU ICMIC Program, KG), R21 CA108624 (NJS) and P30 CA046934 (NJS).

References

  1. 1.
    Griffin, J.L., and Shockcor, J.P. (2004) Metabolic profiles of cancer cells. Nat. Rev. 4, 551–560.CrossRefGoogle Scholar
  2. 2.
    Griffin, J.L., and Kauppinen, R.A. (2007) Tumour metabolomics in animal models of human cancer. J. Proteome Res. 6, 498–505.PubMedCrossRefGoogle Scholar
  3. 3.
    Glunde, K., and Serkova, N.J. (2006) Therapeutic targets and biomarkers identified in cancer choline phospholipid metabolism. Pharmacogenomics. 7, 1109–1123.PubMedCrossRefGoogle Scholar
  4. 4.
    Costello, L.C., and Franklin, R.B. (2005) “Why do tumour cells glycolyse?”: from glycolysis through citrate to lipogenesis. Mol. Cell Biochem. 280, 1–8.PubMedCrossRefGoogle Scholar
  5. 5.
    Griffin, J.L., and Kauppinen, R.A. (2007) A metabolomics perspective of human brain tumours. FEBS J. 274, 1132–1139.PubMedCrossRefGoogle Scholar
  6. 6.
    Millis, K., Weybright, P., Campbell, N., Fletcher, J.A., Fletcher, C.D., Cory, D.G., (1999) Classification of human liposarcoma and lipoma using ex vivo proton NMR spectroscopy. Magn. Reson. Med. 41, 257–267.PubMedCrossRefGoogle Scholar
  7. 7.
    Nicholson, J.K., and Wilson, I.D. (2003) Understanding “global” systems biology: metabolomics and the continuum of metabolism. Nat. Rev. 2, 668–676.CrossRefGoogle Scholar
  8. 8.
    Morvan, D., and Demidem, A. (2007) Metabolomics by proton nuclear magnetic resonance spectroscopy of the response to chloroethylnitrosourea reveals drug efficacy and tumor adaptive metabolic pathways. Cancer Res. 67, 2150–2159.PubMedCrossRefGoogle Scholar
  9. 9.
    Odunsi, K., Wollman, R.M., Ambrosone, C.B., Hutson, A., McCann, S.E., Tammela, J., (2005) Detection of epithelial ovarian cancer using 1H-NMR-based metabolomics. Int. J. Cancer. 113, 782–788.PubMedCrossRefGoogle Scholar
  10. 10.
    Serkova, N.J., and Niemann, C.U. (2006) Pattern recognition and biomarker validation using quantitative 1H-NMR-based metabolomics. Expert Rev. Mol. Diagn. 6, 717–731.PubMedCrossRefGoogle Scholar
  11. 11.
    Weckwerth, W., and Morgenthal, K. (2005) Metabolomics from pattern recognition to biological interpretation. Drug Disc. Today. 10, 1551–1558.CrossRefGoogle Scholar
  12. 12.
    Wishart, D.S., Tzur, D., Knox, C., Eisner, R., Guo, A.C., Young, N., (2007) HMDB: the human metabolome database. Nucleic Acids Res. 35, D521–D526.PubMedCrossRefGoogle Scholar
  13. 13.
    Schmidt, C. (2004) Metabolomics takes its place as latest up-and-coming “omic” science. J. Natl. Cancer Inst. 96, 732–734.PubMedCrossRefGoogle Scholar
  14. 14.
    Gottschalk, S., Anderson, N., Hainz, C., Eckhardt, G., and Serkova, N.J. (2004) Imatinib (STI571)-mediated changes in glucose metabolism in human leukemia BCR-ABL-positive cells. Clin. Cancer Res. 10, 6661–6668.PubMedCrossRefGoogle Scholar
  15. 15.
    King, G.F., and Kuchel, P.W. (1994) Theoretical and practical aspects of NMR studies of cells. Immunomethods. 4, 85–97.PubMedCrossRefGoogle Scholar
  16. 16.
    Katz-Brull, R., Seger, D., Rivenson-Segal, D., Rushkin, E., and Degani, H. (2002) Metabolic markers of breast cancer: enhanced choline metabolism and reduced choline-ether-phospholipid synthesis. Cancer Res. 62, 1966–1970.PubMedGoogle Scholar
  17. 17.
    Franks, S.E., Smith, M.R., Arias-Mendoza, F., Shaller, C., Padavic-Shaller, C., Kappler, F., (2002) Phosphomonoester concentrations differ between chronic lymphocytic leukemia cells and normal human lymphocytes. Leuk. Res. 26, 919–926.PubMedCrossRefGoogle Scholar
  18. 18.
    Beloueche-Babari, M., Jackson, L.E., Al-Saffar, N.M., Eccles, S.A., Raynaud, F.I., Workman, P., (2006) Identification of magnetic resonance detectable metabolic changes associated with inhibition of phosphoinositide 3-kinase signaling in human breast cancer cells. Mol. Cancer Ther. 5, 187–196.PubMedCrossRefGoogle Scholar
  19. 19.
    Glunde, K., Jie, C., and Bhujwalla, Z.M. (2007) Mechanisms of indomethacin-induced alterations in the choline phospholipid metabolism of breast cancer cells. Neoplasia. 8, 758–771.CrossRefGoogle Scholar
  20. 20.
    Glunde, K., Ackerstaff, E., Natarajan, K., Artemov, D., and Bhujwalla, Z.M. (2002) Real-time changes in 1H- and 31P-NMR spectra of malignant human mammary epithelial cells during treatment with the anti-inflammatory agent indomethacin. Magn. Reson. Med. 48, 819–825.PubMedCrossRefGoogle Scholar
  21. 21.
    Flogel, U., Niendorf, T., Serkova, N., Brand, A., Henke, J., and Leibfritz, D. (1995) Changes in organic solutes, volume, energy state, and metabolism associated with osmotic stress in a glial cell line: a multinuclear NMR study. Neurochem. Res. 20, 793–802.PubMedCrossRefGoogle Scholar
  22. 22.
    Maxwell, R.J., Martinez-Perez, I., Cerdan, S., Cabanas, M.E., Arus, C., Moreno, A., (1998) Pattern recognition analysis of 1H-NMR spectra from perchloric acid extracts of human brain tumor biopsies. Magn. Reson. Med. 39, 869–877.PubMedCrossRefGoogle Scholar
  23. 23.
    Gribbestad, I.S., Sitter, B., Lundgren, S., Krane, J., and Axelson, D. (1999) Metabolite composition in breast tumors examined by proton nuclear magnetic resonance spectroscopy. Anticancer Res. 19, 1737–1746.PubMedGoogle Scholar
  24. 24.
    Jordan, B.F., Black, K., Robey, I.F., Runquist, M., Powis, G., and Gillies, R.J. (2005) Metabolite changes in HT-29 xenograft tumors following HIF-1α inhibition with PX-478 as studied by MR spectroscopy in vivo and ex vivo. NMR Biomed. 18, 430–439.PubMedCrossRefGoogle Scholar
  25. 25.
    Sitter, B., Sonnewald, U., Spraul, M., Fjosne, H.E., and Gribbestad, I.S. (2002) High-resolution magic angle spinning MRS of breast cancer tissue. NMR Biomed. 15, 327–337.PubMedCrossRefGoogle Scholar
  26. 26.
    Sitter, B., Lundgren, S., Bathen, T.F., Halgunset, J., Fjosne, H.E., and Gribbestad, I.S. (2006) Comparison of HR MAS MR spectroscopic profiles of breast cancer tissue with clinical parameters. NMR Biomed. 19, 30–40.Google Scholar
  27. 27.
    Bathen, T.F., Jensen, L.R., Sitter, B., Fjosne, H.E., Halgunset, J., Axelson, D.E., et al. (2007) MR-determined metabolic phenotype of breast cancer in prediction of lymphatic spread, grade, and hormone status. Breast Cancer Res. Treat. 104, 181–189.Google Scholar
  28. 28.
    Burns, M.A., He, W., Wu, C.L., and Cheng, L.L. (2004) Quantitative pathology in tissue MR spectroscopy based human prostate metabolomics. Technol. Cancer Res. Treat. 3, 591–598.PubMedGoogle Scholar
  29. 29.
    Cheng, L.L., Burns, M.A., Taylor, J.L., He, W., Halpern, E.F., McDougal, W.S., (2005) Metabolic characterization of human prostate cancer with tissue magnetic resonance spectroscopy. Cancer Res. 65, 3030–3034.PubMedGoogle Scholar
  30. 30.
    Swanson, M.G., Zektzer, A.S., Tabatabai, Z.L., Simko, J., Jarso, S., Keshari, K.R., et al. Quantitative analysis of prostate metabolites using 1H HR-MAS spectroscopy. Magn. Reson. Med. 55, 1257–1264.Google Scholar
  31. 31.
    Valonen, P.K., Griffin, J.L., Lehtimaki, K.K., Liimatainen, T., Nicholson, J.K., Grohn, O.H.J., (2005) High-resolution magic-angle-spinning 1H-NMR spectroscopy reveals different responses in choline-containing metabolites upon gene therapy-induced programmed cell death in rat brain glioma. NMR Biomed. 18, 252–259.PubMedCrossRefGoogle Scholar
  32. 32.
    Tugnoli, V., Schenetti, L., Mucci, A., Nocetti, L., Toraci, C., Mavilla, L., (2005) A comparison between in vivo and ex vivo HR-MAS 1H-MR spectra of a pediatric posterior fossa lesions. Int. J. Mol. Med. 16, 301–307.PubMedGoogle Scholar
  33. 33.
    Sitter, B., Bathen, T., Hagen, B., Arentz, C., Skjeldestad, F.E., and Gribbestad, I.S. (2004) Cervical cancer tissue characterized by high-resolution magic angle spinning MR spectroscopy. MAGMA. 16, 174–181.PubMedCrossRefGoogle Scholar
  34. 34.
    Lyng, H., Sitter, B., Beathen, T.F., Jensen, L.R., Sundfor, K., Kristensen, G.B., (2007) Metabolic mapping by use of high-resolution magic angle spinning 1H-MR spectroscopy for assessment of apoptosis in cervical carcinomas. BMC Cancer. 7, 11–23.PubMedCrossRefGoogle Scholar
  35. 35.
    Tate, A.R., Foxall, P.J., Holmes, E., Moka, D., Spraul, M., Nicholson, J.K., (2000) Distinction between normal and renal cell carcinoma kidney cortical biopsy samples using pattern recognition of 1H magic angle spinning (MAS) NMR spectra. NMR Biomed. 13, 64–71.PubMedCrossRefGoogle Scholar
  36. 36.
    Morvan, D., Demidem, A., Papon, J., De Latour, M., and Madelmont, J.C. (2002) Melanoma tumors acquire a new phospholipid metabolism phenotype under cystemustine as revealed by high-resolution magic angle spinning proton nuclear magnetic resonance spectroscopy of intact tumor samples. Cancer Res. 62, 1890–1897.PubMedGoogle Scholar
  37. 37.
    Sullentrop, F., Moka, D., Neubauer, S., Haupt, G., Engelmann, U., Hahn, J., (2002) 31P-NMR spectroscopy of blood plasma: determination and quantification of phospholipid classes in patients with renal cell carcinoma. NMR Biomed. 15, 60–68.PubMedCrossRefGoogle Scholar
  38. 38.
    Bathen, T.F., Engan, T., Krane, J., and Axelson, D. (2000) Analysis and classification of proton NMR spectra of lipoprotein fractions from healthy volunteers and patients with cancer or CHD. Anticancer Res. 20, 2398–2408.Google Scholar
  39. 39.
    Chen, H., Pan, Z., Talaty, N., Raftery, D., and Cooks, R.G. (2006) Combining desorption electrospray ionization mass spectrometry and nuclear magnetic resonance for differential metabolomics without sample preparation. Rapid Commun. Mass Spectrom. 20, 1577–1584.PubMedCrossRefGoogle Scholar
  40. 40.
    Serkova, N.J., Gamito, E.J., Jones, R.H., O’Donnell, C., Hedlund, T., and Crawford, E.D. (2008) Validation of citrate and derivatives in expressed prostatic secretions to predict prostate cancer: high-resolution 1H-NMR study. Prostate 68, 620–628.Google Scholar
  41. 41.
    Kline, E.E., Treat, E.G., Averna, T.A., Davis, M.S., Smith, A.Y., and Sillerud, L.O. (2006) Citrate concentrations in human seminal fluids and expressed prostatic fluid determined via 1H nuclear magnetic resonance spectroscopy outperform prostate specific antigen in prostate cancer detection. J. Urol. 176, 2274–2279.PubMedCrossRefGoogle Scholar
  42. 42.
    Dunne, V.G., Bhattachayya, S., Besser, M., Rae, C., and Griffin, J.L. (2005) Metabolites from cerebrospinal fluid in aneurismal subarachnoid haemorrhage correlate with vasospasm and clinical outcome: a pattern-recognition 1H NMR study. NMR Biomed. 18, 24–33.PubMedCrossRefGoogle Scholar
  43. 43.
    Boss, E.A., Moolenaar, S.H., Massunger, L.F.A.G., Boonstra, H., Engelke, U.F.H., deJong, J.G.N., et al. High-resolution proton nuclear magnetic resonance spectroscopy of ovarian fluid. NMR Biomed. 13, 297–305.Google Scholar
  44. 44.
    Pilatus, U., Aboagye, E., Artemov, D., Mori, N., Ackerstaff, E., and Bhujwalla, Z.M. (2001) Real-time measurements of cellular oxygen consumption, pH, and energy metabolism using nuclear magnetic resonance spectroscopy. Magn. Reson. Med. 45, 749–755.PubMedCrossRefGoogle Scholar

Copyright information

© Humana Press, a part of Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Department of Anesthesiology and RadiologyUniversity of Colorado at Denver and Health Sciences CenterAuroraUSA

Personalised recommendations

Cite protocol

Buy options