American Journal of Pharmacogenomics

, Volume 5, Issue 5, pp 293–302

Detection of Resistance to Imatinib by Metabolic Profiling

Clinical and Drug Development Implications
Pharmacodiagnostics

Abstract

Acquired resistance to imatinib mesylate is an increasing and continued challenge in the treatment of BCR-ABL tyrosine kinase positive leukemias as well as gastrointestinal stromal tumors. Stable isotope-based dynamic metabolic profiling (SIDMAP) studies conducted in parallel with the development and clinical testing of imatinib revealed that this targeted drug is most effective in controlling glucose transport, direct glucose oxidation for RNA ribose synthesis in the pentose cycle, as well as de novo long-chain fatty acid synthesis. Thus imatinib deprives transformed cells of the key substrate of macromolecule synthesis, malignant cell proliferation, and growth. Tracer-based magnetic resonance spectroscopy studies revealed a restitution of mitochondrial glucose metabolism and an increased energy state by reversing the Warburg effect, consistent with a subsequent decrease in anaerobic glycolysis. Recent in vitro SIDMAP studies that involved myeloid cells isolated from patients who developed resistance against imatinib indicated that non-oxidative ribose synthesis from glucose and decreased mitochondrial glucose oxidation are reliable metabolic signatures of drug resistance and disease progression. There is also evidence that imatinib-resistant cells utilize alternate substrates for macromolecule synthesis to overcome limited glucose transport controlled by imatinib. The main clinical implications involve early detection of imatinib resistance and the identification of new metabolic enzyme targets with the potential of overcoming drug resistance downstream of the various genetic and BCR-ABL-expression derived mechanisms. Metabolic profiling is an essential tool used to predict, clinically detect, and treat targeted drug resistance. This need arises from the fact that targeted drugs are narrowly conceived against genes and proteins but the metabolic network is inherently complex and flexible to activate alternative macromolecule synthesis pathways that targeted drugs fail to control.

References

  1. 1.
    Gadian DG. NMR applications to living systems. 2nd ed. London: Oxford University Press, 1995Google Scholar
  2. 2.
    Savage DG, Antman KH. Imatinib mesylate: a new oral targeted therapy. N Engl J Med 2002; 346: 683–93PubMedCrossRefGoogle Scholar
  3. 3.
    Deiniger MWN, Goldman JM, Lydon N, et al. The tyrosine kinase inhibitor CGP57148B selectively inhibits the growth of BCR-ABL positive cells. Blood 1997; 90: 3691–8Google Scholar
  4. 4.
    Vigneri P, Wang JY. Indication of apoptosis in chronic myelogenous leukemia cells through nuclear entrapment of BCR-ABL tyrosine kinase. Nat Med 2001; 7: 228–34PubMedCrossRefGoogle Scholar
  5. 5.
    Buchdunger E, Zimmermann J, Mett H, et al. Inhibition of the ABL protein-tyrosine kinase in vitro and in vivo by a 2-phenylaminopyrimidine derivative. Cancer Res 1996; 56: 100–4PubMedGoogle Scholar
  6. 6.
    Apperley JF, Gardembas M, Melo JV, et al. Response to imatinib mesylate in patients with chronic myeloproliferative diseases with rearrangements of the platelet-derived growth factor receptor beta. N Engl J Med 2002; 347: 481–7PubMedCrossRefGoogle Scholar
  7. 7.
    Demetri GD, von Mehren M, Blanke CD, et al. Efficacy and safety of imatinib mesylate in advanced gastrointestinal stromal tumors. N Engl J Med 2002 Aug 15; 347(7): 472–80PubMedCrossRefGoogle Scholar
  8. 8.
    Druker BJ, Talpaz M, Resta DJ, et al. Efficacy and safety of a specific inhibitor of the BCR-ABL tyrosine kinase in chronic myeloid leukemia. N Engl J Med 2001; 344: 1031–7PubMedCrossRefGoogle Scholar
  9. 9.
    Kantarjian H, Sawyers C, Hochhaus A, et al. Hematologic and cytogenetic responses to imatinib mesylate in chronic myelogenous leukemia [published erratum appears in N Engl J Med 2002, 347: 68]. N Engl J Med 2002; 346: 645–52PubMedCrossRefGoogle Scholar
  10. 10.
    Von Bubnoff N, Schneller F, Peschel C, et al. BCR-ABL gene mutations in relation to clinical resistance of Philadelphia-chromosome-positive leukemia to STI571: a prospective study. Lancet 2002; 359: 487–91CrossRefGoogle Scholar
  11. 11.
    Gorre ME, Mohammed M, Ellwood K, et al. Clinical resistance to STI-571 cancer therapy caused by BCR-ABL gene mutation or amplification. Science 2001; 293: 876–80PubMedCrossRefGoogle Scholar
  12. 12.
    Goldman JM, Melo JV. Chronic myeloid leukemia: advances in biology and new approaches to treatment. N Engl J Med 2003 Oct 9; 349(15): 1451–64PubMedCrossRefGoogle Scholar
  13. 13.
    Roche-Lestienne C, Soenen-Cornu V, Grardel-Duflos N, et al. Several types of mutations of the Abl gene can be found in chronic myeloid leukemia patients resistant to STI571, and they can pre-exist to the onset of treatment. Blood 2002; 100: 1014–8PubMedCrossRefGoogle Scholar
  14. 14.
    Campbell LJ, Patsouris C, Rayeroux KC, et al. BCR/ABL amplification in chronic myelocytic leukemia blast crisis following imatinib mesylate administration. Cancer Genet Cytogenet 2002; 139: 30–3PubMedCrossRefGoogle Scholar
  15. 15.
    Mahon FX, Belloc F, Lagarde V, et al. MDR1 gene overexpression confers resistance to imatinib mesylate in leukemia cell line models. Blood 2003; 101: 2368–73PubMedCrossRefGoogle Scholar
  16. 16.
    Ferrao PT, Frost MJ, Siah SP, et al. Overexpression of P-glycoprotein in K562 cells does not confer resistance to the growth inhibitory effects of imatinib (STI571) in vitro. Blood 2003 Dec 15; 102(13): 4499–4503. Epub 2003 Jul 24PubMedCrossRefGoogle Scholar
  17. 17.
    Tipping AJ, Mahon FX, Lagarde V, et al. Restoration of sensitivity to STI571 in STI571-resistant chronic myeloid leukemia cells. Blood 2001; 98: 3864–7PubMedCrossRefGoogle Scholar
  18. 18.
    Gatto S, Scappini B, Pham L, et al. The proteasome inhibitor PS-341 inhibits growth and induces apoptosis in BCR/ABL-positive cell lines sensitive and resistant to imatinib mesylate. Haematologica 2003; 88: 853–63PubMedGoogle Scholar
  19. 19.
    Mountford CE, Doran S, Lean CL, et al. Cancer pathology in the year 2000. Biophys Chem 1997; 68: 127–35PubMedCrossRefGoogle Scholar
  20. 20.
    Gillies RJ, Bhujwalla ZM, Evelhoch J, et al. Applications of magnetic resonance in model systems: tumor biology and physiology. Neoplasia 2000; 2: 139–51PubMedCrossRefGoogle Scholar
  21. 21.
    Evelhoch JL, Gillies TJ, Karczmar GS, et al. Applications of magnetic resonance in model systems: cancer therapeutics. Neoplasia 2000; 2: 152–65PubMedCrossRefGoogle Scholar
  22. 22.
    Griffin JL, Shockcor JP. Metabolic profiles of cancer cells. Nat Rev Cancer 2004; 4: 551–61PubMedCrossRefGoogle Scholar
  23. 23.
    Cornel EB, Heerschap A, Smits GA, et al. Magnetic resonance spectroscopy detects metabolic differences between seven Dunning rat prostate tumor sub-lines with different biological behavior. Prostate 1994; 25: 19–28PubMedCrossRefGoogle Scholar
  24. 24.
    Menard C, Smith IC, Somorjai RL, et al. Magnetic resonance spectroscopy of the malignant prostate gland after radiotherapy: a histopathologic study of diagnostic validity. Int J Radiat Oncol Biol Phys 2001; 50: 317–23PubMedCrossRefGoogle Scholar
  25. 25.
    McKnight TR. Proton magnetic resonance spectroscopic evaluation of brain tumor metabolism. Semin Oncol 2004; 31: 605–17PubMedCrossRefGoogle Scholar
  26. 26.
    Pucar D, Koutcher JA, Shah A, et al. Preliminary assessment of magnetic resonance spectroscopic imaging in predicting treatment outcome in patients with prostate cancer at high risk for relapse. Clin Prostate Cancer 2004 Dec; 3(3): 174–81PubMedGoogle Scholar
  27. 27.
    Aboagye EO, Bhujwalla ZM. Malignant transformation alters membrane choline phospholipids metabolism of human mammary epithelial cells. Cancer Res 1999; 59: 80–4PubMedGoogle Scholar
  28. 28.
    Glunde K, Ackerstaff E, Natarajan K, et al. 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 2002; 48: 819–25PubMedCrossRefGoogle Scholar
  29. 29.
    Franks SE, Smith MR, Arias-Mendoza F, et al. Phosphomonoester concentrations differ between chronic lymphocytic leukemia cells and normal human lymphocytes. Leukemia Res 2002; 26: 919–26CrossRefGoogle Scholar
  30. 30.
    Anthony ML, Zhao M, Brindle KM. Inhibition of phosphatidylcholine biosynthesis following induction of apoptosis in HL-60 cells. J Biol Chem 1999; 274: 19686–92PubMedCrossRefGoogle Scholar
  31. 31.
    Ronen SM, DiStefano F, McCoy CL, et al. Magnetic resonance detects metabolic changes associated with chemotherapy-associated apoptosis. Br J Cancer 1999; 80: 1035–41PubMedCrossRefGoogle Scholar
  32. 32.
    Williams SN, Anthony ML, Brindle KM. Induction of apoptosis in two mammalian cell lines results in increased levels of fructose-1,6-biphosphate and CDP-choline as determined by 31P-MRS. Magn Reson Med 1998; 40: 411–20PubMedCrossRefGoogle Scholar
  33. 33.
    Muruganandham M, Alfieri AA, Matei C, et al. Metabolic signatures associated with a NAD synthesis inhibitor-induced tumor apoptosis identified by 1H-decoupled-31P magnetic resonance spectroscopy. Clin Cancer Res 2005; 11: 3503–13PubMedCrossRefGoogle Scholar
  34. 34.
    Kuliszkiewicz-Janus M, Baczynski S, Jurczyk A. Bone marrow transplantation in the course of hematological malignancies: follow-up study in blood serum by 31P MRS. Med Sci Monit 2004; 10: 485–92Google Scholar
  35. 35.
    Ronen SM, Leach MO. Imaging biochemistry: applications to breast cancer. Breast Cancer Res 2001; 3: 36–40PubMedCrossRefGoogle Scholar
  36. 36.
    Boros LG, Williams RD. Isofenphos induced metabolic changes in K562 myeloid blast cells. Leuk Res 2001; 25: 883–90PubMedCrossRefGoogle Scholar
  37. 37.
    Zhou R, Vander Heiden MG, Rudin CM. Genotoxic exposure is associated with alterations in glucose uptake and metabolism. Cancer Res 2002; 62: 3515–20PubMedGoogle Scholar
  38. 38.
    Bernes-Price SJ, Sant ME, Christopherson RI, et al. 1H and 31P NMR and HPLC studies on mouse L1210 leukemia cell extracts: the effect of AU(I) and Cu(I) diphosphine complexes on the cell metabolism. Magn Reson Med 1991; 18: 142–58CrossRefGoogle Scholar
  39. 39.
    Boros LG, Cascante M, Lee WN. Metabolic profiling of cell growth and death in cancer: applications in drug discovery. Drug Discov Today 2002; 7: 364–72PubMedCrossRefGoogle Scholar
  40. 40.
    Boros LG, Lee WN, Go VL. A metabolic hypothesis of cell growth and death in pancreatic cancer. Pancreas 2002; 24: 26–33PubMedCrossRefGoogle Scholar
  41. 41.
    Boros LG, Lerner MR, Morgan DL, et al. [1,2-13C2]-D-glucose profiles of the serum, liver, pancreas and DMBA-induced pancreatic tumors of rats. Pancreas 2005, In pressGoogle Scholar
  42. 42.
    Boros LG, Lee WNP, Cascante M. Imatinib and chronic-phase leukemias. N Engl J Med 2002; 347: 67–8PubMedCrossRefGoogle Scholar
  43. 43.
    Boros LG, Brackett DJ, Harrigan GG. Metabolic biomarker and kinase target discovery in cancer using stable isotope-based dynamic metabolic profiling (SIDMAP). Curr Cancer Drug Target 2003; 3: 447–55CrossRefGoogle Scholar
  44. 44.
    Gottschalk S, Anderson N, Miljus J, et al. Imatinib (STI571)-mediated changes in glucose metabolism in human leukemia BCR-ABL positive cells. Clin Cancer Res 2004; 10: 6661–8PubMedCrossRefGoogle Scholar
  45. 45.
    Miljus J, Melo JV, Boros LG, et al. Metabolic profile of imatinib resistance in chronic myeloid leukemia cells. 46th American Society of Hematology Annual Meeting and Exposition; 2004 Dec 4–7; San Diego (CA)Google Scholar
  46. 46.
    Sahai I, Montefusco MC, Fleming JC, et al. Role of defective high-affinity thiamine transporter slcl9a2 in marrow from a mouse model of thiamineresponsive anemia syndrome: evidence for defective deoxyribose and heme synthesis. 47th American Society of Hematology Annual Meeting; 2005 Dec 4–6; Atlanta (GA).Google Scholar
  47. 47.
    O’Reilly T, Wartmann M, Maira SM, et al. Patupilone (epothilone B, EPO906) and imatinib (STI571, Glivec) in combination display enhanced antitumour activity in vivo against experimental rat C6 glioma. Cancer Chemother Pharmacol 2004; 55: 307–17PubMedCrossRefGoogle Scholar
  48. 48.
    Dresemann G. Imatinib and hydroxyurea in pretreated progressive glioblastoma multiforme: a patient series. Ann Oncol 2005 Jul 20. Epub ahead of printGoogle Scholar
  49. 49.
    Kilic T, Alberta JA, Zdunek PR, et al. Intracranial inhibition of platelet-derived growth factor-mediated glioblastoma cell growth by an orally active kinase inhibitor of the 2-phenylaminopyrimidine class. Cancer Res 2000 Sep 15; 60(18): 5143–50PubMedGoogle Scholar
  50. 50.
    Hagedorn M, Javerzat S, Gilges D, et al. Accessing key steps of human tumor progression in vivo by using an avian embryo model. Proc Natl Acad Sci U S A 2005 Feb 1; 102(5): 1643–8PubMedCrossRefGoogle Scholar
  51. 51.
    Peng B, Lloyd P, Schran H. Clinical pharmacokinetics of imatinib. Clin Pharmacokinet 2005; 44(9): 879–94PubMedCrossRefGoogle Scholar
  52. 52.
    Chevanne M, Caldini R. Relationship between pyridine nucleotide levels and ribonucleotide reductase activity in Yoshida ascites hepatoma AH130. Exp Cell Res 1986 Dec; 167(2): 327–36PubMedCrossRefGoogle Scholar
  53. 53.
    Van den Abbeele AD, Balawi RD. Use of positron emission tomography (PET) in oncology and its potential role to assess response to imatinib mesylate therapy in gastrointestinal stromal tumors (GISTs). Eur J Cancer 2002; 38: S60–5PubMedCrossRefGoogle Scholar
  54. 54.
    Buchanan TA, Xiang A, Kjos SL, et al. Gestational diabetes: antepartum characteristics that predict postpartum glucose intolerance and type 2 diabetes in Latino women. Diabetes 1998; 47: 1302–10PubMedCrossRefGoogle Scholar
  55. 55.
    Garg M, Bassilian S, Bell C, et al. Hepatic de novo lipogenesis in stable low-birth-weight infants during exclusive breast milk feedings and during parenteral nutrition. JPEN J Parenter Enteral Nutr 2005; 29: 81–6PubMedCrossRefGoogle Scholar

Copyright information

© Adis Data Information BV 2005

Authors and Affiliations

  1. 1.Department of Anesthesiology, Biomedical MRS/MRI Cancer CoreUniversity of Colorado Health Sciences CenterDenverUSA
  2. 2.SIDMAP, LLCLos AngelesUSA
  3. 3.Los Angeles Biomedical Research Institute at UCLATorranceUSA

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