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Myoinositol as a Biomarker in Recurrent Glioblastoma Treated with Bevacizumab: A 1H-Magnetic Resonance Spectroscopy Study

Author

Listed:
  • Eike Steidl
  • Ulrich Pilatus
  • Elke Hattingen
  • Joachim P Steinbach
  • Friedhelm Zanella
  • Michael W Ronellenfitsch
  • Oliver Bähr

Abstract

Background: Antiangiogenic treatment of glioblastomas with Bevacizumab lacks predictive markers. Myoinositol (MI) is an organic osmolyte, with intracellular concentration changes depending on the extracellular osmolality. Since Bevacizumab markedly reduces tumor edema and influences the tumor microenvironment, we investigated whether the MI concentration in the tumor changes during therapy. Methods: We used 1H-magnetic resonance spectroscopy to measure the MI concentrations in the tumor and contralateral control tissue of 39 prospectively recruited patients with recurrent glioblastomas before and 8–12 weeks after starting therapy. 30 patients received Bevacizumab and 9 patients were treated with CCNU/VM26 as control. We performed a survival analysis to evaluate MI as a predictive biomarker for Bevacizumab therapy. Results: MI concentrations increased significantly during Bevacizumab therapy in tumor (p 1,817 mmol/l. No differences were observed for the relative changes or the post treatment concentrations. Additionally calculated creatine concentrations showed no differences in between subgroups or between pre and post treatment measurements. Conclusion: Our data suggest that recurrent glioblastoma shows a strong metabolic reaction to Bevacizumab. Further, our results support the hypothesis that MI might be a marker for early tumor cell invasion. Pre-therapeutic MI concentrations are predictive of overall survival in patients with recurrent glioblastoma treated with Bevacizumab.

Suggested Citation

  • Eike Steidl & Ulrich Pilatus & Elke Hattingen & Joachim P Steinbach & Friedhelm Zanella & Michael W Ronellenfitsch & Oliver Bähr, 2016. "Myoinositol as a Biomarker in Recurrent Glioblastoma Treated with Bevacizumab: A 1H-Magnetic Resonance Spectroscopy Study," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-15, December.
    • Handle: RePEc:plo:pone00:0168113
    DOI: 10.1371/journal.pone.0168113
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    References listed on IDEAS

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    1. Jan Budczies & Frederick Klauschen & Bruno V Sinn & Balázs Győrffy & Wolfgang D Schmitt & Silvia Darb-Esfahani & Carsten Denkert, 2012. "Cutoff Finder: A Comprehensive and Straightforward Web Application Enabling Rapid Biomarker Cutoff Optimization," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-7, December.
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