Myoinositol as a predictive baseline biomarker for overall survival of patients with recurrent glioblastoma treated with Bevacizumab: A 1H-magnetic resonance spectroscopy study.
Eike Steidl1,2,3, Oliver Baehr2,3, Joachim P. Steinbach2,3, Michael W. Ronellenfitsch2,3, Friedhelm Zanella1, Elke Hattingen1, and Ulrich Pilatus1

1Institute of Neuroradiology, Frankfurt am Main, Germany, 2Dr. Senckenberg Institute of Neurooncology, Frankfurt am Main, Germany, 3German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany

Synopsis

Myoinositol is an organic osmolyte, with intracellular concentration changes depending on the extracellular osmolality. Since Bevacizumab reduces tumor edema, we asked whether the Myoinositol concentration changes during therapy.

We used 1H-MRS to measure the Myoinositol concentrations in the tumor and contralateral control of patients with recurrent glioblastomas treated with Bevacizumab (n=30) and CCNU/VM26 (n=9).

Pre-therapeutic Myoinositol concentrations in the contralateral control were predictive of overall survival in patients treated with Bevacizumab. Furthermore our data confirm that recurrent glioblastoma show a strong metabolic reaction to Bevacizumab and support the hypothesis that Myoinositol might be a marker for early tumor cell invasion.

Introduction

For a better understanding of the antiangiogenic Bevacizumab (BVZ) therapy and to identify patients who might benefit from it, we used 1H MRS to monitor metabolic changes during treatment. Up to now most of the research employing MRS has been focused on the effects of BVZ on the tumor’s energy and membrane metabolites as potential markers 1–3. A different metabolite that can be measured with 1H-MRS is myoinositol (MI). MI plays an important role in the cellular osmoregulation of the brain and is predominantly produced by astrocytes 4. Its intracellular concentration changes depending on the extracellular osmolality 5–7. BVZ has a strong impact on tumor vessels, the blood-brain barrier and thus most likely on the osmotic environment 8. We therefore hypothesized that a change of the MI concentration should be measurable during BVZ therapy. To investigate our hypothesis we evaluated the spectroscopic data of 30 prospectively evaluated patients with recurrent glioblastoma before and during therapy with BVZ. Another 9 patients with recurrent glioblastoma receiving CCNU (Lomustine) and VM26 (Teniposid) chemotherapy served as a control group.

Methods

Patients with a histological diagnosis of glioblastoma and radiologically confirmed recurrence were included. All participants underwent an MRS examination before the start of therapy and at regular MRI follow up. Follow ups were performed after 8 weeks for BVZ patients and 10-12 weeks for CCNU/VM26 patients (Patient characteristics shown in Table 1). The detailed MRS protocol can be found in the previously mentioned publication by Hattingen et al. 2. The data was sampled from voxels within the tumor ROI and the control ROI in the contralateral hemisphere. LCModel was employed to analyze the MI signal intensity. To evaluate the potential of MI as a predictive marker for BVZ therapy we performed an overall survival (OS) analysis for the BVZ cohort.

Results

MI concentrations in the tumor were lower compared to control tissue (p< .001) for both cohorts. Concentrations increased significantly during BVZ therapy in tumor (p<.001) and control tissue (p=.001), but not during CCNU/VM26 treatment (Figure 1). For the BVZ cohort, higher MI concentrations in the control tissue at baseline (p=.021) and higher differences between control and tumor tissue (delta MI, p=.011) were associated with longer survival. A Kaplan-Meier analysis showed a median OS of 164 days for patients with a deltaMI < 1,817 mmol/l and 275 days for patients with a deltaMI > 1,817 mmol/l (Figure 2). No differences were observed for the relative changes or the post treatment concentrations (data shown in Table 2).

Discussion

A low MI concentration in the tumor compared to the control tissue is in accordance with previous MRS studies 9–11. The VEGF secretion of glioblastoma causes a disruption of the blood-brain barrier followed by a leakage of electrolytes and small molecules from the vessels, affecting the osmolality of the extracellular environment 12. The distinct reduction of contrast enhancement and peritumoral edema during BVZ therapy suggests a normalization of the osmotic environment, which is reflected by the increase of the MI concentration in the tumor. In contrast, we did not observe changes of the MI concentrations during CCNU/VM26 therapy, indicating that the cytotoxic treatment does not affect the regulation of intracellular MI.

While tumor MI concentrations were not significant, we identified baseline control MI and delta MI levels to be predictive for overall survival. As in the tumor, control MI was increased after BVZ treatment. This either suggests an impact of BVZ on healthy tissue or, alternatively, a tumor related decrease of MI at baseline with a therapy effect comparable to the one in the tumor. Since low baseline values in the control tissue and a lower difference to the values in the tumor were negative predictors for overall survival, they might indicate a more widespread effect of the tumor. Consequently this would indicate an affection of the contralateral control tissue. We assume that this observation could either be explained by direct tumor cell Infiltration, which has already been described to occur in more than 50% of untreated tumors by Matsukado et al. in 1961 13 or an indirect tumor effect. Concerning indirect effects, a spreading edema that is not yet visible in MRI scans or increased intracranial pressure affecting the contralateral hemisphere have to be taken into account.

Conclusion

Pre-therapeutic MI concentrations are predictive of overall survival in patients with recurrent glioblastoma treated with BVZ. Our data confirm that recurrent glioblastoma show a strong metabolic reaction to BVZ. Further, our results support the hypothesis that MI might be a marker for early tumor cell invasion.

Acknowledgements

We thank the staff and nurses of Dr. Senckenberg Institute of Neurooncology who supported this study, including Elena Gomez-Bravo, Elvira Müller, Clarissa Schaumburg-Bähr, Jana Hartan as well as our medical-technological radiology assistants at the Brain Imaging Center Stefanie Pellikan and Maurice Harth.

References

1. Hattingen E, Bähr O, Rieger J, Blasel S, Steinbach J, Pilatus U. Phospholipid metabolites in recurrent glioblastoma: in vivo markers detect different tumor phenotypes before and under antiangiogenic therapy. PLoS ONE. 2013;8(3):e56439.

2. Hattingen E, Jurcoane A, Pilatus U, et al. Bevacizumab impairs oxidative energy metabolism and shows antitumoral effects in recurrent glioblastomas: a 31P/1H MRSI and quantitative magnetic resonance imaging study. Neuro-oncol. 2011;13(12):1349–1363.

3. Ratai EM, Zhang Z, Barboriak DP. Magnetic resonance spectroscopy as an early indicator of response to anti-angiogenic therapy in patients with recurrent glioblastoma: RTOG 0625/ACRIN 6677. Neuro-oncol. 2013;15(7):936–944.

4. Brand A, Richter-Landsberg C, Leibfritz D. Multinuclear NMR studies on the energy metabolism of glial and neuronal cells. Dev Neurosci. 1993;15(3-5):289–98.

5. Restuccia T, Gomez-Anson B, Arroyo V. Effects of dilutional hyponatremia on brain organic osmolytes and water content in patients with cirrhosis. Hepatology. 2004;39(6):1613–22.

6. Videen JS, Michaelis T, Pinto P, Ross BD. Human cerebral osmolytes during chronic hyponatremia. A proton magnetic resonance spectroscopy study. J Clin Invest. 1995;95:788–793.

7. Zhang LJ, Zhong J, Lu GM. Multimodality MR imaging findings of low-grade brain edema in hepatic encephalopathy. AJNR Am J Neuroradiol. 2013;34:707–15.

8. Gil-Gil MJ, Mesia C, Rey M, Bruna J. Bevacizumab for the treatment of glioblastoma. Clin Med Insights Oncol. 2013;7:123–135.

9. Candiota AP, Majós C, Arús C, et al. Non-invasive grading of astrocytic tumours from the relative contents of myo-inositol and glycine measured by in vivo MRS. JBR-BTR. 2011;94:319–329.

10. Choi C, Ganji SK, Maher EA, et al. Measurement of glycine in the human brain in vivo by 1H-MRS at 3 T: application in brain tumors. Magn Reson Med. 2011;66:609–618.

11. Righi V, Andronesi OC, Mintzopoulos D, Black PM, Tzika AA. High-resolution magic angle spinning magnetic resonance spectroscopy detects glycine as a biomarker in brain tumors. Int J Oncol. 2010;36:301–306.

12. Papadopoulos MC, Saadoun S, Binder DK, Manley GT, Krishna S, Verkman AS. Molecular mechanisms of brain tumor edema. Neuroscience. 2004;129:1011–1020.

13. Matsukado Y, McCarty CS, Kernohan IW. The growth of glioblastoma multiforme (astrocytomas, grades 3 and 4) in neurosurgical practice. J Neurosurg. 1961;18:636–644.

Figures

Figure 1. Box-Whisker-plot showing the median and quartiles for tumor (A) and control tissue (B) at baseline and post treatment for BVZ (orange) and CCNU/VM26 (blue). Each * marks a significant increase from baseline to post treatment.

Figure 2. Kaplan-Meier-Curves for patients with delta MI > 1.817 (red) and < 1.817 (brown). The figure shows an extract with an OS of 1829 days for the remaining patient of the brown cohort and a censored survival of 1424 days for the one remaining patient in the red cohort.

Table 1. Patient characteristics, pretreatments and concomitant therapies for all patients in the BVZ cohort as well as the CCNU/VM26 cohort.

GBM= Glioblastoma.


Table 2. Mean values and standard deviations (in brackets) for the Myoinositol concentrations (mmol/l) and the relative increase during treatment. Boldface font indicates a significant difference between the BVZ and CCNU/VM26 cohorts or the long -OS and short -OS. Italic font indicates a significant difference between baseline and post treatment.



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
4181