SCIENCE TIMES
Figure. NADH- and AMP-sensing pathways drive ischemic succinate accumulation to control reperfusion pathologies in vivo through mitochondrial reactive oxygen species production. A, model of succinate accumulation during ischemia and superoxide formation by reverse electron transport during reperfusion. Dp, proton motive force. B, representative cross sections from mouse hearts after myocardial infarction inhibition of ischemic succinate accumulation and reintroduction of ischemic succinate. Infarcted tissue is shown in white; the rest of the area at risk is shown in red; and tissue not at risk is shown in dark blue. C, quantification of myocardial infarct size as described in B (n ¼ 56). D, effect of intravenous infusion of dimethyl succinate in combination with succinate dehydrogenase (SDH) inhibition by dimethyl malonate on citric acid cycle metabolite abundance in the ischemic myocardium in vivo (n ¼ 54). E, effect of intravenous infusion of dimethyl malonate on succinate accumulation in the ischemic brain in vivo (n ¼ 54). F through H, protection by dimethyl malonate against brain ischemia-induced reperfusion (IR) injury in vivo. Quantification of brain infarct volume (F) and rostrocaudal infarct distribution (G) of 6dimethyl malonate after brain IR injury by transient middle cerebral artery occlusion in vivo (untreated, n ¼ 56; dimethyl malonate, n ¼ 54). H, neurological scores for rats after transient middle cerebral artery occlusion with 6-dimethyl malonate (untreated, n ¼ 56; dimethyl malonate, n ¼ 54). *P ¼ .05, **P ¼ .01, ***P ¼ .001 (2-tailed Student t test for pairwise comparisons, and 2-way ANOVA [C-E] or 3-way ANOVA [F-H] for multiple comparisons). Data are mean 6 SEM of at least 3 biological replicates, except for H, for which data are median 6 confidence interval. Reprinted with permission from. Chouchani ET, Pell VR, Gaude E, et al. Ischaemic accumulation of succinate controls reperfusion injury through mitochondrial ROS. Nature. 2014;515(7527):431-435.
The role of mROS production in early IR injury has been extensively studied. mROS production was previously thought to result from a nonspecific dysfunctional reaction between the electron transport chain and oxygen during reperfusion. To date, a specific metabolic pathway has not been identified for this process. The authors of the present study demonstrate that accumulation of succinate via reversal of SDH was common in all ischemic tissues in vivo and that succinate was the primary driver of the mROS production during reperfusion injury through reverse electron transport at complex I of the mitochondrial electron transport chain. Stroke is a major health problem worldwide and has an incidence of 800 000 per year in the United States.4 Timely recanalization of the occluded vasculature remains the only effective treatment. Recent advances in the field of endovascular therapy have made it possible for more stroke patients to receive reperfusion therapy. With increasing numbers of patients receiving intravenous and intra-arterial therapy, the incidence of reperfusion injury has also been rising. The brain has significantly lower levels of antioxidant
N14 | VOLUME 77 | NUMBER 6 | DECEMBER 2015
activities such as superoxide dismutase, catalase, glutathione peroxidase, and hemeoxygenase-1 compared with the kidney, lung, and heart.5 In addition, the brain has high levels of polysaturated fatty acids, which are highly susceptive to oxidative damage, leading to activation of cellular pathways and causing calcium overload and further cytotoxicity.5 Chouchani et al identified succinate as one of the intermediates responsible for the oxidative damage seen in reperfusion injury. Furthermore, they were able to diminish this succinate production by competitively inhibiting SDH, revealing a potential therapeutic target to minimize IR injury in patients suffering a stroke. Alp Ozpinar, MD Gregory M. Weiner, MD Andrew F. Ducruet, MD University of Pittsburgh Medical Center Pittsburgh, Pennsylvania
REFERENCES 1. Murry CE, Jennings RB, Reimer KA. Preconditioning with ischemia: a delay of lethal cell injury in ischemic myocardium. Circulation. 1986;74(5):1124-1136.
2. Chouchani ET, Pell VR, Gaude E, et al. Ischaemic accumulation of succinate controls reperfusion injury through mitochondrial ROS. Nature. 2014;515(7527): 431-435. 3. Smith AC, Robinson AJ. A metabolic model of the mitochondrion and its use in modelling diseases of the tricarboxylic acid cycle. BMC Syst Biol. 2011;5:102. 4. Roger VL, Go AS, Lloyd-Jones DM, et al. Executive summary: heart disease and stroke statistics—2012 update: a report from the American Heart Association. Circulation. 2012;125(1):188-197. 5. Adibhatha RM, Hatcher JF. Lipid oxidation and peroxidation in CNS health and disease: from molecular mechanisms to therapeutic opportunities. Antioxid Redox Signal. 2010;12(1):125-169.
Neuroimaging as a Prognostication Tool for Glioblastoma
G
lioblastoma multiforme (GBM) is one of the most difficult adult cancers to treat. Molecular analysis has demonstrated that GBM is a genetically heterogeneous
www.neurosurgery-online.com
Copyright © Congress of Neurological Surgeons. Unauthorized reproduction of this article is prohibited
SCIENCE TIMES
disease process1; for this reason, there is great interest in personalizing treatment to each patient’s specific tumor type.2 Biological markers derived from pathological tissue analysis are the most well-known tools in current use to stratify tumors, in terms of both prognosis and potential therapeutic targets. Examples include O-6-methylguanine-DNA methyltransferase (MGMT), isocitrate dehydrogenase 1 and 2 (IDH1/2), p53, epidermal growth factor receptor (EGFR), platelet-derived growth factor receptor (PDGFR), phosphatase and tensin homolog (PTEN), phosphoinositide 3-kinase (PI3K), 1p/19q, and telomerase reverse transcriptase (TERT) promoter mutations.3-5 Radiological features, however, may offer another source of predictive information about GBM, as demonstrated by a multicenter imaging study recently organized by the MD Anderson Cancer Center in Houston.6 The authors searched the National Cancer Institute’s imaging archive database and identified 94 patients with GBM and available pretreatment imaging and complete clinical data. Specifically, every patient had available pretreatment MRI brain (precontrast, postcontrast, and
fluid-attenuated inversion-recovery sequences), age, Karnofsky Performance Scale status, and the dates of pathological diagnosis, first disease recurrence, and death. Using a standardized set of glioma imaging parameters,7 they focused on 3 volumetric quantitative imaging findings: (1) the area of fluid-attenuated inversion-recovery signal change, which is believed to represent vasogenic edema and infiltrative tumor, called edema/tumor invasion; (2) the area of postcontrast enhancement, which is believed to represent active viable tumor with disrupted blood-brain barrier, called tumor; and (3) the nonenhancing region within the tumor, called necrosis. Next, they used a validated software platform (www. slicer.org) to outline the regions of edema/tumor invasion, tumor, and necrosis for each patient’s preoperative MRI (Figure). Experienced neuroradiologists also graded the MRIs to identify predefined qualitative glioma features such as deep white matter invasion, multifocal distribution, ependymal extension, and midline crossing. Finally, the investigators used statistical modeling to assess any relationship between quantitative and qualitative pretreatment imaging findings and clinical outcomes.
The study generated many statistically significant findings, and we highlight several here. Analysis of quantitative imaging features showed that edema/tumor invasion volume .85 000 mm3 was associated with shorter overall survival (hazard ratio [HR] ¼ 2.09; 95% confidence interval [CI] ¼ 1.29 to 3.39; P ¼ .003), as was the proportion of tumor enhancement (ie, tumor/ [edema/tumor invasion 1 tumor 1 necrosis]; HR ¼ 17.21; 95% CI ¼ 2.42-122.55; P ¼ .004). Analysis of qualitative imaging features showed that deep white matter invasion was associated with shorter overall survival (HR ¼ 1.89; 95% CI ¼ 1.11-2.73; P ¼ .006). In addition, the age- and Karnofsky Performance Scale–adjusted multivariable model showed that tumor volume .35 000 mm3 and eloquent brain involvement were associated with shorter overall survival (HR ¼ 1.79; 95% CI ¼ 0.94-3.42; P ¼ .08; and HR ¼ 2.44; 95% CI ¼ 1.28-4.65; P ¼ .007, respectively). The findings of the study represent the first quantitative, volumetric radiological assessment for GBM prognostication. Although the utility of prognostic markers in clinical decision making for patients with GBM continues to evolve,8 it
Figure. Segmentation example of the type of magnetic resonance imaging analysis used in the study. A, fluid-attenuated inversionrecovery hyperintensity (blue) shows the edema/tumor invasion volume. B, postcontrast enhancement shows the tumor (yellow) and necrosis (orange). C, combined segmented image. Modified from Wangaryattawanich P, Hatami M, Wang J, et al. Multicenter imaging outcomes study of the Cancer Genome Atlas glioblastoma patient cohort: imaging predictors of overall and progression-free survival. Neuro Oncol. 2015;0:1-13.
NEUROSURGERY
VOLUME 77 | NUMBER 6 | DECEMBER 2015 | N15
Copyright © Congress of Neurological Surgeons. Unauthorized reproduction of this article is prohibited
SCIENCE TIMES
seems likely that, if validated in a prospective manner, these findings could augment conversations about life expectancy with patients and their families. Moreover, they challenge us to reconceptualize the role of MRI as a multifaceted tool used not only for surgical planning but also for disease stratification. Unfortunately, this study did not assess the potential correlation of specific imaging findings with certain potential genetic profiles in GBM. In addition, the analysis did not include variables such as extent of tumor resection and individualized patient treatment. Perhaps future studies will integrate radiological, biological, surgical, and treatment data to deepen our understanding of GBM subtypes and their optimal management, as well as whether we can assess potential molecular characteristics of these tumors before histological diagnosis.9,10 The authors should be congratulated on a thoughtful and insightful analysis. Benjamin M. Zussman, MD Alp Ozpinar, MD Johnathan A. Engh, MD University of Pittsburgh Pittsburgh, Pennsylvania
REFERENCES 1. Liang Y, Diehn M, Watson N, et al. Gene expression profiling reveals molecularly and clinically distinct subtypes of glioblastoma multiforme. Proc Natl Acad Sci U S A. 2005;102(16):5814-5819. 2. Weller M, Stupp R, Reifenberger G, et al. MGMT promoter methylation in malignant gliomas: ready for personalized medicine? Nat Rev Neurol. 2010;6 (1):39-51. 3. Karsy M, Neil JA, Guan J, Mark MA, Colman H, Jensen RL. A practical review of prognostic correlations of molecular biomarkers in glioblastoma. Neurosurg Focus. 2015;38(3):E4. 4. Beiko J, Suki D, Hess KR, et al. IDH1 mutant malignant astrocytomas are more amenable to surgical resection and have a survival benefit associated with maximal surgical resection. Neuro Oncol. 2014;16(1):81-91. 5. Spiegl-kreinecker S, Lötsch D, Ghanim B, et al. Prognostic quality of activating TERT promoter mutations in glioblastoma: interaction with the rs2853669 polymorphism and patient age at diagnosis. Neuro Oncol. 2015;17(9):1231-1240. 6. Wangaryattawanich P, Hatami M, Wang J, et al. Multicenter imaging outcomes study of the Cancer Genome Atlas glioblastoma patient cohort: imaging predictors of overall and progression-free survival. Neuro Oncol. 2015;0:1-13. 7. Visually accessible Rembrandt images (VASARI) feature set for human glioma. 8. Holdhoff M, Ye X, Blakeley JO, et al. Use of personalized molecular biomarkers in the clinical care of adults with glioblastomas. J Neurooncol. 2012;110(2):279-285. 9. Zinn PO, Mahajan B, Majadan B, et al. Radiogenomic mapping of edema/cellular invasion MRI-phenotypes
N16 | VOLUME 77 | NUMBER 6 | DECEMBER 2015
in glioblastoma multiforme. PLoS One. 2011;6(10): e25451. 10. Jamshidi N, Diehn M, Bredel M, Kuo MD. Illuminating radiogenomic characteristics of glioblastoma multiforme through integration of MR imaging, messenger RNA expression, and DNA copy number variation. Radiology. 2014;270(1):1-2.
Excitotoxic SLC7A11 Expression Is a Marker of Poor Glioblastoma Survival and a Potential Therapeutic Target
G
lioblastoma (GBM) is the most common adult primary brain cancer, and approximately half of GBM patients have seizures that significantly alter their quality of life and complicate clinical management. Recent research supports an emerging hypothesis that glutamate, an excitatory neurotransmitter, is partially responsible for seizures and is associated with worse GBM survival. It is postulated that glioma upregulation of the system xc2 (SXC) cysteine/glutamate exchanger (SLC7A11 is the key catalytic subunit) causes glutamate release in exchange for tumor cysteine uptake. Cysteine is used in glutathione synthesis that supports tumor proliferation. Therefore, the released glutamate accumulates to a high level around GBMs, inducing seizures, mediating excitotoxicity (increased firing of surrounding normal neuronal cells) through high calcium influx into peritumoral neurons, and causing apoptosis. Pathogenic excitotoxicity is already implicated in traumatic brain injury, neurodegenerative diseases, stroke, and epilepsy. Robert et al1 directly implicate SLC7A11 in glioma-associated seizure activity, establish SLC7A11 expression as a poor prognostic marker, and show that SXC inhibitors are potentially useful to treat SXC-positive glioma patients. Robert et al first analyzed SLC7A11 protein expression in an annotated tissue microarray of patient-matched GBM and peritumoral normal brain tissue. Comparison of SXC protein levels in GBMs with matched normal tissue in 41 GBM patients showed that about half highly express SLC7A11 (1.17 relative to normal tissue, SLC7A11hi), whereas the other half did not express SXC (0.08 relative to normal tissue, SLC7A11neg). To establish glioma-associated excitotoxicity, cortical neurons were treated with conditioned medium derived from SLC7A11hi and SLC7A11neg glioblastomas.
Significantly more calcium influx was seen in cortical neurons treated with SLC7A11hiconditioned medium. Addition of glutamate receptor antagonists effectively blocked the Ca11 influx. In cocultured experiments, normal neurons grown with SLC7A11hi GBM were substantially less viable compared with those cocultured with SLC7A11neg GBM. In vivo testing showed an 80% reduction in peritumoral neurons in the brains of mice implanted with SLC7A11hi glioma cells compared with SLC7A11neg glioma cells. The mice implanted with SLC7A11hi glioma cells also demonstrated shortened mean survival (20-22 days) compared with mice implanted with SLC7A11neg glioma (27-32 days). Next, the authors assessed whether the SLC7A11-mediated glutamate release may lead to tumor-associated seizures by patchclamp analysis of peritumoral neurons in brain slices of mice implanted with glioma cells. Recordings showed that peritumoral neurons near SLC7A11hi glioma xenografts were significantly more depolarized at baseline compared with controls. Pharmacological induction of excitability increased epileptiform activity in SLC7A11hi xenograft brain slices compared with SLC7A11neg xenograft slices. Enhanced in vivo seizure susceptibility was demonstrated with continuous electroencephalography monitoring of mice implanted with SLC7A11-expressing GBM, with 70% to 77% of such mice developing seizures compared with about 10% of mice implanted with SLC7A11neg gliomas. These findings illustrate that SLC7A11-induced hyperexcitability leads to increased glioma-associated seizures. The clinical relevance of these data is validated by SLC7A11-stratified patient survival from the REMBRANDT database: Patients with high SLC7A11-expressing tumors ($150% mRNA expression of nonneoplastic brain) on average lived 9 months less than those with low SLC7A11 expression (#66%; Figure). In a pilot randomized prospective clinical trial, magnetic resonance spectroscopy was used to assess peritumoral glutamate levels in 9 patients with grade II to IV gliomas. In addition, peritumoral glutamate was assessed before and after administration of a US Food and Drug Administration–approved SXC inhibitor, sulfasalazine. Magnetic resonance spectroscopy showed a greater decrease in glutamate levels after sulfasalazine in biopsy-proven, high SLC7A11expressing tumors. This strongly suggest a key role for SLC7A11 in peritumoral excitotoxicity in human glioma patients and that it is a valid druggable target.
www.neurosurgery-online.com
Copyright © Congress of Neurological Surgeons. Unauthorized reproduction of this article is prohibited
Figure. NADH- and AMP-sensing pathways drive ischemic succinate accumulation to control reperfusion pathologies in vivo through mitochondrial reactive oxygen species production. A, model of succinate accumulation during ischemia and superoxide formation by reverse electron transport during reperfusion. Dp, proton motive force. B, representative cross sections from mouse hearts after myocardial infarction inhibition of ischemic succinate accumulation and reintroduction of ischemic succinate. Infarcted tissue is shown in white; the rest of the area at risk is shown in red; and tissue not at risk is shown in dark blue. C, quantification of myocardial infarct size as described in B (n ¼ 56). D, effect of intravenous infusion of dimethyl succinate in combination with succinate dehydrogenase (SDH) inhibition by dimethyl malonate on citric acid cycle metabolite abundance in the ischemic myocardium in vivo (n ¼ 54). E, effect of intravenous infusion of dimethyl malonate on succinate accumulation in the ischemic brain in vivo (n ¼ 54). F through H, protection by dimethyl malonate against brain ischemia-induced reperfusion (IR) injury in vivo. Quantification of brain infarct volume (F) and rostrocaudal infarct distribution (G) of 6dimethyl malonate after brain IR injury by transient middle cerebral artery occlusion in vivo (untreated, n ¼ 56; dimethyl malonate, n ¼ 54). H, neurological scores for rats after transient middle cerebral artery occlusion with 6-dimethyl malonate (untreated, n ¼ 56; dimethyl malonate, n ¼ 54). *P ¼ .05, **P ¼ .01, ***P ¼ .001 (2-tailed Student t test for pairwise comparisons, and 2-way ANOVA [C-E] or 3-way ANOVA [F-H] for multiple comparisons). Data are mean 6 SEM of at least 3 biological replicates, except for H, for which data are median 6 confidence interval. Reprinted with permission from. Chouchani ET, Pell VR, Gaude E, et al. Ischaemic accumulation of succinate controls reperfusion injury through mitochondrial ROS. Nature. 2014;515(7527):431-435.
The role of mROS production in early IR injury has been extensively studied. mROS production was previously thought to result from a nonspecific dysfunctional reaction between the electron transport chain and oxygen during reperfusion. To date, a specific metabolic pathway has not been identified for this process. The authors of the present study demonstrate that accumulation of succinate via reversal of SDH was common in all ischemic tissues in vivo and that succinate was the primary driver of the mROS production during reperfusion injury through reverse electron transport at complex I of the mitochondrial electron transport chain. Stroke is a major health problem worldwide and has an incidence of 800 000 per year in the United States.4 Timely recanalization of the occluded vasculature remains the only effective treatment. Recent advances in the field of endovascular therapy have made it possible for more stroke patients to receive reperfusion therapy. With increasing numbers of patients receiving intravenous and intra-arterial therapy, the incidence of reperfusion injury has also been rising. The brain has significantly lower levels of antioxidant
N14 | VOLUME 77 | NUMBER 6 | DECEMBER 2015
activities such as superoxide dismutase, catalase, glutathione peroxidase, and hemeoxygenase-1 compared with the kidney, lung, and heart.5 In addition, the brain has high levels of polysaturated fatty acids, which are highly susceptive to oxidative damage, leading to activation of cellular pathways and causing calcium overload and further cytotoxicity.5 Chouchani et al identified succinate as one of the intermediates responsible for the oxidative damage seen in reperfusion injury. Furthermore, they were able to diminish this succinate production by competitively inhibiting SDH, revealing a potential therapeutic target to minimize IR injury in patients suffering a stroke. Alp Ozpinar, MD Gregory M. Weiner, MD Andrew F. Ducruet, MD University of Pittsburgh Medical Center Pittsburgh, Pennsylvania
REFERENCES 1. Murry CE, Jennings RB, Reimer KA. Preconditioning with ischemia: a delay of lethal cell injury in ischemic myocardium. Circulation. 1986;74(5):1124-1136.
2. Chouchani ET, Pell VR, Gaude E, et al. Ischaemic accumulation of succinate controls reperfusion injury through mitochondrial ROS. Nature. 2014;515(7527): 431-435. 3. Smith AC, Robinson AJ. A metabolic model of the mitochondrion and its use in modelling diseases of the tricarboxylic acid cycle. BMC Syst Biol. 2011;5:102. 4. Roger VL, Go AS, Lloyd-Jones DM, et al. Executive summary: heart disease and stroke statistics—2012 update: a report from the American Heart Association. Circulation. 2012;125(1):188-197. 5. Adibhatha RM, Hatcher JF. Lipid oxidation and peroxidation in CNS health and disease: from molecular mechanisms to therapeutic opportunities. Antioxid Redox Signal. 2010;12(1):125-169.
Neuroimaging as a Prognostication Tool for Glioblastoma
G
lioblastoma multiforme (GBM) is one of the most difficult adult cancers to treat. Molecular analysis has demonstrated that GBM is a genetically heterogeneous
www.neurosurgery-online.com
Copyright © Congress of Neurological Surgeons. Unauthorized reproduction of this article is prohibited
SCIENCE TIMES
disease process1; for this reason, there is great interest in personalizing treatment to each patient’s specific tumor type.2 Biological markers derived from pathological tissue analysis are the most well-known tools in current use to stratify tumors, in terms of both prognosis and potential therapeutic targets. Examples include O-6-methylguanine-DNA methyltransferase (MGMT), isocitrate dehydrogenase 1 and 2 (IDH1/2), p53, epidermal growth factor receptor (EGFR), platelet-derived growth factor receptor (PDGFR), phosphatase and tensin homolog (PTEN), phosphoinositide 3-kinase (PI3K), 1p/19q, and telomerase reverse transcriptase (TERT) promoter mutations.3-5 Radiological features, however, may offer another source of predictive information about GBM, as demonstrated by a multicenter imaging study recently organized by the MD Anderson Cancer Center in Houston.6 The authors searched the National Cancer Institute’s imaging archive database and identified 94 patients with GBM and available pretreatment imaging and complete clinical data. Specifically, every patient had available pretreatment MRI brain (precontrast, postcontrast, and
fluid-attenuated inversion-recovery sequences), age, Karnofsky Performance Scale status, and the dates of pathological diagnosis, first disease recurrence, and death. Using a standardized set of glioma imaging parameters,7 they focused on 3 volumetric quantitative imaging findings: (1) the area of fluid-attenuated inversion-recovery signal change, which is believed to represent vasogenic edema and infiltrative tumor, called edema/tumor invasion; (2) the area of postcontrast enhancement, which is believed to represent active viable tumor with disrupted blood-brain barrier, called tumor; and (3) the nonenhancing region within the tumor, called necrosis. Next, they used a validated software platform (www. slicer.org) to outline the regions of edema/tumor invasion, tumor, and necrosis for each patient’s preoperative MRI (Figure). Experienced neuroradiologists also graded the MRIs to identify predefined qualitative glioma features such as deep white matter invasion, multifocal distribution, ependymal extension, and midline crossing. Finally, the investigators used statistical modeling to assess any relationship between quantitative and qualitative pretreatment imaging findings and clinical outcomes.
The study generated many statistically significant findings, and we highlight several here. Analysis of quantitative imaging features showed that edema/tumor invasion volume .85 000 mm3 was associated with shorter overall survival (hazard ratio [HR] ¼ 2.09; 95% confidence interval [CI] ¼ 1.29 to 3.39; P ¼ .003), as was the proportion of tumor enhancement (ie, tumor/ [edema/tumor invasion 1 tumor 1 necrosis]; HR ¼ 17.21; 95% CI ¼ 2.42-122.55; P ¼ .004). Analysis of qualitative imaging features showed that deep white matter invasion was associated with shorter overall survival (HR ¼ 1.89; 95% CI ¼ 1.11-2.73; P ¼ .006). In addition, the age- and Karnofsky Performance Scale–adjusted multivariable model showed that tumor volume .35 000 mm3 and eloquent brain involvement were associated with shorter overall survival (HR ¼ 1.79; 95% CI ¼ 0.94-3.42; P ¼ .08; and HR ¼ 2.44; 95% CI ¼ 1.28-4.65; P ¼ .007, respectively). The findings of the study represent the first quantitative, volumetric radiological assessment for GBM prognostication. Although the utility of prognostic markers in clinical decision making for patients with GBM continues to evolve,8 it
Figure. Segmentation example of the type of magnetic resonance imaging analysis used in the study. A, fluid-attenuated inversionrecovery hyperintensity (blue) shows the edema/tumor invasion volume. B, postcontrast enhancement shows the tumor (yellow) and necrosis (orange). C, combined segmented image. Modified from Wangaryattawanich P, Hatami M, Wang J, et al. Multicenter imaging outcomes study of the Cancer Genome Atlas glioblastoma patient cohort: imaging predictors of overall and progression-free survival. Neuro Oncol. 2015;0:1-13.
NEUROSURGERY
VOLUME 77 | NUMBER 6 | DECEMBER 2015 | N15
Copyright © Congress of Neurological Surgeons. Unauthorized reproduction of this article is prohibited
SCIENCE TIMES
seems likely that, if validated in a prospective manner, these findings could augment conversations about life expectancy with patients and their families. Moreover, they challenge us to reconceptualize the role of MRI as a multifaceted tool used not only for surgical planning but also for disease stratification. Unfortunately, this study did not assess the potential correlation of specific imaging findings with certain potential genetic profiles in GBM. In addition, the analysis did not include variables such as extent of tumor resection and individualized patient treatment. Perhaps future studies will integrate radiological, biological, surgical, and treatment data to deepen our understanding of GBM subtypes and their optimal management, as well as whether we can assess potential molecular characteristics of these tumors before histological diagnosis.9,10 The authors should be congratulated on a thoughtful and insightful analysis. Benjamin M. Zussman, MD Alp Ozpinar, MD Johnathan A. Engh, MD University of Pittsburgh Pittsburgh, Pennsylvania
REFERENCES 1. Liang Y, Diehn M, Watson N, et al. Gene expression profiling reveals molecularly and clinically distinct subtypes of glioblastoma multiforme. Proc Natl Acad Sci U S A. 2005;102(16):5814-5819. 2. Weller M, Stupp R, Reifenberger G, et al. MGMT promoter methylation in malignant gliomas: ready for personalized medicine? Nat Rev Neurol. 2010;6 (1):39-51. 3. Karsy M, Neil JA, Guan J, Mark MA, Colman H, Jensen RL. A practical review of prognostic correlations of molecular biomarkers in glioblastoma. Neurosurg Focus. 2015;38(3):E4. 4. Beiko J, Suki D, Hess KR, et al. IDH1 mutant malignant astrocytomas are more amenable to surgical resection and have a survival benefit associated with maximal surgical resection. Neuro Oncol. 2014;16(1):81-91. 5. Spiegl-kreinecker S, Lötsch D, Ghanim B, et al. Prognostic quality of activating TERT promoter mutations in glioblastoma: interaction with the rs2853669 polymorphism and patient age at diagnosis. Neuro Oncol. 2015;17(9):1231-1240. 6. Wangaryattawanich P, Hatami M, Wang J, et al. Multicenter imaging outcomes study of the Cancer Genome Atlas glioblastoma patient cohort: imaging predictors of overall and progression-free survival. Neuro Oncol. 2015;0:1-13. 7. Visually accessible Rembrandt images (VASARI) feature set for human glioma. 8. Holdhoff M, Ye X, Blakeley JO, et al. Use of personalized molecular biomarkers in the clinical care of adults with glioblastomas. J Neurooncol. 2012;110(2):279-285. 9. Zinn PO, Mahajan B, Majadan B, et al. Radiogenomic mapping of edema/cellular invasion MRI-phenotypes
N16 | VOLUME 77 | NUMBER 6 | DECEMBER 2015
in glioblastoma multiforme. PLoS One. 2011;6(10): e25451. 10. Jamshidi N, Diehn M, Bredel M, Kuo MD. Illuminating radiogenomic characteristics of glioblastoma multiforme through integration of MR imaging, messenger RNA expression, and DNA copy number variation. Radiology. 2014;270(1):1-2.
Excitotoxic SLC7A11 Expression Is a Marker of Poor Glioblastoma Survival and a Potential Therapeutic Target
G
lioblastoma (GBM) is the most common adult primary brain cancer, and approximately half of GBM patients have seizures that significantly alter their quality of life and complicate clinical management. Recent research supports an emerging hypothesis that glutamate, an excitatory neurotransmitter, is partially responsible for seizures and is associated with worse GBM survival. It is postulated that glioma upregulation of the system xc2 (SXC) cysteine/glutamate exchanger (SLC7A11 is the key catalytic subunit) causes glutamate release in exchange for tumor cysteine uptake. Cysteine is used in glutathione synthesis that supports tumor proliferation. Therefore, the released glutamate accumulates to a high level around GBMs, inducing seizures, mediating excitotoxicity (increased firing of surrounding normal neuronal cells) through high calcium influx into peritumoral neurons, and causing apoptosis. Pathogenic excitotoxicity is already implicated in traumatic brain injury, neurodegenerative diseases, stroke, and epilepsy. Robert et al1 directly implicate SLC7A11 in glioma-associated seizure activity, establish SLC7A11 expression as a poor prognostic marker, and show that SXC inhibitors are potentially useful to treat SXC-positive glioma patients. Robert et al first analyzed SLC7A11 protein expression in an annotated tissue microarray of patient-matched GBM and peritumoral normal brain tissue. Comparison of SXC protein levels in GBMs with matched normal tissue in 41 GBM patients showed that about half highly express SLC7A11 (1.17 relative to normal tissue, SLC7A11hi), whereas the other half did not express SXC (0.08 relative to normal tissue, SLC7A11neg). To establish glioma-associated excitotoxicity, cortical neurons were treated with conditioned medium derived from SLC7A11hi and SLC7A11neg glioblastomas.
Significantly more calcium influx was seen in cortical neurons treated with SLC7A11hiconditioned medium. Addition of glutamate receptor antagonists effectively blocked the Ca11 influx. In cocultured experiments, normal neurons grown with SLC7A11hi GBM were substantially less viable compared with those cocultured with SLC7A11neg GBM. In vivo testing showed an 80% reduction in peritumoral neurons in the brains of mice implanted with SLC7A11hi glioma cells compared with SLC7A11neg glioma cells. The mice implanted with SLC7A11hi glioma cells also demonstrated shortened mean survival (20-22 days) compared with mice implanted with SLC7A11neg glioma (27-32 days). Next, the authors assessed whether the SLC7A11-mediated glutamate release may lead to tumor-associated seizures by patchclamp analysis of peritumoral neurons in brain slices of mice implanted with glioma cells. Recordings showed that peritumoral neurons near SLC7A11hi glioma xenografts were significantly more depolarized at baseline compared with controls. Pharmacological induction of excitability increased epileptiform activity in SLC7A11hi xenograft brain slices compared with SLC7A11neg xenograft slices. Enhanced in vivo seizure susceptibility was demonstrated with continuous electroencephalography monitoring of mice implanted with SLC7A11-expressing GBM, with 70% to 77% of such mice developing seizures compared with about 10% of mice implanted with SLC7A11neg gliomas. These findings illustrate that SLC7A11-induced hyperexcitability leads to increased glioma-associated seizures. The clinical relevance of these data is validated by SLC7A11-stratified patient survival from the REMBRANDT database: Patients with high SLC7A11-expressing tumors ($150% mRNA expression of nonneoplastic brain) on average lived 9 months less than those with low SLC7A11 expression (#66%; Figure). In a pilot randomized prospective clinical trial, magnetic resonance spectroscopy was used to assess peritumoral glutamate levels in 9 patients with grade II to IV gliomas. In addition, peritumoral glutamate was assessed before and after administration of a US Food and Drug Administration–approved SXC inhibitor, sulfasalazine. Magnetic resonance spectroscopy showed a greater decrease in glutamate levels after sulfasalazine in biopsy-proven, high SLC7A11expressing tumors. This strongly suggest a key role for SLC7A11 in peritumoral excitotoxicity in human glioma patients and that it is a valid druggable target.
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Copyright © Congress of Neurological Surgeons. Unauthorized reproduction of this article is prohibited
