Bredel, Markus

OBJECTIVE Stereotactic radiosurgery (SRS) is an effective treatment for refractory tremor. However, the lack of reliable patient-specific targeting biomarkers leads to varying outcomes. Although connectomic-based targeting is commonly used in deep brain stimulation, its application in SRS is limited. This study aimed to develop a new targeting approach by using patient-specific structural connectivity to improve outcomes after SRS. METHODS The authors performed a retrospective study of patients in a prospective trial for frameless virtual-cone SRS on a linear accelerator for essential tremor or tremor-dominant Parkinson disease. The primary endpoint was percentage improvement in Fahn-Tolosa-Marin tremor rating scale scores contralateral to the treatment side. Probabilistic tractography assessed connectivity from each thalamic voxel to the primary motor cortex (M1), primary sensory cortex (S1), and supplemental motor area/premotor cortex (SMA/PMC). Group-level comparisons were conducted to evaluate the relationship between the sweet spot for maximum contralateral tremor improvement and areas maximally connected to M1, S1, and SMA/PMC. Multiple regression analysis assessed the relationship between the lesion centerpoint coordinates and the maximally connected voxel to M1, S1, and SMA/PMC at the individual level. RESULTS The analysis included 27 patients with a mean follow-up of 17.9 ± 11.1 months. The sweet spot for maximal contralateral tremor improvement at the group level was in the region most connected to M1 cortex. Smaller y-distances (anterior-posterior) from the lesion center to the M1 maximally connected voxel significantly correlated with tremor improvement at the single-subject level (p < 0.001). However, the authors found no significant correlation between the lesion y-coordinate and the maximally connected voxel to SMA/PMC and S1, nor between the x-distances from the lesions to the SMA/PMC, M1, and S1 voxels (p > 0.07). CONCLUSIONS This study demonstrates that patient-specific connectivity between the treatment target and M1 correlates with treatment outcomes. The authors’ approach provides a practical targeting method for SRS thalamotomy for tremor.

Abstract Purpose: Bevacizumab, a humanized monoclonal antibody to VEGF, is used routinely in the treatment of patients with recurrent glioblastoma (GBM). However, very little is known regarding the effects of bevacizumab on the cells in the perivascular space in tumors. Experimental Design: Established orthotopic xenograft and syngeneic models of GBM were used to determine entry of monoclonal anti-VEGF-A into, and uptake by cells in, the perivascular space. Based on the results, we examined CD133+ cells derived from GBM tumors in vitro. Bevacizumab internalization, trafficking, and effects on cell survival were analyzed using multilabel confocal microscopy, immunoblotting, and cytotoxicity assays in the presence/absence of inhibitors. Results: In the GBM mouse models, administered anti-mouse-VEGF-A entered the perivascular tumor niche and was internalized by Sox2+/CD44+ tumor cells. In the perivascular tumor cells, bevacizumab was detected in the recycling compartment or the lysosomes, and increased autophagy was found. Bevacizumab was internalized rapidly by CD133+/Sox2+-GBM cells in vitro through macropinocytosis with a fraction being trafficked to a recycling compartment, independent of FcRn, and a fraction to lysosomes. Bevacizumab treatment of CD133+ GBM cells depleted VEGF-A and induced autophagy thereby improving cell survival. An inhibitor of lysosomal acidification decreased bevacizumab-induced autophagy and increased cell death. Inhibition of macropinocytosis increased cell death, suggesting macropinocytosis of bevacizumab promotes CD133+ cell survival. Conclusions: We demonstrate that bevacizumab is internalized by Sox2+/CD44+-GBM tumor cells residing in the perivascular tumor niche. Macropinocytosis of bevacizumab and trafficking to the lysosomes promotes CD133+ cell survival, as does the autophagy induced by bevacizumab depletion of VEGF-A. Clin Cancer Res; 23(22); 7059–71. ©2017 AACR.