How neuronal activity regulates glioma cell proliferation

Glioma‑neuronal interactions in tumor progression: Mechanism, therapeutic strategies and perspectives (Review)

An increasing body of evidence has become available to reveal the synaptic and functional integration of glioma into the brain network, facilitating tumor progression. The novel discovery of glioma-neuronal interactions has fundamentally challenged our understanding of this refractory disease. The present review aimed to provide an overview of how the neuronal activities function through synapses, neurotransmitters, ion channels, gap junctions, tumor microtubes and neuronal molecules to establish communications with glioma, as well as a simplified explanation of the reciprocal effects of crosstalk on neuronal pathophysiology. In addition, the current state of therapeutic avenues targeting critical factors involved in glioma-euronal interactions is discussed and an overview of clinical trial data for further investigation is provided. Finally, newly emerging technologies, including immunomodulation, a neural stem cell-based delivery system, optogenetics techniques and co-culture of neuron organoids and glioma, are proposed, which may pave a way towards gaining deeper insight into both the mechanisms associated with neuron- and glioma-communicating networks and the development of therapeutic strategies to target this currently lethal brain tumor.

Postoperative oscillatory brain activity as an add-on prognostic marker in diffuse glioma

Introduction

Progression-free survival (PFS) in glioma patients varies widely, even when stratifying for known predictors (i.e. age, molecular tumor subtype, presence of epilepsy, tumor grade and Karnofsky performance status). Neuronal activity has been shown to accelerate tumor growth in an animal model, suggesting that brain activity may be valuable as a PFS predictor. We investigated whether postoperative oscillatory brain activity, assessed by resting-state magnetoencephalography is of additional value when predicting PFS in glioma patients.

Methods

We included 27 patients with grade II–IV gliomas. Each patient’s oscillatory brain activity was estimated by calculating broadband power (0.5–48 Hz) in 56 epochs of 3.27 s and averaged over 78 cortical regions of the Automated Anatomical Labeling atlas. Cox proportional hazard analysis was performed to test the predictive value of broadband power towards PFS, adjusting for known predictors by backward elimination.

Results

Higher broadband power predicted shorter PFS after adjusting for known prognostic factors (n = 27; HR 2.56 (95% confidence interval (CI) 1.15–5.70); p = 0.022). Post-hoc univariate analysis showed that higher broadband power also predicted shorter overall survival (OS; n = 38; HR 1.88 (95% CI 1.00–3.54); p = 0.038).

Conclusions

Our findings suggest that postoperative broadband power is of additional value in predicting PFS beyond already known predictors.

Electronic supplementary material

The online version of this article (10.1007/s11060-019-03386-7) contains supplementary material, which is available to authorized users.

Label-Free Neurosurgical Pathology with Stimulated Raman Imaging

The goal of brain tumor surgery is to maximize tumor removal without injuring critical brain structures. Achieving this goal is challenging as it can be difficult to distinguish tumor from nontumor tissue. While standard histopathology provides information that could assist tumor delineation, it cannot be performed iteratively during surgery as freezing, sectioning, and staining of the tissue require too much time. Stimulated Raman scattering (SRS) microscopy is a powerful label-free chemical imaging technology that enables rapid mapping of lipids and proteins within a fresh specimen. This information can be rendered into pathology-like images. Although this approach has been used to assess the density of glioma cells in murine orthotopic xenografts models and human brain tumors, tissue heterogeneity in clinical brain tumors has not yet been fully evaluated with SRS imaging. Here we profile 41 specimens resected from 12 patients with a range of brain tumors. By evaluating large-scale stimulated Raman imaging data and correlating this data with current clinical gold standard of histopathology for 4,422 fields of view, we capture many essential diagnostic hallmarks for glioma classification. Notably, in fresh tumor samples, we observe additional features, not seen by conventional methods, including extensive lipid droplets within glioma cells, collagen deposition in gliosarcoma, and irregularity and disruption of myelinated fibers in areas infiltrated by oligodendroglioma cells. The data are freely available in a public resource to foster diagnostic training and to permit additional interrogation. Our work establishes the methodology and provides a significant collection of reference images for label-free neurosurgical pathology. Cancer Res; 76(12); 3451-62. ©2016 AACR.