Therapeutic approaches targeting seizure networks.

Epilepsy is one of the most common neurological disorders, affecting over 65 million people worldwide. Despite medical management with anti-seizure medications (ASMs), many patients fail to achieve seizure freedom, with over one-third of patients having drug-resistant epilepsy (DRE). Even with surgical management through resective surgery and/or neuromodulatory interventions, over 50 % of patients continue to experience refractory seizures within a year of surgery. Over the past 2 decades, studies have increasingly suggested that treatment failure is likely driven by untreated components of a pathological seizure network, a shift in the classical understanding of epilepsy as a focal disorder. However, this shift in thinking has yet to translate to improved treatments and seizure outcomes in patients. Here, we present a narrative review discussing the process of surgical epilepsy management. We explore current surgical interventions and hypothesized mechanisms behind treatment failure, highlighting evidence of pathologic seizure networks. Finally, we conclude by discussing how the network theory may inform surgical management, guiding the identification and targeting of more appropriate surgical regions. Ultimately, we believe that adapting current surgical practices and neuromodulatory interventions towards targeting seizure networks offers new therapeutic strategies that may improve seizure outcomes in patients suffering from DRE.

Differential gene expression underlying epileptogenicity in patients with gliomas.

Background: Seizures are a common sequela for patients suffering from gliomas. Molecular properties are known to influence the initiation of seizures that may influence tumor growth. Different levels of gene expression with seizures related to gliomas remain unclear. We analyzed RNA sequencing of gliomas to further probe these differences. Methods: Total RNA sequencing was obtained from The Cancer Genome Atlas-Lower-Grade Glioma project, comprised of 2021 World Health Organization classification low-grade gliomas, including IDH-mutant and IDH-wild type, to distinguish differential expression in patients who did and did not experience seizures. Utilizing QIAGEN Ingenuity Pathways Analysis, we identified canonical and functional pathways to characterize differential expression. Results: Of 289 patients with gliomas, 83 (28.7%) had available information regarding seizure occurrence prior to intervention and other pertinent variables of interest. Of these, 50 (60.2%) were allocated to the seizure group. When comparing the level of RNA expression from these tumors between the seizure and non-seizure groups, 52 genes that were significantly differentially regulated were identified. We found canonical pathways that were altered, most significantly RhoGDI and semaphorin neuronal repulsive signaling. Functional gene analysis revealed tumors that promoted seizures had significantly increased functional gene sets involving neuronal differentiation and synaptogenesis. Conclusions: In the setting of gliomas, differences in tumor gene expression exist between individuals with and without seizures, despite similarities in patient demographics and other tumor characteristics. There are significant differences in gene expression associated with neuron development and synaptogenesis, ultimately suggesting a mechanistic role of a tumor-neuron synapse in seizure initiation.

Microglia in Glioblastomas: Molecular Insight and Immunotherapeutic Potential.

Glioblastoma (GBM) is one of the most aggressive and devastating primary brain tumors, with a median survival of 15 months following diagnosis. Despite the intense treatment regimen which routinely includes maximal safe neurosurgical resection followed by adjuvant radio- and chemotherapy, the disease remains uniformly fatal. The poor prognosis associated with GBM is multifactorial owing to factors such as increased proliferation, angiogenesis, and metabolic switching to glycolytic pathways. Critically, GBM-mediated local and systemic immunosuppression result in inadequate immune surveillance and ultimately, tumor-immune escape. Microglia-the resident macrophages of the central nervous system (CNS)-play crucial roles in mediating the local immune response in the brain. Depending on the specific pathological cues, microglia are activated into either a pro-inflammatory, neurotoxic phenotype, known as M1, or an anti-inflammatory, regenerative phenotype, known as M2. In either case, microglia secrete corresponding pro- or anti-inflammatory cytokines and chemokines that either promote or hinder tumor growth. Herein, we review the interplay between GBM cells and resident microglia with a focus on contemporary studies highlighting the effect of GBM on the subtypes of microglia expressed, the associated cytokines/chemokines secreted, and ultimately, their impact on tumor pathogenesis. Finally, we explore how understanding the intricacies of the tumor-immune landscape can inform novel immunotherapeutic strategies against this devastating disease.

Current Status of Awake Spine Surgery: A Bibliometric Analysis.

BACKGROUND: Spine surgery accounts for a large proportion of neurosurgical procedures, with approximately 313 million spine surgeries conducted annually worldwide. Considering delayed recovery and postoperative complications that are commonly reported, there has been a recent shift toward minimally invasive spine procedures conducted under local anesthesia. Despite proven success, there exists a limited body of literature on the use of awake surgery in spinal procedures. METHODS: A bibliometric analysis was conducted to map the current landscape of work in this field. 190 articles were identified from the Web of Science (Clarivate, NY) database. A comprehensive bibliometric analysis was performed on a narrowed list of the most relevant articles using Bibliometrix, an R-based programming tool. RESULTS: There has been a rise in academic papers published on the topic of awake spine surgery since 2016, with an increase in publication count by approximately 18% annually and each article cited approximately ten times on average to date. The year 2022 saw an uptick in publications, with 9 throughout the entire year. The most impactful article, with a total of 95 citations, was published by Sairyo et al.1 Thematic analysis revealed that the terms "lumbar spine" and "stenosis" are well-developed topics in the literature, whereas the topics of "complications," "fusion," and "cost-analysis" are less well-developed topics. CONCLUSIONS: This study provides a comprehensive overview of the most-cited articles in the field of awake spine surgery. Specifically, it identifies areas that are well represented in the literature and those which are underrepresented and should be areas of continued future research.

Differential metabolic alterations in IDH1 mutant vs. wildtype glioma cells promote epileptogenesis through distinctive mechanisms.

Glioma-related epilepsy (GRE) is a hallmark clinical presentation of gliomas with significant impacts on patient quality of life. The current standard of care for seizure management is comprised of anti-seizure medications (ASMs) and surgical resection. Seizures in glioma patients are often drug-resistant and can often recur after surgery despite total tumor resection. Therefore, current research is focused on the pro-epileptic pathological changes occurring in tumor cells and the peritumoral environment. One important contribution to seizures in GRE patients is metabolic reprogramming in tumor and surrounding cells. This is most evident by the significantly heightened seizure rate in patients with isocitrate dehydrogenase mutated (IDHmut) tumors compared to patients with IDH wildtype (IDHwt) gliomas. To gain further insight into glioma metabolism in epileptogenesis, this review compares the metabolic changes inherent to IDHmut vs. IDHwt tumors and describes the pro-epileptic effects these changes have on both the tumor cells and the peritumoral environment. Understanding alterations in glioma metabolism can help to uncover novel therapeutic interventions for seizure management in GRE patients.

Alternative patterns of deep brain stimulation in neurologic and neuropsychiatric disorders.

Deep brain stimulation (DBS) is a widely used clinical therapy that modulates neuronal firing in subcortical structures, eliciting downstream network effects. Its effectiveness is determined by electrode geometry and location as well as adjustable stimulation parameters including pulse width, interstimulus interval, frequency, and amplitude. These parameters are often determined empirically during clinical or intraoperative programming and can be altered to an almost unlimited number of combinations. Conventional high-frequency stimulation uses a continuous high-frequency square-wave pulse (typically 130-160 Hz), but other stimulation patterns may prove efficacious, such as continuous or bursting theta-frequencies, variable frequencies, and coordinated reset stimulation. Here we summarize the current landscape and potential clinical applications for novel stimulation patterns.

Responsive Neurostimulation for Seizure Control: Current Status and Future Directions.

Electrocorticography (ECoG) data are commonly obtained during drug-resistant epilepsy (DRE) workup, in which subdural grids and stereotaxic depth electrodes are placed on the cortex for weeks at a time, with the goal of elucidating seizure origination. ECoG data can also be recorded from neuromodulatory devices, such as responsive neurostimulation (RNS), which involves the placement of electrodes deep in the brain. Of the neuromodulatory devices, RNS is the first to use recorded ECoG data to direct the delivery of electrical stimulation in order to control seizures. In this review, we first introduced the clinical management for epilepsy, and discussed the steps from seizure onset to surgical intervention. We then reviewed studies discussing the emergence and therapeutic mechanism behind RNS, and discussed why RNS may be underperforming despite an improved seizure detection mechanism. We discussed the potential utility of incorporating machine learning techniques to improve seizure detection in RNS, and the necessity to change RNS targets for stimulation, in order to account for the network theory of epilepsy. We concluded by commenting on the current and future status of neuromodulation in managing epilepsy, and the role of predictive algorithms to improve outcomes.