Seizure control by adding on other anti-seizure medication on seizure during levetiracetam administration in patients with glioma-related epilepsy.

BACKGROUND: Epilepsy is a major symptom in patients with glioma. Levetiracetam (LEV) is recognized as a first-line treatment for glioma-related epilepsy. Increasing the LEV dose is allowed into patients with seizure occurrence against its initial dose. However, the therapeutic efficacy of increasing the LEV dose in response to seizure occurrence remains unclear. METHODS: We retrospectively analyzed 236 glioma patients who were treated with antiseizure medications (ASMs) internally at our institute between September 2010 and December 2017. Of these, the analysis focused on 156 patients treated with LEV who had a clear history of administration. RESULTS: Seizure occurrences were observed in 21 of 75 patients (26.7%) who received LEV as first-line therapy and in 33 of 81 patients (40.7%) who received LEV as non-first-line treatment. The seizure control rate for seizure occurrence with LEV as first-line treatment was significantly higher in patients treated with addition of other ASMs (72.7%) than in those treated with increasing dose of LEV (20.0%) (p = 0.016). The seizure control rate for seizure occurrence with LEV as non-first-line treatment did not differ significantly between patients with addition of other ASMs (58.3%) and those treated with increasing dose of LEV (47.6%) (p = 0.554). CONCLUSIONS: Adding other ASMs was more effective than increasing the LEV dose for seizure control in patients treated with LEV as first-line treatment, but they demonstrated comparable efficacy in patients treated with LEV as non-first-line treatment.

Multiparametric mapping of white matter reorganizations in patients with frontal glioma-related epilepsy.

AIMS: Epilepsy is a common symptom in diffuse lower-grade glioma (DLGG). The specific role of white matter (WM) alteration in patients with glioma-related epilepsy (GRE) is largely unknown. This study aims to investigate the reorganization of WM tracts and changes in structural networks related to GRE. METHODS: Diffusion-weighted images were collected from 70 patients with left frontal DLGG (GRE = 33, non-GRE = 37) and 41 healthy controls (HC). Tractometry with TractSeg was applied to segment tracts and quantify fractional anisotropy (FA) along each tract. Structural network was constructed using constrained spherical deconvolution and probabilistic tractography. FA and network properties were compared among three groups. RESULTS: Compared with HC, both GRE and non-GRE showed decreased FA in contralateral inferior fronto-occipital fasciculus, superior longitudinal fasciculus II and arcuate fasciculus, increased nodal efficiency in contralateral nodes of frontal-parietal and limbic networks, whereas decreased degree centrality and betweenness centrality in nodes of dorsal temporal lobe and rostral middle frontal gyrus (rMFG). Additionally, when compared GRE with non-GRE, increased FA in contralateral corticospinal tract (CST) and lower betweenness centrality in paracentral lobule (PCL) in GRE (all p < 0.05 after Bonferroni correction). CONCLUSION: This study indicates that patients with left frontal DLGG exhibit complex WM reorganization, and the altered regions mainly concentrated in the language, frontal-parietal and limbic networks. Moreover, the preserved integrity in contralateral CST and server decreased nodal betweenness in PCL may be potential neuroimaging markers underlying the occurrence of presurgical seizures of GRE.

Effects of Propofol on Cortical Electroencephalograms in the Operation of Glioma-Related Epilepsy.

BACKGROUND: A cortical electroencephalogram (ECoG) is often used for the intraoperative monitoring of epilepsy surgery, and propofol is an important intravenous anesthetic, but its effect on EEGs is unclear. OBJECTIVES: To further clarify the effect of propofol on cortical ECoGs during glioma-related epilepsy surgery and to clarify the possible clinical value. METHODS: A total of 306 patients with glioma were included in the study. Two hundred thirty-nine with glioma-related epilepsy were included in the epilepsy group, and 67 without glioma-related epilepsy were included in the control group. All patients experienced continuous, real-time ECoG monitoring and long-term follow-up after surgery. RESULTS: After injection of low-dose propofol, the rate of activated ECoGs in the epilepsy group (74%) was significantly higher than in the control group (9%). Furthermore, compared with patients in the untreated group, patients in the treated group had lower rates of early and long-term postoperative seizure frequencies and fewer interictal epileptiform discharges (IEDs). CONCLUSIONS: Low-dose infusion of propofol can specifically activate ECoGs in epilepsy patients. Therefore, activated ECoGs might provide an accurate and reliable method for identifying potential epileptic zones during glioma-related epilepsy surgery, resulting in better early and long-term prognoses after epilepsy surgery.

Glioma epileptiform activity and progression are driven by IGSF3-mediated potassium dysregulation.

Seizures are a frequent pathophysiological feature of malignant glioma. Recent studies implicate peritumoral synaptic dysregulation as a driver of brain hyperactivity and tumor progression; however, the molecular mechanisms that govern these phenomena remain elusive. Using scRNA-seq and intraoperative patient ECoG recordings, we show that tumors from seizure patients are enriched for gene signatures regulating synapse formation. Employing a human-to-mouse in vivo functionalization pipeline to screen these genes, we identify IGSF3 as a mediator of glioma progression and dysregulated neural circuitry that manifests as spreading depolarization (SD). Mechanistically, we discover that IGSF3 interacts with Kir4.1 to suppress potassium buffering and found that seizure patients exhibit reduced expression of potassium handlers in proliferating tumor cells. In vivo imaging reveals that dysregulated synaptic activity emanates from the tumor-neuron interface, which we confirm in patients. Our studies reveal that tumor progression and seizures are enabled by ion dyshomeostasis and identify SD as a driver of disease.

Development of an integrated predictive model for postoperative glioma-related epilepsy using gene-signature and clinical data.

BACKGROUND: This study aimed to develop an integrated model for predicting the occurrence of postoperative seizures in patients with diffuse high-grade gliomas (DHGGs) using clinical and RNA-seq data. METHODS: Patients with DHGGs, who received prophylactic anti-epileptic drugs (AEDs) for three months following surgery, were enrolled into the study. The patients were assigned randomly into training (n = 166) and validation (n = 42) cohorts. Differentially expressed genes (DEGs) were identified based on preoperative glioma-related epilepsy (GRE) history. Least absolute shrinkage and selection operator (LASSO) logistic regression analysis was used to construct a predictive gene-signature for the occurrence of postoperative seizures. The final integrated prediction model was generated using the gene-signature and clinical data. Receiver operating characteristic analysis and calibration curve method were used to evaluate the accuracy of the gene-signature and prediction model using the training and validation cohorts. RESULTS: A seven-gene signature for predicting the occurrence of postoperative seizures was developed using LASSO logistic regression analysis of 623 DEGs. The gene-signature showed satisfactory predictive capacity in the training cohort [area under the curve (AUC) = 0.842] and validation cohort (AUC = 0.751). The final integrated prediction model included age, temporal lobe involvement, preoperative GRE history, and gene-signature-derived risk score. The AUCs of the integrated prediction model were 0.878 and 0.845 for the training and validation cohorts, respectively. CONCLUSION: We developed an integrated prediction model for the occurrence of postoperative seizures in patients with DHGG using clinical and RNA-Seq data. The findings of this study may contribute to the development of personalized management strategies for patients with DHGGs and improve our understanding of the mechanisms underlying GRE in these patients.

Predictors of seizure outcomes in patients with diffuse low-grade glioma-related epilepsy after complete glioma removal.

AIMS: We aimed to identify predictors of postoperative seizures in patients with diffuse low-grade glioma (DLGG)-related epilepsy after complete tumor resection in this study. METHODS: We retrospectively collected data from individuals with DLGG-related epilepsy whose tumors were completely resected at Xiangya Hospital, Central South University between January 2014 and January 2020. The predictors of seizure outcomes were assessed by employing univariate analysis and a multivariate logistic regression model in a backward binary logistic regression model. RESULTS: Among the 118 cases that met the inclusion criteria, 83.05% were seizure-free following an average follow-up of 4.27 ± 1.65 years, all of whom were classified as International League Against Epilepsy class I outcome. Univariate and multivariate analyses indicated that seizure duration of >6 years (odds ratio [OR], 6.62; 95% confidence interval [CI], 1.76-24.98; p = 0.005) and first clinical symptoms other than seizures (OR, 4.51; 95% CI, 1.43-14.23; p = 1.010) were both independent predictors of unfavorable seizure outcomes. CONCLUSION: Our results imply that satisfactory seizure outcomes can be achieved in most patients with DLGG-related epilepsy after complete tumor resection. Patients with seizure duration of >6 years or first clinical symptoms other than seizures were more likely to experience postoperative seizure recurrence.

Characteristics of Microstructural Changes Associated with Glioma Related Epilepsy: A Diffusion Tensor Imaging (DTI) Study.

(1) Background: Glioma is the most common primary tumor in the central nervous system, and glioma-related epilepsy (GRE) is one of its common symptoms. The abnormalities of white matter fiber tracts are involved in attributing changes in patients with epilepsy (Rudà, R, 2012).This study aimed to assess frontal lobe gliomas' effects on the cerebral white matter fiber tracts. (2) Methods: Thirty patients with frontal lobe glioma were enrolled and divided into two groups (Ep and nEep). Among them, five patients were excluded due to apparent insular or temporal involvement. A set of 14 age and gender-matched healthy controls were also included. All the enrolled subjects underwent preoperative conventional magnetic resonance images (MRI) and diffusion tensor imaging (DTI). Furthermore, we used tract-based spatial statistics to analyze the characteristics of the white matter fiber tracts. (3) Results: The two patient groups showed similar patterns of mean diffusivity (MD) elevations in most regions; however, in the ipsilateral inferior fronto-occipital fasciculus (IFOF), superior longitudinal fasciculus (SLF), and superior corona radiata, the significant voxels of the EP group were more apparent than in the nEP group. No significant fractional anisotropy (FA) elevations or MD degenerations were found in the current study. (4) Conclusions: Gliomas grow and invade along white matter fiber tracts. This study assessed the effects of GRE on the white matter fiber bundle skeleton by TBSS, and we found that the changes in the white matter skeleton of the frontal lobe tumor-related epilepsy were mainly concentrated in the IFOF, SLF, and superior corona radiata. This reveals that GRE significantly affects the white matter fiber microstructure of the tumor.

Integrative analysis of expression profile indicates the ECM receptor and LTP dysfunction in the glioma-related epilepsy.

BACKGROUND: Seizures are a common symptom in glioma patients, and they can cause brain dysfunction. However, the mechanism by which glioma-related epilepsy (GRE) causes alterations in brain networks remains elusive. OBJECTIVE: To investigate the potential pathogenic mechanism of GRE by analyzing the dynamic expression profiles of microRNA/ mRNA/ lncRNA in brain tissues of glioma patients. METHODS: Brain tissues of 16 patients with GRE and 9 patients with glioma without epilepsy (GNE) were collected. The total RNA was dephosphorylated, labeled, and hybridized to the Agilent Human miRNA Microarray, Release 19.0, 8 × 60 K. The cDNA was labeled and hybridized to the Agilent LncRNA + mRNA Human Gene Expression Microarray V3.0, 4 × 180 K. The raw data was extracted from hybridized images using Agilent Feature Extraction, and quantile normalization was performed using the Agilent GeneSpring. P-value < 0.05 and absolute fold change > 2 were considered the threshold of differential expression data. Data analyses were performed using R and Bioconductor. RESULTS: We found that 3 differentially expressed miRNAs (miR-10a-5p, miR-10b-5p, miR-629-3p), 6 differentially expressed lncRNAs (TTN-AS1, LINC00641, SNHG14, LINC00894, SNHG1, OIP5-AS1), and 49 differentially expressed mRNAs play a vitally critical role in developing GRE. The expression of GABARAPL1, GRAMD1B, and IQSEC3 were validated more than twofold higher in the GRE group than in the GNE group in the validation cohort. Pathways including ECM receptor interaction and long-term potentiation (LTP) may contribute to the disease's progression. Meanwhile, We built a lncRNA-microRNA-Gene regulatory network with structural and functional significance. CONCLUSION: These findings can offer a fresh perspective on GRE-induced brain network changes.

Expression changes in ion channel and immunity genes are associated with glioma-related epilepsy in patients with diffuse gliomas.

BACKGROUND: Glioma-related epilepsy (GRE) is a common symptom in patients with diffuse gliomas. However, the underlying mechanisms of GRE remain unclear. The current study aimed to investigate the underlying epileptogenic mechanisms of GRE through RNA sequencing analysis. METHODS: Demographic, RNA sequencing, and follow-up data of 643 patients were reviewed. Patients were divided into test and validation groups (223 and 420 patients, respectively) by different time periods for RNA sequencing. The differentially expressed genes (DEGs) associated with preoperative GRE were identified using R software. Functional enrichment analysis was subsequently performed, and tissue-infiltrating immune cells were also estimated. Weighted correlation network analysis (WGCNA) was conducted to further identify key modules exhibiting the highest correlation with preoperative GRE. Overlapping genes between the DEG set and key gene set identified by WGCNA were selected and verified in the validation cohort. The protein-protein interaction (PPI) network analysis was then constructed to identify hub genes for preoperative GRE. RESULTS: A total of 219 DEGs were identified, among which 112 were upregulated and 107 downregulated in patients with GRE. Functional enrichment analysis revealed that upregulated DEGs were related to ion channel activity, while downregulated genes were related to immunity. Forty-two genes were further selected from overlapping DEGs and the key gene set. Among these genes, 31 genes showed significant differences in the validation cohort. Finally, the PPI network analysis identified six genes, including SCN3B, KCNIP2, KCNJ11, VEGFA, MMP9, and ANXA2, as hub genes for GRE. CONCLUSION: The current study revealed that ion channel activity and immunity dysfunction in diffuse glioma patients contributed to the occurrence of GRE, and SCN3B might be a shared therapeutic target for both diffuse gliomas and GRE. These findings could improve the understanding of the mechanisms of GRE and promote individualized medications for glioma management.

Decreasing Shortest Path Length of the Sensorimotor Network Induces Frontal Glioma-Related Epilepsy.

BACKGROUND: Glioma-related epilepsy (GRE) is a common symptom in patients with prefrontal glioma. Epilepsy onset is associated with functional network alterations. This study investigated alterations of functional networks in patients with prefrontal glioma and GRE. METHODS: Sixty-five patients with prefrontal lobe gliomas were retrospectively assessed and classified into GRE and non-GRE groups. Additionally, 25 healthy participants were enrolled after matching for general information. Imaging data were acquired within 72 h in pre-operation. The sensorimotor network was used to delineate alterations in functional connectivity (FC) and topological properties. One-way analysis of variance and post-hoc analysis with Bonferroni correction were used to calculate differences of FC and topological properties. RESULTS: All significant alterations were solely found in the sensorimotor network. Irrespective of gliomas located in the left or right prefrontal lobes, the edge between medial Brodmann area 6 and caudal ventrolateral Brodmann area 6 decreased FC in the GRE group compared with the non-GRE group [p < 0.0001 (left glioma), p = 0.0002 (right glioma)]. Moreover, the shortest path length decrease was found in the GRE group compared with the non-GRE group [p = 0.0292 (left glioma) and p = 0.0129 (right glioma)]. CONCLUSIONS: The reduction of FC between the medial BA 6 (supplementary motor area) and caudal ventrolateral BA 6 in the ipsilateral hemisphere and the shortening of the path length of the sensorimotor network were characteristics alterations in patients with GRE onset. These findings fill in the gap which is the relationship between GRE onset and the alterations of functional networks in patients with prefrontal glioma. SIGNIFICANCE STATEMENT: Glioma related epilepsy is the most common symptom of prefrontal glioma. It is important to identify characteristic alterations in functional networks in patients with GRE. We found that all significant alterations occurred in the sensorimotor network. Moreover, a decreased FC in the supplementary motor area and a shortening of the path's length are additional characteristics of glioma-related epilepsy. We believe that our findings indicate new directions of research that will contribute to future investigations of glioma-related epilepsy onset.

Glioma-related epilepsy in patients with diffuse high-grade glioma after the 2016 WHO update: seizure characteristics, risk factors, and clinical outcomes.

OBJECTIVE: The aim of this study was to investigate the epidemiological characteristics, associated risk factors, and prognostic value of glioma-related epilepsy in patients with diffuse high-grade gliomas (DHGGs) that were diagnosed after the 2016 updated WHO classification was released. METHODS: Data from 449 patients with DHGGs were retrospectively collected. Definitive diagnosis was reaffirmed according to the 2016 WHO classification. Seizure outcome was assessed using the Engel classification at 12 months after surgery. Univariate and multivariate analyses were performed to identify risk factors associated with preoperative and postoperative glioma-related epilepsy. Lastly, the prognostic value of glioma-related epilepsy was evaluated by Kaplan-Meier and Cox analysis. RESULTS: The incidence of glioma-related epilepsy decreased gradually as the malignancy of the tumor increased. Age < 45 years (OR 2.601, p < 0.001), normal neurological function (OR 3.024, p < 0.001), and lower WHO grade (OR 2.028, p = 0.010) were independently associated with preoperative glioma-related epilepsy, while preoperative glioma-related epilepsy (OR 7.554, p < 0.001), temporal lobe involvement (OR 1.954, p = 0.033), non-gross-total resection (OR 2.286, p = 0.012), and lower WHO grade (OR 2.130, p = 0.021) were identified as independent predictors of poor seizure outcome. Furthermore, postoperative glioma-related epilepsy, rather than preoperative glioma-related epilepsy, was demonstrated as an independent prognostic factor for overall survival (OR 0.610, p = 0.010). CONCLUSIONS: The updated WHO classification seems conducive to reveal the distribution of glioma-related epilepsy in DHGG patients. For DHGG patients with high-risk predictors of poor seizure control, timely antiepileptic interventions could be beneficial. Moreover, glioma-related epilepsy (especially postoperative glioma-related epilepsy) is associated with favorable overall survival.

Development of a Rat Model for Glioma-Related Epilepsy.

Seizures are common in patients with high-grade gliomas (30-60%) and approximately 15-30% of glioblastoma (GB) patients develop drug-resistant epilepsy. Reliable animal models are needed to develop adequate treatments for glioma-related epilepsy. Therefore, fifteen rats were inoculated with F98 GB cells (GB group) and four rats with vehicle only (control group) in the right entorhinal cortex. MRI was performed to visualize tumor presence. A subset of seven GB and two control rats were implanted with recording electrodes to determine the occurrence of epileptic seizures with video-EEG recording over multiple days. In a subset of rats, tumor size and expression of tumor markers were investigated with histology or mRNA in situ hybridization. Tumors were visible on MRI six days post-inoculation. Time-dependent changes in tumor morphology and size were visible on MRI. Epileptic seizures were detected in all GB rats monitored with video-EEG. Twenty-one days after inoculation, rats were euthanized based on signs of discomfort and pain. This study describes, for the first time, reproducible tumor growth and spontaneous seizures upon inoculation of F98 cells in the rat entorhinal cortex. The development of this new model of GB-related epilepsy may be valuable to design new therapies against tumor growth and associated epileptic seizures.

Scale-Free Analysis of Intraoperative ECoG During Awake Craniotomy for Glioma.

BACKGROUND: Electrocorticography (ECoG) has been utilized in many epilepsy cases however, the use of this technique for evaluating electrophysiological changes within tumoral zones is spare. Nonetheless, epileptic activities seem to arise from the neocortex surrounding the gliomas suggesting a link between epileptogenesis and glioma cell infiltration in the peritumoral area. The purpose of this study was to implement novel scale-free measures to assess how cortical physiology is altered by the presence of an invasive brain tumor. METHODS: Twelve patients undergoing an awake craniotomy for resection of a supratentorial glioma were included. ECoG data over the main tumor and the exposed surroundings was acquired intra-operatively just prior to tumor resection. Six of the patients presented with seizures and had data acquired both in the awake and anesthetic state. The corresponding anatomical location of each electrode in relation to the macroscopically-detectable tumor was recorded using the neuronavigation system based on structural anatomical images obtained pre-operatively. The electrodes were classified into tumoral, healthy or peritumoral based on the macroscopically detectable tumoral tissue from the pre-operative structural MRI. RESULTS: The electrodes overlying the tumoral tissue revealed higher power law exponent (PLE) values across tumoral area compared to the surrounding tissues. The difference between the awake and anesthetic states was significant in the tumoral and healthy tissue (p < 0.05) but not in the peritumoral tissue. The absence of a significant PLE reduction in the peritumoral tissue from the anesthetic to the awake state could be considered as an index of the presence or absence of infiltration of tumor cells into the peritumoral tissue. CONCLUSIONS: The current study portrays for the first time distinct power law exponent features in the tumoral tissue, which could provide a potential novel electrophysiological marker in the future. The distinct features seen in the peritumoral tissue of gliomas seem to indicate the area where both the onset of epileptiform activity and the tumor infiltration take place.