Recording of single-unit activities with flexible micro-electrocorticographic array in rats for decoding of whole-body navigation.

OBJECTIVE: Micro-electrocorticographic (µECoG) arrays are able to record neural activities from the cortical surface, without the need to penetrate the brain parenchyma. Owing in part to small electrode sizes, previous studies have demonstrated that single-unit spikes could be detected from the cortical surface, and likely from Layer I neurons of the neocortex. Here we tested the ability to use µECoG array to decode, in rats, body position during open field navigation, through isolated single-unit activities. Approach: µECoG arrays were chronically implanted onto primary motor cortex (M1) of Wistar rats, and neural recording was performed in awake, behaving rats in an open-field enclosure. The signals were band-pass filtered between 300 to 3000 Hz. Threshold-crossing spikes were identified and sorted into distinct units based on defined criteria including waveform morphology and refractory period. Body positions were derived from video recordings. We used gradient-boosting machine to predict body position based on previous 100 ms of spike data, and correlation analyses to elucidate the relationship between position and spike patterns. Main results: Single-unit spikes could be extracted during chronic recording from µECoG, and spatial position could be decoded from these spikes with a mean absolute error of prediction of 0.135 and 0.090 in the x- and y- dimensions (of a normalized range from 0 to 1), and Pearson's r of 0.607 and 0.571, respectively. Significance: µECoG can detect single-unit activities that likely arise from superficial neurons in the cortex and is a promising alternative to intracortical arrays, with the added benefit of scalability to cover large cortical surface with minimal incremental risks. More studies should be performed in human related to its use as brain-machine interface.

Dual p38MAPK and MEK inhibition disrupts adaptive chemoresistance in mesenchymal glioblastoma to temozolomide.

BACKGROUND: Precision treatment of glioblastoma is increasingly focused on molecular subtyping, with the mesenchymal subtype particularly resistant to temozolomide. Here, we aim to develop a targeted therapy for temozolomide resensitization in the mesenchymal subtype. METHODS: We integrated kinomic profiles and kinase inhibitor screens from patient-derived proneural and mesenchymal glioma-propagating cells and public clinical datasets to identify key protein kinases implicated in temozolomide resistance. RNAseq, apoptosis assays, and comet assays were used to examine the role of p38MAPK signaling and adaptive chemoresistance in mesenchymal cells. The efficacy of dual p38MAPK and MEK/ERK inhibition using ralimetinib (selective orally active p38MAPK inhibitor; phase I/II for glioblastoma) and binimetinib (approved MEK1/2 inhibitor for melanoma; phase II for high-grade glioma) in primary and recurrent mesenchymal tumors was evaluated using an intracranial patient-derived tumor xenograft model, focusing on survival analysis. RESULTS: Our transcriptomic-kinomic integrative analysis revealed p38MAPK as the prime target whose gene signature enables patient stratification based on their molecular subtypes and provides prognostic value. Repurposed p38MAPK inhibitors synergize favorably with temozolomide to promote intracellular retention of temozolomide and exacerbate DNA damage. Mesenchymal cells exhibit adaptive chemoresistance to p38MAPK inhibition through a pH-/calcium-mediated MEK/ERK pathway. Dual p38MAPK and MEK inhibition effectively maintain temozolomide sensitivity in primary and recurrent intracranial mesenchymal glioblastoma xenografts. CONCLUSIONS: Temozolomide resistance in mesenchymal glioblastoma is associated with p38MAPK activation. Adaptive chemoresistance in p38MAPK-resistant cells is mediated by MEK/ERK signaling. Adjuvant therapy with dual p38MAPK and MEK inhibition prolongs temozolomide sensitivity, which can be developed into a precision therapy for the mesenchymal subtype.

Unveiling the Influence of Tumor Microenvironment and Spatial Heterogeneity on Temozolomide Resistance in Glioblastoma Using an Advanced Human In Vitro Model of the Blood-Brain Barrier and Glioblastoma.

Glioblastoma (GBM) is the most common primary malignant brain cancer in adults with a dismal prognosis. Temozolomide (TMZ) is the first-in-line chemotherapeutic; however, resistance is frequent and multifactorial. While many molecular and genetic factors have been linked to TMZ resistance, the role of the solid tumor morphology and the tumor microenvironment, particularly the blood-brain barrier (BBB), is unknown. Here, the authors investigate these using a complex in vitro model for GBM and its surrounding BBB. The model recapitulates important clinical features such as a dense tumor core with tumor cells that invade along the perivascular space; and a perfusable BBB with a physiological permeability and morphology that is altered in the presence of a tumor spheroid. It is demonstrated that TMZ sensitivity decreases with increasing cancer cell spatial organization, and that the BBB can contribute to TMZ resistance. Proteomic analysis with next-generation low volume sample workflows of these cultured microtissues revealed potential clinically relevant proteins involved in tumor aggressiveness and TMZ resistance, demonstrating the utility of complex in vitro models for interrogating the tumor microenvironment and therapy validation.

Multiplexed RNA profiling by regenerative catalysis enables blood-based subtyping of brain tumors.

Current technologies to subtype glioblastoma (GBM), the most lethal brain tumor, require highly invasive brain biopsies. Here, we develop a dedicated analytical platform to achieve direct and multiplexed profiling of circulating RNAs in extracellular vesicles for blood-based GBM characterization. The technology, termed 'enzyme ZIF-8 complexes for regenerative and catalytic digital detection of RNA' (EZ-READ), leverages an RNA-responsive transducer to regeneratively convert and catalytically enhance signals from rare RNA targets. Each transducer comprises hybrid complexes - protein enzymes encapsulated within metal organic frameworks - to configure strong catalytic activity and robust protection. Upon target RNA hybridization, the transducer activates directly to liberate catalytic complexes, in a target-recyclable manner; when partitioned within a microfluidic device, these complexes can individually catalyze strong chemifluorescence reactions for digital RNA quantification. The EZ-READ platform thus enables programmable and reliable RNA detection, across different-sized RNA subtypes (miRNA and mRNA), directly in sample lysates. When clinically evaluated, the EZ-READ platform established composite signatures for accurate blood-based GBM diagnosis and subtyping.

Integrative multi-omics approach to targeted therapy for glioblastoma.

This review describes recent technological advances applied to glioblastoma (GBM), a brain tumor with dismal prognosis. International consortial efforts suggest the presence of molecular subtypes within histologically identical GBM tumors. This emphasizes that future treatment decisions should no longer be made based solely on morphological analyses, but must now take into consideration such molecular and cellular heterogeneity. The use of single-cell technologies has advanced our understanding and assignation of functional subtypes revealing therapeutic vulnerabilities. Our team has developed stratification approaches in the past few years, and we have been able to identify patient cohorts enriched for various signaling pathways. Importantly, our Glioportal brain tumor resource has been established under the National Neuroscience Institute Tissue Bank in 2021. This resource offers preclinical capability to validate working hypotheses established from patient clinical datasets. This review highlights recent developments with the ultimate goal of assigning functional meaning to molecular subtypes, revealing therapeutic vulnerabilities.

Adaptive mechanoproperties mediated by the formin FMN1 characterize glioblastoma fitness for invasion.

Glioblastoma are heterogeneous tumors composed of highly invasive and highly proliferative clones. Heterogeneity in invasiveness could emerge from discrete biophysical properties linked to specific molecular expression. We identified clones of patient-derived glioma propagating cells that were either highly proliferative or highly invasive and compared their cellular architecture, migratory, and biophysical properties. We discovered that invasiveness was linked to cellular fitness. The most invasive cells were stiffer, developed higher mechanical forces on the substrate, and moved stochastically. The mechano-chemical-induced expression of the formin FMN1 conferred invasive strength that was confirmed in patient samples. Moreover, FMN1 expression was also linked to motility in other cancer and normal cell lines, and its ectopic expression increased fitness parameters. Mechanistically, FMN1 acts from the microtubule lattice and promotes a robust mechanical cohesion, leading to highly invasive motility.

Pharmacokinetics of levetiracetam in neurosurgical ICU patients.

BACKGROUND/OBJECTIVES: The pharmacokinetics (PK) of drugs is dramatically altered in critical illness. Augmented renal clearance (ARC), a phenomenon characterized by creatinine clearance (CrCl) greater than 130 ml/min/1.73m2, is commonly described in critically ill patients. Levetiracetam, an antiepileptic drug commonly prescribed for seizure prophylaxis in the neurosurgical ICU, undergoes predominant elimination via the kidneys. Hence, we hypothesize that current dosing practice of intravenous (IV) levetiracetam 500 mg twice daily is inadequate for critically ill patients due to enhanced drug elimination. The objectives of our study were to describe the population PK of levetiractam using a nonparametric approach to design an optimal dosing regimen for critically ill neurosurgical patients. METHODS: This was a prospective, observational, population PK study. Serial blood samples were obtained from neurosurgical ICU patients who received at least one dose of IV levetiracetam. We used uHPLC to analyze these samples and Pmetrics™ software to perform PK analysis. RESULTS: Twenty subjects were included, with a median age of 54 years and CrCl of 104 ml/min. A two-compartmental model with linear elimination adequately described the profile of levetiracetam. Mean clearance (CL) was 3.55 L/h and volume of distribution (V) was 18.8 L. No covariates were included in the final model. Monte Carlo simulations showed a low probability of target attainment (PTA, trough at steady state of ≥6 mg/L) with a standard dose of 500 mg twice daily. A dose of at least 1000 mg twice daily was required to achieve 80% PTA. Two subjects, both with subtherapeutic trough levels, developed early onset seizures. CONCLUSION: Our study examined the population PK of levetiracetam in a critically ill neurosurgical population. We found that this population displayed higher clearance and required higher doses to achieve target levels.

Topography of transcriptionally active chromatin in glioblastoma.

Molecular profiling of the most aggressive brain tumor glioblastoma (GBM) on the basis of gene expression, DNA methylation, and genomic variations advances both cancer research and clinical diagnosis. The enhancer architectures and regulatory circuitries governing tumor-intrinsic transcriptional diversity and subtype identity are still elusive. Here, by mapping H3K27ac deposition, we analyze the active regulatory landscapes across 95 GBM biopsies, 12 normal brain tissues, and 38 cell line counterparts. Analyses of differentially regulated enhancers and super-enhancers uncovered previously unrecognized layers of intertumor heterogeneity. Integrative analysis of variant enhancer loci and transcriptome identified topographies of transcriptional enhancers and core regulatory circuitries in four molecular subtypes of primary tumors: AC1-mesenchymal, AC1-classical, AC2-proneural, and AC3-proneural. Moreover, this study reveals core oncogenic dependency on super-enhancer-driven transcriptional factors, long noncoding RNAs, and druggable targets in GBM. Through profiling of transcriptional enhancers, we provide clinically relevant insights into molecular classification, pathogenesis, and therapeutic intervention of GBM.

Kinomic profile in patient-derived glioma cells during hypoxia reveals c-MET-PI3K dependency for adaptation.

Hypoxic microenvironment is a hallmark of solid tumors, especially glioblastoma. The strong reliance of glioma-propagating cells (GPCs) on hypoxia-induced survival advantages is potentially exploitable for drug development. Methods: To identify key signaling pathways for hypoxia adaptation by patient-derived GPCs, we performed a kinase inhibitor profiling by screening 188 small molecule inhibitors against 130 different kinases in normoxia and hypoxia. Potential kinase candidates were prioritized for in vitro and in vivo investigations using a ranking algorithm that integrated information from the kinome connectivity network and estimated patients' survival based on expression status. Results: Hypoxic drug screen highlighted extensive modifications of kinomic landscape and a crucial functionality of c-MET-PI3K. c-MET inhibitors diminished phosphorylation of c-MET and PI3K in GPCs subjected to hypoxia, suggesting its role in the hypoxic adaptation of GPCs. Mechanistically, the inhibition of c-MET and PI3K impaired antioxidant defense, leading to oxidative catastrophe and apoptosis. Repurposed c-MET inhibitors PF04217903 and tivantinib exhibited hypoxic-dependent drug synergism with temozolomide, resulting in reduced tumor load and growth of GPC xenografts. Detailed analysis of bulk and single-cell glioblastoma transcriptomes associates the cellular subpopulation over-expressing c-MET with inflamed, hypoxic, metastatic, and stem-like phenotypes. Conclusions: Thus, our "bench to bedside (the use of patient-derived GPCs and xenografts for basic research) and back (validation with independent glioblastoma transcriptome databases)" analysis unravels the novel therapeutic indications of c-MET and PI3K/Akt inhibitors for the treatment of glioblastoma, and potentially other cancers, in the hypoxic tumor microenvironment.

Mapping the Intratumoral Heterogeneity in Glioblastomas with Hyperspectral Stimulated Raman Scattering Microscopy.

Recent genomic studies on the glioblastoma (GBM) subtypes (e.g., mesenchymal, proneural, and classical) pave a way for effective clinical treatments of the recurrent brain tumor. However, identification of the GBM subtype is complicated by the intratumoral heterogeneity that results in coexistence of multiple subtypes within the tissue specimen. Here, we present the use of hyperspectral stimulated Raman scattering (SRS) microscopy for rapid, label-free molecular assessment of GBM intratumoral heterogeneity with submicron resolution. We develop a unique label-free Raman imaging diagnostic platform consisting of the spectral focusing hyperspectral SRS imaging of the large-area GBM tissue specimens, SRS images, and spectrum retrieval using the multivariate curve resolution algorithm and subtype classification based on the quadratic support vector machine model for rapid molecular subtyping of GBMs. Both the stain-free SRS histological images and 2D subtype maps can be obtained within 20-30 min which is superior to the days of the conventional single-cell RNA sequencing. While the SRS histology assesses the demyelination status as a new diagnostic feature, the SRS mapping provides a new insight into intratumoral heterogeneity across GBM tissue specimens. We find that the major proportions of the GBM tissues agree with the diagnostic results of the genomic analysis, but nontrivial portions of the remaining SRS image tiles in the specimens are found to belong to other molecular subtypes, implying the substantial degree of GBM heterogeneity. The rapid SRS imaging diagnostic platform developed has shown the ability of unveiling tumor heterogeneity in GBM tissues accurately, which would promote the improvement of the GBM-targeted therapy in near future.

Incidence of biomarkers in high-grade gliomas and their impact on survival in a diverse SouthEast Asian cohort - a population-based study.

BACKGROUND: Gliomas consist of a heterogeneous group of tumors. This study aimed to report the incidences of O6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation, 1p19q co-deletion, isocitrate dehydrogenase (IDH) gene mutations, and inactivating mutations of alpha-thalassemia/mental retardation syndrome X-linked (ATRX) in high-grade gliomas in an ethnically diverse population. METHODS: Records of patients who underwent surgery for high-grade gliomas from January 2013 to March 2017 at our institution were obtained. The patients' age, gender, ethnicity, Karnofsky Performance Scale (KPS) score, ability to perform activities of daily living (ADLs), tumor location and biomarkers status were recorded. Data were analyzed using chi-square and Mann-Whitney U tests, Kaplan-Meier estimates and log-rank test. RESULTS: 181 patients were selected (56 with grade III gliomas, 125 with grade IV gliomas). In the grade III group, 55% had MGMT promoter methylation, 41% had 1p19q co-deletion, 35% had IDH1 mutation and none had ATRX loss. In the grade IV group, 30% had MGMT promoter methylation, 2% had 1p19q co-deletion, 15% had IDH1 mutation and 8% had ATRX loss. After adjusting for effects of age, surgery and pre-operative ADL statuses, only MGMT promoter methylation was found to be significantly associated with longer overall survival time in grade III (p = 0.024) and IV patients (p = 0.006). CONCLUSIONS: The incidences of MGMT promoter methylation and IDH1 mutation were found to be comparable to globally reported rates, but those of 1p19q co-deletion and ATRX loss seemed to be lower in our cohort. MGMT promoter methylation was associated with increased overall survival in our cohort and might serve as favorable prognostic factor.

The National Neuroscience Institute External Ventricular Drain Study: A Pragmatic Multisite Risk-Stratification Pathway to Reduce Ventriculostomy-Related Infection.

OBJECTIVE: Ventriculostomy-related infection (VRI) is associated with potential serious morbidity, extended hospitalization duration, increased health care costs, and mortality. We assessed the effectiveness of a pragmatic risk-stratification pathway for external ventricular drain (EVD) management, allowing for surgical decision making, in reducing the rate of VRIs. METHODS: Two studies were performed concurrently. A retrospective audit of EVD infection rates and outcomes in our unit across 3 hospitals was conducted from January to December 2014. The second prospective study compared the same variables during the implementation of the EVD pathway across the 3 sites from January 2015 to December 2016. RESULTS: The number of patients requiring EVDs increased from 2014 to 2016 (165 vs. 189 vs. 197 patients, respectively), with a significant increase in patients with intraventricular hemorrhage (P = 0.009). Despite increasing risk, overall EVD infections decreased during the implementation period, from 4.8% (8/165) in 2014 to 3.7% in 2015 (7/189) and 2.0% in 2016 (4/197, P = 0.33). In 2 sites (site 1, 2.0% vs. 2.1% vs. 1.9%, and site 2, 4.7% vs. 5.0% vs. 5.3%), transition to the EVD risk-stratification pathway maintained already low infection rates; in site 3, EVD infections decreased from 6.8% (5/73) to 3.9% (4/102) and 0% (0/86, P = 0.06). CONCLUSIONS: The introduction of a pragmatic evidence-based risk-stratification pathway, in which different options for EVD management are incorporated, results in low EVD infection rates across a multisite institutional practice. Our results are comparable to published protocols involving the implementation of standard care bundles and/or antibacterial EVDs alone, in reducing VRIs.

A STAT3-based gene signature stratifies glioma patients for targeted therapy.

Intratumoral heterogeneity is a hallmark of glioblastoma (GBM) tumors, thought to negatively influence therapeutic outcome. Previous studies showed that mesenchymal tumors have a worse outcome than the proneural subtype. Here we focus on STAT3 as its activation precedes the proneural-mesenchymal transition. We first establish a STAT3 gene signature that stratifies GBM patients into STAT3-high and -low cohorts. STAT3 inhibitor treatment selectively mitigates STAT3-high cell viability and tumorigenicity in orthotopic mouse xenograft models. We show the mechanism underlying resistance in STAT3-low cells by combining STAT3 signature analysis with kinome screen data on STAT3 inhibitor-treated cells. This allows us to draw connections between kinases affected by STAT3 inhibitors, their associated transcription factors and target genes. We demonstrate that dual inhibition of IGF-1R and STAT3 sensitizes STAT3-low cells and improves survival in mice. Our study underscores the importance of serially profiling tumors so as to accurately target individuals who may demonstrate molecular subtype switching.

Regression based overall survival prediction of glioblastoma multiforme patients using a single discovery cohort of multi-institutional multi-channel MR images.

Glioblastoma multiforme (GBM) are malignant brain tumors, associated with poor overall survival (OS). This study aims to predict OS of GBM patients (in days) using a regression framework and assess the impact of tumor shape features on OS prediction. Multi-channel MR image derived texture features, tumor shape, and volumetric features, and patient age were obtained for 163 GBM patients. In order to assess the impact of tumor shape features on OS prediction, two feature sets, with and without tumor shape features, were created. For the feature set with tumor shape features, the mean prediction error (MPE) was 14.6 days and its 95% confidence interval (CI) was 195.8 days. For the feature set excluding shape features, the MPE was 17.1 days and its 95% CI was observed to be 212.7 days. The coefficient of determination (R2) value obtained for the feature set with shape features was 0.92, while it was 0.90 for the feature set excluding shape features. Although marginal, inclusion of shape features improves OS prediction in GBM patients. The proposed OS prediction method using regression provides good accuracy and overcomes the limitations of GBM OS classification, like choosing data-derived or pre-decided thresholds to define the OS groups. Graphical abstract Two feature sets: with and without tumor shape features were extracted from T1-weighted contrast-enhanced, T2-weighted and FLAIR MRI. These feature sets were analyzed using the Mean Prediction Error (MPE) and its 95% Confidence Interval (CI) obtained from the Bland-Altman plot, along with the coefficient of determination (R2) value to assess the impact of tumor shape features on overall survival prediction of glioblastoma multiforme patients.

Pathogenic mutations in neurofibromin identifies a leucine-rich domain regulating glioma cell invasiveness.

Glioblastoma (GBM) is the most aggressive tumor of the brain. NF1, a tumor suppressor gene and RAS-GTPase, is one of the highly mutated genes in GBM. Dysregulated NF1 expression promotes cell invasion, proliferation, and tumorigenesis. Loss of NF1 expression in glioblastoma is associated with increased aggressiveness of the tumor. Here, we show that NF1-loss in patient-derived glioma cells using shRNA increases self-renewal, heightens cell invasion, and promotes mesenchymal subtype and epithelial mesenchymal transition-specific gene expression that enhances tumorigenesis. The neurofibromin protein contains at least four major domains, with the GAP-related domain being the most well-studied. In this study, we report that the leucine-rich domain (LRD) of neurofibromin inhibits invasion of human glioblastoma cells without affecting their proliferation. Moreover, under conditions tested, the NF1-LRD fails to hydrolyze Ras-GTP to Ras-GDP, suggesting that its suppressive function is independent of Ras signaling. We further demonstrate that rare variants within the NF1-LRD domain found in a subset of the patients are pathogenic and reduce NF1-LRD's invasion suppressive function. Taken together, our results show, for the first time, that NF1-LRD inhibits glioma invasion, and provides evidence of a previously unrecognized function of NF1-LRD in glioma biology.

Effects of surgery on neurocognitive function in patients with glioma: a meta-analysis of immediate post-operative and long-term follow-up neurocognitive outcomes.

PURPOSE: This study aims to identify the neuropsychological tests commonly used for assessment in each neurocognitive domain, and quantify the post-operative changes in neurocognitive function in the immediate post-operation and follow-up. METHODS: With the use of the PubMed, a comprehensive search of the English literature was performed following PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) guidelines. There were 1021 publications identified for screening. Standardized mean differences (SMD) in neuropsychological task performance were calculated both for immediate post-operation (up to 1 week) and follow-up (up to 6 months). RESULTS: Out of 12 studies which met the inclusion criteria, 11 studies were analyzed in this meta-analysis, with a total of 313 patients (age range 18-82, 50% males) with intracranial gliomas (45% high-grade, 55% low-grade). Complex attention, language and executive function were the most frequently tested neurocognitive domains. Surgery had a positive impact in the domains of complex attention, language, learning and memory tasks in the immediate post-operative period and sustained improvement at follow-up. In contrast, surgery was found to negatively impact performance for executive function in the immediate post-operative period with sustained decline in performance in the long term. CONCLUSIONS: This meta-analysis suggests that surgery for glioma confers a benefit for the domains of complex attention, language, learning and memory, while negatively affecting executive function, in the periods immediately after surgery and at 6 months follow-up. In addition, awake surgery seemed to confer a beneficial effect on neurocognitive functions. Future research should attempt to standardize a battery of neuropsychological tests for patients undergoing surgical resection for glioma, perhaps with a particular focus on executive function.

Overall survival prediction in glioblastoma multiforme patients from volumetric, shape and texture features using machine learning.

Glioblastoma multiforme (GBM) are aggressive brain tumors, which lead to poor overall survival (OS) of patients. OS prediction of GBM patients provides useful information for surgical and treatment planning. Radiomics research attempts at predicting disease prognosis, thus providing beneficial information for personalized treatment from a variety of imaging features extracted from multiple MR images. In this study, MR image derived texture features, tumor shape and volumetric features, and patient age were obtained for 163 patients. OS group prediction was performed for both 2-class (short and long) and 3-class (short, medium and long) survival groups. Support vector machine classification based recursive feature elimination method was used to perform feature selection. The performance of the classification model was assessed using 5-fold cross-validation. The 2-class and 3-class OS group prediction accuracy obtained were 98.7% and 88.95% respectively. The shape features used in this work have been evaluated for OS prediction of GBM patients for the first time. The feature selection and prediction scheme implemented in this study yielded high accuracy for both 2-class and 3-class OS group predictions. This study was performed using routinely acquired MR images for GBM patients, thus making the translation of this work into a clinical setup convenient.