Glioblastoma Multiforme Brain Research Articles

Brain Tumor Immunotherapy: Current Advances and Future Prospects

Malignant brain tumors, particularly gliomas and glioblastoma multiforme (GBM), remain among the most lethal cancers due to their aggressive nature, genetic complexity, and resistance to conventional therapies. Immunotherapy has emerged as a promising approach to combat these tumors by harnessing the immune system’s capacity to target and destroy cancer cells. This review explores the current advances in brain tumor immunotherapy, including immune checkpoint inhibitors, chimeric antigen receptor (CAR) T-cell therapy, cancer vaccines, and oncolytic viruses. Despite significant progress, challenges such as the immunosuppressive tumor microenvironment, the blood-brain barrier, and tumor heterogeneity hinder the efficacy of these treatments. The review also delves into the unique immunological landscape of the brain, examining the role of microglia, astrocytes, and infiltrating immune cells, and their involvement in tumor-immune evasion. Prominent tumor-associated antigens like EGFRvIII, HER2, and survivin are discussed as key targets for immunotherapeutic strategies. Finally, the review outlines future prospects and research directions aimed at overcoming current obstacles and enhancing the effectiveness of immunotherapy for brain tumors Keywords: Brain Tumor, Immunotherapy, Current Advances, Future Prospects

Green-synthesis of silver nanoparticles AgNPs from Podocarpus macrophyllus for targeting GBM and LGG brain cancers via NOTCH2 gene interactions

Brain tumors, particularly Glioblastoma Multiforme (GBM) and Low-Grade Gliomas (LGG), present significant clinical challenges due to their aggressive nature and resistance to conventional treatments. Traditional therapies such as surgery, chemotherapy, and radiation are often limited in efficacy, necessitating novel therapeutic strategies. Nanotechnology, particularly the use of silver nanoparticles (Ag NPs), offers a targeted and potentially more effective approach. This study focuses on the green synthesis of Ag NPs using Podocarpus macrophyllus leaf extract as a reducing agent. The synthesized Ag NPs were characterized for their physicochemical properties, demonstrating a controlled particle size of 13 nm as determined by scanning electron microscopy (SEM). Fourier-transform infrared (FTIR) spectroscopy confirmed the presence of functional groups, and energy-dispersive X-ray (EDX) spectroscopy revealed that silver constituted approximately 90% of the nanoparticle composition. The Ag NPs exhibited promising biological activity, including 90% free radical scavenging (antioxidant) activity, 99.15% inhibition of protein denaturation (anti-inflammatory activity), and 90.56% inhibition of alpha-amylase (anti-diabetic activity). Additionally, the nanoparticles displayed significant anti-hemolytic (89.9% inhibition) and antimicrobial activities, with a 20 mm inhibition zone against Staphylococcus species. Computational analyses further indicated that the NOTCH2 gene, which is upregulated in LGG and GBM, may interact with Ag NPs, suggesting their potential in brain cancer therapy. The green synthesis approach offers a sustainable and bioactive method for producing Ag NPs, underscoring their therapeutic promise for treating GBM and LGG.

Comparative Analysis of Transcription Factors TWIST2, GATA3, and HES5 in Glioblastoma Multiforme : Evaluating Biomarker Potential and Therapeutic Targets Using In Silico Methods.

Glioblastoma multiforme (GBM) is characterized by substantial heterogeneity and limited therapeutic options. As molecular approaches to central nervous system (CNS) tumors have gained prominence, this study examined the roles of three genes, TWIST2, GATA3, and HES5, known to be involved in oncogenesis, developmental processes, and maintenance of cancer stem cell properties, which have not yet been extensively studied in GBM. This study is the first to present gene expression data for TWIST2, GATA3, and HES5 specifically within the context of GBM patient survival. Gene expression data for TWIST2, GATA3, and HES5 were collected from GBM and normal brain tissues using datasets from The Cancer Genome Atlas (TCGA) via the Genomic Data Commons (GDC) portal and the Genotype-Tissue Expression (GTEx) database. These data were rigorously analyzed using in silico methods. All three genes were significantly more expressed in GBM tissues than in normal tissues. TWIST2 and GATA3 were linked to lower survival rates in GBM patients. Interestingly, higher HES5 levels were associated with better survival rates, suggesting a complex role that needs more investigation. This study shows that TWIST2, GATA3, and HES5 could help predict outcomes in GBM patients. Our multigene model offers a better understanding of GBM and points to new treatment options, bringing hope for improved therapies and patient outcomes. This research advances our knowledge of GBM and highlights the potential of molecular diagnostics in oncology.

A novel approach to the analysis of Overall Survival (OS) as response with Progression-Free Interval (PFI) as condition based on the RNA-seq expression data in The Cancer Genome Atlas (TCGA)

BackgroundOverall Survival (OS) and Progression-Free Interval (PFI) as survival times have been collected in The Cancer Genome Atlas (TCGA). It is of biomedical interest to consider their dependence in pathway detection and survival prediction. We intend to develop novel methods for integrating PFI as condition based on parametric survival models for identifying pathways associated with OS and predicting OS.ResultsBased on the framework of conditional probability, we developed a family of frailty-based parametric-models for this purpose, with exponential or Weibull distribution as baseline. We also considered two classes of existing methods with PFI as a covariate. We evaluated the performance of three approaches by analyzing RNA-seq expression data from TCGA for lung squamous cell carcinoma and lung adenocarcinoma (LUNG), brain lower grade glioma and glioblastoma multiforme (GBMLGG), as well as skin cutaneous melanoma (SKCM). Our focus was on fourteen general cancer-related pathways. The 10-fold cross-validation was employed for the evaluation of predictive accuracy. For LUNG, p53 signaling and cell cycle pathways were detected by all approaches. Furthermore, three approaches with the consideration of PFI demonstrated significantly better predictive performance compared to the approaches without the consideration of PFI. For GBMLGG, ten pathways (e.g., Wnt signaling, JAK-STAT signaling, ECM-receptor interaction, etc.) were detected by all approaches. Furthermore, three approaches with the consideration of PFI demonstrated better predictive performance compared to the approaches without the consideration of PFI. For SKCM, p53 signaling pathway was detected only by our Weibull-baseline-based model. And three approaches with the consideration of PFI demonstrated significantly better predictive performance compared to the approaches without the consideration of PFI.ConclusionsBased on our study, it is necessary to incorporate PFI into the survival analysis of OS. Furthermore, PFI is a survival-type time, and improved results can be achieved by our conditional-probability-based approach.

Evaluating the Efficacy of the 3D U-Net Architecture For Glioblastoma Multiforme Tumor Segmentation

Glioblastoma is the deadliest form of brain cancer which begins as a congregation of cancerous cells within the brain but then progresses into invading and destroying healthy brain tissue. Radiation therapy, the most popular treatment option, is where neuro-oncologists apply intense radiation energy beams directly on the tumor region to kill the cancerous cells. However, for radiation therapy to be effective, the segmented magnetic resonance image (MRI) in which the oncologists base where to apply the radiation must be segmented nearly 100% accurately, or else the energy beams will mistakenly damage healthy brain tissue. Additionally, radiation therapy will be futile if the MRI segmentation is not complete in time for the therapy appointment. My research problem is evaluating the performance of notable segmentation models for accurate and immediate 3D segmentation of glioblastoma multiforme brain tumors from MRIs while focusing on one particular architecture, the 3D U-Net. Each of the models was given 850 MRIs from the same dataset called BraTS, which is an annual competition hosted by the University of Pennsylvania. My 3D U-Net model ended up having the highest training (0.9928), validation (0.968) and testing (0.9867) accuracies of all the models and took approximately 55 seconds to predict segmentations of the tumor region. The results reveal that the 3D U-Net model is capable of automating glioblastoma tumor segmentation in significantly fewer hours than a human oncologist would take, all while maintaining similar or higher accuracy, where even a minor difference can mean the distinction between life and death.

Studying the Pathogenic Effect of New Nucleotide Changes in the Promoter Region of the TERT Gene in Patients with Glioblastoma Brain Tumor

Introduction: Brain tumors are considered to be one of the most dangerous types of cancer, despite decades of research and treatment efforts. The activation of the telomerase enzyme is a critical factor in the immortality of these cells. Mutations in the promoter region of the TERT gene, particularly in the promoter hot spots, can influence the binding of activating transcription factors and inhibit the binding of negative regulatory factors of the TERT gene, ultimately regulating the gene's expression. This study aimed to identify and investigate the mutations of the TERT gene promoter region in glioblastoma, a malignant brain tumor, using bioinformatics. Methods: A study was conducted using the case-control method where 35 patients with glioblastoma multiform brain tumor were examined along with 40 people who were examined as control samples. In this research, the Touchdown PCR technique and direct DNA sequencing were used to detect mutations in the promoter region of the TERT gene in patients with glioblastoma. Furthermore, bioinformatic analyses were conducted to investigate the pathogenic effect of nucleotide changes in this gene region. Results: In the core region of the TERT gene promoter, three-point mutations were identified (c.*146C>T، c.*144C>G and c.*143G>C). Two of these mutations were novel and have been observed for the first time in glioblastoma multiform. The remaining mutation was located in the promoter core's hot spot of the gene. This mutation was known as c.*146C>T. Conclusion: In this research, the harmful impact of TERT promoter region mutations as a biomarker for glioblastoma was examined. These findings suggest that mutations in regulatory regions, as well as coding sequences, could be significant contributory factors in the process of carcinogenesis.

Wasserstein HOG: Local Directionality Extraction via Optimal Transport.

Directionally sensitive radiomic features including the histogram of oriented gradient (HOG) have been shown to provide objective and quantitative measures for predicting disease outcomes in multiple cancers. However, radiomic features are sensitive to imaging variabilities including acquisition differences, imaging artifacts and noise, making them impractical for using in the clinic to inform patient care. We treat the problem of extracting robust local directionality features by mapping via optimal transport a given local image patch to an iso-intense patch of its mean. We decompose the transport map into sub-work costs each transporting in different directions. To test our approach, we evaluated the ability of the proposed approach to quantify tumor heterogeneity from magnetic resonance imaging (MRI) scans of brain glioblastoma multiforme, computed tomography (CT) scans of head and neck squamous cell carcinoma as well as longitudinal CT scans in lung cancer patients treated with immunotherapy. By considering the entropy difference of the extracted local directionality within tumor regions, we found that patients with higher entropy in their images, had significantly worse overall survival for all three datasets, which indicates that tumors that have images exhibiting flows in many directions may be more malignant. This may seem to reflect high tumor histologic grade or disorganization. Furthermore, by comparing the changes in entropy longitudinally using two imaging time points, we found patients with reduction in entropy from baseline CT are associated with longer overall survival (hazard ratio = 1.95, 95% confidence interval of 1.4-2.8, p = 1.65e-5). The proposed method provides a robust, training free approach to quantify the local directionality contained in images.

Comprehensive analysis of the potential biological significance of cuproptosis-related gene LIPT2 in pan-cancer prognosis and immunotherapy

Lipoyltransferase 2 (LIPT2) acts as a key enzyme involved in fatty acid metabolism and cell membrane synthesis. However, the biological function of LIPT2 in various cancer types and its potential significance in prognosis continue to be unresolved. For this analysis, we evaluated the expression levels and the significance of prognosis of LIPT2 gene in all cancers by various bioinformatics methods. The results found that LIPT2 was dramatically overexpressed in the vast majority of cancers. The upregulated LIPT2 was related to bad prognosis in Brain Lower Grade Glioma (LGG), Glioma (GBMLGG), Glioblastoma multiforme (GBM), Kidney Chromophobe (KICH), and High-Risk Wilms Tumor (WT), while it had a favorable prognosis in Kidney renal clear cell carcinoma (KIRC), and Ovarian serous cystadenocarcinoma (OV), Pan-kidney cohort (KIPAN). Furthermore, we assessed the mutation status, methylation levels, and immune status of LIPT2 in pan-cancer. Single-cell sequencing results revealed the correlation of LIPT2 expression with various biological characteristics such as DNA lesion, tumor angiogenesis, cell apoptosis, metastasis, and invasion. Enrichment analysis unveiled potential molecular regulatory mechanisms. In conclusion, our research reveals a detailed key role of LIPT2 in the progression, prognosis, and immune efficacy of various forms of cancer. Therefore, we have reason to believe that LIPT2 has the potential to be a candidate biomarker for tumors.

Signal enhancement in spark-assisted laser-induced breakdown spectroscopy for discrimination of glioblastoma and oligodendroglioma lesions.

Here, the discrimination of two types of lethal brain cancers, i.e., glioblastoma multiforme (GBM) and oligodendroglioma (OG) are investigated under the laser-induced breakdown spectroscopy (LIBS) and the electrical spark-assisted laser-induced breakdown spectroscopy (SA-LIBS) in order to discriminate the human brain glioma lesions against the infiltrated tissues. It is shown there are notable differences between the plasma emissions over the brain gliomas against those of infiltrated tissues. In fact, a notable enhancement appears in the characteristic emissions in favor of SA-LIBS against those of conventional LIB spectra. Moreover, the plasma properties such as temperature, electron density, and degree of ionization are probed through the data processing of the plasma emissions. The corresponding parameters, taken from SA-LIBS data, attest to be lucidly larger than those of LIBS up to one order of magnitude. In addition, the ionic species such as Mg II characteristic line at 279 nm and caII emission at 393 nm are notably enhanced in favor of SA-LIBS. In general, the experimental evidence verifies that SA-LIBS is beneficial in the discrimination and grading of GBM/OG neoplasia against healthy (infiltrate) tissues in the early stages.

CircMTA1 promotes glioblastoma angiogenesis by encoding MTA1-134aa.

Glioblastoma multiforme (GBM) is the most malignant brain tumor with rapid angiogenesis. How to inhibit GBM angiogenesis is a key problem to be solved. To explore the targets of inhibiting GBM angiogenesis, this study confirmed that the expression of circMTA1 (hsa_circ_0033614) was significantly upregulated in human brain microvascular endothelial cells exposed to glioma cell-conditioned medium (GECs). The expression of circMTA1 in the cytoplasm was significantly higher than that in the nucleus. Upregulated circMTA1 in GECs can promote cell proliferation, migration, and tube formation. Further exploration of the circularization mechanism of circMTA1 confirmed that KHDRBS1 protein can bind to the upstream and downstream flanking sequences of circMTA1 and promote circMTA1 biogenesis by coordinating Alu element pairing. KHDRBS1 upregulated the proliferation, migration, and tube formation of GECs by promoting the biogenesis of circMTA1. CircMTA1 can encode the protein MTA1-134aa by internal ribosome entry site sequence-mediated translation mechanism, and promote the proliferation, migration, and tube formation of GECs through the encoded MTA1-134aa. This study provides a new target for inhibiting angiogenesis in brain GBM and a new strategy for improving the therapeutic efficacy of GBM.

The Antitumor Effect of the DNA Polymerase Alpha Inhibitor ST1926 in Glioblastoma: A Proteomics Approach.

Glioblastoma Multiforme (GBM) is the most aggressive form of malignant brain tumor. The median survival rate does not exceed two years, indicating an imminent need to develop novel therapies. The atypical adamantyl retinoid ST1926 induces apoptosis and growth inhibition in different cancer types. We have shown that ST1926 is an inhibitor of the catalytic subunit of DNA polymerase alpha (POLA1), which is involved in initiating DNA synthesis in eukaryotic cells. POLA1 levels are elevated in GBM versus normal brain tissues. Therefore, we studied the antitumor effects of ST1926 in several human GBM cell lines. We further explored the global protein expression profiles in GBM cell lines using liquid chromatography coupled with tandem mass spectrometry to identify new targets of ST1926. Low sub-micromolar concentrations of ST1926 potently decreased cell viability, induced cell damage and apoptosis, and reduced POLA1 protein levels in GBM cells. The proteomics profiles revealed 197 proteins significantly differentially altered upon ST1926 treatment of GBM cells involved in various cellular processes. We explored the differential gene and protein expression of significantly altered proteins in GBM compared to normal brain tissues.

Influence of physical and radiobiological models on evaluation of radiotherapy treatment fractionation schedules for GBM brain tumours

This study aims to evaluate the radiotherapy planning performance considering the clinical results of glioblastoma multiforme (GBM)-treated patients from both physical and radiobiological perspectives. Radiotherapy plans are done for 20 patients with GBM tumors who have received radical VMAT treatment on Eclipse-13.5. Dosimetric and radiobiological evaluation metrics are estimated to compare the two plans in terms of TCP, NTCP, and P+ in the context of the evaluated physical metrics. Both conventional and hypofractionation give better dose homogeneity and conformity to the tumour. In addition, hypofractionation schedule coverage targets cells with radiation doses higher than conventional schemes. However, both schedules are at acceptable and safe levels. Statistically, the calculated metrics showed good significance between conventional and hypofractionated radiotherapy schedules. The results have led to the safe use of hypofractionated radiotherapy that can be extended for different tumours, which helps in breaking down the waiting list of patients in many hospitals, especially in cases of pandemics such as COVID-19.

Association of Traumatic Brain Injury and Glioblastoma Multiforme: A Case Series.

Glioblastoma multiforme (GBM) is an aggressive variant of central nervous system gliomas that carries a dismal prognosis. Although GBM is the most frequently occurring and malignant type of glioma accounting for more than 60% of all brain tumors in adults, its overall incidence is rare, occurring at a rate of 3.21 per 100,000 persons. Little is known about the etiology of GBM, but one proposed theory is that GBM pathogenesis may be linked to a chronic inflammatory course initiated by traumatic injury to the brain. Limited case reports have suggested an association between GBMs and traumatic brain injury (TBI), but larger case-control and epidemiologic studies have been inconclusive. We present three service members (two active duty and one retired) who developed GBM near the original site of prior head trauma. Each service member's military occupation was in the special operations community and shared a common theme of TBI following head trauma/injury. The current research on the association between TBI and GBM is limited and conflicting, predominantly due to the low incidence of the disease in the general population. Evidence has indicated that TBI should be considered a chronic disease with long-term health impacts, including long-term disability, dementia, epilepsy, mental health conditions, and cardiovascular diseases. With the addition of our patients, as well as a recently published study proposing a molecular association between trauma and GBM, further research is needed to better understand the potential relationship.

Pericyte-Glioblastoma Cell Interaction: A Key Target to Prevent Glioblastoma Progression.

Multiple biological processes rely on direct intercellular interactions to regulate cell proliferation and migration in embryonic development and cancer processes. Tumor development and growth depends on close interactions between cancer cells and cells in the tumor microenvironment. During embryonic development, morphogenetic signals and direct cell contacts control cell proliferation, polarity, and morphogenesis. Cancer cells communicate with cells in the tumor niche through molecular signals and intercellular contacts, thereby modifying the vascular architecture and antitumor surveillance processes and consequently enabling tumor growth and survival. While looking for cell-to-cell signaling mechanisms that are common to both brain development and cancer progression, we have studied the infiltration process in glioblastoma multiforme (GBM), which is the most malignant primary brain tumor and with the worst prognosis. Cell-to-cell contacts, by means of filopodia-like structures, between GBM cells and brain pericytes (PCs) are necessary for adequate cell signaling during cancer infiltration; similarly, contacts between embryonic regions, via cytonemes, are required for embryo regionalization and development. This GBM-PC interaction provokes two important changes in the physiological function of these perivascular cells, namely, (i) vascular co-option with changes in cell contractility and vascular malformation, and (ii) changes in the PC transcriptome, modifying the microvesicles and protein secretome, which leads to the development of an immunosuppressive phenotype that promotes tumor immune tolerance. Moreover, the GTPase Cdc42 regulates cell polarity across organisms, from yeast to humans, playing a central role in GBM cell-PC interaction and maintaining vascular co-option. As such, a review of the molecular and cellular mechanisms underlying the development and maintenance of the physical interactions between cancer cells and PCs is of particular interest.

Integrated transcriptome, proteome and single-cell sequencing uncover the prognostic and immunological features of colony-stimulating factor 3 receptor in pan-cancer.

Colony-stimulating factor 3 receptor (CSF3R) has been demonstrated to be associated with various hematological tumors, especially chronic neutrophilic leukemia; however, the detailed roles of CSF3R in other cancers remain to be explored. In the present study, we systematically analyzed the expression profiles of CSF3R in pan-cancer by comprehensive bioinformatics databases, such as Tumor Immune Estimation Resource, version 2 (TIMER2.0), Gene Expression Profiling Interactive Analysis, version 2 (GEPIA2.0), etc. GEPIA2.0 was also used to analyze the relationship between CSF3R expression and patients' survival prognosis. We found that the high expression of CSF3R was associated with a poor prognosis in the brain tumor patients, such as brain lower grade glioma and glioblastoma multiforme. In addition, we further investigated the genetic mutation and DNA methylation level of CSF3R in multiple cancers. Immune infiltration analysis showed that CSF3R expression was positively correlated with a variety of tumor-infiltrating immune cells in most cancers. Single cell sequencing indicated that CSF3R levels were correlated with several cancer-associated pathways, such as DNA damage, cell invasion, and stemness. Taken together, the role of CSF3R in multiple cancers might reveal its potential as a novel prognostic biomarker and therapeutic target for cancer patients.

SLC12A5 as a novel potential biomarker of glioblastoma multiforme.

Glioblastoma multiforme (GBM) is the most prevalent and malignant intracranial tumor with significant features of dismal prognosis and limited therapeutic solutions. Consequently, the present studies are committed to exploring potential biomarkers through bioinformatics analysis, which may serve as valuable prognostic predictors or novel therapeutic targets and provide new insights into the pathogenesis of GBM. We filtered overlapping differentially expressed genes (DEGs) based on expression profilings from three GBM microarray datasets (GSE116520, GSE4290 and GSE68848) and combined RNA sequencing data from The Cancer Genome Atlas and the Genotype-Tissue Expression databases. Hub genes were prioritized from DEGs after performing protein-protein interaction (PPI) network analysis and weighted gene co-expression network analysis (WGCNA). This was followed by survival analysis to identify potential biomarkers among hub genes. Ultimately, the distributions of gene expressions, genetic alterations, upstream regulatory mechanisms and enrichments of gene functions of the identified biomarkers were analysed on public databases. QRT-PCR, immunohistochemical staining and western blotting was also used to confirm the gene expression patterns in GBM and normal brain tissues. CCK-8 assay clarified the effects of the genes on GBM cells. A total of 322 common DEGs were determined and nine genes were subsequently considered as hub genes by the combination of PPI network analysis and WGCNA. Only SLC12A5 had prognostic significance, which was deficient in GBM whereas especially enriched in normal neural tissues. SLC12A5 overexpression would inhibit cell proliferation of U251MG. Genetic alterations of SLC12A5 were rarely seen in GBM patients, and there was no apparent association existed between SLC12A5 expression and DNA methylation. SLC12A5 was prominently involved in ion transport, synapse and neurotransmitter. SLC12A5 shows promise to function as a novel effective biomarker for GBM and deserves further systematic research.

Cryo-EM structure of human heptameric pannexin 2 channel

Pannexin 2 (Panx2) is a large-pore ATP-permeable channel with critical roles in various physiological processes, such as the inflammatory response, energy production and apoptosis. Its dysfunction is related to numerous pathological conditions including ischemic brain injury, glioma and glioblastoma multiforme. However, the working mechanism of Panx2 remains unclear. Here, we present the cryo-electron microscopy structure of human Panx2 at a resolution of 3.4 Å. Panx2 structure assembles as a heptamer, forming an exceptionally wide channel pore across the transmembrane and intracellular domains, which is compatible with ATP permeation. Comparing Panx2 with Panx1 structures in different states reveals that the Panx2 structure corresponds to an open channel state. A ring of seven arginine residues located at the extracellular entrance forms the narrowest site of the channel, which serves as the critical molecular filter controlling the permeation of substrate molecules. This is further verified by molecular dynamics simulations and ATP release assays. Our studies reveal the architecture of the Panx2 channel and provide insights into the molecular mechanism of its channel gating.

Substantial adaptive artificial bee colony algorithm implementation for glioblastoma detection

<p><span lang="EN-US">Glioblastoma multiforme (GBM) is a high-grade brain tumor that is extremely dangerous and aggressive. Due to its rapid development rate, high-grade cancers require early detection and treatment, and early detection may possibly increase the chances of survival. The current practice of GBM detection is performed by a radiologist; due to the enormous number of cases, it is nevertheless tedious, intrusive, and error-prone. Thus, this study attempted a substantial adaptive artificial bee colony (a-ABC) algorithm implementation in providing a non-invasive approach for GBM detection. The basic statistical intensity-based analysis of minimum (minGL), maximum (maxGL), and mean (meanGL) of grey level data was employed to investigate the GBM's feature properties. The a-ABC's performance for adaptive GBM detection identification was evaluated using T1-weighted (T1), T2-weighted (T2), fluid attenuated inversion recovery (FLAIR), and T1-contrast (T1C) which are four different magnetic resonance imaging (MRI) imaging sequences. Hundred and twenty MRI of GBM images were assessed in total, with 30 images per imaging sequence. The overall mean of GBM detection accuracy percentage was 93.67%, implying that the proposed a-ABC algorithm is capable of detecting GBM brain tumors. Other feature extraction strategies, on the other hand, may be added in the future to enhancee the performance of feature extraction. </span></p>

Development and validation of an advanced ex vivo brain slice invasion assay to model glioblastoma cell invasion into the complex brain microenvironment.

Organotypic cultures of murine brain slices are well-established tools in neuroscience research, including electrophysiology studies, modeling neurodegeneration, and cancer research. Here, we present an optimized ex vivo brain slice invasion assay that models glioblastoma multiforme (GBM) cell invasion into organotypic brain slices. Using this model, human GBM spheroids can be implanted with precision onto murine brain slices and cultured ex vivo to allow tumour cell invasion into the brain tissue. Traditional top-down confocal microscopy allows for imaging of GBM cell migration along the top of the brain slice, but there is limited resolution of tumour cell invasion into the slice. Our novel imaging and quantification technique involves embedding stained brain slices into an agar block, re-sectioning the slice in the Z-direction onto slides, and then using confocal microscopy to image cellular invasion into the brain tissue. This imaging technique allows for the visualization of invasive structures beneath the spheroid that would otherwise go undetected using traditional microscopy approaches. Our ImageJ macro (BraInZ) allows for the quantification of GBM brain slice invasion in the Z-direction. Importantly, we note striking differences in the modes of motility observed when GBM cells invade into Matrigel in vitro versus into brain tissue ex vivo highlighting the importance of incorporating the brain microenvironment when studying GBM invasion. In summary, our version of the ex vivo brain slice invasion assay improves upon previously published models by more clearly differentiating between migration along the top of the brain slice versus invasion into the slice.

Integrating clinical access limitations into iPDT treatment planning with PDT-SPACE.

PDT-SPACE is an open-source software tool that automates interstitial photodynamic therapy treatment planning by providing patient-specific placement of light sources to destroy a tumor while minimizing healthy tissue damage. This work extends PDT-SPACE in two ways. The first enhancement allows specification of clinical access constraints on light source insertion to avoid penetrating critical structures and to minimize surgical complexity. Constraining fiber access to a single burr hole of adequate size increases healthy tissue damage by 10%. The second enhancement generates an initial placement of light sources as a starting point for refinement, rather than requiring entry of a starting solution by the clinician. This feature improves productivity and also leads to solutions with 4.5% less healthy tissue damage. The two features are used in concert to perform simulations of various surgery options of virtual glioblastoma multiforme brain tumors.