Uncovering Spatiotemporal Heterogeneity of High-Grade Gliomas: From Disease Biology to Therapeutic Implications

Microtubule-associated NAV3 regulates invasive phenotypes in glioblastoma cells

Glioblastomas are aggressive brain tumors for which effective therapy is still lacking, resulting in dismal survival rates. These tumors display significant phenotypic plasticity, harboring diverse cell populations ranging from tumor core cells to dispersed, highly invasive cells. Neuron navigator 3 (NAV3), a microtubule-associated protein affecting microtubule growth and dynamics, is downregulated in various cancers, including glioblastoma, and has thus been considered a tumor suppressor. In this study, we challenge this designation and unveil distinct expression patterns of NAV3 across different invasion phenotypes. Using glioblastoma cell lines and patient-derived glioma stem-like cell cultures, we disclose an upregulation of NAV3 in invading glioblastoma cells, contrasting with its lower expression in cells residing in tumor spheroid cores. Furthermore, we establish an association between low and high NAV3 expression and the amoeboid and mesenchymal invasive phenotype, respectively, and demonstrate that overexpression of NAV3 directly stimulates glioblastoma invasive behavior in both 2D and 3D environments. Consistently, we observed increased NAV3 expression in cells migrating along blood vessels in mouse xenografts. Overall, our results shed light on the role of NAV3 in glioblastoma invasion, providing insights into this lethal aspect of glioblastoma behavior.

Spatiotemporal Insights into Glioma Oncostream Dynamics: Unraveling Formation, Stability, and Disassembly Pathways

Glioblastoma (GBM) remains a challenge in Neuro-oncology, with a poor prognosis showing only a 5% survival rate beyond two years. This is primarily due to its aggressiveness and intra-tumoral heterogeneity, which limits complete surgical resection and reduces the efficacy of existing treatments. The existence of oncostreams-neuropathological structures comprising aligned spindle-like cells from both tumor and non-tumor origins- is discovered earlier. Oncostreams are closely linked to glioma aggressiveness and facilitate the spread into adjacent healthy brain tissue. A unique molecular signature intrinsic to oncostreams, with overexpression of key genes (i.e., COL1A1, ACTA2) that drive the tumor's mesenchymal transition and malignancy is also identified. Pre-clinical studies on genetically engineered mouse models demonstrated that COL1A1 inhibition disrupts oncostreams, modifies TME, reduces mesenchymal gene expression, and extends survival. An in vitro model using GFP+ NPA cells to investigate how various treatments affect oncostream dynamics is developed. Analysis showed that factors such as cell density, morphology, neurotransmitter agonists, calcium chelators, and cytoskeleton-targeting drugs influence oncostream formation. This data illuminate the patterns of glioma migration and suggest anti-invasion strategies that can improve GBM patient outcomes when combined with traditional therapies. This work highlights the potential of targeting oncostreams to control glioma invasion and enhance treatment efficacy.

Delineation of three-dimensional tumor margins based on normalized absolute difference mapping via volumetric optical coherence tomography

The extent of surgical resection is an important prognostic factor in the treatment of patients with glioblastoma. Optical coherence tomography (OCT) imaging is one of the adjunctive methods available to achieve the maximal surgical resection. In this study, the tumor margins were visualized with the OCT image obtained from a murine glioma model. A commercialized human glioblastoma cell line (U-87) was employed to develop the orthotopic murine glioma model. A swept-source OCT (SS-OCT) system of 1300 nm was used for three-dimensional imaging. Based on the OCT intensity signal, which was obtained via accumulation of each A-scan data, an en-face optical attenuation coefficient (OAC) map was drawn. Due to the limited working distance of the focused beam, OAC values decrease with depth, and using the OAC difference in the superficial area was chosen to outline the tumor boundary, presenting a challenge in analyzing the tumor margin along the depth direction. To overcome this and enable three-dimensional tumor margin detection, we converted the en-face OAC map into an en-face difference map with x- and y-directions and computed the normalized absolute difference (NAD) at each depth to construct a volumetric NAD map, which was compared with the corresponding H&E-stained image. The proposed method successfully revealed the tumor margin along the peripheral boundaries as well as the margin depth. We believe this method can serve as a useful adjunct in glioma surgery, with further studies necessary for real-world practical applications.

Survival Analysis of Patients Undergoing Intraoperative Contrast-enhanced Ultrasound in the Surgical Treatment of Malignant Glioma

OBJECTIVE

Complete resection of malignant gliomas is often challenging. Our previous study indicated that intraoperative contrast-enhanced ultrasound (ICEUS) could aid in the detection of residual tumor remnants and the total removal of brain lesions. This study aimed to investigate the survival rates of patients undergoing resection with or without the use of ICEUS and to assess the impact of ICEUS on the prognosis of patients with malignant glioma.

METHODS

A total of 64 patients diagnosed with malignant glioma (WHO grade HI and IV) who underwent surgery between 2012 and 2018 were included. Among them, 29 patients received ICEUS. The effects of ICEUS on overall survival (OS) and progression-free survival (PFS) of patients were evaluated. A quantitative analysis was performed to compare ICEUS parameters between gliomas and the surrounding tissues.

RESULTS

The ICEUS group showed better survival rates both in OS and PFS than the control group. The univariate analysis revealed that age, pathology and ICEUS were significant prognostic factors for PFS, with only age being a significant prognostic factor for OS. In multivariate analysis, age and ICEUS were significant prognostic factors for both OS and PFS. The quantitative analysis showed that the intensity and transit time of microbubbles reaching the tumors were significantly different from those of microbubbles reaching the surrounding tissue.

CONCLUSION

ICEUS facilitates the identification of residual tumors. Age and ICEUS are prognostic factors for malignant glioma surgery, and use of ICEUS offers a better prognosis for patients with malignant glioma.

Molecular diversity in isocitrate dehydrogenase-wild-type glioblastoma

In the dynamic landscape of glioblastoma, the 2021 World Health Organization Classification of Central Nervous System tumours endeavoured to establish biological homogeneity, yet isocitrate dehydrogenase-wild-type (IDH-wt) glioblastoma persists as a tapestry of clinical and molecular diversity. Intertumoural heterogeneity in IDH-wt glioblastoma presents a formidable challenge in treatment strategies. Recent strides in genetics and molecular biology have enhanced diagnostic precision, revealing distinct subtypes and invasive patterns that influence survival in patients with IDH-wt glioblastoma. Genetic and molecular biomarkers, such as the overexpression of neurofibromin 1, phosphatase and tensin homolog and/or cyclin-dependent kinase inhibitor 2A, along with specific immune cell abundance and neurotransmitters, correlate with favourable outcomes. Conversely, increased expression of epidermal growth factor receptor tyrosine kinase, platelet-derived growth factor receptor alpha and/or vascular endothelial growth factor receptor, coupled with the prevalence of glioma stem cells, tumour-associated myeloid cells, regulatory T cells and exhausted effector cells, signifies an unfavourable prognosis. The methylation status of O6-methylguanine-DNA methyltransferase and the influence of microenvironmental factors and neurotransmitters further shape treatment responses. Understanding intertumoural heterogeneity is complemented by insights into intratumoural dynamics and cellular interactions within the tumour microenvironment. Glioma stem cells and immune cell composition significantly impact progression and outcomes, emphasizing the need for personalized therapies targeting pro-tumoural signalling pathways and resistance mechanisms. A successful glioblastoma management demands biomarker identification, combination therapies and a nuanced approach considering intratumoural variability. These advancements herald a transformative era in glioblastoma comprehension and treatment.

Glioblastoma Margin as a Diffusion Barrier Revealed by Photoactivation of Plasmonic Nanovesicles

Glioblastoma (GBM) is the most complex and lethal primary brain cancer. Adequate drug diffusion and penetration are essential for treating GBM, but how the spatial heterogeneity in GBM impacts drug diffusion and transport is poorly understood. Herein, we report a new method, photoactivation of plasmonic nanovesicles (PANO), to measure molecular diffusion in the extracellular space of GBM. By examining three genetically engineered GBM mouse models that recapitulate key clinical features including the angiogenic core and diffuse infiltration, we found that the tumor margin has the lowest diffusion coefficient (highest tortuosity) compared with the tumor core and surrounding brain tissue. Analysis of the cellular composition shows that tortuosity in the GBM is strongly correlated with neuronal loss and astrocyte activation. Our all-optical measurement reveals the heterogeneous GBM microenvironment and highlights the tumor margin as a diffusion barrier for drug transport in the brain, with implications for therapeutic delivery.

Aquaporin 1 overexpression may enhance glioma tumorigenesis by interacting with the transcriptional regulation networks of Foxo4, Maz, and E2F families

BACKGROUND

The glioblastoma has served as a valuable experimental model system for investigating the growth and invasive properties of glioblastoma. Aquaporin-1 (AQP1) in facilitating cell migration and potentially contributing to tumor progression. In this study, we analyzed the role of AQP1 overexpression in glioblastoma and elucidated the main mechanisms involved.

METHODS

AQP1 overexpression recombinant vector was introduced into C6 rat glioma cells to construct an AQP1 overexpression C6 cell line, and its effect on cell viability and migration ability was detected by MTT and Transwell. RNA was extracted by Trizol method for gene sequencing and transcriptomics analysis, and the differentially expressed genes (DEGs) were enriched for up- and downregulated genes by Principal component analysis (PCA), and the molecular mechanism of AQP1 overexpression was analyzed in comparison with the control group using the NCBI GEO database. Statistical analysis was performed using Mann-Whitney paired two tailed t test.

RESULTS

The cell viability of AQP1-transfected cell lines increased by 23% and the mean distance traveled increased by 67% compared with the control group. Quantitative analysis of gene expression showed that there were 12,121 genes with an average transcripts per million (TPM) value greater than 1. DEGs accounted for 13% of the genes expressed, with the highest correlation with upregulated genes being FOXO4 and MAZ, and the highest with downregulated genes being E2F TFs.

CONCLUSIONS

AQP1 may be implicated in glioma formation by interacting with the transcriptional regulation networks involving the FOXO4, MAZ, and E2F1/2. These findings shed light on the potential significance of AQP1 in glioma pathogenesis and warrant further investigations to unravel the underlying molecular mechanisms.

Development of a "Geo-Tagged" tumor sample registry: intra-operative linkage of sample location to imaging

PURPOSE

There is a growing body of literature documenting glioma heterogeneity in terms of radiographic, histologic, molecular, and genetic characteristics. Incomplete spatial specification of intraoperative tumor samples may contribute to variability in the results of pathological and biological investigations. We have developed a system, termed geo-tagging, for routine intraoperative linkage of each tumor sample to its location via neuronavigation.

METHODS

This is a single-institution, IRB approved, prospective database of undergoing clinically indicated surgery. We evaluated relevant factors affecting data collection by this registry, including tumor and surgical factors (e.g. tumor volume, location, grade and surgeon).

RESULTS

Over a 2-year period, 487 patients underwent craniotomy for an intra-axial tumor. Of those, 214 underwent surgery for a newly diagnosed or recurrent glioma. There was significant variation in the average number of samples collected per registered case, with a range of samples from 2.53 to 4.75 per tumor type. Histology and grade impacted on sampling with a range of 2.0 samples per tumor in Grade four, IDH-WT gliomas to 4.5 samples in grade four, IDH-mutant gliomas. The range of cases with sampling per surgeon was 6 to 99 with a mean of 47.6 cases and there was a statistically significant differences between surgeons. Tumor grade did not have a statistically significant impact on number of samples per case. No significant correlation was found between the number of samples collected and enhancing tumor volume, EOR, or volume of tumor resected.

CONCLUSION

We are using the results of this analysis to develop a prospective sample collection protocol.

Novel approaches targeting ferroptosis in treatment of glioma

Glioma is a malignant brain tumor with a high mortality rate; hence novel treatment approaches are being explored to improve patient outcomes. Ferroptosis, a newly described form of regulated cell death, is emerging as a potential therapeutic target in glioma. Ferroptosis is characterized by the accumulation of lipid peroxides due to a loss of intracellular antioxidant systems represented by the depletion of glutathione and decreased activity of glutathione peroxidase 4 (GPX4). Since glioma cells have a high demand for iron and lipid metabolism, modulation of ferroptosis may represent a promising therapeutic approach for this malignancy. Recent studies indicate that ferroptosis inducers like erastin and RSL3 display potent anticancer activity in a glioma model. In addition, therapeutic strategies, including GPX4 targeting, lipid metabolism modulation, inhibition of amino acid transporters, and ferroptosis targeting natural compounds, have shown positive results in preclinical studies. This review will provide an overview of the functions of ferroptosis in glioma and its potential as a suitable target for glioma therapy.

Glioblastoma Margin as a Diffusion Barrier Revealed by Photoactivation of Plasmonic Nanovesicles

Glioblastoma (GBM) is the most complex and lethal adult primary brain cancer. Adequate drug diffusion and penetration are essential for treating GBM, but how the spatial heterogeneity in GBM impacts drug diffusion and transport is poorly understood. Herein, we report a new method, photoactivation of plasmonic nanovesicles (PANO), to measure molecular diffusion in the extracellular space of GBM. By examining three genetically engineered GBM mouse models that recapitulate key clinical features including angiogenic core and diffuse infiltration, we found that the tumor margin has the lowest diffusion coefficient (highest tortuosity) compared with the tumor core and surrounding brain tissue. Analysis of the cellular composition shows that the tortuosity in the GBM is strongly correlated with neuronal loss and astrocyte activation. Our all-optical measurement reveals the heterogeneous GBM microenvironment and highlights the tumor margin as a diffusion barrier for drug transport in the brain, with implications for therapeutic delivery.

Agent-Based Modelling Reveals the Role of the Tumor Microenvironment on the Short-Term Success of Combination Temozolomide/Immune Checkpoint Blockade to Treat Glioblastoma

Glioblastoma is the most common and deadly primary brain tumor in adults. All glioblastoma patients receiving standard-of-care surgery-radiotherapy-chemotherapy (i.e., temozolomide (TMZ)) recur, with an average survival time of only 15 months. New approaches to the treatment of glioblastoma, including immune checkpoint blockade and oncolytic viruses, offer the possibility of improving glioblastoma outcomes and have as such been under intense study. Unfortunately, these treatment modalities have thus far failed to achieve approval. Recently, in an attempt to bolster efficacy and improve patient outcomes, regimens combining chemotherapy and immune checkpoint inhibitors have been tested in trials. Unfortunately, these efforts have not resulted in significant increases to patient survival. To better understand the various factors impacting treatment outcomes of combined TMZ and immune checkpoint blockade, we developed a systems-level, computational model that describes the interplay between glioblastoma, immune, and stromal cells with this combination treatment. Initializing our model to spatial resection patient samples labeled using imaging mass cytometry, our model's predictions show how the localization of glioblastoma cells, influence therapeutic success. We further validated these predictions in samples of brain metastases from patients given they generally respond better to checkpoint blockade compared with primary glioblastoma. Ultimately, our model provides novel insights into the mechanisms of therapeutic success of immune checkpoint inhibitors in brain tumors and delineates strategies to translate combination immunotherapy regimens more effectively into the clinic. SIGNIFICANCE STATEMENT: Extending survival times for glioblastoma patients remains a critical challenge. Although immunotherapies in combination with chemotherapy hold promise, clinical trials have not shown much success. Here, systems models calibrated to and validated against patient samples can improve preclinical and clinical studies by shedding light on the factors distinguishing responses/failures. By initializing our model with imaging mass cytometry visualization of patient samples, we elucidate how factors such as localization of glioblastoma cells and CD8+ T cell infiltration impact treatment outcomes.

Nanoparticle-Based Treatment in Glioblastoma

Glioblastoma (GB) is a malignant glioma associated with a mean overall survival of 12 to 18 months, even with optimal treatment, due to its high relapse rate and treatment resistance. The standardized first-line treatment consists of surgery, which allows for diagnosis and cytoreduction, followed by stereotactic fractionated radiotherapy and chemotherapy. Treatment failure can result from the poor passage of drugs through the blood-brain barrier (BBB). The development of novel and more effective therapeutic approaches is paramount to increasing the life expectancy of GB patients. Nanoparticle-based treatments include epitopes that are designed to interact with specialized transport systems, ultimately allowing the crossing of the BBB, increasing therapeutic efficacy, and reducing systemic toxicity and drug degradation. Polymeric nanoparticles have shown promising results in terms of precisely directing drugs to the brain with minimal systemic side effects. Various methods of drug delivery that pass through the BBB, such as the stereotactic injection of nanoparticles, are being actively tested in vitro and in vivo in animal models. A significant variety of pre-clinical studies with polymeric nanoparticles for the treatment of GB are being conducted, with only a few nanoparticle-based drug delivery systems to date having entered clinical trials. Pre-clinical studies are key to testing the safety and efficacy of these novel anticancer therapies and will hopefully facilitate the testing of the clinical validity of this promising treatment method. Here we review the recent literature concerning the most frequently reported types of nanoparticles for the treatment of GB.

Advances in computational and translational approaches for malignant glioma

Gliomas are the most common primary brain tumors in adults and carry a dismal prognosis for patients. Current standard-of-care for gliomas is comprised of maximal safe surgical resection following by a combination of chemotherapy and radiation therapy depending on the grade and type of tumor. Despite decades of research efforts directed towards identifying effective therapies, curative treatments have been largely elusive in the majority of cases. The development and refinement of novel methodologies over recent years that integrate computational techniques with translational paradigms have begun to shed light on features of glioma, previously difficult to study. These methodologies have enabled a number of point-of-care approaches that can provide real-time, patient-specific and tumor-specific diagnostics that may guide the selection and development of therapies including decision-making surrounding surgical resection. Novel methodologies have also demonstrated utility in characterizing glioma-brain network dynamics and in turn early investigations into glioma plasticity and influence on surgical planning at a systems level. Similarly, application of such techniques in the laboratory setting have enhanced the ability to accurately model glioma disease processes and interrogate mechanisms of resistance to therapy. In this review, we highlight representative trends in the integration of computational methodologies including artificial intelligence and modeling with translational approaches in the study and treatment of malignant gliomas both at the point-of-care and outside the operative theater in silico as well as in the laboratory setting.

Applying single cell multi-omic analyses to understand treatment resistance in pediatric high grade glioma

Despite improvements in cancer patient outcomes seen in the past decade, tumor resistance to therapy remains a major impediment to achieving durable clinical responses. Intratumoral heterogeneity related to genetic, epigenetic, transcriptomic, proteomic, and metabolic differences between individual cancer cells has emerged as a driver of therapeutic resistance. This cell to cell heterogeneity can be assessed using single cell profiling technologies that enable the identification of tumor cell clones that exhibit similar defining features like specific mutations or patterns of DNA methylation. Single cell profiling of tumors before and after treatment can generate new insights into the cancer cell characteristics that confer therapeutic resistance by identifying intrinsically resistant sub-populations that survive treatment and by describing new cellular features that emerge post-treatment due to tumor cell evolution. Integrative, single cell analytical approaches have already proven advantageous in studies characterizing treatment-resistant clones in cancers where pre- and post-treatment patient samples are readily available, such as leukemia. In contrast, little is known about other cancer subtypes like pediatric high grade glioma, a class of heterogeneous, malignant brain tumors in children that rapidly develop resistance to multiple therapeutic modalities, including chemotherapy, immunotherapy, and radiation. Leveraging single cell multi-omic technologies to analyze naïve and therapy-resistant glioma may lead to the discovery of novel strategies to overcome treatment resistance in brain tumors with dismal clinical outcomes. In this review, we explore the potential for single cell multi-omic analyses to reveal mechanisms of glioma resistance to therapy and discuss opportunities to apply these approaches to improve long-term therapeutic response in pediatric high grade glioma and other brain tumors with limited treatment options.

Spatial metabolic heterogeneity of oligodendrogliomas at single-cell resolution

Oligodendrogliomas are a type of rare and incurable gliomas whose metabolic profiles have yet to be fully examined. The present study examined the spatial differences in metabolic landscapes underlying oligodendrogliomas and should provide unique insights into the metabolic characteristics of these uncommon tumors. Single-cell RNA-sequencing expression profiles from 4044 oligodendroglioma cells derived from tumors resected from four locations frontal, temporal, parietal, and frontotemporoinsular) and in which 1p/19q co-deletion and IDH1 or IDH2 mutations were confirmed were computationally analyzed through a robust workflow to elucidate relative differences in metabolic pathway activities among the different locations. Dimensionality reduction using metabolic expression profiles exhibited clustering corresponding to each location subgroup. From the 80 metabolic pathways examined, over 70 pathways had significantly different activity scores between location subgroups. Further analysis of metabolic heterogeneity suggests that mitochondrial oxidative phosphorylation accounts for considerable metabolic variation within the same locations. Steroid and fatty acid metabolism pathways were also found to be major contributors to heterogeneity. Oligodendrogliomas display distinct spatial metabolic differences in addition to intra-location metabolic heterogeneity.

A generalizable strategy for crosslinkable albumin-based hydrogels and application as potential anti-tumor nanoplatform

Albumin-based hydrogels have emerged as promising nanoparticle systems for the effective delivery of hydrophobic anticancer drugs. Anti-cancer drugs often cause some adverse effects, such as toxicity and rapid clearance by mononuclear phagocytic systems. Herein, a new strategy of synthesizing N-hydroxysuccinimide (NHS)-activated linker to form crosslinkable albumin-based hydrogels (CABH) is reported. The CABH favored physiochemical characteristics improvement of doxorubicin (Dox) and drug release. The CABH was constructed depending on the crosslinking reaction between NHS activated glycerol and albumin. The size of CABH was approximately 200 nm examined by dynamic light scattering (DLS) and transmission electron microscopy (TEM). It was found that the particle size and size distribution of the CABH remained stable in neutral PBS for 1 week. Dox loaded CABH would be controllably released in weak acidic environment verified by in vitro release and in vitro cell imaging. The Dox loaded hydrogel results in significant killing in the case of acidic culture medium. Our work provides a crosslinking method to formulate albumin nanoplatform and improve the size, stability, drug loading capacity and controlled release, which throws light on the potential application in drug delivery.

Imaging biomarkers for clinical applications in neuro-oncology: current status and future perspectives

Biomarker discovery and development are popular for detecting the subtle diseases. However, biomarkers are needed to be validated and approved, and even fewer are ever used clinically. Imaging biomarkers have a crucial role in the treatment of cancer patients because they provide objective information on tumor biology, the tumor's habitat, and the tumor's signature in the environment. Tumor changes in response to an intervention complement molecular and genomic translational diagnosis as well as quantitative information. Neuro-oncology has become more prominent in diagnostics and targeted therapies. The classification of tumors has been actively updated, and drug discovery, and delivery in nanoimmunotherapies are advancing in the field of target therapy research. It is important that biomarkers and diagnostic implements be developed and used to assess the prognosis or late effects of long-term survivors. An improved realization of cancer biology has transformed its management with an increasing emphasis on a personalized approach in precision medicine. In the first part, we discuss the biomarker categories in relation to the courses of a disease and specific clinical contexts, including that patients and specimens should both directly reflect the target population and intended use. In the second part, we present the CT perfusion approach that provides quantitative and qualitative data that has been successfully applied to the clinical diagnosis, treatment and application. Furthermore, the novel and promising multiparametric MR imageing approach will provide deeper insights regarding the tumor microenvironment in the immune response. Additionally, we briefly remark new tactics based on MRI and PET for converging on imaging biomarkers combined with applications of bioinformatics in artificial intelligence. In the third part, we briefly address new approaches based on theranostics in precision medicine. These sophisticated techniques merge achievable standardizations into an applicatory apparatus for primarily a diagnostic implementation and tracking radioactive drugs to identify and to deliver therapies in an individualized medicine paradigm. In this article, we describe the critical principles for imaging biomarker characterization and discuss the current status of CT, MRI and PET in finiding imaging biomarkers of early disease.

Alternative normalization and analysis pipeline to address systematic bias in NanoString GeoMx Digital Spatial Profiling data

Spatial transcriptomics is a novel technique that provides RNA-expression data with tissue-contextual annotations. Quality assessments of such techniques using end-user generated data are often lacking. Here, we evaluated data from the NanoString GeoMx Digital Spatial Profiling (DSP) platform and standard processing pipelines. We queried 72 ROIs from 12 glioma samples, performed replicate experiments of eight samples for validation, and evaluated five external datasets. The data consistently showed vastly different signal intensities between samples and experimental conditions that resulted in biased analysis. We evaluated the performance of alternative normalization strategies and show that quantile normalization can adequately address the technical issues related to the differences in data distributions. Compared to bulk RNA sequencing, NanoString DSP data show a limited dynamic range which underestimates differences between conditions. Weighted gene co-expression network analysis allowed extraction of gene signatures associated with tissue phenotypes from ROI annotations. Nanostring GeoMx DSP data therefore require alternative normalization methods and analysis pipelines.

Molecular profile and clinical features of patients with gliomas using a broad targeted next generation-sequencing panel

Gliomas are the most common malignant primary brain tumors characterized by poor prognosis. The genotyping of tumors using next generation sequencing (NGS) platforms enables the identification of genetic alterations that constitute diagnostic, prognostic and predictive biomarkers. The present study investigated the molecular profile of 32 tumor samples from 32 patients with high-grade gliomas by implementing a broad 80-gene targeted NGS panel while reporting their clinicopathological characteristics and outcomes. Subsequently, 14 of 32 tumor specimens were also genotyped using a 55-gene NGS panel to validate the diagnostic accuracy and clinical utility of the extended panel. The median follow-up was 19.2 months. In total, 129 genetic alterations including 33 structural variants were identified in 38 distinct genes. Among 96 variants (single nucleotide variants and insertions and deletions), 38 were pathogenic and 58 variants of unknown clinical significance. TP53 was the most frequently mutated gene, followed by PTEN and IDH1 genes. Glioma patients with IDH1 mutant tumors were younger and had significantly longer overall survival compared to patients with wild-type IDH1 tumors. Similarly, tumors with TP53 mutations were more likely observed in younger patients with glioma. Subsequently, a comparison of mutational profiles of samples analyzed by both panels was also performed. Implementation of the comprehensive pan-cancer and the MOL panels resulted in the identification of 37 and 15 variants, respectively. Of those, 13 were common. Comprehensive pan-cancer panel identified 24 additional variants, 22 of which were located in regions that were not targeted by the MOL panel. By contrast, the MOL panel identified two additional variants. Overall, the present study demonstrated that using an extended tumor profile assay instead of a glioma-specific tumor profile panel identified additional genetic changes that may be taken into consideration as potential therapeutic targets for glioma diagnosis and molecular classification.

Role of nerves in neurofibromatosis type 1-related nervous system tumors

BACKGROUND

Neurofibromatosis type 1 (NF1) is an autosomal dominant genetic disorder that affects nearly 1 in 3000 infants. Neurofibromin inactivation and NF1 gene mutations are involved in various aspects of neuronal function regulation, including neuronal development induction, electrophysiological activity elevation, growth factor expression, and neurotransmitter release. NF1 patients often exhibit a predisposition to tumor development, especially in the nervous system, resulting in the frequent occurrence of peripheral nerve sheath tumors and gliomas. Recent evidence suggests that nerves play a role in the development of multiple tumor types, prompting researchers to investigate the nerve as a vital component in and regulator of the initiation and progression of NF1-related nervous system tumors.

CONCLUSION

In this review, we summarize existing evidence about the specific effects of NF1 mutation on neurons and emerging research on the role of nerves in neurological tumor development, promising a new set of selective and targeted therapies for NF1-related tumors.

Melanoma central nervous system metastases: An update to approaches, challenges, and opportunities

Brain metastases are the most common brain malignancy. This review discusses the studies presented at the third annual meeting of the Melanoma Research Foundation in the context of other recent reports on the biology and treatment of melanoma brain metastases (MBM). Although symptomatic MBM patients were historically excluded from immunotherapy trials, efforts from clinicians and patient advocates have resulted in more inclusive and even dedicated clinical trials for MBM patients. The results of checkpoint inhibitor trials were discussed in conversation with current standards of care for MBM patients, including steroids, radiotherapy, and targeted therapy. Advances in the basic scientific understanding of MBM, including the role of astrocytes and metabolic adaptations to the brain microenvironment, are exposing new vulnerabilities which could be exploited for therapeutic purposes. Technical advances including single-cell omics and multiplex imaging are expanding our understanding of the MBM ecosystem and its response to therapy. This unprecedented level of spatial and temporal resolution is expected to dramatically advance the field in the coming years and render novel treatment approaches that might improve MBM patient outcomes.

Integration of single-cell RNA sequencing and spatial transcriptomics to reveal the glioblastoma heterogeneity

Glioblastoma (GBM), a deadly brain tumor, is still one of a few lasting challenges of contemporary oncology. Current therapies fail to significantly improve patient survival due to GBM tremendous genetic, transcriptomic, immunological, and sex-dependent heterogeneity. Over the years, clinical differences between males and females were characterized. For instance, higher incidence of GBM in males or distinct responses to cancer chemotherapy and immunotherapy between males and females have been noted. Despite the introduction of single-cell RNA sequencing and spatial transcriptomics, these differences were not further investigated as studies were focused only on revealing the general picture of GBM heterogeneity. Hence, in this mini-review, we summarized the current state of knowledge on GBM heterogeneity revealed by single-cell RNA sequencing and spatial transcriptomics with regard to genetics, immunology, and sex-dependent differences. Additionally, we highlighted future research directions which would fill the gap of knowledge on the impact of patient's sex on the disease outcome.

Integration of single-cell RNA sequencing and spatial transcriptomics to reveal the glioblastoma heterogeneity

Glioblastoma (GBM), a deadly brain tumor, is still one of the few lasting challenges of contemporary oncology. Current therapies fail to significantly improve patient survival due to GBM's tremendous genetic, transcriptomic, immunological, and sex-dependent heterogeneity. Over the years, clinical differences between males and females were characterized. For instance, higher incidence of GBM in males or distinct responses to cancer chemotherapy and immunotherapy between males and females have been noted. However, despite the introduction of single-cell RNA sequencing and spatial transcriptomics, these differences were not further investigated as studies were focused only on exposing the general picture of GBM heterogeneity. Hence, in this study, we summarized the current state of knowledge on GBM heterogeneity exposed by single-cell RNA sequencing and spatial transcriptomics with regard to genetics, immunology, and sex-dependent differences. Additionally, we highlighted future research directions which would fill the gap of knowledge on the impact of patient's sex on the disease outcome.

The complex interactions between the cellular and non-cellular components of the brain tumor microenvironmental landscape and their therapeutic implications

Glioblastoma (GBM), an aggressive high-grade glial tumor, is resistant to therapy and has a poor prognosis due to its universal recurrence rate. GBM cells interact with the non-cellular components in the tumor microenvironment (TME), facilitating their rapid growth, evolution, and invasion into the normal brain. Herein we discuss the complexity of the interactions between the cellular and non-cellular components of the TME and advances in the field as a whole. While the stroma of non-central nervous system (CNS) tissues is abundant in fibrillary collagens, laminins, and fibronectin, the normal brain extracellular matrix (ECM) predominantly includes proteoglycans, glycoproteins, and glycosaminoglycans, with fibrillary components typically found only in association with the vasculature. However, recent studies have found that in GBMs, the microenvironment evolves into a more complex array of components, with upregulated collagen gene expression and aligned fibrillary ECM networks. The interactions of glioma cells with the ECM and the degradation of matrix barriers are crucial for both single-cell and collective invasion into neighboring brain tissue. ECM-regulated mechanisms also contribute to immune exclusion, resulting in a major challenge to immunotherapy delivery and efficacy. Glioma cells chemically and physically control the function of their environment, co-opting complex signaling networks for their own benefit, resulting in radio- and chemo-resistance, tumor recurrence, and cancer progression. Targeting these interactions is an attractive strategy for overcoming therapy resistance, and we will discuss recent advances in preclinical studies, current clinical trials, and potential future clinical applications. In this review, we also provide a comprehensive discussion of the complexities of the interconnected cellular and non-cellular components of the microenvironmental landscape of brain tumors to guide the development of safe and effective therapeutic strategies against brain cancer.

Protein Quality Control in Glioblastoma: A Review of the Current Literature with New Perspectives on Therapeutic Targets

Protein quality control allows eukaryotes to maintain proteostasis under the stress of constantly changing conditions. In this review, we discuss the current literature on PQC, highlighting flaws that must exist for malignancy to occur. At the nidus of PQC, the expression of BAG1-6 reflects the cell environment; each isoform directs proteins toward different, parallel branches of the quality control cascade. The sum of these branches creates a net shift toward either homeostasis or apoptosis. With an established role in ALP, Bag3 is necessary for cell survival in stress conditions including those of the cancerous niche (i.e., hypoxia, hypermutation). Evidence suggests that excessive Bag3–HSP70 activity not only sustains, but also propagates cancers. Its role is anti-apoptotic—which allows malignant cells to persist—and intercellular—with the production of infectious ‘oncosomes’ enabling cancer expansion and recurrence. While Bag3 has been identified as a key prognostic indicator in several cancer types, its investigation is limited regarding glioblastoma. The cochaperone HSP70 has been strongly linked with GBM, while ALP inhibitors have been shown to improve GBM susceptibility to chemotherapeutics. Given the highly resilient, frequently recurrent nature of GBM, the targeting of Bag3 is a necessary consideration for the successful and definitive treatment of GBM.

Histone Deacetylase Inhibitors Impair Glioblastoma Cell Motility and Proliferation

Simple Summary

Glioblastoma (GBM) is considered the deadliest brain tumor; with patients displaying a high incidence of relapse and a 3-year survival of only 3–5%. For these reasons, investigation of the molecular basis of the disease could provide novel targets for therapy and improve patient prognoses. Based on our previous data, demonstrating that high levels of the transcription factor TCF4 (TCF7L2) sustain the aggressiveness and the stem cell features of these tumors, in this study we tested the ability of the histone deacetylase inhibitors (HDI) Trichostatin-A and Vorinostat to suppress TCF4 levels. We demonstrated that HDI treatment impairs proliferation and viability of GBM cells. Moreover, molecular analysis of HDI effects disclosed their ability to counteract tumor cell motility by affecting the RhoA-GTPase and the interferon pathways, supporting their further characterization as potential anti-GBM agents.

Abstract

Despite being subjected to high-dose chemo and radiotherapy, glioblastoma (GBM) patients still encounter almost inevitable relapse, due to the capability of tumor cells to disseminate and invade normal brain tissues. Moreover, the presence of a cancer stem cell (CSC) subpopulation, already demonstrated to better resist and evade treatments, further frustrates potential therapeutic approaches. In this context, we previously demonstrated that GBM is characterized by a tightly-regulated balance between the β-catenin cofactors TCF1 and TCF4, with high levels of TCF4 responsible for sustaining CSC in these tumors; thus, supporting their aggressive features. Since histone deacetylase inhibitors (HDI) have been reported to strongly reduce TCF4 levels in colon cancer cells, we hypothesized that they could also exert a similar therapeutic action in GBM. Here, we treated primary GBM cultures with Trichostatin-A and Vorinostat, demonstrating their ability to strongly suppress the Wnt-dependent pathways; thus, promoting CSC differentiation and concomitantly impairing GBM cell viability and proliferation. More interestingly, analysis of their molecular effects suggested a prominent HDI action against GBM cell motility/migration, which we demonstrated to rely on the inhibition of the RhoA-GTPase and interferon intracellular cascades. Our results suggest HDI as potential therapeutic agents in GBM, through their action on multiple cancer hallmarks.

Mechanical Properties in the Glioma Microenvironment: Emerging Insights and Theranostic Opportunities

Gliomas represent the most common malignant primary brain tumors, and a high-grade subset of these tumors including glioblastoma are particularly refractory to current standard-of-care therapies including maximal surgical resection and chemoradiation. The prognosis of patients with these tumors continues to be poor with existing treatments and understanding treatment failure is required. The dynamic interplay between the tumor and its microenvironment has been increasingly recognized as a key mechanism by which cellular adaptation, tumor heterogeneity, and treatment resistance develops. Beyond ongoing lines of investigation into the peritumoral cellular milieu and microenvironmental architecture, recent studies have identified the growing role of mechanical properties of the microenvironment. Elucidating the impact of these biophysical factors on disease heterogeneity is crucial for designing durable therapies and may offer novel approaches for intervention and disease monitoring. Specifically, pharmacologic targeting of mechanical signal transduction substrates such as specific ion channels that have been implicated in glioma progression or the development of agents that alter the mechanical properties of the microenvironment to halt disease progression have the potential to be promising treatment strategies based on early studies. Similarly, the development of technology to measure mechanical properties of the microenvironment in vitro and in vivo and simulate these properties in bioengineered models may facilitate the use of mechanical properties as diagnostic or prognostic biomarkers that can guide treatment. Here, we review current perspectives on the influence of mechanical properties in glioma with a focus on biophysical features of tumor-adjacent tissue, the role of fluid mechanics, and mechanisms of mechanical signal transduction. We highlight the implications of recent discoveries for novel diagnostics, therapeutic targets, and accurate preclinical modeling of glioma.