Pediatric gliomas, the most frequent brain tumors in children, are characterized by heterogeneity and a unique tumor immune microenvironment. They are categorized into different subtypes, including low-grade gliomas like pilocytic astrocytomas and high-grade gliomas such as diffuse midline gliomas and diffuse intrinsic pontine gliomas, each exhibiting distinct immunological profiles. The tumor immune microenvironment in pediatric gliomas is shaped by cellular and non-cellular components, including immune cells, cytokines, and the extracellular matrix, involved in tumor progression, immune evasion, and response to therapy. While pediatric low-grade gliomas often display an immunosuppressed microenvironment, high-grade gliomas are characterized by complex immune infiltrates and intricate immunosuppressive mechanisms. The blood-brain barrier further obscures immune cell recruitment and therapeutic delivery. Despite advances in understanding adult gliomas, the immunobiology of pediatric tumors is poorly investigated, with limited data on the interactions between glioma cells and immune populations such as T and natural killer cells, as well as tumor-associated macrophages. Herein, we provide an update of the current knowledge on tumor immune microenvironment interactions in pediatric gliomas, highlighting the immunosuppressive mechanisms and emerging immunotherapeutic strategies aiming at overcoming these barriers to improve clinical outcomes for affected children.

Glioblastoma (GBM) is a highly aggressive malignancy with a poor prognosis and frequent resistance to temozolomide (TMZ), the standard-of-care chemotherapy. The complex mechanisms underlying GBM chemoresistance, particularly the role of pericytes, remain poorly understood due to the lack of physiologically relevant in vitro models replicating the complex tumor microenvironment (TME). Here, we present a biomimetic 3D GBM microphysiological system that replicates the biomechanical properties of brain tissue (G'∼800Pa, G"∼100Pa) and enables the study of pericyte-mediated TMZ resistance. GBM spheroids (U87, LN229, PDM140) were cultured alone or co-cultured with pericytes in a composite hydrogel for 14 days and remained viable and proliferative. In response to TMZ, PDM140 was the most sensitive (IC50=73μM), followed by LN229 (IC50=278μM) and U87 (IC50=446μM). Co-culture with pericytes significantly increased GBM spheroid viability by 22.7% (PDM140), 32.5% (LN229), and 22.1% (U87), confirming pericyte-induced TMZ resistance. Notably, pericytes exhibited a 160-fold upregulation of C-C motif chemokine ligand 5 (CCL5) upon TMZ treatment, implicating the CCL5-mediated pathway in chemoresistance. This innovative brain-mimicking 3D GBM model provides a physiologically relevant platform for studying tumor-pericyte interactions and testing therapeutic strategies targeting CCL5-mediated resistance mechanisms in GBM. STATEMENT OF SIGNIFICANCE: We developed a multicellular 3D glioblastoma microphysiological system mimicking the physicochemical properties of brain tissues and pericyte-mediated temozolomide resistance that can be used to screen for standard-of-care chemotherapy. This advanced hydrogel-based platform demonstrated the critical role of the glioblastoma tumor microenvironment in modulating chemotherapy sensitivity, particularly the pericyte-induced CCL5-CCR5 paracrine axis that can lead to the identification of therapeutic targets within the CCL5-CCR5 pathway toward more effective treatments disrupting these resistance mechanisms. Overall, the proposed 3D glioblastoma microphysiological system can transform drug screening and personalized treatment for GBM by offering ethical and cost-effective alternatives to animal testing and more effective drug screening and discovery efforts, ultimately improving GBM patient outcomes.

Glioblastoma (GBM) is the most aggressive form of brain cancer, with limited therapeutic options. While microglia contribute to GBM progression, the mechanisms by which they foster a protumorigenic immune environment remain poorly understood. We identify the zinc transporter Zrt- And Irt-Like Protein 4 (ZIP4) as a pivotal regulator of the GBM immune landscape. In orthotopic mouse models, ZIP4 drives tumor growth and behavioral changes. Mechanistically, ZIP4 modulates microglial plasticity through tumor-derived extracellular vesicles carrying triggering receptor expressed on myeloid cells-1 (TREM1), a process regulated by the zinc-dependent transcription factor Zinc Finger E-box Binding Homeobox 1 in GBM cells. TREM1 enhances microglial plasticity through the spleen associated tyrosine kinase-Pyruvate dehydrogenase kinase-signal transducer and activator of transcription 3 (SYK-PDK-STAT3) signaling axis, ultimately promoting an immune environment favorable to tumor progression. ZIP4 depletion or TREM1 inhibition attenuates tumor growth and behavioral effects in vivo by disrupting the tumor-microglia interaction. These findings establish ZIP4 as a key modulator of the GBM immune landscape and suggest a promising therapeutic target to counteract microglia-mediated tumor progression.

Glioma, a highly malignant central nervous system tumor, exhibits aggressive invasiveness, extensive infiltration, and poor prognosis. Conventional treatments such as surgery, radiotherapy, and chemotherapy are hindered by limitations including the inability to overcome the blood-brain barrier (BBB), drug resistance, and high recurrence rates. Ferroptosis induced by nanoparticle-based systems offers an innovative strategy for glioma therapy by efficiently traversing the BBB, precisely delivering ferroptosis inducers, enhancing tumor accumulation, and enabling stimuli-responsive drug release. These features collectively improve the induction efficiency of ferroptosis in glioma cells. Various nanoplatforms, including inorganic nanoparticles, biomimetic carriers, and polymer-based systems, have demonstrated potential in crossing the BBB, inducing ferroptosis, and suppressing glioma progression. These systems enhance reactive oxygen species generation, deplete glutathione, and disrupt tumor microenvironment defense mechanisms, achieving synergistic therapeutic effects. The integration of ferroptosis with nanotechnology is emerging as a promising, non-invasive strategy for the treatment of gliomas, offering substantial therapeutic potential.

Glioma subtyping is crucial for treatment decisions, but traditional approaches often fail to capture tumor heterogeneity. This study proposes a novel framework integrating multiplex immunohistochemistry (mIHC) and machine learning for glioma subtyping and prognosis prediction. 185 patient samples from the Huashan hospital cohort were stained using a multi-label mIHC panel and analyzed with an AI-based auto-scanning system to calculate cell ratios and determine the proportion of positive tumor cells for various markers. Patients were divided into two cohorts (training: N = 111, testing: N = 74), and a machine learning model was then developed and validated for subtype classification and prognosis prediction. The framework identified two distinct glioma subtypes with significant differences in prognosis, clinical characteristics, and molecular profiles. The high-risk subtype, associated with older age, poorer outcomes, astrocytoma/glioblastoma, higher tumor grades, elevated mesenchymal scores, and an inhibitory immune microenvironment, exhibited IDH wild-type, 1p19q non-codeletion, and MGMT promoter unmethylation, suggesting chemotherapy resistance. Conversely, the low-risk subtype, characterized by younger age, better prognosis, astrocytoma/oligodendroglioma, lower tumor grades, and favorable molecular profiles (IDH mutation, 1p19q codeletion, MGMT promoter methylation), indicated chemotherapy sensitivity. The mIHC-based framework enables rapid glioma classification, facilitating tailored treatment strategies and accurate prognosis prediction, potentially improving patient management and outcomes.

Glioblastoma is a fatal primary malignant brain tumor. Despite therapies involving surgical resection, chemotherapy, and radiation therapy, the average survival for glioblastoma patients remains at approximately 15 months. MicroRNAs (miRNAs) are short noncoding RNA molecules that regulate the expression of the majority of human genes. Numerous genes are concurrently deregulated in glioblastoma. Consequently, molecular monotherapies have failed to achieve improvements in clinical outcomes. Several lines of evidence suggest that simultaneous targeting of several deregulated molecules is required to achieve better therapies. However, the simultaneous targeting of several deregulated oncogenic drivers is severely limited by the fact that the drugs needed to target many deregulated molecules do not currently exist, and because combining several drugs in a clinical setting leads to an exponential increase in toxicity. We hypothesized that we can develop and use miRNA to simultaneously inhibit multiple deregulated genes for more efficacious glioblastoma therapies. The goal of this study was therefore to identify master regulatory microRNAs (miRNAs) and use them to simultaneously target multiple deregulated molecules for GBM therapy. We defined master regulatory miRNAs as those that target several deregulated genes in glioblastoma. To find master regulatory miRNAs, we first used PAR-CLIP screenings to identify all targets of all miRNAs in glioblastoma cells. We then analyzed TCGA tumor data to determine which of these targets are deregulated in human tumors. We developed and used an algorithm to rank these targets for significance in glioblastoma malignancy based on their magnitude of deregulation, frequency of deregulation, and correlation with patient survival. We then ranked the miRNAs for their capacity of targeting multiple glioblastoma-deregulated genes and therefore the potential to exhibit strong anti-tumor effects when delivered as therapy. Using this strategy, we selected two tumor suppressor master regulatory miRNAs, miR-340, miR-382 and an oncogenic master regulatory miRNA, miR-17. We validated the target genes of the miRNAs and showed that they form part of important glioblastoma regulatory pathways. We then showed that the miRNAs (miR-340 and miR-582) or the miR-17 inhibitor have strong inhibitory effects on glioblastoma cell growth, survival, invasion, stemness and in vivo tumor growth. Ultimately, we developed and successfully tested a new therapeutic approach to delivery miR-340 using MRI guided focused ultrasound and microbubbles (FUS-MB) and special brain penetrating nanoparticles (BPN). This approach resulted in a substantial reduction in tumor volume and prolongation of the survival of glioblastoma-bearing mice and can be translated into clinical trials. We therefore developed and successfully tested a novel strategy to discover and deliver miRNAs for glioblastoma and cancer therapy.

Glioma, as one of the most complex and prognostically variable malignant tumors of the central nervous system, poses a significant challenge to clinical decision-making due to its molecular heterogeneity. This study aims to deepen our understanding of glioma molecular subtypes and explore key gene markers with prognostic and diagnostic value. We utilized an angiogenesis-related gene set and employed the Non-negative Matrix Factorization (NMF) algorithm to successfully identify two distinct prognostic subtypes, with subtype one exhibiting more unfavorable prognostic characteristics. To further elucidate the biological functional differences between these two subtypes, we conducted Gene Ontology (GO) functional annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and Gene Set Enrichment Analysis (GSEA). Building on this, we integrated differentially expressed genes between subtypes with core genes revealed by Weighted Gene Co-expression Network Analysis (WGCNA) through intersection analysis to pinpoint a series of key candidate genes. Subsequently, we constructed a Protein-Protein Interaction (PPI) network to identify genes occupying central nodes within the network. To screen markers with high specificity and sensitivity for prognosis and diagnosis, we adopted a dual-track strategy: on the one hand, we utilized machine learning algorithms such as Lasso regression, Support Vector Machine (SVM), and Random Forest (RF) to select core genes, identifying markers that can accurately predict the subtype with a poor prognosis; on the other hand, we employed a comprehensive evaluation system incorporating 101 machine learning ensemble algorithms to further validate and screen prognosis-related genes. Through cross-validation using these two strategies, we ultimately determined SERPINH1 and CTSZ as dual prognostic and diagnostic markers for glioma. This study not only provides a new perspective and tool for the molecular subclassification of glioma but also, through a rigorous multi-algorithm, multi-dimensional screening process, uncovers SERPINH1 and CTSZ as markers with potential clinical translational value. These findings are expected to offer more precise biomarker support for the early diagnosis and prognostic assessment of glioma, potentially paving new avenues for the development of personalized treatment strategies and improving patient outcomes. This has far-reaching implications for the clinical management of glioma in the field of neurosurgery.

Glioma-associated macrophages (GAMs) constitute the most abundant subset of immune cells in the glioblastoma (GBM) microenvironment, but the underlying mechanism of intense infiltration needs to be elucidated. In this study, we found that GBM cells secrete ICAM1 via FASN signaling to promote GAM infiltration. FASN expression is correlated with GAM density in GBM patients. In vitro experiments revealed that FASN regulates the type-I interferon pathway, particularly STAT1 expression. Moreover, disrupting FASN-STAT1 signaling through the overexpression or inhibition of FASN or STAT1 in GBM cells strongly influences microglial recruitment. Additionally, ICAM1 acts as a direct transcriptional candidate of FASN-STAT1 and a paracrine soluble factor, recruiting microglia to GBM tumors. This study revealed crosstalk between GBM cells and GAMs through FASN-STAT1-ICAM1 signaling to promote microglial infiltration, suggesting potential strategies for treating GBM patients.

Pilocytic astrocytoma (PA) is the commonest low-grade tumour affecting children and is frequently experienced as a chronic disease associated with extended treatment, periods of regrowth, and long-term disability. This contrasts with the view of PA as a benign tumour with positive clinical outcomes and raises the fundamental question of biologically driven change over time within these tumours, which will impact diagnosis, stratification, and management. To investigate the molecular, cellular, and pathological stability of PA we performed RNA sequencing, methylation array profiling, immunohistochemistry, and targeted panel DNA sequencing on a cohort of 15 PA patients with matched primary/longitudinal samples at a mean sampling interval of 2.7 years. Through pairwise analysis of primary versus longitudinal tumour samples we identified changes to immune-related pathways within the expression and methylation profiles of longitudinal PA. Further interrogation of these changes revealed an enrichment over time for microglial cell populations, which was validated by immunohistochemistry against common monocyte/microglial markers. Moreover, immunohistochemical characterisation revealed concurrent increases in the expression of M2-like and anti-inflammatory markers. Microglial enrichments were consistent across the cohort and were not adequately explained by a range of potential confounders, including receipt of adjuvant therapy. Taken together, these data challenge the idea of pilocytic astrocytoma as a static entity and indicate that they consistently accumulate microglia over time, potentially co-opting the immune microenvironment towards an anti-inflammatory phenotype that may affect the natural course and treatment response of the tumours.

Brain cancers such as glioblastoma (GBM) cause a disproportionate level of morbidity and mortality among cancer patients. Therapeutic advances over the past decade have done little to change this bleak prognosis, helping only a minority of patients. The brain tumor microenvironment (TME) is highly supportive of the tumors. It differs from other peripheral malignancies due to its unique composition, which includes the glial, neural, and immune cell populations. Until recently, the study of the brain TME was limited by the lack of methods to target the different cells in TME. This protocol describes stereotaxic surgery optimized for gene delivery by recombinant adeno-associated viruses or lentiviruses in mice and rats. This method allows the manipulation of gene expression in the TME with excellent spatiotemporal control in specific cells (or a subpopulation of cells). Many aspects of the technique, including its versatility, ease of application, and high reproducibility, make it an attractive approach for studying cellular and circuit functions in the TME.

Glioblastoma (GBM) is an aggressive form of cancer, comprising ≈80% of malignant brain tumors. However, there are no effective treatments for GBM due to its heterogeneity and the presence of the blood-brain barrier (BBB), which restricts the delivery of therapeutics to the brain. Despite in vitro models contributing to the understanding of GBM, conventional 2D models oversimplify the complex tumor microenvironment. Organ-on-a-chip (OoC) models have emerged as promising platforms that recapitulate human tissue physiology, enabling disease modeling, drug screening, and personalized medicine. There is a sudden increase in GBM-on-a-chip models that can significantly advance the knowledge of GBM etiology and revolutionize drug development by reducing animal testing and enhancing translation to the clinic. In this review, an overview of GBM-on-a-chip models and their applications is reported for drug screening and discussed current challenges and potential future directions for GBM-on-a-chip models.

Glioblastoma multiforme (GBM) is recognized as the most aggressive and malignant form of brain cancer, characterized by a highly heterogeneous phenotype, poor prognosis, and a median survival time of less than 16 months. Recent studies have highlighted the critical role of glioblastoma-associated macrophages (GAMs) in promoting tumor progression and resistance not only to immunotherapy but also to radiotherapy and chemotherapy. GAMs actively suppress immune responses, promote angiogenesis, facilitate tumor metastasis, and induce therapy resistance, through various mechanisms such as cytokines production, signaling pathways regulation, and angiogenesis. In this context, understanding these regulatory mechanisms is essential for developing efficient therapies. Preclinical studies have investigated diverse approaches to target these cells, both as monotherapies or in combination with other treatments. While these approaches have shown promise in strengthening antitumor immune responses in animal models, their clinical success remains to be fully determined. Herein, we provide a comprehensive overview of GAMs's role in GBM therapeutic resistance and summarizes existing approaches to target GAMs in overcoming tumor resistance.

Background: Glioblastoma IDH-wildtype (GBM IDH-wt) is the most aggressive brain tumor in adults and is characterized by an immunosuppressive microenvironment. Different factors shaping its tumor microenvironment (TME) regulate tumor progression and treatment response. The aim of this study was to characterize the main immunosuppressive elements of the GBM IDH-wt TME. Methods: Immunohistochemistry for CD3, CD4, CD8, CD163, programmed death ligand 1 (PD-L1) and programmed death 1 (PD1) was performed on surgical tumor specimens from patients diagnosed with GBM IDH-wt, according to the CNS WHO 2021 criteria. The impact of categorical variables on time-dependent outcomes such as overall survival (OS) and progression-free survival (PFS) has been estimated through the Kaplan-Meier method. Results: We included 30 patients (19 males and 11 females), median age of 59.8 years (range 40.2-69.1 years). All patients underwent surgery followed by temozolomide concurrent with and adjuvant to radiotherapy. MGMT was methylated in 14 patients (47%) and unmethylated in 16 patients (53%). The overall absolute percentages of CD4+ lymphocytes, both intratumoral and perivascular, were significantly more represented than CD8+ lymphocytes in the TME (p = 0.02). A low density of CD4+ lymphocytes (≤10%) was found to be a favorable prognostic factor for GBM outcome (p = 0.02). Patients with MGMT methylated and unmethylated tumors exhibited a distinct TME composition, with a significant higher number of perivascular CD8+ lymphocytes (p = 0.002), intratumoral CD8+ lymphocytes (p = 0.0024) and perivascular CD4+ lymphocytes (p = 0.014) in MGMT unmethylated tumors. PD-L1 expression in tumor cell surface was observed in four tumors (13.3%), and PD1 expression in infiltrating T lymphocytes was observed in nine (30%) tumors, with predominantly perivascular distribution. Conclusions: MGMT methylated and unmethylated tumors exhibit different immune profiles, likely reflecting the different biology of these tumors. The expression of PD-L1 in GBM IDH-wt patients is confined to a small subpopulation. While we found a significant association between low CD4+ lymphocyte density (≤10%) and survival, given the small numbers of our cohort, the prognostic value of CD4+ lymphocyte density will need to be validated in large-scale studies.

Glioma is known for its immunosuppressive microenvironment, which makes it challenging to target through immunotherapies. Immune cells like macrophages, microglia, myeloid-derived suppressor cells, and T lymphocytes are known to infiltrate the glioma tumor microenvironment and regulate immune response distinctively. Among the variety of immune cells, T lymphocytes have highly complex and multifaceted roles in the glioma immune landscape. T lymphocytes, which include CD4+ helper and CD8+ cytotoxic T cells, are known for their pivotal roles in anti-tumor responses. However, these cells may behave differently in the highly dynamic glioma microenvironment, for example, via an immune invasion mechanism enforced by tumor cells. Therefore, T lymphocytes play dual roles in glioma immunity, firstly by their anti-tumor responses, and secondly by exploiting gliomas to promote immune invasion. As an immunosuppression strategy, glioma induces T-cell exhaustion and suppression of effector T cells by regulatory T cells (Tregs) or by altering their signaling pathways. Further, the expression of immune checkpoint inhibitors on the glioma cell surface leads to T cell anergy and dysfunction. Overall, this dynamic interplay between T lymphocytes and glioma is crucial for designing more effective immunotherapies. The current review provides detailed knowledge on the roles of T lymphocytes in the glioma immune microenvironment and helps to explore novel therapeutic approaches to reinvigorate T lymphocytes.

Prior studies have described the complex interplay that exists between glioma cells and neurons; however, the electrophysiological properties endogenous to glioma cells remain obscure. To address this, we employed Patch-sequencing (Patch-seq) on human glioma specimens and found that one-third of patched cells in IDH mutant (IDHmut) tumors demonstrate properties of both neurons and glia. To define these hybrid cells (HCs), which fire single, short action potentials, and discern if they are of tumoral origin, we developed the single cell rule association mining (SCRAM) computational tool to annotate each cell individually. SCRAM revealed that HCs possess select features of GABAergic neurons and oligodendrocyte precursor cells, and include both tumor and non-tumor cells. These studies characterize the combined electrophysiological and molecular properties of human glioma cells and describe a cell type in human glioma with unique electrophysiological and transcriptomic properties that may also exist in the non-tumor brain.

For decades, researchers have studied how brain tumors, the immune system, and drugs interact. With the advances in cancer neuroscience, which centers on defining and therapeutically targeting nervous system-cancer interactions, both within the local tumor microenvironment (TME) and on a systemic level, the subtle relationship between neurons and tumors in the central nervous system (CNS) has been deeply studied. Neurons, as the executors of brain functional activities, have been shown to significantly influence the emergence and development of brain tumors, including both primary and metastatic tumors. They engage with tumor cells via chemical or electrical synapses, directly regulating tumors or via intricate coupling networks, and also contribute to the TME through paracrine signaling, secreting proteins that exert regulatory effects. For instance, in a study involving a mouse model of glioblastoma, the authors observed a 42% increase in tumor volume when neuronal activity was stimulated, compared to controls (p < 0.01), indicating a direct correlation between neural activity and tumor growth. These thought-provoking results offer promising new strategies for brain tumor therapies, highlighting the potential of neuronal modulation to curb tumor progression. Future strategies may focus on developing drugs to inhibit or neutralize proteins and other bioactive substances secreted by neurons, break synaptic connections and interactions between infiltrating cells and tumor cells, as well as disrupt electrical coupling within glioma cell networks. By harnessing the insights gained from this research, we aspire to usher in a new era of brain tumor therapies that are both more potent and precise.

Treatment of gliomas, the most prevalent primary malignant neoplasm of the central nervous system, is challenging. Arachidonate 5-lipoxygenase activating protein (ALOX5AP) is crucial for converting arachidonic acid into leukotrienes and is associated with poor prognosis in multiple cancers. Nevertheless, its relationship with the prognosis and the immune microenvironment of gliomas remains incompletely understood.

The differential expression of ALOX5AP was evaluated based on public Databases. Kaplan-Meier, multivariate Cox proportional hazards regression analysis, time-dependent receiver operating characteristic, and nomogram were used to estimate the prognostic value of ALOX5AP. The relationship between ALOX5AP and immune infiltration was calculated using ESTIMATE and CIBERSORT algorithms. Relationships between ALOX5AP and human leukocyte antigen molecules, immune checkpoints, tumor mutation burden, TIDE score, and immunophenoscore were calculated to evaluate glioma immunotherapy response. Single gene GSEA and co-expression network-based GO and KEGG enrichment analysis were performed to explore the potential function of ALOX5AP. ALOX5AP expression was verified using multiplex immunofluorescence staining and its prognostic effects were confirmed using a glioma tissue microarray.

ALOX5AP was highly expressed in gliomas, and the expression level was related to World Health Organization (WHO) grade, age, sex, IDH mutation status, 1p19q co-deletion status, MGMTp methylation status, and poor prognosis. Single-cell RNA sequencing showed that ALOX5AP was expressed in macrophages, monocytes, and T cells but not in tumor cells. ALOX5AP expression positively correlated with M2 macrophage infiltration and poor immunotherapy response. Immunofluorescence staining demonstrated that ALOX5AP was upregulated in WHO higher-grade gliomas, localizing to M2 macrophages. Glioma tissue microarray confirmed the adverse effect of ALOX5AP in the prognosis of glioma.

ALOX5AP is highly expressed in M2 macrophages and may act as a potential biomarker for predicting prognosis and immunotherapy response in patients with glioma.

Recent studies have revealed that PTPRZ1-MET (ZM) fusion plays a pivotal role in the progression of glioma to glioblastoma multiforme (GBM), thus serving as a biomarker to distinguish between primary GBM and secondary GBM (sGBM). However, the mechanisms through which ZM fusion influences this progression remain to be elucidated. GBMs with ZM showed poorer prognoses and greater infiltration of tumor-associated macrophages (TAMs) than those without ZM. Glioma stem-like cells (GSCs) and TAMs play complex roles in glioma recurrence, glioma progression and therapy resistance. In this study, we analyzed RNA-seq data from sGBM patients' glioma tissues with or without ZM fusion, and found that stemness and macrophage markers were more highly expressed in sGBM patients harboring ZM than in those without ZM fusion. ZM enhanced the self-renewal and proliferation of GSCs, thereby accelerating glioma progression. In addition, ZM-positive GSCs facilitated the infiltration of TAMs and drove their polarization toward an immunosuppressive phenotype, which was primarily accomplished through the extracellular secretion of ISG20. Our research identified the MET-STAT3-ISG20 axis within GSCs, thus demonstrating the critical role of ZM in GBM initiation and progression. Our study demonstrated that, in contrast to ZM-positive differentiated glioma cells, ZM-positive GSCs upregulated ISG20 expression through the MET-STAT3-ISG20 axis. The extracellular secretion of ISG20 recruited and induced M2-like polarization in macrophages, thereby promoting tumor progression. Our results reveal a novel mechanism involved in ZM-positive GBM pathogenesis and identify potential therapeutic targets.

Radiologists encounter significant challenges when segmenting and determining brain tumors in patients because this information assists in treatment planning. The utilization of artificial intelligence (AI), especially deep learning (DL), has emerged as a useful tool in healthcare, aiding radiologists in their diagnostic processes. This empowers radiologists to understand the biology of tumors better and provide personalized care to patients with brain tumors. The segmentation of brain tumors using multi-modal magnetic resonance imaging (MRI) images has received considerable attention. In this survey, we first discuss multi-modal and available magnetic resonance imaging modalities and their properties. Subsequently, we discuss the most recent DL-based models for brain tumor segmentation using multi-modal MRI. We divide this section into three parts based on the architecture: the first is for models that use the backbone of convolutional neural networks (CNN), the second is for vision transformer-based models, and the third is for hybrid models that use both convolutional neural networks and transformer in the architecture. In addition, in-depth statistical analysis is performed of the recent publication, frequently used datasets, and evaluation metrics for segmentation tasks. Finally, open research challenges are identified and suggested promising future directions for brain tumor segmentation to improve diagnostic accuracy and treatment outcomes for patients with brain tumors. This aligns with public health goals to use health technologies for better healthcare delivery and population health management.

Glioblastoma multiform (GBM) is the most prevalent CNS (central nervous system) tumor in adults, with an average survival length shorter than 2 years and rare metastasis to organs other than CNS. Despite extensive attempts at surgical resecting, the inherently permeable nature of this disease has rendered relapse nearly unavoidable. Thus, immunotherapy is a feasible alternative, as stimulated immune cells can enter into the remote and inaccessible tumor cells. Immunotherapy has revolutionized patient upshots in various malignancies and might introduce different effective ways for GBM patients. Currently, researchers are exploring various immunotherapeutic strategies in patients with GBM to target both the innate and acquired immune responses. These approaches include reprogrammed tumor-associated macrophages, the use of specific antibodies to inhibit tumor progression and metastasis, modifying tumor-associated macrophages with antibodies, vaccines that utilize tumor-specific dendritic cells to activate anti-tumor T cells, immune checkpoint inhibitors, and enhanced T cells that function against tumor cells. Despite these findings, there is still room for improving the response faults of the many currently tested immunotherapies. This study aims to review the currently used immunotherapy approaches with their molecular mechanisms and clinical application in GBM.

The adaptability of glioblastoma (GBM) cells, encouraged by complex interactions with the tumour microenvironment (TME), currently renders GBM an incurable cancer. Despite intensive research, with many clinical trials, GBM patients rely on standard treatments including surgery followed by radiation and chemotherapy, which have been observed to induce a more aggressive phenotype in recurrent tumours. This failure to improve treatments is undoubtedly a result of insufficient models which fail to incorporate components of the human brain TME. Research has increasingly uncovered mechanisms of tumour-TME interactions that correlate to worsened patient prognoses, including tumour-associated astrocyte mitochondrial transfer, neuronal circuit remodelling and immunosuppression. This tumour hijacked TME is highly implicated in driving therapy resistance, with further alterations within the TME and tumour resulting from therapy exposure inducing increased tumour growth and invasion. Recent developments improving organoid models, including aspects of the TME, are paving an exciting future for the research and drug development for GBM, with the hopes of improving patient survival growing closer. This review focuses on GBMs interactions with the TME and their effect on tumour pathology and treatment efficiency, with a look at challenges GBM models face in sufficiently recapitulating this complex and highly adaptive cancer.

Glioma is one of the most severe central nervous systems (CNS)-specific tumors, with rapidly growing malignant glial cells accounting for roughly half of all brain tumors and having a poor survival rate ranging from 12 to 15 months. Despite being the most often used technique for glioma therapy, conventional chemotherapy suffers from low permeability of the blood-brain barrier (BBB) and blood-brain tumor barrier (BBTB) to anticancer drugs. When it comes to nanocarriers, liposomes are thought of as one of the most promising nanocarrier systems for glioma treatment. However, owing to BBB tight junctions, non-targeted liposomes, which passively accumulate in most cancer cells primarily via the increased permeability and retention effect (EPR), would not be suitable for glioma treatment. The surface modification of liposomes with various active targeting ligands has shown encouraging outcomes in the recent times by allowing various chemotherapy drugs to pass across the BBB and BBTB and enter glioma cells. This review article introduces by briefly outlining the landscape of glioma, its classification, and some of the pathogenic causes. Further, it discusses major barriers for delivering drugs to glioma such as the BBB, BBTB, and tumor microenvironment. It further discusses modified liposomes such as long-acting circulating liposomes, actively targeted liposomes, stimuli responsive liposomes. Finally, it highlighted the limitations of liposomes in the treatment of glioma and the various actively targeted liposomes undergoing clinical trials for the treatment of glioma.

Glioblastoma (GBM) poses a significant challenge in clinical oncology due to its aggressive nature, heterogeneity, and resistance to therapies. Cancer stem cells (CSCs) play a critical role in GBM, particularly in treatment resistance and tumor relapse, emphasizing the need to comprehend the mechanisms regulating these cells. Also, their multifaceted contributions to the tumor microenvironment (TME) underline their significance, driven by their unique properties. This study aimed to characterize glioblastoma stem cells (GSCs), specifically slow-cycling cells (SCCs), in an immunocompetent murine GBM model to explore their similarities with their human counterparts. Using the KR158 mouse model, we confirmed that SCCs isolated from this model exhibited key traits and functional properties akin to human SCCs. KR158 murine SCCs, expanded in the gliomasphere assay, demonstrated sphere forming ability, self-renewing capacity, positive tumorigenicity, enhanced stemness and resistance to chemotherapy. Together, our findings validate the KR158 murine model as a framework to investigate GSCs and SCCs in GBM pathology, and explore specifically the SCC-immune system communications, understand their role in disease progression, and evaluate the effect of therapeutic strategies targeting these specific connections.

Breast cancer metastasis to the brain is a clinical challenge rising in prevalence. However, the underlying mechanisms, especially how cancer cells adapt a distant brain niche to facilitate colonization, remain poorly understood. A unique metabolic feature of the brain is the coupling between neurons and astrocytes through glutamate, glutamine, and lactate. Here we show that extracellular vesicles from breast cancer cells with a high potential to develop brain metastases carry high levels of miR-199b-5p, which shows higher levels in the blood of breast cancer patients with brain metastases comparing to those with metastatic cancer in other organs. miR-199b-5p targets solute carrier transporters (SLC1A2/EAAT2 in astrocytes and SLC38A2/SNAT2 and SLC16A7/MCT2 in neurons) to hijack the neuron-astrocyte metabolic coupling, leading to extracellular retention of these metabolites and promoting cancer cell growth. Our findings reveal a mechanism through which cancer cells of a non-brain origin reprogram neural metabolism to fuel brain metastases.

Glioblastomas (GBM) are the most common primary malignant brain tumors, comprising 2% of all cancers in adults. Their location and cellular and molecular heterogeneity, along with their highly infiltrative nature, make their treatment challenging. Recently, our research group reported promising results from a prospective phase II clinical trial involving allogeneic vaccination with dendritic cells (DCs). To date, six out of the thirty-seven reported cases remain alive without tumor recurrence. In this study, we focused on the characterization of infiltrating immune cells observed at the time of surgical resection. An analytical model employing a neural network-based predictive algorithm was used to ascertain the potential prognostic implications of immunological variables on patients' overall survival. Counterintuitively, immune phenotyping of tumor-associated macrophages (TAMs) has revealed the extracellular marker PD-L1 to be a positive predictor of overall survival. In contrast, the elevated expression of CD86 within this cellular subset emerged as a negative prognostic indicator. Fundamentally, the neural network algorithm outlined here allows a prediction of the responsiveness of patients undergoing dendritic cell vaccination in terms of overall survival based on clinical parameters and the profile of infiltrated TAMs observed at the time of tumor excision.

Prior studies have described the complex interplay that exists between glioma cells and neurons, however, the electrophysiological properties endogenous to tumor cells remain obscure. To address this, we employed Patch-sequencing on human glioma specimens and found that one third of patched cells in IDH mutant (IDH mut ) tumors demonstrate properties of both neurons and glia by firing single, short action potentials. To define these hybrid cells (HCs) and discern if they are tumor in origin, we developed a computational tool, Single Cell Rule Association Mining (SCRAM), to annotate each cell individually. SCRAM revealed that HCs represent tumor and non-tumor cells that feature GABAergic neuron and oligodendrocyte precursor cell signatures. These studies are the first to characterize the combined electrophysiological and molecular properties of human glioma cells and describe a new cell type in human glioma with unique electrophysiological and transcriptomic properties that are likely also present in the non-tumor mammalian brain.

Reactive astrogliosis is a hallmark of various brain pathologies, including neurodegenerative diseases and glioblastomas. However, the specific intermediate metabolites contributing to reactive astrogliosis remain unknown. This study investigated how glioblastomas induce reactive astrogliosis in the neighboring microenvironment and explore 11C-acetate PET as an imaging technique for detecting reactive astrogliosis.

Through in vitro, mouse models, and human tissue experiments, we examined the association between elevated 11C-acetate uptake and reactive astrogliosis in gliomas. We explored acetate from glioblastoma cells, which triggers reactive astrogliosis in neighboring astrocytes by upregulating MAO-B and monocarboxylate transporter 1 (MCT1) expression. We evaluated the presence of cancer stem cells in the reactive astrogliosis region of glioblastomas and assessed the correlation between the volume of 11C-acetate uptake beyond MRI and prognosis.

Elevated 11C-acetate uptake is associated with reactive astrogliosis and astrocytic MCT1 in the periphery of glioblastomas in human tissues and mouse models. Glioblastoma cells exhibit increased acetate production as a result of glucose metabolism, with subsequent secretion of acetate. Acetate derived from glioblastoma cells induces reactive astrogliosis in neighboring astrocytes by increasing the expression of MAO-B and MCT1. We found cancer stem cells within the reactive astrogliosis at the tumor periphery. Consequently, a larger volume of 11C-acetate uptake beyond contrast-enhanced MRI was associated with a worse prognosis.

Our results highlight the role of acetate derived from glioblastoma cells in inducing reactive astrogliosis and underscore the potential value of 11C-acetate PET as an imaging technique for detecting reactive astrogliosis, offering important implications for the diagnosis and treatment of glioblastomas.

Brain tumors are a heterogeneous group of brain neoplasms that are highly prevalent in individuals of all ages worldwide. Within this pathological framework, the most prevalent and aggressive type of primary brain tumor is glioblastoma (GB), a subtype of glioma that falls within the IV-grade astrocytoma group. The death rate for patients with GB remains high, occurring within a few months after diagnosis, even with the gold-standard therapies now available, such as surgery, radiation, or a pharmaceutical approach with Temozolomide. For this reason, it is crucial to continue looking for cutting-edge therapeutic options to raise patients' survival chances. Pentraxin 3 (PTX3) is a multifunctional protein that has a variety of regulatory roles in inflammatory processes related to extracellular matrix (ECM). An increase in PTX3 blood levels is considered a trustworthy factor associated with the beginning of inflammation. Moreover, scientific evidence suggested that PTX3 is a sensitive and earlier inflammation-related marker compared to the short pentraxin C-reactive protein (CRP). In several tumoral subtypes, via regulating complement-dependent and macrophage-associated tumor-promoting inflammation, it has been demonstrated that PTX3 may function as a promoter of cancer metastasis, invasion, and stemness. Our review aims to deeply evaluate the function of PTX3 in the pathological context of GB, considering its pivotal biological activities and its possible role as a molecular target for future therapies.

The tumor microenvironment (TME) plays an important role in the process of tumorigenesis, regulating the growth, metabolism, proliferation, and invasion of cancer cells, as well as contributing to tumor resistance to the conventional chemoradiotherapies. Several types of cells with relatively stable phenotypes have been identified within the TME, including cancer-associated fibroblasts (CAFs), tumor-associated macrophages (TAMs), neutrophils, and natural killer (NK) cells, which have been shown to modulate cancer cell proliferation, metastasis, and interaction with the immune system, thus promoting tumor heterogeneity. Growing evidence suggests that tumor-cell-derived extracellular vesicles (EVs), via the transfer of various molecules (e.g., RNA, proteins, peptides, and lipids), play a pivotal role in the transformation of normal cells in the TME into their tumor-associated protumorigenic counterparts. This review article focuses on the functions of EVs in the modulation of the TME with a view to how exosomes contribute to the transformation of normal cells, as well as their importance for cancer diagnosis and therapy.

Microglia are the brain's resident macrophages that play pivotal roles in immune surveillance and maintaining homeostasis of the Central Nervous System (CNS). Microglia are functionally implicated in various cerebrovascular diseases, including stroke, aneurysm, and tumorigenesis as they regulate neuroinflammatory responses and tissue repair processes. Here, we review the manifold functions of microglia in the brain under physiological and pathological conditions, primarily focusing on the implication of microglia in glioma propagation and progression. We further review the current status of therapies targeting microglial cells, including their re-education, depletion, and re-population approaches as therapeutic options to improve patient outcomes for various neurological and neuroinflammatory disorders, including cancer.

Glioblastoma (GBM) poses a significant challenge in clinical oncology due to its aggressive nature, heterogeneity, and resistance to therapies. Cancer stem cells (CSCs) play a critical role in GBM, particularly in treatment-resistance and tumor relapse, emphasizing the need to comprehend the mechanisms regulating these cells. Also, their multifaceted contributions to the tumor-microenvironment (TME) underline their significance, driven by their unique properties. This study aimed to characterize glioblastoma stem cells (GSCs), specifically slow-cycling cells (SCCs), in an immunocompetent murine GBM model to explore their similarities with their human counterparts. Using the KR158 mouse model, we confirmed that SCCs isolated from this model exhibited key traits and functional properties akin to human SCCs. KR158 murine SCCs, expanded in the gliomasphere assay, demonstrated sphere forming ability, self-renewing capacity, positive tumorigenicity, enhanced stemness and resistance to chemotherapy. Together, our findings validate the KR158 murine model as a framework to investigate GSCs and SCCs in GBM-pathology, and explore specifically the SCC-immune system communications, understand their role in disease progression, and evaluate the effect of therapeutic strategies targeting these specific connections.

Glioblastoma (GBM) stands as the most aggressive and lethal among the main types of primary brain tumors. It exhibits malignant growth, infiltrating the brain tissue, and displaying resistance toward treatment. GBM is a complex disease characterized by high degrees of heterogeneity. During tumour growth, microglia and astrocytes, among other cells, infiltrate the tumour microenvironment and contribute extensively to gliomagenesis. Tumour-associated macrophages (TAMs), either of peripheral origin or representing brain-intrinsic microglia, are the most numerous nonneoplastic populations in the tumour microenvironment in GBM. The complex heterogeneous nature of GBM cells is facilitated by the local inflammatory tumour microenvironment, which mostly induces tumour aggressiveness and drug resistance. The immunosuppressive tumour microenvironment of GBM provides multiple pathways for tumour immune evasion, contributing to tumour progression. Additionally, TAMs and astrocytes can contribute to tumour progression through the release of cytokines and activation of signalling pathways. In this review, we summarize the role of the microenvironment in GBM progression, focusing on neuroinflammation. These recent advancements in research of the microenvironment hold the potential to offer a promising approach to the treatment of GBM in the coming times.

Diffuse midline gliomas (DMGs), including diffuse intrinsic pontine glioma, have among the highest mortality rates of all childhood cancers, despite recent advancements in cancer therapeutics. This is partly because, unlike some CNS tumors, the blood-brain barrier (BBB) of DMG tumor vessels remains intact. The BBB prevents the permeation of many molecular therapies into the brain parenchyma, where the cancer cells reside. Focused ultrasound (FUS) with microbubbles has recently emerged as an innovative and exciting technology that non-invasively permeabilizes the BBB in a small focal region with millimeter precision. In this review, current treatment methods and biological barriers to treating DMGs are discussed. State-of-the-art FUS-mediated BBB opening is then examined, with a focus on the effects of various ultrasound parameters and the treatment of DMGs.

This comprehensive article explores the complex field of glioma treatment, with a focus on the important roles of non-coding RNAsRNAs (ncRNAs) and exosomes, as well as the potential synergies of immunotherapy. The investigation begins by examining the various functions of ncRNAs and their involvement in glioma pathogenesis, progression, and as potential diagnostic biomarkers. Special attention is given to exosomes as carriers of ncRNAs and their intricate dynamics within the tumor microenvironment. The exploration extends to immunotherapy methods, analyzing their mechanisms and clinical implications in the treatment of glioma. By synthesizing these components, the article aims to provide a comprehensive understanding of how ncRNAs, exosomes, and immunotherapy interact, offering valuable insights into the evolving landscape of glioma research and therapeutic strategies.