Search Results (638)

Pediatric high-grade glioma (pHGG) is a devastating group of childhood cancers associated with poor outcomes. Traditionally, diagnosis was based on histologic and immunohistochemical characteristics, including high mitotic activity, presence of necrosis, and presence of glial cell markers (e.g., GFAP). With advances in molecular tumor profiling, these tumors have been recategorized based on specific molecular findings that better lend themselves to prediction of treatment response and prognosis. pHGG is now categorized into four subtypes: H3K27-altered, H3G34-mutant, H3/IDH-WT, and infant-type high-grade glioma (iHGG). Molecular profiling has not only increased the specificity of diagnosis but also improved prognostication. Additionally, these molecular findings provide novel targets for individual tumor-directed therapy. While these therapies are largely still under investigation, continued investigation of distinct molecular markers in these tumors is imperative to extending event-free survival (EFS) and overall survival (OS) for patients with pHGG. Full article

Pediatric high-grade gliomas (pHGGs), particularly diffuse midline gliomas (DMGs), are among the most lethal brain tumors due to poor survival and resistance to therapies. DMGs possess a distinct genetic profile, primarily driven by hallmark mutations such as H3K27M, ACVR1, and PDGFRA mutations/amplifications and TP53 inactivation, all of which contribute to tumor biology and therapeutic resistance. Developing physiologically relevant preclinical models that replicate both tumor biology and the tumor microenvironment (TME) is critical for advancing effective treatments. This review highlights recent progress in in vitro, ex vivo, and in vivo models, including patient-derived brain organoids, genetically engineered mouse models (GEMMs), and region-specific midline organoids incorporating SHH, BMP, and FGF2/8/19 signaling to model pontine gliomas. Key genetic alterations can now be introduced using lipofectamine-mediated transfection, PiggyBac plasmid systems, and CRISPR-Cas9, allowing the precise study of tumor initiation, progression, and therapy resistance. These models enable the investigation of TME interactions, including immune responses, neuronal infiltration, and therapeutic vulnerabilities. Future advancements involve developing immune-competent organoids, integrating vascularized networks, and applying multi-omics platforms like single-cell RNA sequencing and spatial transcriptomics to dissect tumor heterogeneity and lineage-specific vulnerabilities. These innovative approaches aim to enhance drug screening, identify new therapeutic targets, and accelerate personalized treatments for pediatric gliomas. Full article

High-grade gliomas (HGGs, WHO grades 3–4) are highly aggressive, with a poor prognosis and treatment resistance. Immune evasion may contribute to their progression, but the role of cytotoxic T-lymphocyte immune evasion (CTLE) is not well-validated. This study analyzed the transcriptomic data of 525 patients from TCGA-GBM-HG_U133A. Two molecular subtypes were identified based on 182 CTLE-associated genes, with 238 differentially expressed genes between them. A prognostic model was developed, identifying BST2 and DIRAS3 as key risk factors, and validated in multiple cohorts. The subtypes had distinct immune profiles, with Cluster 2 showing higher immune infiltration but a poorer prognosis. The model had a good predictive performance. High-risk patients had upregulated BST2 and DIRAS3, linked to immunosuppression and shorter survival. Knockdown experiments confirmed their roles in GBM cell migration and invasion. Mechanistically, they promote immune evasion. BST2 and DIRAS3 could be therapeutic targets for HGG immunotherapy. Full article

Background: High-grade glioma (HGG) is the most common primary malignant brain tumor, with peak incidence in the fifth and sixth decades of life. Although HGG is rare in children, the prognosis remains poor, with a median overall survival (OS) of less than two years. Recently, TRK inhibitors have been approved for the treatment of tumors harboring NTRK gene fusions. In this review, we analyzed data from early clinical trials investigating the use of these agents in patients with HGG. Methods: A systematic literature search was performed in the PubMed database. Studies involving patients with HGG treated with TRK inhibitors were included. We analyzed progression-free survival (PFS), 24-week disease control rate, and complete or partial radiological responses according to the Response Assessment in Neuro-Oncology (RANO) criteria. Results: Sixteen studies comprising 55 patients with HGG harboring NTRK gene fusions (19 adults and 36 children) were included. A statistically significant difference in PFS was observed between pediatric and adult patients treated with TRK inhibitors (17 vs. 8.5 months; p < 0.001). Pediatric patients also exhibited a higher rate of complete or partial radiological response compared to adults (94% vs. 57%). Discussion: Although the available evidence on TRK inhibitors in HGG is limited, the findings of this review highlight a potentially promising role for these agents, particularly in the treatment of pediatric HGGs. Full article

Background: Pediatric high-grade glioma (pHGG) is a highly aggressive cancer with unique biology distinct from adult high-grade glioma, limiting the effectiveness of standard treatment protocols derived from adult research. Objective: The purpose of this report is to present preliminary results from an ongoing pilot study integrating spectroscopic magnetic resonance imaging (sMRI) to guide proton beam therapy and longitudinal imaging analysis in pediatric patients with high-grade glioma (pHGG). Methods: Thirteen pediatric patients under 21 years old with supratentorial WHO grade III-IV glioma underwent baseline and serial whole-brain spectroscopic MRI alongside standard structural MRIs. Radiation targets were defined using T1-weighted contrast enhanced, T2-FLAIR, and Cho/NAA ≥ 2X maps. Longitudinal analyses included voxel-level metabolic change maps and spatial overlap metrics comparing pre-proton therapy and post-. Results: Six patients had sufficient longitudinal data; five received sMRI-guided PBT. Significant positive correlation (R² = 0.89, p < 0.0001) was observed between T2-FLAIR and Cho/NAA ≥ 2X volumes. Voxel-level difference maps of Cho/NAA and Choline revealed dynamic metabolic changes across follow-up scans. Analyzing Cho/NAA and Cho changes over time allowed differentiation between true progression and pseudoprogression, which conventional MRI alone struggles to achieve. Conclusions: Longitudinal sMRI enhanced metabolic tracking in pHGG, detects early tumor changes, and refines RT targeting beyond structural imaging. This first in-kind study highlights the potential of sMRI biomarkers in tracking treatment effects and emphasizes the complementary roles of metabolic and radiographic metrics in evaluating therapy response in pHGG. Full article

Chronic inflammation is increasingly recognized as a driver of glioma progression, with tumor necrosis factor-alpha (TNF-α) playing a central role in modulating the tumor microenvironment. This study aimed to investigate the expression profiles and regulatory mechanisms of TNF-α and its downstream mediators—including interleukin-1 beta (IL-1β), Mitogen-Activated Protein Kinase Kinase Kinase 8 (MAP3K8), and Mitogen-activated protein kinase kinase 7 (MAP2K7)—in astrocytic tumors of varying malignancy. We conducted an integrative molecular analysis of 60 human astrocytic tumor samples (20 G2, 12 G3, 28 G4) using transcriptomic microarrays, Reverse Transcription Quantitative Polymerase Chain Reaction (RT-qPCR), Enzyme-Linked Immunosorbent Assay (ELISA), Western blotting, immunohistochemistry, methylation-specific PCR, and miRNA profiling. Prognostic associations were evaluated using Kaplan–Meier survival and Cox regression analyses. TNF-α, IL-1β, and MAP3K8 were significantly upregulated in high-grade tumors, with log₂ fold changes ranging from 5.56 to 8.76 (p < 0.001). High expression of TNF-α (HR = 2.10, 95% CI: 1.27–3.46, p = 0.004), IL-1β (HR = 2.35, 95% CI: 1.45–3.82, p = 0.001), and MAP3K8 (Hazard Ratio; HR = 1.88, 95% confidence interval; 95% CI: 1.12–3.16, p = 0.015) was associated with poorer overall survival. miR-34a-3p and miR-30 family members, predicted to target TNF-α and IL-1β, were markedly downregulated in G3/G4 tumors (e.g., miR-30e-3p fold change: –3.78, p < 0.01). Promoter hypomethylation was observed in G3/G4 tumors, supporting epigenetic activation. Our findings establish a multi-layered regulatory mechanism of TNF-α signaling in astrocytic tumors. These data highlight the TNF-α/IL-1β/MAP3K8 axis as a critical driver of glioma aggressiveness and a potential therapeutic target. Full article

Background: The occurrence (incidence or prevalence) of delirium in brain tumors is unknown, yet delirium is associated with increased morbidity and mortality and worse quality of life. We conducted a systematic review and meta-analysis to determine the occurrence of delirium in hospitalized patients with brain tumors. Methods: PubMed, Scopus, and Web of Science were systematically searched for papers from 1 January 1999 to 12 July 2024, including references from texts. Cross-sectional, prospective, and other cohort study designs were included, and individual case reports, case series, editorials, and reviews were excluded. The included papers were scored using a validated sensitivity analysis tool and tested for quality and bias using funnel plots and Egger’s test. We used random effects models for the summary estimates. We performed subgroup analyses by tumor type, tumor location, delirium subtype, and length of stay. Results: Of the 452 studies screened, 27 were included, representing 35,958 patients. The overall occurrence of delirium was 0.17 (95% CI [0.11–0.24]). Delirium occurrence in patients with low-grade gliomas, high-grade gliomas, and brain metastases was 0.10 [0.06–0.16], 0.21 [0.10–0.40], and 0.31 [0.16–0.50], respectively. Compared to the occipital lobe, there was a higher occurrence of delirium for tumors in the frontal (RR 3.08 [1.35–8.22]) and temporal lobes (RR 2.88 [1.22–7.93]). The patients were more likely to have hypoactive (RR 1.61 [1.30; 1.98]) than hyperactive delirium. Delirium was associated with 4.62 additional hospitalized days compared to those without delirium (CI [3.23–6.01]). Discussion: We confirmed high occurrence rates of delirium in patients hospitalized with brain tumors. Patients with brain metastases had a higher occurrence of delirium compared to patients with gliomas, and delirium occurrence rates were higher in patients with frontotemporal tumors. Delirium occurrence rates in the literature are very heterogeneous and point toward a need for tailored assessments in patients with brain tumors. Full article

Background/Objectives: Positron emission tomography (PET) imaging with radiolabeled amino acids is increasingly used in glioma patients for biopsy planning, tumor delineation, prognostication, and therapy response assessment. This study investigated whether baseline amino acid PET imaging could identify regions at risk of future tumor recurrence. Methods: Retrospective case series of 14 patients with high-grade glioma. Contrast-enhanced magnetic resonance imaging (MRI) data of tumor recurrence and baseline imaging (PET-MRI) were co-registered. Volumes of interest (VOIs) of the high-grade glioma were derived from contrast-enhanced MRI at baseline and follow-up and from amino acid PET at baseline. The Dice similarity coefficient (DSC) was used to assess the overlap between VOIs. Furthermore, dynamic and static PET parameters were compared between the VOIs derived from contrast-enhanced MRI at follow-up and from the region of increased amino acid transport at baseline. Results: Regions of tumor recurrence in high-grade glioma patients overlap significantly more with baseline regions of increased amino acid transport on PET compared to regions of contrast enhancement on baseline MRI (p < 0.001). However, the static and dynamic PET statistics did not differentiate between regions that would later develop tumor recurrence and other areas of increased amino acid transport at baseline. Conclusions: These findings reaffirm the ability of amino acid PET to visualize the infiltrative components of gliomas not detected by contrast-enhanced MRI. Also, this study supports the role of amino acid PET in visualizing glioma infiltration beyond the MRI-visible tumor, but also indicates that accurately predicting the specific regions of recurrence based on baseline PET remains limited. Full article

Gliomas are incurable, heterogeneous brain tumors, with rare forms often constituting diagnostic and treatment challenges. Molecular diagnostics, mainly implemented through the World Health Organization (WHO) 2021 guidelines, have refined the classification, but highlight difficulties in diagnosing rare gliomas remain. This case series analyzes four patients with rare gliomas treated at the University Hospital, Ulm, between 2002 and 2024. Patients were selected based on unique histopathological features and long-term clinical follow-up. Clinical records, imaging, and histological data were reviewed. Molecular diagnostics followed WHO 2021 guidelines. Quality of life was assessed using standardized tools including the EQ-5D-5L, EQ VAS, the Distress Thermometer, and the Montreal Cognitive Assessment (MoCA). In the first case, a 51-year-old male’s diagnosis evolved from pleomorphic xanthoastrocytoma to a high-grade glioma with pleomorphic and pseudopapillary features, later identified as a neuroepithelial tumor with a PATZ1 fusion over 12 years. Despite multiple recurrences, extensive surgical interventions led to excellent outcomes. The second case involved a young female with long-term survival of astroblastoma, demonstrating significant improvements in both longevity and quality of life through personalized care. The third case involved a patient with oligodendroglioma, later transforming into glioblastoma, emphasizing the importance of continuous diagnostic reevaluation and adaptive treatment strategies, contributing to prolonged survival and quality of life improvements. Remarkably, the patient has achieved over 20 years of survival, including 10 years of being both therapy- and progression-free. The fourth case presents a young woman with neurofibromatosis type 1, initially misdiagnosed with glioblastoma based on histopathological findings. Subsequent molecular diagnostics revealed a subependymal giant cell astrocytoma-like astrocytoma, highlighting the critical role of early advanced diagnostic techniques. These cases underscore the importance of precise molecular diagnostics, individualized treatments, and ongoing diagnostic reevaluation to optimize outcomes. They also address the psychological impact of evolving diagnoses, stressing the need for comprehensive patient support. Even in complex cases, extensive surgical interventions can yield favorable results, reinforcing the value of adaptive, multidisciplinary strategies based on evolving tumor characteristics. Full article

Background High-grade gliomas (HGGs) are aggressive brain tumors with poor prognoses. Maximizing the extent of resection (EOR) is a critical surgical goal. Fluorescence-guided surgery using 5-aminolevulinic acid (5-ALA) has been proposed to enhance tumor visualization and resection. MethodsWe retrospectively analyzed 141 patients with histologically confirmed HGGs who underwent either 5-ALA-guided (n = 71) or conventional white-light (n = 70) resection between 2018 and 2023. Propensity score matching and multivariate Cox regression models were used to assess the impact of 5-ALA on surgical outcomes and survival. Results: Gross total resection (GTR) was significantly more common in the 5-ALA group than the conventional white-light group (28.17% vs. 12.86%, p = 0.0245). Kaplan–Meier analysis showed no statistically significant difference in overall survival between groups after matching (log-rank p = 0.6371). However, patients with GTR had significantly improved survival compared to those with subtotal resection (log-rank p = 0.0423). Multivariate Cox regression identified radiotherapy (HR = 0.291, 95% CI: 0.166–0.513, p < 0.001), higher Karnofsky Performance Status (HR = 0.962, 95% CI: 0.942–0.982, p = 0.0003), and GTR (HR = 0.476, 95% CI: 0.272–0.834, p = 0.0091) as independent predictors of improved survival. 5-ALA usage was not an independent predictor (HR = 0.885, 95% CI: 0.554–1.413, p = 0.612). Radiotherapy and chemotherapy were more frequently administered in the conventional white-light group (p = 0.0404 and p = 0.0085, respectively). Conclusions 5-ALA fluorescence-guided surgery significantly increases the rate of gross total resection in high-grade glioma patients but does not independently confer a survival advantage. Survival outcomes are primarily influenced by the extent of resection, adjuvant therapy, and functional status. Integration of 5-ALA within a comprehensive oncological framework may enhance its clinical utility. Full article

Background/Objectives: This study evaluates intratumoral susceptibility signals (ITSS) as imaging markers for glioma grade prediction and their association with molecular and histopathologic features, in the context of the fifth edition of the World Health Organization Classification of Tumors of the Central Nervous System (WHO CNS5). Methods: We retrospectively analyzed patients with adult diffuse gliomas who underwent pretreatment magnetic resonance imaging. ITSS were semiquantitatively graded by two radiologists: grade 0 (no signal), grade 1 (1–5), grade 2 (6–10), and grade 3 (≥11). Relative cerebral blood volume (rCBV) and tumor volume were also obtained. Histopathologic features included tumor grade, Ki-67, mitotic count, necrosis, microvascular proliferation, and molecular alterations (isocitrate dehydrogenase [IDH], 1p/19q, cyclin-dependent kinase inhibitors 2A and 2B [CDKN2A/B], and p53). Regression models predicted tumor grade (low: 1–2, high: 3–4) using ITSS, tumor volume, and rCBV. ROC curves and diagnostic performance metrics were analyzed. Results: 99 patients were included. ITSS grading correlated with rCBV, tumor volume, mitotic count, Ki-67, and tumor grade (p < 0.001). ITSS grades 0–1 were associated with oligodendrogliomas and astrocytomas (p < 0.001), IDH mutations (p < 0.001), and 1p/19q co-deletions (p = 0.01). ITSS grades 2–3 were linked to glioblastomas (p < 0.001), necrosis (p < 0.001), microvascular proliferation (p < 0.001), and CDKN2A/B homozygous deletions (p = 0.02). Models combining ITSS with rCBV and volume showed AUC of 0.94 and 0.96 (p < 0.001), outperforming univariate models. Conclusions: Semiquantitative ITSS grading correlates with key histopathologic and molecular glioma features. Combined with perfusion and volumetric parameters, ITSS enhance non-invasive glioma grading, in alignment with WHO CNS5. Full article

Background and Objectives: Gliomas are characterized by high disability rates, frequent recurrence, and low survival rates, posing a significant threat to human health. Accurate grading of gliomas is crucial for treatment plan selection and prognostic assessment. Previous studies have primarily focused on the binary classification (i.e., high grade vs. low grade) of gliomas. In order to perform the four-grade (grades I, II, III, and IV) glioma classification preoperatively, we constructed an artificial neural network (ANN) model using magnetic resonance imaging data. Materials and Methods: We reviewed and included patients with gliomas who underwent preoperative MRI examinations. Radiomics features were derived from contrast-enhanced T1-weighted images (CE-T₁WI) using Pyradiomics and were selected based on their Spearman’s rank correlation with glioma grades. We developed an ANN model to classify the four pathological grades of glioma, assigning training and validation sets at a 3:1 ratio. A diagnostic confusion matrix was employed to demonstrate the model’s diagnostic performance intuitively. Results: Among the 362-patient cohort, the ANN model’s diagnostic performance plateaued after incorporating the first 19 of the 530 extracted radiomic features. At this point, the average overall diagnostic accuracy ratings for the training and validation sets were 91.28% and 87.04%, respectively, with corresponding coefficients of variation (CVs) of 0.0190 and 0.0272. The diagnostic accuracies for grades I, II, III, and IV in the training set were 91.9%, 89.9%, 92.1%, and 90.7%, respectively. The diagnostic accuracies for grades I, II, III, and IV in the validation set were 88.7%, 87.1%, 86.5%, and 86.9%, respectively. Conclusions: The MRI radiomics-based ANN model shows promising potential for the four-type classification of glioma grading, offering an objective and noninvasive method for more refined glioma grading. This model could aid in clinical decision making regarding the treatment of patients with various grades of gliomas. Full article

Glioblastoma, IDH-wildtype (GBM), is the most aggressive and complex brain tumour classified by the World Health Organization (WHO), characterised by high mortality rates and diagnostic limitations inherent to invasive conventional procedures. Early detection is essential for improving patient outcomes, underscoring the need for non-invasive diagnostic tools. This study presents a convolutional neural network (CNN) specifically optimised for GBM detection from T1-weighted magnetic resonance imaging (MRI), with systematic evaluations of layer depth, activation functions, and hyperparameters. The model was trained on the RSNA-MICCAI data set and externally validated on the Erasmus Glioma Database (EGD), which includes gliomas of various grades and preserves cranial structures, unlike the skull-stripped RSNA-MICCAI images. This morphological discrepancy demonstrates the generalisation capacity of the model across anatomical and acquisition differences, achieving an F1-score of 0.88. Furthermore, statistical tests, such as Shapiro–Wilk, Mann–Whitney U, and Chi-square, confirmed the absence of demographic bias in model predictions, based on p-values, confidence intervals, and statistical power analyses supporting its demographic fairness. The proposed model achieved an area under the curve–receiver operating characteristic (AUC-ROC) of 0.63 on the RSNA-MICCAI test set, surpassing all prior results submitted to the BraTS 2021 challenge, and establishing a reliable and generalisable approach for non-invasive GBM detection. Full article

Background: High-grade gliomas (HGGs), particularly glioblastoma (GBM), are associated with exceptionally high mortality and inevitable recurrence. In considering novel treatment options for these devastating diseases, immunotherapies represent promising candidates. Immunotherapies have demonstrated efficacy for several advanced tumors outside the central nervous system, highlighting a potential role for these agents in treating HGGs. However, multiple challenges to immunotherapy efficacy have tempered therapeutic benefit in practice, including local and systemic immunosuppression, intratumoral heterogeneity, and various mechanisms of intrinsic and acquired resistance. In the past 30 years, diverse immunotherapeutic subclasses have been assessed for benefit against HGGs. Methods: We performed a PubMed search for randomized clinical trials performed within the last 30 years evaluating the following immunotherapy agents for high-grade gliomas: immune checkpoint inhibitors, vaccines, oncologic viruses, cytokines, and CAR T-cells. The present review offers a critical analysis of key pre-clinical and clinical trials that have shaped the immunotherapy landscape for high-grade gliomas over the past two decades. Results/Conclusions: Across the different immunotherapeutic methods and modalities explored thus far, a recurring theme emerges: while therapeutic strategies with a compelling conceptual basis are continually under development and even demonstrate a benefit in preclinical and early-phase trials, larger and later-phase trials consistently fail to produce concordantly significant outcomes. To date, no large-scale clinical trial has demonstrated a benefit of sufficient consequence to change practice. Continued critical appraisal of the strengths and pitfalls of prior investigative work, optimization of treatment development and delivery, and innovative approaches to combination therapy design will collectively be integral to future therapeutic advancement. Full article