Search Results (400)

Thalamic gliomas are among the most challenging pediatric brain tumors due to the delicate functions of the thalamus. Limited surgical intervention leads to the use of adjuvant therapies, including targeted therapy. Thalamic gliomas can be divided into two distinct groups: diffuse midline glioma (DMG) and low-grade glioma (LGG). The most common mutations that can be targeted for treatment are the KIAA1549-BRAF fusion; BRAF V600E mutation; EGFR, FGFR, PDGFR, NTRK, and CDK4/6 mutations; other MAP kinase pathway alterations; and PI3K/AKT/mTOR activation. The bithalamic high-grade glioma especially demonstrates EGFR mutations which makes it a distinct entity. Targeted therapy, including tyrosine kinas inhibitors has been shown to improve the overall survival compared to conventional therapy in certain situations. Demonstrating the mutation carried by the tumor is very critical in this regard. The purpose of this article is to focus on the treatment of thalamic glioma in pediatric patients in light of molecular information. Full article

While research on high-incidence tumors such as breast, prostate, and lung cancer has led to significant increases in patient survival in recent years, this has not been the case for low-incidence tumors such as high-grade gliomas, the most common and lethal brain tumors, for which the last significant therapeutic advance dates back to 2005. The high infiltration capacity of these tumors into normal brain tissue essential for both vegetative and relational life, the tumor microenvironment, with poor immunological activity, the multiple resistance mechanisms, and the unattractiveness of research investments due to the limited number of patients have made, and continue to make, the path to achieving significant improvements in the survival of patients with high-grade gliomas long and arduous. The objective of this article is to update the slow but continuous radiotherapeutic progress for adult and pediatric high-grade gliomas to the second half of 2023. We analyzed the progress of preclinical and clinical research on both adult and pediatric high-grade gliomas, with a particular focus on improvements in radiotherapy. Interactions between non-radiant new therapies and radiotherapy were also covered. A literature search was conducted in PubMed using the terms (“glioma* and radio*”) and the time limit of 1 July 2023 to 31 December 2023. The inclusion and exclusion criteria for the review were relevance to advances in radiotherapy for high-grade gliomas in adults and children. Treating patients with advanced disease progression only, using “historical” data as controls, as well as repurposing drugs developed for purposes completely different from their intended use, were the major (but not the only) methods to assess risk of bias in the included studies. The effect measures used in the synthesis or presentation of the results were tabulated and/or displayed in figures. A total of 100 relevant references were reviewed. Advances in preclinical studies and in clinical radiotherapy treatment planning, innovative fractionation, use of radioisotopes/radiopharmaceuticals, radiosensitization procedures, and radiation-induced damage were focused on. While this analysis may be limited by the relatively short publication period, high-grade glioma research remains impacted, especially at the clinical level, by potential issues with trial design, such as treating patients with advanced disease progression, using “historical” data as controls, and repurposing drugs developed for completely different purposes than intended. Addressing these aspects of high-grade glioma research could improve its efficacy, which often remains low despite the associated costs. Full article

Glioblastoma (GBM) is the most common malignant primary brain tumor in adults. Since numerous studies highlight the significance of cholinergic system components in tumor development, acetylcholine (ACh) and the differential activation of its receptors could play a crucial role in GBM progression. The aim of this study was to test this hypothesis by assessing the relevance of the cholinergic system in GBM cells and their microenvironment. We analyzed bulk RNA-seq expression data using the TIMER2.0 web server, focusing on the impact of patient survival in relation to muscarinic receptors (CHRM) and neutrophil infiltration in low-grade glioma (LGG) and GBM. Our analysis revealed a marked decrease in survival associated with all CHRMs, particularly in LGG. Moreover, GBM showed higher neutrophil infiltration and reduced survival, especially in relation to CHRM3. These findings were validated in the U251 cell line and in human GBM tumor biopsies (GBM-b), which also displayed CHRM3 expression. Additionally, we show that GBM cells exposed to cholinergic stimulation exhibited increased vascular endothelial growth factor (VEGF), IL-8 production, and PD-L1 expression, while the VEGF increase was blocked by tiotropium (Tio), a CHRM3 antagonist. Similarly, polymorphonuclear cells from GBM patients (PMN-p) displayed increased PD-L1 expression and IL-8 production upon cholinergic stimulation. Finally, as we previously reported on the relevance of thymic stromal lymphopoietin (TSLP) in GBM pathophysiology, here, we found that TSLP upregulated CHRM3 expression. Our findings highlight the importance of the cholinergic system in the tumor microenvironment, where it may act directly on tumor cells or influence neutrophil physiology, thereby modulating tumor progression. Full article

Background: Emerging evidence suggests that biological sex shapes glioma biology and therapeutic response. Methods: We performed a sex-stratified analysis of CGGA (Chinese Glioma Genome Atlas) RNA sequencing data comparing low-grade glioma (LGG) with high-grade glioma (HGG) and glioblastoma (GBM). Using the 3PodR framework, we integrated differential expression analysis with Gene Set Enrichment Analysis (GSEA), EnrichR, leading-edge analysis, and iLINCS drug repurposing. Results: These comparisons provide a proxy for biological processes underlying malignant transformation. In LGG vs. HGG, 973 significantly differentially expressed genes (DEGs) were identified in females and 1236 in males, with 15.5% and 33.5% unique to each sex, respectively. In LGG vs. GBM, 2011 DEGs were identified in females and 2537 in males, with 12.6% and 30.7% being unique. Gene-level contrasts included GLI1 upregulation in males and downregulation in females, GCGR upregulation in males, MYOD1 upregulation in females, and HIST1H2BH downregulation in males. Additional top DEGs included PRLHR, DGKK, DNMBP-AS1, HOXA9, CTB-1I21.1, RP11-47I22.1, HPSE2, SAA1, DLK1, H19, PLA2G2A, and PI3. In both sexes, LGG–HGG and LGG–GBM grade comparisons converged on neuronal and synaptic programs, with enrichment of glutamatergic receptor genes and postsynaptic modules, including GRIN2B, GRIN2A, GRIN2C, GRIN1, and CHRNA7. In contrast, collateral pathways diverged by sex: females showed downregulation of mitotic and chromosome-segregation programs, whereas males showed reduction of extracellular matrix and immune-interaction pathways. Perturbagen analysis nominated signature-reversing compounds across sexes, including histone deacetylase inhibitors, Aurora kinase inhibitors, microtubule-targeting agents such as vindesine, and multi-kinase inhibitors targeting VEGFR, PDGFR, FLT3, PI3K, and MTOR. Conclusions: Glioma grade comparisons reveal a shared neuronal–synaptic program accompanied by sex-specific transcriptional remodeling. These findings support sex-aware therapeutic strategies that pair modulation of neuron–glioma coupling with chromatin- or receptor tyrosine kinase/angiogenic-targeted agents, and they nominate biomarkers such as GLI1, MYOD1, GCGR, PRLHR, and HIST1H2BH for near-term validation. Full article

Background and Clinical Significance: Visual agnosia and speech production deficits are well-described sequelae of neurosurgical interventions, but their selective dissociation remains rare. This report presents an unusual combination of postoperative deficits following awake resection of a left frontal low-grade glioma. Case Presentation: We present the case of a right-handed female with left hemisphere language dominance who had a left frontal low-grade glioma. Preoperatively, she exhibited anomia and dysexecutive syndrome, including difficulty completing everyday goal-directed tasks such as sending emails and paying for parking. Following awake tumor resection, she developed two rare, dissociated deficits: (1) speech restricted to infinitive verb forms and (2) selective visual agnosia for static images, with preserved recognition of dynamic stimuli. Conclusions: This uncommon clinical constellation highlights the vulnerability of left frontal language and ventral visual processing networks during surgery and supports the dual-stream model of vision and language production. We describe a selective form of static visual agnosia affecting static images with relative preservation of dynamic and object recognition, for which we use the descriptive label “astatopsia”. This peculiar clinical condition is rarely documented in this particular combination and has not, to the best of our knowledge, previously been denominated in such a manner in the literature. Full article

Advances in neuroimaging and intraoperative mapping have transformed brain tumour surgery from anatomy-based resection to function-guided intervention. This review synthesises current evidence on multimodal strategies for maximising tumour removal while preserving cognitive and neurological function. Integrating task-based and resting-state functional MRI (fMRI), diffusion tensor imaging (DTI), tractography, and connectomic analysis enables personalised mapping of eloquent and cognitive networks. Intraoperatively, awake craniotomy with direct electrical stimulation (DES) remains the gold standard for real-time functional validation, while adjuncts such as intraoperative MRI (iMRI), 5-aminolevulinic acid (5-ALA) fluorescence, and ultrasound-based extended resection accuracy. However, these technologies present unique limitations, including neurovascular uncoupling in fMRI, tract distortion in DTI, and resource constraints in low-income settings. Our review differentiates their application across low-grade and high-grade gliomas, emphasising that tumour biology determines the balance between neuroplasticity-driven mapping and imaging-guided radicality. Key future priorities include validation of multimodal imaging protocols, integration of longitudinal neuropsychological outcomes, and development of interpretable connectomic models. Addressing the technological and ethical challenges of high-field MRI, data standardisation, and cost-effective implementation will be essential for equitable global adoption. Ultimately, the evolution of functional neurosurgery depends not only on new technologies but on integrating multimodal evidence and patient-centred outcome measures to achieve reproducible, safe, and personalised brain tumour surgery. Full article

Background/Objectives: High-grade gliomas (HGGs), including glioblastomas, are among the most aggressive brain tumors due to their high intratumoral heterogeneity and extensive infiltration. Glioma stem-like cells (GSCs) frequently invade along white matter tracts such as the corpus callosum, but the molecular programs driving this region-specific invasion remain poorly defined. The aim of this study was to identify transcriptional signatures associated with GSC infiltration into the corpus callosum. Methods: We established an orthotopic xenograft model by implanting fluorescently labeled human GSCs into nude mouse brains. Tumor growth and invasion patterns were assessed using tissue clearing, light-sheet fluorescence microscopy, and histological analyses. To characterize region-specific molecular profiles, we performed microfluidic-based single-cell RNA expression analysis of 48 invasion- and stemness-related genes in cells isolated from the tumor bulk (TB) and corpus callosum (CC). Results: By six weeks post-implantation, GSCs displayed marked tropism for the corpus callosum, with distinct infiltration patterns captured by three-dimensional imaging. Single-cell gene expression profiling revealed significant differences in 7 of the 48 genes (14.6%) between TB- and CC-derived GSCs. These genes—NES, CCND1, GUSB, NOTCH1, E2F1, EGFR, and TGFB1—collectively defined a “corpus callosum invasion signature” (CC-Iv). CC-derived cells showed a unimodal, high-expression profile of CC-Iv genes, whereas TB cells exhibited bimodal distributions, suggesting heterogeneous transcriptional states. Importantly, higher CC-Iv expression correlated with worse survival in patients with low-grade gliomas. Conclusions: This multimodal approach identified a corpus callosum-specific invasion signature in glioma stem-like cells, revealing how local microenvironmental cues shape transcriptional reprogramming during infiltration. These findings provide new insights into the spatial heterogeneity of gliomas and highlight potential molecular targets for therapies designed to limit tumor spread through white matter tracts. Full article

Objectives: Cancer, characterized by its profound complexity and heterogeneity, arises from a multitude of molecular disruptions. The pursuit of identifying distinct cancer subtypes is driven by the need to stratify patients into clinically coherent subgroups, each exhibiting unique prognostic outcomes. The integration of multi-omics datasets enhances the precision of subtyping and advances precision medicine. Methods: Considering the high-dimensional nature inherent to various multi-omics data types, we introduce an innovative deep learning framework, DAE-MKL, which integrates denoising autoencoders with multi-kernel learning for identifying cancer subtypes. Leveraging the capabilities of DAE, we extract non-linearly transformed features that retain pertinent information while mitigating noise and redundancy. These refined data representations are then funneled into the MKL framework, thereby enhancing the accuracy of subtype identification. We applied the DAE-MKL framework to both simulated studies and empirical datasets derived from two distinct cancer types, low-grade glioma (LGG, $n$ = 86) and kidney renal clear cell carcinoma (KIRC, $n$ = 285), thereby validating its utility and feasibility. Results: In simulations, DAE-MKL achieved superior performance with NMI gains up to 0.78 compared to other state-of-the-art methods. For real datasets, DAE-MKL identified three LGG subtypes and three KIRC subtypes, showing significant survival differences (KIRC log-rank $p$ = 3.33 × 10⁻⁸, LGG log-rank $p$ = 3.99 × 10⁻⁸). Additionally, we explored potential cancer-related biomarkers. Conclusions: The DAE-MKL effectively identifies molecular subtypes, reduces data dimensionality, and improves prognostic stratification in multi-omics cancer datasets, providing an effective tool for precision oncology. Full article

Bevacizumab is often used off-label in pediatric neuro-oncology, and evidence for indications of bevacizumab use in pediatric neuro-oncology is often fragmented. Therefore, this review aims to provide an organized summary of efficacy across different types of tumors, highlight outcomes, and link findings to the underlying biology. Gaps in the literature were also identified to guide future research. We narratively synthesized various pediatric studies, and the following tumor categories were identified for discussion: low-grade glioma, high-grade glioma, diffuse intrinsic pontine glioma, schwannoma, medulloblastoma, radiation necrosis, and cerebral edema. Key outcomes considered included overall survival, event-free survival, progression-free survival, vision and/or hearing improvements, steroid use, quality of life, and toxicity. The greatest benefits were observed in cases such as recurrent medulloblastoma in combination with temozolomide and irinotecan, optic pathway glioma visual function, and diminished steroid use in radiation necrosis. Results were poorer in cases of newly diagnosed high-grade gliomas and diffuse intrinsic pontine gliomas. The medication was overall well tolerated, with adverse events like hypertension, proteinuria, and epistaxis often being manageable with surveillance. In consideration of the results, bevacizumab should be considered based on the tumor profile, and its outcome measured along functional endpoints, besides radiological evolution. Continued investigations into outcome measures, as well as combination with targeted treatments and optimizing therapy, will contribute to improving outcomes in this vulnerable population. Full article

Background: Enhancer RNAs (eRNAs), a subclass of long non-coding RNAs transcribed from enhancer regions, have emerged as dynamic regulators of gene expression, tumor progression, and therapeutic response. In gliomas, their biological and clinical significance is only recently being elucidated. This systematic review aimed to synthesize current evidence regarding the role of eRNAs in gliomagenesis, chemoresistance, and prognosis. Methods: We conducted a systematic review following PRISMA 2020 guidelines. PubMed/MEDLINE and Scopus databases were searched on September 2025 using a predefined strategy. Eligible studies included clinical or pre-clinical analyses of eRNAs in gliomas, reporting associations with tumorigenicity, survival, or resistance to temozolomide (TMZ). Risk of bias was assessed using ROBINS-I (Version 2), and findings were qualitatively synthesized. Results: From 26 retrieved records, 10 studies were included, encompassing 22 unique eRNAs. Two studies demonstrated that TMZR1-eRNA and LINC02454* modulate TMZ sensitivity by regulating STAT3, SORBS2, and DDR1 pathways. Seven studies evaluated prognostic implications: 12 eRNAs (e.g., AC003092.1, CYP1B1-AS1, CRNDE) were consistently associated with poor survival, while seven (e.g., LINC00844, ENSR00000260547) correlated with favorable outcomes, particularly in low-grade gliomas. One mechanistic study showed that HOXDeRNA directly promotes gliomagenesis by displacing PRC2 repression at key transcription factor promoters and activating oncogenic super-enhancers. Conclusions: eRNAs are not passive transcriptional by-products but active modulators of glioma biology. They influence tumor initiation, therapeutic resistance, and survival outcomes, underscoring their potential as prognostic biomarkers and therapeutic targets. Future research should validate these findings in larger clinical cohorts and explore strategies for eRNA-directed therapies in precision neuro-oncology. Full article

Background: Primary spinal gliomas are rare in the pediatric population. Separately, FGFR1 genomic aberrations are also uncommon in spinal cord tumors. We report a case of a previously well adolescent who presented with progressive symptoms secondary to an intramedullary tumor with unique radiological and molecular characteristics. Case Presentation: A previously well 17-year-old male presented with worsening mid-back pain associated with lower limb long-tract signs. Magnetic resonance imaging (MRI) of his neuro-axis reported a long-segment intramedullary lesion with enhancing foci and a multi-septate syrinx containing hemorrhagic components from C4 to T12. The largest enhancement focus was centered at T7. Additional MRI sequences observed no intracranial involvement or vascular anomaly. He underwent an emergent laminoplasty and excision of the thoracic lesion. Intraoperative findings demonstrated a soft, grayish intramedullary tumor associated with extensive hematomyelia that had multiple septations. Active fenestration of the latter revealed blood products in various stages of resolution. Postoperatively, the patient recovered well, with neurological improvement. Final histology reported a circumscribed low-grade glial neoplasm. Further molecular interrogation via next-generation sequencing panels showed FGFR1 p.K656E and V561M alterations. The unique features of this case are presented and discussed in corroboration with a focused literature review. Conclusions: We highlight an interesting case of an intramedullary tumor with unusual radiological and pathological findings. Emphasis is on the importance of tissue sampling in corroboration with genomic investigations to guide clinical management. Full article

Astrocytoma is the most common type of brain glioma and is classified by the World Health Organization into four grades, providing prognostic insights and guiding treatment decisions. The accurate determination of astrocytoma grade is critical for patient management, especially in high-malignancy-grade cases. This study proposes a fully optimized Convolutional Neural Network (CNN) for the classification of astrocytoma MRI slices across the three malignant grades (G2–4). The training dataset consisted of 1284 pre-operative axial 2D MRI slices from T1-weighted contrast-enhanced and FLAIR sequences derived from 69 patients. To provide the best possible model performance, an extensive hyperparameter tuning was carried out through the Hyperband method, a variant of Successive Halving. Training was conducted using Repeated Hold-Out Validation across four randomized data splits, achieving a mean classification accuracy of 98.05%, low loss values, and an AUC of 0.997. Comparative evaluation against state-of-the-art pre-trained models using transfer learning demonstrated superior performance. For validation purposes, the proposed CNN trained on an altered version of the training set yielded 93.34% accuracy on unmodified slices, which confirms the model’s robustness and potential use for clinical deployment. Model interpretability was ensured through the application of two Explainable AI (XAI) techniques, SHAP and LIME, which highlighted the regions of the slices contributing to the decision-making process. Full article

Background/Objectives: Accurate classification of brain tumors and reliable prediction of patient survival are essential in neuro-oncology, guiding clinical decisions and enabling precision treatment planning. However, conventional machine learning and deep learning methods often struggle with challenges such as data scarcity, class imbalance, limited model interpretability, and poor generalization across diverse clinical settings. This study presents GlioSurvQNet, a novel reinforcement learning-based framework designed to address these limitations for both glioma grading and survival prediction. Methods: GlioSurvQNet is built upon a DuelContextAttn Deep Q-Network (DQN) architecture, tailored for binary classification of low-grade vs. high-grade gliomas and multi-class survival prediction (short-, medium-, and long-term categories). Radiomics features were extracted from multimodal MRI scans, including FLAIR, T1CE, and T2 sequences. Feature optimization was performed using a hybrid ensemble of metaheuristic algorithms, including Harris Hawks Optimization (HHO), Modified Gorilla Troops Optimization (mGTO), and Zebra Optimization Algorithm (ZOA). Subsequently, SHAP-based feature selection was applied to enhance model interpretability and robustness. Results: The classification module achieved the highest accuracy of 99.27% using the FLAIR + T1CE modality pair, while the survival prediction model attained an accuracy of 93.82% with the FLAIR + T2 + T1CE fusion. Comparative evaluations against established machine learning and deep learning models demonstrated that GlioSurvQNet consistently outperformed existing approaches in both tasks. Conclusions: GlioSurvQNet offers a powerful and interpretable AI-driven solution for brain tumor analysis. Its high accuracy and robustness make it a promising tool for clinical decision support in glioma diagnosis and prognosis. Full article

Background: Pituicytomas are rare, low-grade gliomas arising from pituicytes in the posterior pituitary or infundibulum. Due to its rarity and nonspecific clinical and radiological characteristics, it is frequently misdiagnosed as pituitary adenomas or other sellar tumors. Aims: To present an overview of pituicytoma, including clinical presentation, radiological and histopathological characteristics, differential diagnosis and treatment strategies, illustrated by a case report. Methods: A literature review was conducted to contextualize our patient with a sellar tumor, and to highlight key diagnostic and therapeutic considerations. Results/Case report: A 12-year-old boy presented with visual disturbances. MRI revealed a well-defined contrast-enhancing sellar mass, and the patient underwent transsphenoidal surgery. The diagnosis was assumed to be a nonfunctioning pituitary adenoma (NFPA). Two years later a residual tumor was treated with proton irradiation. Six years after the radiotherapy, the patient had epistaxis. Imaging showed a tumor in the sphenoidale sinus, which was surgically resected. The tumor had histopathological features of pituicytoma and immunoreactivity for TTF-1 and S100. The tissue from the first operation was reviewed, showing more characteristics with pituicytoma than NFPA, leading to re-definition of the initial diagnosis. Follow-up has been without any signs of residual tumor. Conclusion: Our case and literature review emphasize the importance of considering pituicytoma in the differential diagnosis among sellar lesions. The diagnosis relies on a combination of preoperative imaging, intraoperative findings and histopathology. Pituitary surgery is the first-line treatment, and the outcome is generally good. Increased awareness of pituicytomas is necessary to improve preoperative diagnostic accuracy and guide appropriate management. Full article

Objectives: To investigate the correlation between intraoperative conventional ultrasound, SWE, and SMI ultrasound manifestations of glioma and the expression of immunohistochemical markers. Methods: Patients with single superficial supratentorial glioma scheduled for brain tumor resection in our neurosurgery department from October 2020 to October 2022 were prospectively included. High-grade glioma (HGG) and low-grade glioma (LGG) were classified by pathological histological grading, and the differences in conventional ultrasound, SWE Young’s modulus, and SMI intratumoral and peritumoral blood flow architecture between HGG and LGG were analyzed, and the SWE diagnostic cut-off value was calculated by the Youdon index. Logistic regression models were used to analyze the independent predictive ultrasound signs associated with the diagnosis of HGG. HGG and LGG were classified by pathological histological grading. IDH1 expression was measured by immunohistochemical methods to analyze the correlation between IDH1 expression in glioma and clinical and ultrasound characteristics. Results: Forty-eight patients with glioma admitted to our hospital from October 2020 to October 2022 were included in this study, including 30 (62.5%) with HGG and 18 (37.5%) with LGG. For conventional ultrasound, HGG was often associated with severe peritumoral edema compared with LGG (p = 0.048). The sensitivity of HGG was 88.9%, the specificity was 86.7%, and the AUC was 0.855 (95% confidence interval: 0.741–0.968, p = 0.001) using Young’s mode 13.90 kPa as the threshold. Logistic analysis showed that SWE Young’s modulus values, and peritumoral and intratumoral SMI blood flow structures, were associated with the diagnosis of HGG. Among the 48 gliomas, 22 (45.8%) were IDH1-positive and 26 (54.2%) were IDH1-negative, with no statistical difference in age between the two groups and a statistical difference in histological grading (p < 0.05). There was a statistical difference between IDH1 mutant and wild type in terms of peritumoral edema and SMI intratumoral and peritumoral tissue vascular architecture. Logistic regression models showed that intratumoral and peritumoral tissue SMI vascular architecture was a valid predictor of IDH1 positivity, with a classification accuracy of 81.3%, sensitivity of 90.9%, and specificity of 73.1%. Further group analysis of mutant Young’s modulus values in LGG were higher than wild-type Young’s modulus values (p = 0.031). Conclusions: Peritumoral and intratumoral tissue SMI vascular architecture was a valid predictor of IDH1 positivity. Based on intraoperative ultrasound multimodality images, we can preoperatively determine the expression of molecular markers of lesions, which is of clinical significance for optimizing surgical strategies and predicting prognosis. Full article