Recent studies have elucidated various molecular mechanisms underlying glioblastoma, particularly focusing on glioblastoma stem cells (GSCs) and their interactions with the tumor microenvironment. Zhao et al. demonstrated that lymphatic endothelial-like cells (LECs) in glioblastomas promote the growth of CCR7-positive GSCs through the secretion of CCL21, highlighting the role of endothelial cell populations in tumor progression (ref: Zhao doi.org/10.1038/s43018-023-00658-0/). Additionally, Iser et al. introduced a molecular-guided tumor classification using cerebrospinal fluid (CSF) cfDNA sequencing, successfully identifying tumor entities in 75% of glioblastoma cases, which underscores the potential of CSF analysis in glioma diagnostics (ref: Iser doi.org/10.1158/1078-0432.CCR-23-2907/). Drexler et al. explored the temporal changes in DNA methylation subclasses between newly diagnosed and recurrent glioblastomas, revealing that subclass transitions correlate with metabolic process alterations and immune component variations, suggesting a dynamic tumor evolution (ref: Drexler doi.org/10.1007/s00401-023-02677-8/). Wang et al. further contributed to the understanding of glioblastoma metabolism by showing that genomic alterations influence CSF metabolite levels, indicating the clinical utility of CSF metabolite analysis (ref: Wang doi.org/10.1186/s40478-024-01722-1/). Lastly, Huang et al. investigated the role of the long non-coding RNA PVT1 in glioblastoma, finding that its expression promotes tumor proliferation and macrophage immunosuppressive polarization, thereby impacting the tumor microenvironment (ref: Huang doi.org/10.1111/cns.14566/).

The prognostic landscape of astrocytomas, particularly IDH mutant variants, has been significantly advanced through recent research focusing on molecular biomarkers. Galbraith et al. assessed the prognostic value of DNA methylation subclassification, aneuploidy, and CDKN2A/B homozygous deletion, finding that these factors can effectively predict clinical outcomes in IDH mutant astrocytomas (ref: Galbraith doi.org/10.1093/neuonc/). Weller et al. further refined prognostic stratification by analyzing a cohort of 258 patients with IDH-mutant astrocytomas, revealing median overall survival rates of 8.1 years for grade 3 and 4.7 years for grade 4 tumors, emphasizing the importance of tumor grade in survival outcomes (ref: Weller doi.org/10.1007/s00401-023-02662-1/). Chen et al. introduced a novel dual-modality imaging technique for lower-grade gliomas, demonstrating its feasibility in guiding surgical interventions, although the predictive value of preoperative MRI remains debated (ref: Chen doi.org/10.7150/thno.91554/). Pohl et al. highlighted the molecular characteristics of ependymomas, indicating that patients with aggressive subtypes have significantly poorer survival rates, thus reinforcing the need for molecular profiling in prognostic assessments (ref: Pohl doi.org/10.1007/s00401-023-02674-x/). Lastly, Gödicke et al. examined intratumoral heterogeneity in PFA ependymomas, revealing correlations between molecular hallmarks and tumor morphology, which could inform clinical management strategies (ref: Gödicke doi.org/10.1007/s00401-023-02682-x/).

Research into neurodegenerative diseases has increasingly focused on understanding the cellular and molecular underpinnings of conditions such as Parkinson's Disease (PD) and dementia with Lewy bodies (DLB). Martirosyan et al. conducted a single-cell analysis of PD, revealing distinct cellular responses and highlighting the loss of dopaminergic neurons as a key pathological feature (ref: Martirosyan doi.org/10.1186/s13024-023-00699-0/). Reho et al. performed a comprehensive differential methylation analysis in DLB, uncovering significant epigenetic alterations that could serve as biomarkers for this condition (ref: Reho doi.org/10.1038/s42003-023-05725-x/). Longobardi et al. examined autophagy markers across various neurodegenerative diseases, finding alterations in ATG5, UBQLN2, ULK1, and LC3 levels, which may indicate disrupted autophagic processes in DLB and frontotemporal dementia (FTD) (ref: Longobardi doi.org/10.3390/ijms25021125/). Additionally, Ito et al. explored the role of inositol pyrophosphate in amyotrophic lateral sclerosis (ALS), contributing to the understanding of molecular mechanisms associated with this fatal disorder (ref: Ito doi.org/10.3389/fneur.2023.1334004/). Lastly, Aran et al. investigated liquid biopsy techniques in meningioma patients, demonstrating the potential of non-invasive methods to monitor disease progression and treatment responses (ref: Aran doi.org/10.3389/fneur.2023.1321895/).

The molecular characterization of ependymomas has evolved significantly, moving towards integrated diagnostic approaches that combine histopathological and molecular data. Pohl et al. emphasized the importance of molecular profiling in ependymomas, reporting that patients with aggressive subtypes such as EPN-PFA and EPN-ZFTA have markedly lower survival rates, with 10-year overall survival rates of 56% and 62%, respectively (ref: Pohl doi.org/10.1007/s00401-023-02674-x/). Neyazi et al. conducted a transcriptomic and epigenetic analysis of spinal ependymomas, identifying clinically relevant subtypes enriched for NF2 mutations, which could inform treatment strategies (ref: Neyazi doi.org/10.1007/s00401-023-02668-9/). Drexler et al. also contributed to the understanding of glioblastoma subclass transitions, linking these changes to metabolic processes and immune responses, which may have implications for ependymoma treatment as well (ref: Drexler doi.org/10.1007/s00401-023-02677-8/). Schumann et al. explored the use of deep neural networks for the morphological classification of spinal cord ependymomas, aiming to enhance diagnostic accuracy and consistency with DNA methylation profiling (ref: Schumann doi.org/10.1111/bpa.13239/). This body of work underscores the necessity of integrating molecular characteristics into the clinical management of ependymomas to improve patient outcomes.

Liquid biopsy techniques have emerged as promising tools for the non-invasive detection and monitoring of various cancers, including brain tumors. Aran et al. demonstrated the efficacy of liquid biopsy in meningioma patients by analyzing circulating tumor DNA, miRNAs, and cytokines, successfully identifying biomarkers that could aid in treatment monitoring (ref: Aran doi.org/10.3389/fneur.2023.1321895/). In a related study, Sanders et al. characterized outcomes of epilepsy surgery in patients with MRI-negative findings, highlighting the challenges in identifying suitable candidates for surgical intervention (ref: Sanders doi.org/10.1212/WNL.0000000000208007/). Arjuna et al. evaluated the rapid detection of mutations in cerebrospinal fluid samples using the Genexus Integrated Sequencer, which could facilitate timely clinical decision-making in oncology (ref: Arjuna doi.org/10.1007/s11060-023-04487-0/). Furthermore, the exploration of iron-based biomarkers for personalizing pharmacological ascorbate therapy in glioblastoma by Petronek et al. emphasizes the potential for tailored treatment approaches based on molecular characteristics (ref: Petronek doi.org/10.1007/s11060-024-04571-z/). Collectively, these studies highlight the growing importance of liquid biopsies and biomarkers in enhancing diagnostic accuracy and treatment personalization in neuro-oncology.

Innovative imaging techniques are revolutionizing the field of neuropathology, offering new insights into tumor characterization and diagnosis. Lechpammer et al. introduced Microscopy with Ultraviolet Surface Excitation (MUSE), which allows for high-resolution imaging of brain tumors without the need for traditional fixation and sectioning, potentially streamlining the diagnostic process (ref: Lechpammer doi.org/10.3390/brainsci14010108/). Herranz et al. utilized simultaneous MR-PET imaging to characterize translocator protein expression in multiple sclerosis, providing valuable information on disease pathology and potential therapeutic targets (ref: Herranz doi.org/10.1093/brain/). Gold et al. investigated the developmental basis of SHH medulloblastoma heterogeneity through single-nucleus RNA sequencing, revealing insights into the cellular origins of these tumors and their diverse histological features (ref: Gold doi.org/10.1038/s41467-023-44300-0/). Dottermusch et al. examined the clinicopathological features of pituitary neuroendocrine tumors, highlighting the importance of transcription factor co-expression in tumor classification (ref: Dottermusch doi.org/10.1007/s00401-024-02686-1/). These advancements in imaging and characterization techniques are paving the way for more accurate diagnoses and improved understanding of tumor biology in neuropathological contexts.

Therapeutic strategies in neuro-oncology are increasingly focusing on personalized and targeted approaches to improve patient outcomes. Fadul et al. conducted a phase I study on the safety and feasibility of using bispecific antibody armed T cells (EGFR BATs) in combination with radiation and temozolomide for treating newly diagnosed grade 4 astrocytomas, demonstrating promising immunologic responses (ref: Fadul doi.org/10.1007/s11060-024-04564-y/). Petronek et al. explored the role of iron-based biomarkers in personalizing pharmacological ascorbate therapy for glioblastoma, indicating that tumor characteristics could guide treatment decisions (ref: Petronek doi.org/10.1007/s11060-024-04571-z/). Additionally, Sanders et al. investigated the outcomes of epilepsy surgery in patients with MRI-negative findings, emphasizing the need for tailored surgical approaches based on individual patient profiles (ref: Sanders doi.org/10.1212/WNL.0000000000208007/). Galbraith et al. highlighted the prognostic value of molecular biomarkers in IDH mutant astrocytomas, suggesting that integrating these biomarkers into clinical practice could enhance treatment stratification (ref: Galbraith doi.org/10.1093/neuonc/). These studies collectively underscore the importance of innovative therapeutic approaches and the integration of molecular insights into clinical practice to optimize treatment outcomes in neuro-oncology.