Search Results (243)

Neuroinflammation within the tumor microenvironment (TME) of central nervous system (CNS) neoplasms, particularly glioblastoma (GBM), is no longer viewed merely as a reactive phenomenon but rather as a major driver of gliomagenesis and malignant transformation. This process involves a shift from acute immune activation to a chronic, sterile state that reshapes the CNS borders and immune niches to favor tumor evasion. This narrative review provides a comprehensive mechanistically focused analysis of the mechanisms governing the inflammatory stroma in primary and metastatic brain neoplasms. It critically examines the ontogeny and transcriptomic profile of myeloid and glial populations, dismantling the binary M1/M2 polarization model in favor of a continuum of functional states determined by metabolic and oxygenation gradients. It also analyzes intracellular signaling cascades, the subversion of innate immunity sensors such as the cGAS-STING pathway, the epigenetic reprogramming of stromal cells, and the role of extracellular vesicles. The electrochemical integration of tumor cells into neuronal circuits via glutamatergic synapses and connexin 43 gap junction coupling is addressed in detail, defining the mitogenic impact of neuronal activity on the tumor. The inflammatory profiles of IDH-wildtype and IDH-mutant gliomas and of secondary brain metastases are contrasted. Finally, the correlates of functional neuroimaging, liquid biopsies, and resistance mechanisms to conventional therapies are analyzed, including the GIANT and SENIPERA clinical trials, CARv3-TEAM-E bivalent cellular immunotherapy preconditioned with the LDC + R regimen, and the accelerated approval of dordaviprone (Modeyso) in H3 K27M-mutant diffuse midline gliomas. Full article

Phosphorylated ACC (pACC), a downstream effector of the LKB1/AMPK pathway, may support tumor bioenergetics and exert a tumor-promoting role in glioblastoma (GBM). In the randomized REGOMA trial, pACC expression was associated with improved overall survival (OS) in GBM patients treated with regorafenib, but its validity in large cohorts is unclear. This study aimed to characterize pACC and phosphorylated AMPK (pAMPK) expression in a real-world GBM cohort and to assess their prognostic and predictive value in patients receiving second-line regorafenib or fotemustine/lomustine. In this retrospective, multicenter translational study, pACC and pAMPK were assessed by immunohistochemistry on FFPE tumor sections from 174 IDH-wild-type GBM patients treated with regorafenib (n = 84) or fotemustine/lomustine (n = 90). Staining was performed with a validated anti-pACC monoclonal antibody and quantified by digital pathology. Survival analyses included univariable and multivariable Cox proportional hazards models, with interaction testing. pACC and pAMPK were expressed in 85.6% and 95.4% of samples, respectively, with heterogeneous spatial patterns. Neither marker was significantly associated with OS in the univariable analyses, and neither retained independent prognostic value in multivariable analysis. Regorafenib was associated with significantly longer OS than alkylating agents (10.4 vs. 6.3 months; p = 0.0021). However, the treatment-by-pACC interaction test was not statistically significant (adjusted p = 0.610), providing no formal evidence of a differential treatment effect by pACC status. Although pACC-positive expression was enriched among patients experiencing longer overall survival under regorafenib, formal treatment-by-biomarker interaction was non-significant. These exploratory findings indicate that pACC is not an established predictive biomarker and warrant prospectively powered evaluation. Full article

Objective: The glioma prognostic literature contains a large number of transcriptomic risk signatures, yet whether these signatures add measurable information beyond a clinical model containing grade and molecular markers is rarely tested. We pursued three objectives jointly: to evaluate a leakage-controlled signature in terms of both discrimination and calibration; to test it against a clinical reference model and against a null distribution of random signatures; and to quantify the reporting practice of the field. Methods: The CGGA mRNAseq_693 cohort (n = 404, 209 deaths) served as development, the CGGA mRNAseq_325 cohort (n = 222, 138 deaths) as independent internal validation, and the TCGA lower-grade glioma and glioblastoma cohorts (n = 664, 247 deaths) as external validation. A univariate Cox score test was applied to 17,544 genes with false discovery rate control by the Benjamini–Hochberg procedure, and an elastic-net penalised Cox model was fitted on the top 200 candidate genes. Every model-building operation-imputation, scaling, candidate pool, and penalty selection was confined to the development cohort, and the final model was locked. Three arms were compared: clinical only, transcriptomic only, and combined. Calibration was quantified by the integrated calibration index derived from a smoothed calibration curve. In addition, the abstract-level reporting content of 515 glioma signature records indexed in Web of Science was analysed. Results: The signature made no measurable contribution beyond the clinical reference model. In the independent internal validation cohort the clinical model reached a concordance index of 0.800 (95% CI 0.767–0.831) and the signature 0.801 (0.769–0.832); the paired bootstrap difference was indistinguishable from zero (Δ = +0.001; 95% CI −0.032 to +0.035), and restricting the clinical model to variables known at diagnosis did not change this (Δ = +0.008; −0.024 to +0.043). Against a null distribution of 1000 random 20-gene sets drawn from the same candidate pool, the signature exceeded the null internally (p = 0.015) but was indistinguishable from it in external validation (p = 0.154); 99.2% of random sets reached a concordance index above 0.75 and 82.2% above 0.80 in the external cohort. Discrimination fell markedly within the IDH-wildtype (0.629) and WHO grade IV (0.606) strata, and the risk score correlated at 0.722 with a proliferation metagene despite containing no canonical proliferation gene. The concordance indices themselves—0.801 internally and 0.824 externally for the 17-gene subset available in TCGA, with an integrated calibration index of 0.045 at 36 months—are therefore best read as an illustration of the problem rather than as evidence of clinical utility: they sit squarely inside the range that random gene sets reach in the same data, and they fall in the range routinely presented as successful in the published literature. In the literature survey, 8.7% of the 515 records mentioned calibration, 4.5% decision curve analysis, and only 1.0% any comparison against a clinical reference model; none reported all three. Conclusions: A signature developed under a leakage-controlled protocol and well calibrated was nevertheless indistinguishable from the appropriate references on two of the three criteria we propose. Most of its discrimination rests on the IDH and grade axis that a broad range of prognostic gene sets can capture. Concordance indices reported in the glioma signature literature cannot be interpreted without a clinical reference model and a random-signature null distribution. Full article

Background/Objectives: Oligodendroglioma-like morphology may generate diagnostic uncertainty in central nervous system tumors, although oligodendroglioma is defined by the integrated presence of IDH mutation and whole-arm 1p/19q codeletion. This study aimed to evaluate the diagnostic pitfalls of oligodendroglioma-like morphology by comparing initial microscopic impressions with final integrated diagnoses. Methods: We retrospectively reviewed 23 non-oligodendroglial central nervous system tumors showing focal or predominant oligodendroglioma-like morphology but not fulfilling the integrated diagnostic criteria for oligodendroglioma. Clinical, radiological, histopathological, immunohistochemical, molecular/cytogenetic, initial microscopic impression, final integrated diagnosis, and follow-up data were analyzed descriptively. Results: Initial microscopic impressions included low-grade glial tumor, high-grade glial tumor, dysembryoplastic neuroepithelial tumor, ependymoma, astroblastoma, oligodendroglioma, dysplasia, central neurocytoma, metastatic epithelial tumor, and pilocytic astrocytoma/low-grade glial tumor. Final integrated diagnoses were astrocytoma, IDH-mutant, CNS WHO grade 2–4 (n = 9); dysembryoplastic neuroepithelial tumor (n = 3); central neurocytoma (n = 3); metastatic renal cell carcinoma (n = 2); low-grade glioneuronal tumor (n = 2); and PLNTY, glioblastoma IDH-wildtype, supratentorial ependymoma, and pilocytic astrocytoma (n = 1 each). Conclusions: Oligodendroglioma-like morphology should be interpreted as a diagnostic pitfall pattern rather than a specific diagnosis. Structured integrated reappraisal using targeted immunohistochemical and molecular/cytogenetic testing helps refine differential diagnosis in routine neuropathology practice. Full article

Background: Glioblastoma (GBM) carries a median survival of 15 months. Approximately 16–27% of patients die within six months despite standard therapy. Radiomic MRI features have been proposed as prognostic biomarkers, yet many published studies employ standard cross-validation (CV) with feature selection on the full dataset, introducing data leakage. Methods: Sixty patients with IDH-wildtype GBM from the publicly available UCSF-PDGM dataset (single-center, GE Discovery MR750, 3 T; 2015–2021) with BraTS 2021 segmentation masks were analyzed. One thousand two hundred eighty-four (1284) IBSI-compliant radiomic features (7 feature classes × 4 MRI sequences × 3 tumor subregions) were extracted using PyRadiomics. After preprocessing (variance filter, correlation filter |r| > 0.95), approximately 120 features remained per fold. Feature selection was performed strictly within each training fold of a nested 5-fold cross-validation framework (5-fold × 3 repeats = 15 outer folds). Results: For 1-year mortality, radiomics AUC dropped from 0.816 (standard CV) to 0.593 (nested CV; ΔAUC = −0.223, 27% inflation), while clinical models remained stable (0.708 vs. 0.705). For early mortality (≤180 days, n = 16 events), standard CV inflated radiomics AUC to 0.888, whereas nested CV yielded 0.815 (ΔAUC = −0.073, 8% inflation). In feature stability analysis, whole-tumor surface area (13/15 folds) and mesh volume (10/15 folds) showed the highest cross-endpoint stability; nine of 13 exploratory OS-associated features were never selected for early mortality classification. Extent of resection (HR = 0.44, p = 0.009) and age (HR = 1.03, p = 0.038) were independently associated with overall survival; tumor surface area remained independently associated with survival (HR = 1.38, p = 0.021). Conclusions: Nested cross-validation revealed substantial performance inflation in standard radiomics pipelines. These descriptive inflation estimates are specific to this dataset and pipeline configuration and should not be generalized as universal parameters for radiomics. Full article

Background/Objectives: Recurrent glioblastoma has a poor prognosis and no universally accepted standard of care. Regorafenib has been investigated in this setting, but its use may be limited by treatment-related toxicity. This study evaluated the feasibility, safety, and clinical outcomes of reduced-dose regorafenib in patients with recurrent IDH-wildtype glioblastoma. Methods: We retrospectively analyzed 21 patients with recurrent IDH-wildtype glioblastoma (WHO 2021) treated at a single center after progression according to the Stupp protocol. Regorafenib was started at 80 mg/day on the standard 3-weeks-on/1-week-off schedule. We assessed overall survival from diagnosis (OS1) and from first progression (OS2), progression-free survival from diagnosis (PFS1) and from first progression (PFS2), treatment exposure, dose modifications, and treatment-related adverse events (CTCAE v5.0). Results: Median PFS2 was 5 months (95% CI, 3–8), median OS2 was 6 months (95% CI, 5–10), and median OS1 was 21 months (95% CI, 15–27). No grade ≥ 3 adverse events occurred, and no patient discontinued treatment permanently because of toxicity. Conclusions: In this retrospective single-center cohort, reduced-dose regorafenib was feasible and well tolerated in selected patients. These descriptive, hypothesis-generating findings warrant prospective studies to define the role of individualized regorafenib dosing in recurrent glioblastoma. Full article

Background: Glioblastoma (GBM) shows marked heterogeneity in overall survival (OS), yet robust radiological prognostic markers remain limited. The prognostic value of peritumoral edema and tumor location remains uncertain. Objective: To evaluate whether peritumoral edema, tumor burden, and spatial tumor distribution predict OS using automated MRI analysis and Brain-Grid-based topographical mapping. Methods: In this retrospective study, preoperative T1-contrast-enhanced and T2-FLAIR MRI sequences from 271 patients with IDH-wildtype GBM were analyzed using automated segmentation (Raidionics). Tumor and edema volumes, edema-to-tumor ratio (ETR), and voxel-wise infiltration patterns were extracted. Location was mapped using the Brain-Grid system. Survival was assessed using Kaplan–Meier and multivariable Cox regression adjusted for age and tumor volume, with correction for multiple testing. Results: In multivariable analysis, only age remained a conventional independent predictor of OS (HR 1.03, p < 0.001). Tumor volume, edema volume, and ETR were not associated with survival. In contrast, Brain-Grid analysis identified two centrally located subcortical voxel regions that remained significantly associated with shorter OS after full adjustment and multiple testing correction. Total number of infiltrated voxels showed no prognostic value. Conclusions: Spatially defined subcortical infiltration patterns, rather than global tumor or edema burden, independently stratify survival in GBM. These findings highlight the prognostic relevance of voxel-level tumor topography and support further validation of Brain-Grid-based imaging biomarkers. Full article

Background/Objectives: Angiogenesis in glioblastoma (GBM) is a multifactorial process, and blood–brain barrier disruption enables the detection of circulating mediators. The clinical relevance of circulating placental growth factor (PlGF) in GBM remains unclear. This study aimed to investigate the role of PlGF in GBM and its association with disease characteristics and outcomes. Methods: We conducted a prospective observational study on 54 patients with IDH-wildtype GBM. Plasma samples collected at diagnosis and recurrence were analyzed using a multiplex panel of angiogenesis mediators. Associations with clinical, radiological, molecular, and treatment-related variables were assessed, along with survival outcomes. Statistical analysis was performed with R 4.5.0. Results: At baseline, PlGF correlated with multiple angiogenic mediators, including VEGF, IL-6, angiopoietin-1, EGF, FGF, IL-8, and TNF-α. Higher PlGF levels were associated with radiopathological features of tumor biology, including proliferation markers and the FLAIR/contrast enhancement ratio. In high-risk patients (RPA 3–4; n = 33), low baseline PlGF identified a subgroup with significantly longer overall survival (17.6 vs. 8.5 months; log-rank p = 0.031) and retained a protective association in multivariable models. In the overall cohort, this association was weaker and did not reach statistical significance. Exploratory longitudinal analyses suggested an increase in PlGF at recurrence in selected molecular and treatment-defined subgroups, while no association with bevacizumab exposure was observed. Conclusions: Circulating PlGF may reflect tumor biology in GBM and shows prognostic relevance in high-risk patients, where low baseline levels identify a subgroup with improved survival. These findings support PlGF as a candidate circulating biomarker and warrant validation in larger prospective cohorts. Full article

Postoperative radiotherapy (RT) improves survival in glioblastoma, and its role in standard management is not disputed. The randomized trials establishing this benefit, however, were conducted before computed tomography, magnetic resonance imaging (MRI), molecular classification, and temozolomide (TMZ), in heterogeneous populations of “operated malignant glioma” treated with whole-brain or large-field RT versus best supportive care. Their pooled survival benefit (risk ratio 0.81; 95% CI 0.74–0.88) robustly answers the historical question they were designed to address. Since then, advances in surgery, imaging, molecular diagnostics, and systemic therapy have created a modern best-prognosis subgroup—young patients with excellent performance status, MRI-confirmed complete or supramaximal resection of an IDH-wildtype glioblastoma, and median survival approaching or exceeding three years—for whom no clearly defined historical counterpart exists. This perspective provides a structured appraisal of the directness of the landmark randomized evidence using GRADE concepts and translates that appraisal into a graded roadmap for future de-escalation trial designs. Across population, intervention, comparator, and outcomes, the historical trials exhibit substantial indirectness, while the only randomized RT-versus-no-RT evidence from the modern era derives from elderly patients representing the opposite prognostic extreme. This is not an argument against RT. The infiltrative biology of glioblastoma, predominantly in-field recurrence, and radioresistant stem-cell populations strongly support continued benefit. Rather, the unresolved question concerns the magnitude of benefit after maximal contemporary therapy and whether selected de-escalation strategies merit prospective evaluation. Our thesis is one of collective scientific equipoise regarding an unresolved evidence question rather than individual clinician equipoise or refutation of current standard care. Full article

Background/Objectives: ¹⁸F-fluorodeoxyglucose positron emission tomography (FDG PET) reflects glucose metabolism but has limited diagnostic value for gliomas because of its high physiological uptake in the normal brain. This study visualized and characterized patterns of hypometabolism in non-contrast-enhanced gliomas using Z-score analysis and explored its potential for estimating isocitrate dehydrogenase (IDH) status. Methods: We retrospectively analyzed 116 patients with non-contrast-enhanced supratentorial gliomas, classified according to the 2021 World Health Organization classification (26 glioblastomas, IDH-wildtype; 54 astrocytomas, IDH-mutant; and 36 oligodendrogliomas, IDH-mutant and 1p/19q-codeleted). Z-score maps of FDG images were generated using a normal database. Tumor-associated hypometabolic regions (Z < −2) were analyzed, focusing on the proportion of severely hypometabolic regions (Z6–: Z < −6) and sphericity. Results: The mean Z-score differed significantly among the three subtypes, with the highest value observed in glioblastomas and the lowest in astrocytomas (p < 0.001). IDH-mutant gliomas showed a higher proportion of Z6– regions (p < 0.001) and higher sphericity (p = 0.009) than IDH-wildtype gliomas. In multivariable logistic regression, both the proportion of Z6– and sphericity were independent predictors of IDH status. Their combination demonstrated a strong discriminative performance for IDH status (area under the receiver operating characteristic curve = 0.839). On visual assessment, tumors with both small Z6– extent and low sphericity were primarily IDH-wildtype (75%), whereas the absence of both features indicated IDH-mutant status (94.8%). Conclusions: Z-score-based analysis enables the objective visualization and quantification of tumor-associated hypometabolic regions in non-contrast-enhanced gliomas, providing a potentially useful imaging biomarker for estimating IDH status. Full article

Background: Clinical outcomes in isocitrate dehydrogenase (IDH)-wildtype grade 4 diffuse glioma remain highly heterogeneous despite standard multimodal therapy. We evaluated the prognostic significance of pretreatment platelet-to-albumin ratio (PAR) and compared its performance with established inflammatory biomarkers. Methods: This retrospective cohort study included 166 patients with histopathologically confirmed IDH-wildtype grade 4 diffuse glioma treated between 2017 and 2025. Pretreatment PAR, neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), pan-immune inflammation value (PIV), C-reactive protein-to-albumin ratio (CAR), and lactate dehydrogenase-to-albumin ratio (LAR) were evaluated. Discriminative performance was assessed using classical and inverse probability of censoring weighting (IPCW)-adjusted time-dependent receiver operating characteristic (ROC) analyses. Survival outcomes were evaluated using Kaplan–Meier analyses and predefined baseline-adjusted multivariable Cox proportional hazards regression models. Internal validation was performed using 1000 bootstrap resampling iterations. Results: PAR demonstrated the highest discriminative performance for 12-month overall survival (OS), with an area under the curve of 0.853. Using an optimal cutoff value of 79.459, patients with elevated PAR experienced significantly shorter OS (median, 6.2 vs. 16.7 months; p < 0.001) and progression-free survival (PFS) (median, 5.9 vs. 12.3 months; p < 0.001). In baseline-adjusted multivariable analyses, elevated pretreatment PAR remained independently associated with inferior OS (hazard ratio [HR], 3.287; 95% confidence interval [CI], 2.196–4.921; p < 0.001) and PFS (HR, 3.791; 95% CI, 2.501–5.749; p < 0.001). These findings were supported by sensitivity analyses and bootstrap internal validation. Conclusions: Pretreatment PAR was independently associated with survival outcomes and demonstrated favorable discriminative performance relative to other inflammatory biomarkers. PAR may represent an accessible biomarker reflecting tumor–host interactions in IDH-wildtype grade 4 diffuse glioma. The proposed PAR cutoff should be considered exploratory and requires external validation before routine clinical application. Full article

Background: Glioblastoma (GBM) is the most aggressive primary brain tumor in adults and is characterized by poor prognosis and marked molecular heterogeneity. Mitochondrial ribosomal proteins have emerged as regulators of cancer metabolism, yet the clinical significance of MRPL23 in GBM remains unclear. This study aimed to evaluate the prognostic relevance of MRPL23 expression in glioblastoma and its association with patient survival and mitochondrial functional profiles. Methods: MRPL23 protein expression was assessed by immunohistochemistry in tissue microarrays derived from 89 patients with primary glioblastoma and 36 samples of adjacent non-tumorous brain tissue. Survival analyses were performed using Kaplan–Meier estimates and Cox proportional hazards models. In silico validation was conducted using transcriptomic and proteomic data from 296 IDH-wildtype glioblastomas from The Cancer Genome Atlas. Correlation analyses were used to explore associations between MRPL23 expression and mitochondrial respiratory chain components. Results: MRPL23 protein expression was significantly upregulated in glioblastoma compared with non-tumorous brain tissue (p < 0.001). High MRPL23 expression was associated with significantly shorter overall survival in the institutional cohort (median 13.5 vs. 21 months, p = 0.013). Consistently, low MRPL23 expression in the TCGA cohort was associated with improved overall and progression-free survival. MRPL23 expression showed strong positive correlations with key mitochondrial respiratory chain proteins, including COX5B, UQCRC1, and COX4I1. Conclusions: MRPL23 is overexpressed in glioblastoma and is associated with unfavorable patient outcomes. These findings identify MRPL23 as a potential prognostic biomarker and highlight mitochondrial translation as a relevant biological process in aggressive glioblastoma. Full article

Neuropeptide Y [NPY; encoded by the NPY gene] is a widely expressed 36-amino-acid neuropeptide that regulates neuronal function, vascular regulation, and immune regulation; its role in glioblastoma [GBM] remains incompletely characterized. We performed an integrative in silico multi-scale transcriptomic analysis combining bulk RNA-sequencing of IDH-wildtype GBM [n = 169] and lower-grade glioma [n = 510] surgical resections from TCGA, normal cortical tissue from GTEx [n = 207], and four independent GEO validation cohorts of surgical GBM and non-tumor brain specimens [GSE4290, GSE50161, GSE131928 scRNA-seq of ~20,426 cells from 28 patients, and GSE194329 10X Visium spatial transcriptomics from five patients], along with survival modeling, pathway enrichment, single-cell RNA sequencing, spatial transcriptomics, and cell–cell communication analysis. NPY and its principal receptor, NPY1R, were significantly downregulated in GBM, while genes associated with hypoxia, angiogenesis, invasion, and immune suppression were upregulated. Single-cell analysis showed that NPY-axis transcript expression was elevated in neural progenitor-like populations. In contrast, hypoxia and metabolic programs were concentrated in mesenchymal tumors and stromal compartments, indicating distinct cellular contexts. Spatial analysis revealed a weak and heterogeneous relationship between NPY and hypoxia signatures, with substantial inter-patient variability and no significant global spatial cross-correlation. These findings indicate that loss of NPY signaling is a consistent feature of GBM and is associated with hypoxia-driven tumor states, while the spatial relationship between NPY and hypoxia appears weak, heterogeneous, and patient-specific. Full article

Glioblastoma multiforme (GBM), isocitrate dehydrogenase (IDH)-wildtype, is the most aggressive primary malignant tumor of the central nervous system, characterized by poor prognosis and high recurrence rates despite standard multimodal treatment. This study investigates the molecular response of glioblastoma cells to 5-aminolevulinic acid (5-ALA)-based photodynamic therapy (PDT), focusing on gene expression changes associated with apoptosis, ferroptosis, and oxidative stress. Human glioblastoma T98G cells were treated with 5-ALA followed by light irradiation, and gene expression was analyzed using RT-qPCR. PDT induced moderate upregulation of pro-apoptotic genes (BAX, CASP3, FAS) alongside increased expression of the anti-apoptotic gene BCL2, indicating simultaneous activation of cell death and survival pathways. Ferroptosis-related genes showed mixed responses, with slight upregulation of ACSL4 and downregulation of GPX4, suggesting increased susceptibility to lipid peroxidation. The most significant change was observed in GCH1 expression, reflecting activation of oxidative stress response mechanisms. However, none of the observed changes reached statistical significance, likely due to the limited sample size. These findings demonstrate that PDT induces a complex and dual biological response in glioblastoma cells, involving both cytotoxic and adaptive mechanisms. This may limit therapeutic efficacy and contribute to treatment resistance. The results support the rationale for combining PDT with targeted molecular therapies aimed at inhibiting antioxidant defenses and anti-apoptotic pathways. Additionally, personalized therapeutic strategies based on tumor molecular profiles may enhance treatment outcomes. Further studies with larger sample sizes and functional validation are required to confirm these preliminary observations. Full article

Characterizing the m6A epigenetic landscape is essential for understanding glioma biology, yet transcriptome-wide mapping of these modifications at isoform resolution across specific tumor subtypes has remained limited. Conventional short-read approaches lack the capacity to resolve full-length transcript isoforms or assign m6A modifications to individual transcripts, representing a critical gap in glioma where alternative splicing is pervasive. Methods: We performed direct RNA nanopore sequencing and transcriptome-wide m6A analysis in 14 glioma tumor tissues, including IDH1-mutant astrocytoma, oligodendroglioma, and IDH1 wild-type glioblastoma, enabling isoform-resolved profiling not accessible by conventional short-read approaches. m6A sites were predicted computationally using the m6Anet deep learning framework, which has been independently benchmarked against MeRIP-seq-derived sites, and high-confidence calls were defined at a probability threshold of ≥0.9 and required detection across multiple patients within each subtype. Results: IDH1-mutant gliomas showed a higher overall burden of computationally inferred m6A-modified sites, transcripts, and genes than IDH1 wild-type glioblastoma, along with variation in transcript biotypes, regional distribution of m6A sites, and extent of isoform methylation. Differential methylation analysis identified subtype-specific patterns of m6A localization, many of which were observed without corresponding changes in gene-level expression, indicating that m6A variation represents a post-transcriptional regulatory layer not captured by gene-level analysis alone. Integration of gene expression, isoform usage, and m6A status further identified variation in isoform composition and transcript features between astrocytoma and glioblastoma. Analysis of m6A regulators showed subtype-associated expression patterns among readers, writers, and erasers, and exploratory analyses identified isoform-level associations with survival that were not apparent at the gene level. Conclusions: Overall, these data describe subtype-specific patterns of m6A marking and isoform architecture across glioma tissues, derived from computational inference using direct RNA sequencing in a modestly sized cohort and warrant validation by orthogonal methods in larger studies. These findings are consistent with concurrent independent evidence that isoform-specific m6A deposition is evolutionarily conserved across mammals and that long-read isoform resolution reveals transcript diversity in glioma not captured by gene-level analysis. While cohort size and the absence of orthogonal site-level validation suggest that the data require cautious interpretation, this work provides a hypothesis-generating resource and methodological framework for future mechanistic and translational investigation of the glioma epitranscriptome. Full article