Search Results (122)

Background: Photodynamic therapy (PDT) leading to immunogenic cell death (ICD) may serve as a promising basis for the development of antitumor therapeutic strategies. However, the mechanisms of action of photoinduced ICD in primary tumor cultures, including human glioma, remain unexplored. Methods: In the present study, the features of regulated cell death induced by photodynamic therapy using a previously described ICD inducer, porphyrazine III (pz III), were investigated. Cell death was studied in 7 primary cultures of high-grade human gliomas (astrocytomas, oligodendrogliomas, and glioblastomas). Results: Accumulation of porphyrazine III was observed in the endoplasmic reticulum (ER), Golgi apparatus, lysosomes, and mitochondria; however, the distribution of the photosensitizer varied across different cultures. A narrow concentration window of porphyrazine III was established to effectively reach IC85, primarily inducing ferroptosis with contributions from apoptosis and necroptosis accompanied by superoxide anion generation and mitochondrial dysfunction. Conclusions: Given the immunogenic potential of ferroptosis, apoptosis and necroptosis we hypothesize that the induction of PDT using porphyrazine III in glioma will trigger immunogenic cell death. 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

Background/Objectives: Increasing evidence indicates that gliomas co-opt mechanisms of excitatory synaptic transmission and plasticity to support tumor progression, yet these processes remain poorly characterized in lower-grade gliomas (LGGs). Here, we investigated whether genes associated with excitatory synaptic function are linked to patient prognosis in LGG. Methods: A curated panel of 36 synaptic genes was analyzed in LGG using RNA-sequencing and clinical data from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) datasets. Results: Among the genes investigated, DLG2, DLG3, and DLG4, which encode the postsynaptic scaffolding proteins PSD-93, SAP-102, and PSD-95, respectively, showed strong associations with patient overall survival (OS). Higher expression of each gene was consistently associated with longer OS across both datasets. Expression of DLG2–DLG4 was higher in oligodendroglioma and IDH-mutant, 1p/19q co-deleted tumors, and lower in astrocytoma and IDH-wild-type tumors. Furthermore, expression of all three genes positively correlated with a broad gene signature associated with a synaptic gene program, including multiple components of glutamatergic signaling and postsynaptic organization. Conclusions: These findings suggest that elevated expression of DLG2–DLG4 is associated with a transcriptional program resembling differentiated neuron-like features and favorable clinical outcome in LGG. Full article

Background: Gliomas are the most common malignant brain tumors in adults, characterized by a poor prognosis. Although the current World Health Organization (WHO) classification provides clear guidelines for classifying oligodendroglioma, astrocytoma, and glioblastoma patients, significant heterogeneity persists within each class, limiting the effectiveness of current treatment strategies. With the increasing availability of large-scale multi-omics datasets resulting from advancements in sequencing technologies and online repositories that provide them, such as The Cancer Genome Atlas (TCGA), it is now possible to investigate these tumors at multiple molecular levels. Methods: In this work, we apply integrative multi-omics analysis to explore the interplay between genomic (mutations), epigenomic (DNA methylation), and transcriptomic (mRNA and miRNA) layers. Our approach relies on Multi-Omics Factor Analysis (MOFA), a Bayesian latent factor analysis model designed to capture sources of variation across different omics types. Results: Our results highlight distinct molecular profiles across the three glioma types and identify potential relationships between methylation and genetic expression. In particular, we uncover novel candidate biomarkers associated with survival as well as a transcriptional profile associated with neural system development. Conclusions: These findings may contribute to more personalized therapeutic strategies, potentially improving treatment effectiveness and survival outcomes in this disease. Full article

Background: Amyloid-related pathways are well studied in neurodegenerative diseases but remain poorly characterized in gliomas. Amyloid-related transcriptional programs in low-grade gliomas (astrocytoma grade II-III) and oligodendrogliomas, and their association with patient survival, were analyzed in this study. Methods: Transcriptomic data from 193 grade II-III astrocytomas and 191 oligodendrogliomas were analyzed to evaluate histology-specific expression patterns and prognostic significance. Differential and single-sample gene set enrichment analyses (ssGSEA) were used to calculate per-sample enrichment scores for 30 amyloid-related Gene Ontology biological process gene sets across the combined cohort. These scores were used to compare pathway activity between grade II-III astrocytoma and oligodendroglioma samples. Pathway-level survival analyses were performed for each tumor type using ssGSEA enrichment scores to evaluate associations with overall survival. Results: Distinct amyloid-related transcriptional programs were identified between glioma subtypes. Grade II-III astrocytomas showed enrichment of pathways related to amyloid precursor protein (APP) processing and amyloid-β clearance, whereas oligodendrogliomas were enriched in lipid transport and negative regulation of amyloid formation. Survival analyses revealed that higher activity of the positive regulation of APP biosynthetic process and amyloid-β clearance by transcytosis was significantly associated with worse overall survival in grade II-III astrocytoma, but not in oligodendroglioma. Gene-level analyses in astrocytoma demonstrated consistent survival associations across multiple genes within these pathways, supporting coordinated pathway-level effects rather than isolated single-gene prognostic markers. Conclusions: Amyloid-related transcriptional programs differ substantially between diffuse glioma subtypes. Increased APP biosynthesis and amyloid-β transcytosis pathways are associated with poorer survival specifically in grade II-III astrocytoma, suggesting a potential role for amyloid metabolism in tumor progression. These findings identify APP-related pathways as candidates for further mechanistic investigation and potential therapeutic targeting in grade II-III astrocytoma. Full article

Alpha-ketoglutarate (aKG) is a central intermediate of cerebral energy metabolism and a precursor for glutamate synthesis in the brain. Alterations in aKG metabolism occur in pathological contexts, including isocitrate dehydrogenase (IDH) mutant astrocytomas and oligodendrogliomas, in which mutant IDH converts aKG to the oncometabolite 2-hydroxyglutarate. Given its central role in brain metabolism, non-invasive interrogation of aKG-dependent metabolic flux is needed. Hyperpolarized (HP) ¹³C MR enables real-time visualization of metabolic conversion by transiently enhancing signal intensity by several orders of magnitude. Leveraging this approach, we report the first-in-human feasibility and safety study of HP [1-¹³C]aKG MR spectroscopy in the healthy brain (n = 3). A standard operating procedure (SOP) was developed for sterile [1-¹³C]aKG dose production, achieving reproducible polarization levels averaging 30.5 ± 2.2%. Following intravenous administration, time-resolved ¹³C spectra in healthy volunteers demonstrated the detection of HP aKG resonance and a measurable downstream glutamate signal, consistent across repeat acquisitions, with a delayed temporal profile relative to aKG observed in a representative dataset. Although performed in healthy volunteers, these results establish feasibility for HP [1-¹³C]aKG metabolic imaging to open a new window into normal and pathological brain cellular metabolism. Full article

Background: Gliomas are among the most common and heterogeneous primary brain tumors, exhibiting substantial molecular and transcriptomic diversity that complicates diagnosis, grading, and treatment planning. Advances in artificial intelligence (AI), particularly machine learning (ML), offer powerful opportunities to analyze high-dimensional gene expression data and support precision oncology. Methods: This study proposes an interpretable ML framework to classify brain tumor subtypes—glioblastoma, astrocytoma, and oligodendroglioma—and to predict tumor grades (2, 3, and 4) using microarray-based gene expression data. The analysis was conducted on the REMBRANDT dataset, comprising 464 labeled samples (221 glioblastoma, 148 astrocytoma, 67 oligodendroglioma, and 28 controls) and 314 tumor samples for grade classification. Results: The ML models achieved high performance for disease classification, with accuracies of 99.6% (AUC 99.89%) for glioblastoma, 98.3% (AUC 99.83%) for astrocytoma, and 98.95% (AUC 100%) for oligodendroglioma. Tumor grade predictions also performed strongly, achieving 83.7% accuracy (AUC 88.2%) for grade II vs. III, 91.3% (AUC 94.8%) for grade II vs. IV, and 84.2% (AUC 90.8%) for grade III vs. IV. SHAP analysis identified key genes contributing to the model predictions (e.g., WIF1, STX6, RGS5, and ACTR2), and KEGG enrichment identified the candidate pathways involved in vesicular transport, metabolism, and immune signaling. Conclusion: Overall, our findings demonstrate that interpretable ML models can accurately differentiate glioma subtypes and grades, and SHAP analysis can help identify the strongest predictors of our models. These findings provide additional insights into the heterogeneous genetic and molecular landscape of brain gliomas and are intended to complement, not replace, conventional histopathological diagnosis. Full article

From an epidemiological perspective, polymorphous low-grade neuroepithelial tumor (PLNTY) represents a small proportion of brain tumors encountered in epilepsy surgery series. Their rarity and relatively recent recognition likely contribute to underdiagnosis and poor prognosis. In terms of histopathological features, they are similar to oligodendrogliomas. Molecular analyses can be used to show the fusion between fibroblast growth factor receptor (FGFR3) and transforming acidic coiled coil (TACC) proteins, which most commonly results in progression towards glioblastoma (GBM). We report a case of a 62-year-old man who underwent left frontal craniotomy to remove a frontal mass. Histologically, the glial lesion consisted of elements associated with oligodendroglia-like features. Immunohistochemistry was positive for glial fibrillary acidic protein (GFAP), oligodendrocyte transcription factor 2 (OLIG2), and α-thalassemia X-linked mental retardation syndrome (ATRX) nuclear expression, but negative for isocitrate dehydrogenase 1 (IDH1) and BRAF-V600E. Next-generation sequencing showed the FGFR-TACC3 fusion, and taken together, these findings supported the final diagnosis of PLNTY. During follow-up, the patient underwent a second neurosurgery, where histological evaluation indicated a GMB. This article presents clinical and radiological data, morphology, immunohistochemistry, molecular features, and treatment to enhance the clinical and pathological understanding of PLNTY with FGFR3-TACC3 fusion for all professionals involved in medical decisions. Full article

Objectives: This retrospective, multi-center study analyzed pre-existing anonymized clinical data from electronic health records and imaging archives. The analysis utilized real-world clinical data from 200 patients across four tertiary care centers, without additional patient recruitment or interventions. This study aims to investigate the impact of metabolic and physiological factors—specifically blood glucose levels, cortisol concentrations, fasting duration, and tumor histology—on the quality and diagnostic reliability of ¹⁸F-FDG PET/CT imaging in patients with primary brain tumors and inflammatory lesions. Methods: A total of 200 patients with primary brain tumors (including astrocytoma, glioblastoma, meningioma, and oligodendroglioma) were evaluated across four institutions using standardized protocols. The study examined the effects of prolonged fasting (>12 h), hyperglycemia (>150 mg/dL), and strict fasting (4–6 h) on tumor-to-background contrast and visual analog scale (DQS) scores. Results: Prolonged fasting was associated with elevated cortisol levels (correlation +0.54, p < 0.001), while hyperglycemia significantly reduced tumor SUVmax by up to 20% (r = −0.35, p = 0.012). Strict fasting and glucose control resulted in improved tumor-to-background contrast and DQS scores (r = +0.83, p < 0.001). Glioblastomas exhibited the highest SUVmax (9.1 ± 3.5), indicating aggressive metabolic activity, whereas meningiomas showed elevated cortisol levels (20.5 ± 6.8 µg/dL) linked to disruption of the hypothalamic–pituitary axis. Regression analysis confirmed that both cortisol and glucose levels independently degraded image quality (β = −0.25 and −0.18, respectively; p < 0.05). Conclusions: The findings highlight the necessity for harmonized patient preparation protocols. Recommendations are in alignment with the SNMMI Procedure Standard/EANM Practice Guideline for Brain [¹⁸F] FDG PET imaging. Full article

Gliomas are notoriously difficult to treat owing to their pronounced heterogeneity and highly variable treatment responses. This reality drives the development of precise diagnostic and prognostic methods. This review explores the modern arsenal of bioinformatic tools aimed at refining diagnosis and stratifying glioma patients by different malignancy grades and types. We perform a comparative analysis of software solutions for processing whole-exome sequencing data, analyzing DNA methylation profiles, and interpreting transcriptomic data, highlighting their key advantages and limited applicability in routine clinical practice. Special emphasis is placed on the contribution of bioinformatics to fundamental oncology, as these tools aid in the discovery of new biomarker genes and potential targets for targeted therapy. The ninth section discusses the role of computational models in predicting immunotherapy efficacy. It demonstrates how integrative data analysis—including tumor mutational burden assessment, characterization of the tumor immune microenvironment, and neoantigen identification—can help identify patients who are most likely to respond to immune checkpoint inhibitors and other immunotherapeutic approaches. The obtained data provide compelling justification for including immunotherapy in standard glioma treatment protocols, provided that candidates are accurately selected based on comprehensive bioinformatic analysis. The tools discussed pave the way for transitioning from an empirical to a personalized approach in glioma patient management. However, we also note that this field remains largely in the preclinical research stage and has not yet revolutionized clinical practice. This review is intended for biological scientists and clinicians who find traditional bioinformatic tools difficult to use. Full article

Background: IDH1-mutant oligodendroglioma and astrocytoma differ not only in growth rate but also in growth pattern. Oligodendrogliomas tend to infiltrate white matter tracts, whereas astrocytomas more often displace them. Such difference could lead to different cognitive outcomes. This study examined differences in executive functioning before and up to one year after surgery between patients with IDH1-mutant astrocytoma and oligodendroglioma. Methods: Patients with WHO grade 2–3 IDH1-mutant oligodendroglioma (1p19q-codeleted) or astrocytoma were included. Cognition was assessed preoperatively, and at 3 and 12 months postoperatively using standardized computerized and paper-and-pencil tests. Groups were compared on demographics, tumor characteristics, surgical modality, extent of resection, adjuvant treatment, and baseline cognition. Longitudinal mixed models were performed to investigate differences in performances over time for the total sample and stratified by surgical approach (awake vs. asleep). Results: 162 patients (67 oligodendroglioma, 95 astrocytoma) were included. Oligodendroglioma patients were older, with more frontal and fewer temporal tumors. Oligodendroglioma patients showed a greater impairment prevalence on a measure of inhibition before surgery. In the awake surgery group, no longitudinal differences were found between diagnoses. In the asleep surgery group, astrocytoma patients remained stable while oligodendroglioma patients declined on a measure of cognitive flexibility, with performance at 3 and 12 months significantly lower than at baseline. Conclusions: Specific aspects of executive functioning in IDH1-mutant gliomas may differ by subtype. Oligodendroglioma patients showed postoperative decline in cognitive flexibility that did not recover to baseline level, particularly in case of surgery under general anesthesia. These results highlight the potential relevance of tumor subtype and surgical approach in limiting cognitive risks after glioma surgery. Full article

The abstract has been submitted for presentation to the AANS 2026 meeting being held in San Antonio, TX, USA. Introduction: Oligodendrogliomas are an uncommon subset of gliomas that are molecularly defined by 1p/19q codeletion in the setting of an isocitrate dehydrogenase (IDH) 1/2 mutation. Standard-of-care management involves maximal safe resection followed by adjuvant chemoradiation with procarbazine, lomustine, and vincristine (PCV). Although PCV confers a durable survival advantage, treatment-limiting toxicity is common and often necessitates discontinuation. IDH inhibitors such as vorasidenib have demonstrated promising efficacy and more favorable tolerability profiles, but a paucity of comparative data across therapeutic classes limits optimal treatment decision-making. Methods: A systematic search was conducted through to 7 March 2025 in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). Eligible studies included adult patients (≥18 years) with IDH-mutant, 1p/19q-codeleted oligodendrogliomas treated with PCV chemotherapy or IDH inhibitors and with a minimum follow-up of 12 months. Outcomes of interest included overall survival (OS), progression-free survival (PFS), and grade ≥ 3 adverse events (AEs) that led to treatment discontinuation. Results: Twenty-eight studies met the inclusion criteria, with a total of 406 patients. All 406 patients carried a confirmed diagnosis of oligodendroglioma. For mixed-histology cohorts, only oligodendroglioma-specific data were extracted and analyzed. Among PCV cohorts, median PFS ranged from 24.3 months to 8.4 years and median OS was reported up to 14.7 years in long-term follow-up from RTOG 9402 and EORTC 26951. Grade ≥ 3 AEs resulted in treatment discontinuation in 65–70% of patients, primarily due to hematologic or neurologic events. In comparison, vorasidenib achieved a median PFS of 27.7 months in the phase III INDIGO trial (HR 0.39; 95% CI 0.27–0.56; p < 0.001), with median OS not yet reached at 14.2 months of follow-up. Grade ≥ 3 AEs occurred in 22.8% of patients and led to treatment discontinuation in only 1–3%, primarily due to asymptomatic transaminitis. Early real-world data from expanded-access programs similarly support these tolerability findings. Conclusions: While PCV chemotherapy remains the standard-of-care systemic therapy for oligodendroglioma supported by mature survival data, IDH inhibitors represent a mechanistically targeted alternative with encouraging early-phase outcomes and a significantly improved safety profile. Direct comparison across these regimens is constrained by differences in study design and limited long-term OS data for IDH inhibitors. Prospective head-to-head trials are essential for defining the optimal therapeutic sequence in this evolving treatment landscape. In the interim, we provide a recommend approach for current use. Full article

Background: The androgen receptor (AR) is a ligand-dependent transcription factor of the nuclear steroid receptor superfamily, implicated in the pathogenesis of various solid tumors. The AR gene, located on chromosome Xq11–12, is accompanied by several X-linked genes that modulate AR expression and function, including FLNA, UXT, and members of the melanoma antigen gene (MAGE) family (MAGEA1, MAGEA11, MAGEC1, MAGEC2). While the AR has been investigated in multiple tumor types, its role in adult-type diffuse gliomas remains largely unexplored. Here, we characterized AR protein expression and the promoter methylation status of the AR and associated regulatory genes in adult-type diffuse gliomas. Methods: A retrospective analysis was conducted on 50 patients with adult-type diffuse gliomas, including IDH-mutant gliomas (grades 2–4) and IDH-wildtype glioblastomas (GBMs), classified according to the 2021 WHO criteria. AR nuclear expression was assessed by immunohistochemistry (IHC). Methylation-specific PCR and quantitative DNA methylation analyses were employed to evaluate promoter methylation of the AR and selected co-regulatory genes. Results: AR nuclear positivity correlated significantly with male sex (p = 0.04) and higher tumor grade, with the highest expression in IDH-wildtype GBMs (p = 0.04). In IDH-mutant gliomas, AR immunoreactivity was more prevalent in astrocytomas than in 1p/19q codeleted oligodendrogliomas (p = 0.02). AR expression was associated with unmethylated MGMT promoter status (p = 0.02). DNA methylation analysis revealed AR gene hypomethylation in tumors displaying nuclear AR positivity and in IDH-wildtype GBMs (Kruskal–Wallis p < 0.05). Additionally, methylation patterns of AR co-regulators located on the X chromosome suggest epigenetic regulation of AR signaling in gliomas. Conclusions: The findings reveal distinct AR pathway activation patterns in adult-type diffuse gliomas, particularly IDH-wildtype GBMs, suggesting that further exploration of antiandrogen therapies is warranted. Full article

Background/Objectives: Methionine (MET) positron emission tomography (PET) and cerebral blood volume (CBV) imaging provide complementary glioma assessment. This study compared MET and CBV across glioma subtypes defined by the 2021 World Health Organization Classification. Methods: This retrospective study enrolled 106 patients (mean age 41.9 ± 12.4 years; 57 males) with MRI non-contrast-enhanced gliomas: 21 glioblastoma, isocitrate dehydrogenase (IDH)-wildtype (G); 50 astrocytoma, IDH-mutant (A); and 35 oligodendrogliomas, IDH-mutant, and 1p/19q-codeleted (O). Relative CBVs (rCBVs) were measured in VOI-T2 and VOI-MET, and the MET tumor-to-normal (T/N) ratio was calculated. Results: MET and rCBV were significantly correlated (r = 0.5, p < 0.001); rCBV was higher in MET-positive tumors and predicted MET accumulation (area under the curve [AUC] = 0.72, cutoff = 2.99). In VOI-T2, rCBV and MET T/N ratio were the highest in G and lowest in A (p < 0.001). Receiver operating characteristic analyses showed no overall significant difference between MET and rCBV for differentiating G/A/O, but rCBV trended toward higher AUC values in key distinctions, such as G (0.736 vs. 0.612) or grade 4 (0.718 vs. 0.617). The increase in rCBV within the MET-positive region (VOI-MET/VOI-T2 rCBV ratio) was significantly higher in A (119.8%, p = 0.002) than in the other groups (p = 0.01). Conclusions: rCBV differentiated glioma subtype with accuracy comparable to MET and could predict MET accumulation. However, its reliability for identifying MET-positive regions varied by subtype, being useful in A but limited in O. Recognizing these subtype-specific differences, rCBV can serve as a practical tool for evaluating non-contrast-enhanced gliomas. Full article

The search for markers applicable for efficient differential diagnosis and personalized therapy is a priority task of experimental neuro-oncology. Modern molecular methods allow us to analyze human biopsy material; however, further actions with this extracted tumor tissue are limited. Relevant and sophisticated CNS tumor models are required for precise therapy development. Although it is possible to use human biomaterial to create 2D and 3D cultures and implant them into xenograft animals, the data generated from such models is limited. Due to changes in the classification of the CNS tumors in 2021, a representative model should have not only morphological similarity to human tumors but also key genetic aberrations for studying the mechanisms of carcinogenesis and personalized therapy (such as PDGFRa, Olig1/2, Sox2, and Mki67) for different glioma models such as astrocytoma, oligodendroglioma, and glioblastoma. On the basis of a unique scientific facility “The Collection of experimental tumors of the nervous system and neural tumor cell lines” (Avtsyn Research Institute of Human Morphology of “Petrovsky National Research Center of Surgery”), there is a biobank of chemically induced transplantable tumors of laboratory animals. Their properties, mechanisms, and progression closely correlate with malignant CNS neoplasms in humans. These are potentially useful for identifying novel signaling pathways associated with oncogenesis in the nervous system and personalizing therapeutic approaches. In our work, we characterized a tissue-transplantable brain tumor strain of rat glioma101.8 using MRI, IHC, scRNA-seq, and qPCR-RT methods. According to this study, the cellular composition of the tissue-transplantable rat glioma 101.8 strain was determined, as well as the major genetic signature characteristics of each cell population of this tissue-transplantable strain and its microenvironment. Full article