Search Results (160)

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

Background: Fluorescence-guided surgery using 5-aminolevulinic acid (5-ALA) enables the intraoperative visualization of glioma. However, its effectiveness varies based on tumor subtype and molecular profile, posing challenges for achieving complete resection. Our systematic review aims to explore the relationship between IDH mutation status and intraoperative fluorescence visualization. Importantly, this is the first study to propose that vorasidenib, an emerging IDH-targeting agent, could enhance 5-ALA-guided surgery, marking a novel direction for translational research. Methods: A systematic literature search was conducted using the PubMed, Cochrane Library, Scopus and Web of Science databases up to May 2025, following PRISMA guidelines. The primary outcomes included fluorescence detection rates across different glioma subtypes and their correlation with IDH mutation status. Secondary outcomes comprised surgical efficacy measures such as gross total resection (GTR), overall survival (OS), and progression-free survival (PFS). Additionally, we analyzed the metabolic consequences of IDH mutations and evaluated the potential role of vorasidenib in enhancing 5-ALA-induced fluorescence. Results: Seven studies including 621 patients included in the final analysis. Fluorescence detection was nearly universal in WHO grade 4 gliomas (94–100%), but lower in grade 3 (43–85%) and rare in grade 2 (7–26%). Several cohorts reported reduced fluorescence in IDH-mutant gliomas, although this was not consistent across all studies. In high-grade gliomas, visible fluorescence correlated with higher GTR rates and, in some series, longer OS. Conversely, in lower-grade IDH-mutant gliomas, fluorescence did not increase GTR and was associated with worse PFS and OS. Conclusions: The effectiveness of 5-ALA-guided fluorescence in glioma surgery is significantly influenced by both tumor grade and IDH mutation status. Vorasidenib may represent a potential avenue for modulating tumor metabolism and enhancing intraoperative fluorescence in IDH-mutant gliomas, a hypothesis that warrants further experimental validation. Full article

WWOX and HIF1α proteins are involved in cancer progression; their functions are closely related. WWOX binds HIF1α through its WW domains, sequestering it in the cytoplasm and inhibiting its transcriptional activity. This study evaluates the prognostic significance of the WWOX/HIF1A interaction across cancers, breast cancer subtypes, glioblastoma (GBM), low-grade glioma (LGG), and hepatocellular carcinoma (HCC) through gene expression and pathway analysis focused on metabolism, ECM, and epithelial–mesenchymal transition. In breast cancer, metabolic pathways correlated with good prognosis in basal subtypes. HER2 subtypes showed enrichment in DNA replication pathways. Luminal A subtypes showed favourable prognosis via TNF and PI3K/AKT signalling, while luminal B subtypes had poor prognosis tied to metabolic activity; genes associated with good prognosis mirrored those tied to poor prognosis in luminal A. In HCC, enhanced metabolic activity was associated with good prognosis. In contrast, poor prognosis involved TNF signalling and cytoskeleton-related pathways, indicating more aggressive tumour behaviour. In LGG, good prognosis was linked to metabolic and cAMP pathways, while poor outcomes involved TNF, cell cycle, apoptosis, and focal adhesion pathways. GBM showed similar patterns: metabolic and cAMP pathways indicated better outcomes, while NFKB, TNF, JAK-STAT, and PI3K/AKT pathways marked poor prognosis. These findings suggest the WWOX/HIF1A ratio is a robust prognostic marker and a possible guide for developing targeted treatments. Full article

Neoplasms of the central nervous system (CNS) constitute a minor fraction of all malignant tumors. CNS accounts for approximately 4% of newly diagnosed oncological cases. Among primary CNS neoplasms, gliomas predominate, comprising nearly 90% of all malignant brain tumors, with Glioblastoma (GBM) representing the most prevalent and aggressive histological subtype. The earliest documented occurrences of GBM date back to the 19th century. Contemporary therapeutic modalities for GBM primarily involve maximal surgical resection, adjuvant radiotherapy, and systemic chemotherapy. However, the intrinsic heterogeneity of GBM poses a formidable obstacle to treatment efficacy. The immunosuppressive tumor microenvironment, coupled with the restrictive nature of the blood–brain barrier (BBB), significantly limits the intratumorally delivery of chemotherapeutic agents. The emergence of nanotechnology in the biomedical domain has been driven by the urgent need to develop more effective and targeted anticancer interventions. Optimizing therapeutic outcomes necessitates the concurrent application of multimodal strategies. This review emphasizes the Nano-Based Technology in GBM. Full article

Glioblastoma multiforme (GBM) is the most aggressive and lethal primary brain tumor in adults, characterized by high intratumoral heterogeneity, therapy resistance, and poor prognosis. Nuclear factor-κB (NF-κB) signaling plays a pivotal role in GBM pathogenesis by promoting proliferation, invasion, inflammation, immune evasion, and treatment resistance. This review provides a comprehensive overview of canonical and non-canonical NF-κB signaling pathways and their molecular mechanisms in GBM, with a focus on their regulation in glioma stem-like cells (GSCs), interactions with key oncogenic factors (including STAT3, FOSL1, and TRPM7), and roles in maintaining tumor stemness, metabolic adaptation, and angiogenesis. We further discuss the reciprocal regulatory dynamics between NF-κB and non-coding RNAs (ncRNAs), particularly microRNAs, highlighting novel ncRNA-mediated epigenetic switches that shape GBM cell plasticity and subtype specification. Additionally, we examine the influence of NF-κB in modulating the tumor microenvironment (TME), where it orchestrates pro-tumorigenic cytokine production, immune cell reprogramming, and stromal remodeling. Finally, we review current NF-κB-targeting therapeutic strategies in GBM, including clinical trial data on small-molecule inhibitors and combinatorial approaches. Understanding the multifaceted roles of NF-κB in GBM offers new insights into targeted therapies aimed at disrupting tumor-promoting circuits within both cancer cells and the TME. Full article

Background/Objectives: Gliomas are complex and heterogeneous brain tumors characterized by an unfavorable clinical course and a fatal prognosis, which can be improved by an early determination of tumor kind. Here, we developed explainable machine learning (ML) models for classifying three major glioma subtypes (astrocytoma, oligodendroglioma, and glioblastoma) and predicting survival rates based on RNA-seq data. Methods: We analyzed publicly available datasets and applied feature selection techniques to identify key biomarkers. Using various ML models, we performed classification and survival analysis to develop robust predictive models. The best-performing models were then interpreted using Shapley additive explanations (SHAP). Results: Thirteen key genes (TERT, NOX4, MMP9, TRIM67, ZDHHC18, HDAC1, TUBB6, ADM, NOG, CHEK2, KCNJ11, KCNIP2, and VEGFA) proved to be closely associated with glioma subtypes as well as survival. Support Vector Machine (SVM) turned out to be the optimal classification model with the balanced accuracy of 0.816 and the area under the receiver operating characteristic curve (AUC) of 0.896 for the test datasets. The Case-Control Cox regression model (CoxCC) proved best for predicting survival with the Harrell’s C-index of 0.809 and 0.8 for the test datasets. Using SHAP we revealed the gene expression influence on the outputs of both models, thus enhancing the transparency of the prediction generation process. Conclusions: The results indicated that the developed models could serve as a valuable practical tool for clinicians, assisting them in diagnosing and determining optimal treatment strategies for patients with glioma. Full article

Glioblastoma (GBM) remains one of the most aggressive and treatment-resistant brain tumors, largely due to its profound intratumoral heterogeneity and immunosuppressive microenvironment. Various classifications of GBM subtypes were created based on transcriptional and methylation profiles. This effort, followed by the development of new technology such as single-nuclei sequencing (snRNAseq) and spatial transcriptomics, led to a better understanding of the glioma cells’ plasticity and their ability to transition between diverse cellular states. GBM cells can mimic neurodevelopmental programs to resemble oligodendrocyte or neural progenitor behavior and hitchhike the local neuronal network to support their growth. The tumor microenvironment, especially under hypoxic conditions, drives the tumor cell clonal selection, which then reshapes the immune cells’ functions. These adaptations contribute to immune evasion by progressively disabling T cell and myeloid cell functions, ultimately establishing a highly immunosuppressive tumor milieu. This complex and metabolically constrained environment poses a major barrier to effective antitumor immunity and limits the success of conventional therapies. Understanding the dynamic interactions between glioma cells and their microenvironment is essential for the development of more effective immunotherapies and rational combination strategies aimed at overcoming resistance and improving patient outcomes. Full article

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

Glioblastoma multiforme (GBM), the most aggressive and therapy-resistant glioma subtype, remains an urgent clinical challenge due to its invasive nature, molecular heterogeneity, and the protective constraints of the blood–brain barrier (BBB). Liposomes and extracellular vesicles (EVs) have emerged as two of the most promising nanocarrier systems capable of overcoming these limitations through improved drug delivery and cellular targeting. Their applications in glioma therapy span chemotherapy, immunotherapy, and gene therapy, each presenting distinct advantages and mechanisms of action. Liposomes offer structural flexibility, controlled release, and a well-established clinical framework, while EVs provide innate biocompatibility, low immunogenicity, and the ability to mimic natural intercellular communication. Both systems demonstrate the capacity to traverse the BBB and selectively accumulate in tumor tissue, yet they differ in scalability, cargo loading efficiency, and translational readiness. Comparative evaluation of their functions across therapeutic modalities reveals complementary strengths that may be leveraged in the development of more effective, targeted strategies for glioma treatment. Full article

Amyloidosis, often referred to as “the great imitator”, is a condition characterized by the abnormal deposition of amyloid proteins in various tissues, potentially leading to organ dysfunction. When these deposits localize in the brain, they can disrupt neurological function and present with diverse clinical manifestations, making diagnosis particularly challenging. Cerebral amyloidosis is a rare entity that frequently mimics other neurological disorders, often resulting in significant delays in recognition and management. This case highlights the diagnostic challenge posed by cerebral amyloidosis and underscores its unique presentation. We present the case of a 76-year-old male with a history of rheumatoid arthritis (RA) who developed progressive right-sided weakness over several months. Three years prior, he experienced numbness on the right side of his face and upper limb. Initial imaging identified a small lesion in the left thalamic region, which was originally diagnosed as a glioma. However, due to the worsening of his clinical symptoms, further evaluation was warranted. Subsequent imaging revealed lesion growth, prompting a biopsy that ultimately confirmed the diagnosis of intracerebral amyloidoma. This case underscores the necessity of considering amyloidosis in the differential diagnosis of atypical neurological deficits, particularly in patients with systemic inflammatory conditions such as RA. The initial presentation of hemiparesis resembling a stroke, coupled with non-specific imaging findings and a prior misdiagnosis of glioma, highlights the complexity of cerebral amyloidosis. Only through brain biopsy was the definitive diagnosis established, emphasizing the need for improved diagnostic modalities to facilitate early detection. Further subtyping of amyloidosis, however, requires mass spectrometry-based proteomics or immunohistochemistry to accurately identify the specific amyloid protein involved. Clinicians should maintain a high index of suspicion for cerebral amyloidosis in patients with RA who present with progressive neurological deficits and atypical brain lesions. Early recognition and accurate diagnosis are essential to guiding appropriate management and improving patient outcomes. Full article

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

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

Background/Objectives: Gliomas, including the most aggressive subtype—glioblastoma multiforme, are brain tumors with an unfavorable prognosis and high mortality. Early diagnosis is essential to improve treatment efficacy. Positron emission tomography PET with O-(2-[¹⁸F] fluoroethyl)-L-tyrosine ([¹⁸F]FET) has been supported by clinical studies for its role in diagnosis and monitoring the disease. However, the low availability of [¹⁸F]FET in Italy has limited its use in clinical praxis. This study describes the technological transfer of the radiopharmaceutical IASOglio^® (the commercial [¹⁸F]FET developed by Curium Pharma in Italy), with the aim of improving national access to this advanced diagnostic technology. Methods: Three consecutive batches were produced using the automated Trasis AllinOne module, and quality control was performed, including chemical and microbiological tests, to successfully validate the production process. Additionally, the stability of the radiopharmaceutical for its entire shelf life has been demonstrated with stability testing at 14 h after end of synthesis (EOS). Results: The production of [¹⁸F]FET achieved a non-corrected yield between 49% and 52%, with a corrected decay rate ranging from 73% to 79%. The process met the required quality specifications, including bio-burden control and filter integrity. The technological transfer was successfully completed, and production authorization was obtained from the Italian Medicines Agency (AIFA) for the Officina Farmaceutica of Institute of Clinical Physiology of the National Research Council (CNR-IFC) located in Pisa. Conclusions: Local production of [¹⁸F]FET in Italy marks a milestone in glioma diagnosis, thereby contributing to timely treatment and improved clinical outcomes. Full article

Background: Human leukocyte antigen class I (HLA-I) plays a pivotal role in shaping anti-tumour immunity by influencing the functionality of T cells and natural killer (NK) cells within the tumour microenvironment. Methods: Here, we explored the transcriptional landscape of HLA-I molecules across various solid cancer transcriptomes from The Cancer Genome Atlas (TCGA) database and assessed the impact of HLA-I expression on the clinical significance of tumour-infiltrating CD56^dim and CD56^bright NK cells. Results: Our analysis revealed that high HLA-I expression correlated with reduced patient survival in the TCGA lower-grade glioma (LGG) cohort, with this association varying by histopathological subtype. We then estimated the relative abundance of 23 immune and stromal cell signatures in LGG transcriptomes using a cellular deconvolution approach, which revealed that LGG patients with low HLA-I expression and high CD56^dim NK cell abundance had better survival outcomes compared to those with high HLA-I expression and low CD56^dim NK cell abundance. Furthermore, HLA-I expression was positively correlated with various inhibitory NK cell receptors and negatively correlated with activating NK cell receptors, particularly those within the killer cell lectin-like receptor (KLR) gene family. High co-expression of HLA-E and NKG2A predicted poor survival outcomes in LGG patients, whereas low HLA-E and high NKG2C/E abundance predicted more favourable outcomes, suggesting a potential modulatory role of HLA-I on the tumour-infiltrating cytotoxic CD56^dim NK cell subset. Conclusions: Overall, our study unveils a potential role for deregulated HLA-I expression in modulating the clinical impact of glioma-infiltrating CD56^dim NK cells. These findings lay the foundation for future in-depth experimental studies to investigate the underlying mechanisms. Full article

Telomere maintenance mechanisms (TMMs) play a critical role in cancer biology, particularly in lower-grade gliomas (LGGs), where telomere dynamics and pathway activity remain poorly understood. In this study, we analyzed TCGA-LGG and CGGA datasets, focusing on telomere length variations, pathway activity, and survival data across IDH subtypes. Additional validation was performed using the GEO COPD and GBM datasets, ensuring consistency in data processing and batch effect correction. Our analysis revealed significant differences in TEL pathway activation between Short- and Long-TL groups, emphasizing the central role of TERT in telomere maintenance. In contrast, ALT pathway activation displayed subtype-specific patterns, with IDH-wt tumors exhibiting the highest ALT activity, primarily driven by the RAD51 branch. Validation using CGGA data confirmed these findings, demonstrating consistent TEL and ALT pathway behaviors across datasets. Additionally, genetic subtype analysis revealed substantial telomere length variability associated with ATRX and IDH mutation status. Notably, IDHwt-ATRX WT tumors exhibited the shortest telomere length and the highest ALT pathway activity. These findings highlight distinct telomere regulatory dynamics across genetic subtypes of LGG and provide new insights into potential therapeutic strategies targeting telomere maintenance pathways. Full article