Search Results (187)

Background: The incidence and prognosis of high-grade gliomas differ according to histopathological and molecular features. The WHO 2021 CNS classification emphasized IDH status, but historical cohorts often lacked systematic molecular profiling. Methods: We conducted a retrospective population-based study including adult patients diagnosed with IDH-wildtype glioblastoma or IDH-mutant astrocytoma in a Spanish tertiary center (2011–2021). Incidence trends and survival outcomes were analyzed according to treatment modality and sex. Results: A total of 1057 patients were included: 530 (50.1%) with IDH-wildtype glioblastoma and 137 (13%) with IDH-mutant astrocytoma. Incidence of both subtypes significantly increased during the study period (p < 0.01). Median overall survival (OS) was 12.3 months for IDH-wildtype glioblastoma and 38.4 months for IDH-mutant astrocytoma. Multimodal therapy (surgery, radiotherapy, chemotherapy) significantly improved OS and progression-free survival (PFS) in both subgroups (p < 0.001). Male sex was associated with longer OS in both tumor types (p < 0.05). Conclusions: IDH-wildtype glioblastoma shows persistently poor outcomes despite increasing incidence, while IDH-mutant astrocytoma demonstrates better survival, particularly in male patients and those receiving multimodal therapy. These findings reflect real-world practice and provide epidemiological and survival data from Southern Europe to guide future clinical and public health strategies. Full article

Background: Tumor-associated macrophages (TAMs) are essential regulators of the glioblastoma (GBM) microenvironment; their functional heterogeneity and interaction networks are not fully elucidated. We identify RNF135 as a novel TAM-enriched gene associated with immune activation and adverse prognosis in GBM. Methods: To evaluate RNF135’s expression profile, prognostic significance, and functional pathways, extensive transcriptome analyses from TCGA and CGGA cohorts were conducted. The immunological landscape and cellular origin of RNF135 were outlined using single-cell RNA-seq analyses and bulk RNA-seq immune deconvolution (MCP-counter, xCell and ssGSEA). Cell–cell communication networks between tumor cells and RNF135-positive and -negative tumor-associated macrophage subsets were mapped using CellChat. Results: RNF135 predicted a poor overall survival and was markedly upregulated in GBM tissues. Functional enrichment analyses showed that increased cytokine signaling, interferon response, and innate immune activation were characteristics of RNF135-high samples. Immune infiltration profiling showed a strong correlation between the abundance of T cells and macrophages and RNF135 expression. According to the single-cell analyses, RNF135 was primarily expressed in TAMs, specifically in proliferation, phagocytic, and transitional subtypes. RNF135-positive TAMs demonstrated significantly improved intercellular communication with aggressive tumor subtypes in comparison to RNF135-negative TAMs. This was facilitated by upregulated signaling pathways such as MHC-II, CD39, ApoE, and most notably, the CCL signaling axis. The CCL3/CCL3L3–CCR1 ligand–receptor pair was identified as a major mechanistic driver of TAM–TAM crosstalk. High RNF135 expression was also linked to greater sensitivity to Selumetinib, a selective MEK1/2 inhibitor that targets the MAPK/ERK pathway, according to drug sensitivity analysis. Conclusions: RNF135 defines a TAM phenotype in GBM that is both immunologically active and immunosuppressive. This phenotype promotes inflammatory signaling and communication between cells in the tumor microenvironment. Targeting the CCL–CCR1 axis or combining RNF135-guided immunomodulation with certain inhibitors could be a promising therapeutic strategies for GBM. 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

Glioblastoma (GBM) remains the most lethal primary brain tumor, owing to profound intratumoral heterogeneity and the limited efficacy of standard treatments. The mesenchymal (MES) molecular subtype is particularly aggressive, exhibiting heightened invasiveness, therapy resistance, and dismal patient survival compared with the proneural (PN) subtype. Emerging evidence implicates the High Mobility Group Box 1 (HMGB1) protein and its cognate receptor, the Receptor for Advanced Glycation End Products (RAGE), as drivers of malignant progression, yet their contribution to the PN-to-MES transition is incompletely defined. We integrated transcriptomic analyses of TCGA-GBM and TCGA-LGG cohorts with immunohistochemistry on in-house patient specimens. Functional studies in patient-derived and established GBM cell lines included migration and invasion assays, tumorsphere formation assays, shRNA knockdowns, and Seahorse XF metabolic profiling to interrogate the HMGB1-RAGE axis. HMGB1 and RAGE expression was markedly elevated in MES GBM tissues and cell lines. Importantly, higher HMGB1 expression correlated with shortened overall survival (p < 0.009). HMGB1 silencing curtailed cell motility and downregulated core epithelial-to-mesenchymal transition markers (N-cadherin, Snail). RAGE knockdown diminished tumorsphere formation efficiency and reduced transcription of stemness genes (OCT4), underscoring its role in sustaining tumor-initiating capacity. Metabolically, HMGB1/RAGE activation boosted both mitochondrial respiration and glycolysis, conferring the bioenergetic flexibility characteristic of MES GBM. The HMGB1-RAGE signaling axis orchestrates mesenchymal identity, invasiveness, stem cell-like properties, and metabolic reprogramming in GBM. Targeting this pathway may disrupt the PN-to-MES transition, mitigate therapeutic resistance, and ultimately improve outcomes for glioblastoma patients. Full article

Several microRNAs (miRNAs) are key influencers of tumor microenvironment (TME) cell plasticity, regulating the progression of various tumor types such as glioblastoma (GBM). Differential expressions of miR-27a-3p and miR-155-5p in GBM cells and biopsies have already been described as markers of tumor subtype and progression. We aimed to evaluate the cellular and molecular impacts of inhibiting these two overexpressed miRNAs in GBM cell lines. A172 cells were transfected with miR-27a-3p and miR-155-5p inhibitors, and the effects on cellular processes and the expression of malignancy-related genes were analyzed by flow cytometry and qPCR, respectively. Thus, several cellular characteristics in A172 cells were modulated; however, only the inhibition of miR-27a-3p resulted in apoptosis, reduced glucose uptake, and a decrease in mitochondrial membrane potential. Both inhibitors modulated metabolic and immunological targets, negatively regulating genes in the glycolysis pathway and modulating other metabolic pathways involving glutamine and fatty acids, for example. Additionally, it modulates the TGF-β pathway, which can influence the GBM microenvironment due to its immunosuppressive role in advanced tumors. miR-27a-3p appears to be a pivotal factor in the functional duality of TGF-β and its interaction with HIF1A in the hypoxic tumor environment, modulating SMAD partners or TGF-β pathway inhibitors. Here, we demonstrate the importance of inhibiting overexpressed miRNAs, particularly miR-27a-3p, in modulating key pathways for tumor cell survival. The results of this work provide new insights into potential targets for immune-metabolic interactions in the TME and their implications for tumorigenesis, shedding light on new therapeutic approaches for GBM. Full article

Background/Objectives: Glioblastomas (GBMs) and brain metastases (BMs) are both frequent brain lesions. Distinguishing between them is crucial for suitable therapeutic and follow-up decisions, but this distinction is difficult to achieve, as it includes clinical, radiological and histopathological correlation. However, non-invasive AI examination of conventional and advanced MRI techniques can overcome this issue. Methods: We retrospectively selected 78 patients with confirmed GBM (39) and single BM (39), with conventional MRI investigations, consisting of T2W FLAIR and CE T1W acquisitions. The MRI images (DICOM) were evaluated by an AI segmentation tool, comparatively evaluating tumor heterogeneity and peripheral edema. Results: We found that GBMs are less edematous than BMs (p = 0.04) but have more internal necrosis (p = 0.002). Of the BM primary cancer molecular subtypes, NSCCL showed the highest grade of edema (p = 0.01). Compared with the ellipsoidal method of volume calculation, the AI machine obtained greater values when measuring lesions of the occipital and temporal lobes (p = 0.01). Conclusions: Although extremely useful in radiomics analysis, automated segmentation applied alone could effectively differentiate GBM and BM on a conventional MRI, calculating the ratio between their variable components (solid, necrotic and peripheral edema). Other studies applied to a broader set of participants are necessary to further evaluate the efficacy of automated segmentation. 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

Glioblastoma (GBM) is the most common and aggressive primary malignant brain tumor. Despite the current standard of care therapy, including maximal surgical resection, chemoradiation, and tumor-treating fields, prognosis remains poor. Therapeutic failure is driven by an immunosuppressive tumor microenvironment, poor drug penetration across the blood–brain barrier, and robust resistance mechanisms. Epigenetic alterations further compound treatment resistance by enhancing DNA repair and promoting survival pathways. Molecular profiling has identified key prognostic and predictive biomarkers. Gene expression analyses have delineated GBM subtypes, each with distinct molecular features and therapeutic vulnerabilities that hinder successful clinical translation. This review integrates the pathophysiological, diagnostic, and therapeutic landscape of GBM to inform of future strategies for improved patient outcomes. 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

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

Glioblastoma is a highly aggressive brain tumor with an overall poor prognosis due to its immunosuppressive tumor microenvironment (TME). Microglia and tumor-associated macrophages (TAMs) with pro-tumorigenic properties are dominant populations of immune cells in the glioblastoma TME. To date, several studies targeting TAMs to fight tumor progression in different tumor entities have been initiated. However, the impact of standard therapy schemes of glioblastoma cells on macrophage polarization, activation, and phagocytosis remains controversial. The same applies to the relevance of PD-1/PD-L1 blockade in the interaction between macrophages and tumor cells. Our study, therefore, investigated patient-oriented treatment of GLIOBLASTOMA by examining the phagocytic capacity of polarized M1- and M2-like macrophages using GL261-luc2 tumor cells as a preclinical model system. Additionally, we analyzed the expression of activation and immune checkpoint markers on these macrophage subtypes following contact with tumor cells and their microenvironment. These factors were also determined after PD-1 blockade was initiated. The analyses revealed that the immunoregulatory M2-like macrophages generally exhibited a higher phagocytosis rate than the pro-inflammatory M1-like macrophages; however, this was not influenced by the pretreatment of glioblastoma cells with chemo- or radiotherapy. This could not be improved by blocking the PD-1 receptor. Furthermore, there were no modulations in the expression of differentiation, activation, or immune checkpoint molecules of M1- and M2-like macrophages after cell-to-cell contact with glioblastoma cells. But the medium conditioned by tumor cells strongly altered M1-like macrophages toward a more activated state, whereas M2-like cells were only mildly influenced. This was further enhanced by tumor cell treatment, with the most prominent effect after irradiation. These results suggest that conventional GLIOBLASTOMA tumor cell treatment affects the immunogenic status of macrophage subtypes, which is relevant for enhancing the anti-tumor immune response in brain tumors. Full article

Background and Aim: Glioblastoma (GBM) is the most aggressive primary brain tumor in adults, with poor prognosis despite maximal surgical resection, radiotherapy (RT), and temozolomide (TMZ) per the Stupp protocol. IDH-wild-type GBM, the predominant molecular subtype, frequently harbors EGFR amplification and is resistant to therapy, while MGMT promoter methylation predicts improved TMZ response. This study aimed to assess the prognostic impact of EGFR and MGMT status on survival and recurrence patterns in IDH-wild-type GBM. Materials and Methods: We retrospectively analyzed 218 patients with IDH-wild-type GBM treated at the Azienda Ospedaliero-Universitaria Senese (2016–2024). All patients underwent maximal safe surgical resection whenever feasible. The cohort includes patients who received gross total resection (GTR), subtotal resection (STR), or biopsy only, depending on tumor location and clinical condition, followed by intensity-modulated RT (59.4–60 Gy) with concurrent and adjuvant TMZ. EGFR amplification was assessed via FISH/NGS and immunohistochemistry; MGMT promoter methylation was determined using methylation-specific PCR. Progression-free survival (PFS), overall survival (OS), and recurrence patterns (in-field, marginal, out-field) were evaluated using Kaplan–Meier, Cox regression, and logistic regression analyses. Results: Among patients (64.7% male; mean age 61.8), 58.7% had EGFR amplification and 49.1% showed MGMT methylation. Median OS and PFS were 14 and 8 months, respectively. EGFR non-amplified/MGMT methylated tumors had the best outcomes (OS: 22.0 months, PFS: 10.5 months), while EGFR-amplified/MGMT unmethylated tumors fared worst (OS: 10.0 months, PFS: 5.0 months; p < 0.001). MGMT methylation was an independent positive prognostic factor (HR: 0.48, p < 0.001), while EGFR amplification predicted worse survival (HR: 1.57, p = 0.02) and higher marginal recurrence (OR: 2.42, p = 0.01). Conclusions: EGFR amplification and MGMT methylation significantly influence survival and recurrence dynamics in IDH-wild-type GBM. Incorporating these biomarkers into treatment planning may enable tailored therapeutic strategies, potentially improving outcomes in this challenging disease. Prospective studies are needed to validate biomolecularly guided management approaches. Full article