Search Results (51)

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

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

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

Increasing evidence highlights the role of aberrant circadian rhythm gene expression in glioblastoma (GBM) progression, but the impact of the circadian rhythm gene network on GBM molecular profiles and prognosis remains unclear. A total of 1042 GBM samples from six public datasets, TCGA and CGGA, were analyzed, with GBM samples stratified into three circadian core-gene patterns using unsupervised clustering based on the expression profiles of 17 circadian rhythm genes. The Limma R package identified differentially expressed genes (DEGs) among the three patterns, and a secondary clustering system, termed circadian-related gene pattern, was established based on DEGs. A circadian risk score was constructed using the Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithm, and the efficiency of these patterns and the circadian risk score in distinguishing molecular profiles and predicting prognosis was systematically analyzed. The relationship between the circadian risk score and response to immune or targeted therapy was examined using the GSE78200 and IMvigor210 datasets. The results showed that GBM patients were clustered into three circadian core-gene patterns based on the expression profiles of 17 core circadian genes, with distinct molecular profiles, malignant characteristics, and patient prognoses among the patterns. Thirty-two DEGs among these patterns were identified and termed circadian-related genes, and secondary clustering based on these 32 DEGs classified GBM samples into two circadian-related gene patterns, which also predicted molecular profiles and prognosis. A circadian risk scoring system was established, allowing the calculation of individual risk scores based on the expression of 10 genes, where GBM patients with lower circadian risk scores had prolonged overall survival and less aggressive molecular subtypes, while higher circadian risk scores correlated with better responses to MAPK-targeted therapy. In conclusion, this study established two clustering patterns based on 17 circadian rhythm genes or 32 circadian-related genes, enabling the rapid classification of GBM patients with distinct molecular profiles and prognoses, while the circadian risk scoring system effectively predicted survival, molecular profiles, and therapeutic responses for individual GBM patients, demonstrating that the circadian rhythm gene network can distinguish molecular profiles and prognosis in GBM. Full article

Background/Objectives: D4R antagonists have recently been suggested as potential therapeutic alternatives to the standard treatments of glioblastoma (GBM). In this study, new piperidine-based ligands, analogs of the potent and selective D4R compounds 77-LH-28-1 (7) and its 4-benzyl analog 8, were synthesized and studied to investigate the effects produced by variations in the distances between the pharmacophoric features on the D4R affinity and selectivity. Methods: All the new compounds 9–20 were evaluated for their radioligand binding affinity at D2-like receptor subtypes and the results were rationalized by docking studies and molecular dynamics (MD) simulations. The functional profiles of the most interesting derivatives were assessed at D4R Go and Gi protein and β-arrestin by BRET assay and their potential anticancer activity was determined in GBM cell lines. Results: Radioligand binding results highlighted that the derivatives bearing a terminal butyl chain showed structure–activity relationships different from those with a benzyl terminal. From functional studies performed on the best derivatives 12 and 16, the response profiles of both compounds were more robust in antagonist mode, with derivative 16 showing higher antagonist potency than 12 across all three transducers. Interestingly, 12 and 16 dose-dependently decreased the cell viability of GBM cells, inducing cell death and cell cycle arrest, promoting an increase in ROS production, causing mitochondrial dysfunction, and significantly inhibiting colony formation. Conclusions: The promising biological profiles of 12 and 16 make them new lead candidates that warrant further investigation to gain a better understanding of the mechanism behind their antitumor activity and better evaluate their potential for GBM treatment. Full article

As the most aggressive primary brain tumor, glioblastoma (GBM) is considered incurable due to its molecular heterogeneity and therapy resistance. Identifying key regulatory factors in GBM is critical for developing effective therapeutic strategies. Based on the analysis of TCGA data, we confirmed a robust co-expression and correlation of OLIG1 and OLIG2 in human GBM. However, their roles in the astrocytic GBM subtype remain unclear. In this study, we first establish an astrocytic-featured GBM mouse model by introducing PiggyBac-driven hEGFRvIII plasmids and demonstrate that both OLIG1 and OLIG2 are highly expressed within this context. Next, using CRISPR/Cas9 technology to knockout Olig1/2, we found that astrocyte differentiation markers such as GFAP, SOX9, and HOPX were preserved, but tumor cell proliferation was significantly diminished. Mechanistically, CUT&Tag-seq revealed that OLIG1/2 directly binds to the promoter region of various cyclins (Cdk4, Ccne2, Ccnd3, and Ccnd1), where an enrichment of the active histone marker H3K4me3 was observed, indicating transcriptional activation of the genes. Notably, Olig1/2 knockout did not suppress tumor initiation or migration, suggesting that their primary role is to amplify proliferation rather than to drive tumorigenesis. This study defines Olig1 and Olig2 as master regulators of GBM proliferation through various cyclins, thereby offering a novel therapeutic target. Full article

Glioblastoma (GBM), a devastating brain malignancy, resists conventional therapies due to molecular heterogeneity and the blood–brain barrier’s significant restriction on drug delivery. Cannabinoids like WIN 55,212-2 show promise but are limited by poor solubility and systemic toxicity. To address these challenges, we evaluated styrene–maleic acid (SMA) micellar encapsulation of WIN 55,212-2 (SMA-WIN) against free WIN in epithelial (LN18) and mesenchymal (A172) GBM cell lines, targeting cytotoxicity and receptor modulation (CB1, CB2, TRPV1, PPAR-γ). SMA-WIN exhibited significantly enhanced cytotoxicity, achieving IC50 values of 12.48 µM (LN18) and 16.72 µM (A172) compared to 20.97 µM and 30.9 µM for free WIN, suggesting improved cellular uptake via micellar delivery. In LN18 cells, both formulations upregulated CB1 and CB2, promoting apoptosis. Notably, SMA-WIN uniquely increased PPAR-γ expression by 2.3-fold in A172 cells, revealing a mesenchymal-specific mechanism absent in free WIN, which primarily modulated CB1/CB2. These findings position SMA-WIN as a promising candidate for precision GBM therapy, particularly for resistant mesenchymal subtypes, paving the way for in vivo validation to confirm blood–brain barrier penetration and clinical translation. Full article

Fatty acid binding protein 7 (FABP7) is a multifunctional chaperone involved in lipid metabolism and signaling. It is primarily expressed in astrocytes and neural stem cells (NSCs), as well as their derived malignant glioma cells within the central nervous system. Despite growing evidence for FABP7’s tumor-intrinsic onco-metabolic functions, its mechanistic role in regulating the brain tumor immune microenvironment (TIME) and its impact on prognosis at the molecular level remain incompletely understood. Utilizing combined transcriptome profiling and pan-cancer analysis approaches, we report that FABP7 mediates the expression of multiple onco-immune drivers, collectively impacting tumor immunity and clinical outcomes across brain cancer subtypes. An analysis of a single-cell expression atlas revealed that FABP7 is predominantly expressed in the glial lineage and malignant cell populations in gliomas, with nuclear localization in their parental NSCs. Pathway and gene enrichment analysis of RNA sequencing data from wild-type (WT) and Fabp7-knockout (KO) mouse brains, alongside control (CTL) and FABP7-overexpressing (FABP7 OV) human astrocytes, revealed a more pronounced effect of FABP7 levels on multiple cancer-associated pathways. Notably, genes linked to brain cancer progression and tumor immunity (ENO1, MUC1, COL5A1, and IL11) were significantly downregulated (>2-fold) in KO brain tissue but were upregulated in FABP7 OV astrocytes. Furthermore, an analysis of data from The Cancer Genome Atlas (TCGA) showed robust correlations between the expression of these factors, as well as FABP7, and established glioma oncogenes (EGFR, BRAF, NF1, PDGFRA, IDH1), with stronger associations seen in low-grade glioma (LGG) than in glioblastoma (GBM). TIME profiling also revealed that the expression of FABP7 and the genes that it modulates was significantly associated with prognosis and survival, particularly in LGG patients, by influencing the infiltration of immunosuppressive cell populations within tumors. Overall, our findings suggest that FABP7 acts as an intracellular regulator of pro-tumor immunomodulatory genes, exerting a synergistic effect on the TIME and clinical outcomes in brain cancer subtypes. Full article

Background/Objectives: The intrinsic molecular heterogeneity of glioblastoma (GBM) is one of the main reasons for its resistance to conventional treatment. Mesenchymal GBM niches are associated with hypoxic signatures and a negative influence on patients’ prognosis. To date, competing endogenous RNA (ceRNA) networks have been shown to have a broad impact on the progression of various cancers. In this study, we decided to construct hypoxia-specific microRNA/ messengerRNA (miRNA/mRNA) networks with a putative circular RNA (circRNA) regulatory component using available bioinformatics tools. Methods: For ceRNA network construction, we combined publicly available data deposited in the Gene Expression Omnibus (GEO) and interaction pairs obtained from miRTarBase and circBank; a differential expression analysis of GBM cells was performed with limma and deseq2. For the gene ontology (GO) enrichment analysis, we utilized clusterProfiler; GBM molecular subtype analysis was performed in the Glioma Bio Discovery Portal (Glioma-BioDP). Results: We observed that miR-26b-5p, generally considered a tumor suppressor, was upregulated under hypoxic conditions in U-87 MG cells. Moreover, miR-26b-5p could potentially inhibit TRIB3, a gene associated with tumor proliferation. Protein-protein interaction (PPI) network and GO enrichment analyses identified a hypoxia-specific subcluster enriched in collagen-associated terms, with six genes highly expressed in the mesenchymal glioma group. This subcluster included hsa_circ_0001081/miR-26b-5p-affected COL15A1, a gene downregulated in hypoxic U-87 MG cells yet highly expressed in the mesenchymal GBM subtype. Conclusions: The interplay between miR-26b-5p, COL15A1, and TRIB3 suggests a complex regulatory mechanism that may influence the extracellular matrix composition and the mesenchymal transformation in GBM. However, the precise impact of the hsa_circ_0001081/miR-26b-5p axis on collagen-associated processes in hypoxia-induced GBM cells remains unclear and warrants further investigation. Full article

Congenital heart disease (CHD) represents a spectrum of inborn heart defects influenced by genetic and environmental factors. This study advances the field by analyzing gene expression profiles in 21,034 cardiac fibroblasts, 73,296 cardiomyocytes, and 35,673 endothelial cells, utilizing single-cell level analysis and machine learning techniques. Six CHD conditions: dilated cardiomyopathy (DCM), donor hearts (used as healthy controls), hypertrophic cardiomyopathy (HCM), heart failure with hypoplastic left heart syndrome (HF_HLHS), Neonatal Hypoplastic Left Heart Syndrome (Neo_HLHS), and Tetralogy of Fallot (TOF), were investigated for each cardiac cell type. Each cell sample was represented by 29,266 gene features. These features were first analyzed by six feature-ranking algorithms, resulting in several feature lists. Then, these lists were fed into incremental feature selection, containing two classification algorithms, to extract essential gene features and classification rules and build efficient classifiers. The identified essential genes can be potential CHD markers in different cardiac cell types. For instance, the LASSO identified key genes specific to various heart cell types in CHD subtypes. FOXO3 was found to be up-regulated in cardiac fibroblasts for both Dilated and hypertrophic cardiomyopathy. In cardiomyocytes, distinct genes such as TMTC1, ART3, ARHGAP24, SHROOM3, and XIST were linked to dilated cardiomyopathy, Neo-Hypoplastic Left Heart Syndrome, hypertrophic cardiomyopathy, HF-Hypoplastic Left Heart Syndrome, and Tetralogy of Fallot, respectively. Endothelial cell analysis further revealed COL25A1, NFIB, and KLF7 as significant genes for dilated cardiomyopathy, hypertrophic cardiomyopathy, and Tetralogy of Fallot. LightGBM, Catboost, MCFS, RF, and XGBoost further delineated key genes for specific CHD subtypes, demonstrating the efficacy of machine learning in identifying CHD-specific genes. Additionally, this study developed quantitative rules for representing the gene expression patterns related to CHDs. This research underscores the potential of machine learning in unraveling the molecular complexities of CHD and establishes a foundation for future mechanism-based studies. Full article

The early 2-factor (E2F) family of transcription factors, including E2F1 through 8, plays a critical role in apoptosis, metabolism, proliferation, and angiogenesis within glioblastoma (GBM). However, the specific functions of E2F transcription factors (E2Fs) and their impact on the malignancy of Bevacizumab (BVZ)-responsive GBM subtypes remain unclear. This study used data from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), European Molecular Biology Laboratory’s European Bioinformatics Institute (EMBL-EBI), and Gene Expression Omnibus (GEO) to explore the impact of eight E2F family members on the clinical characteristics of BVZ-responsive GBM subtypes and possible mechanisms of recurrence after BVZ treatment. Using machine learning algorithms, including TreeBagger and deep neural networks, we systematically predicted and validated GBM patient survival terms based on the expression profiles of E2Fs across BVZ-responsive GBM subtypes. Our bioinformatics analyses suggested that a significant increase in E2F8 post-BVZ treatment may enhance the function of angiogenesis and stem cell proliferation, implicating this factor as a candidate mechanism of GBM recurrence after treatment. In addition, BVZ treatment in unresponsive GBM patients may potentially worsen disease progression. These insights underscore that E2F family members play important roles in GBM malignancy and BVZ treatment response, highlighting their potential as prognostic biomarkers, therapeutic targets, and recommending precision BVZ treatment to individual GBM patients. Full article

In the realm of colon carcinoma, significant genetic and epigenetic diversity is observed, underscoring the necessity for tailored prognostic features that can guide personalized therapeutic strategies. In this study, we explored the association between the type 2 bitter taste receptor (TAS2Rs) family-related genes and colon cancer using RNA-sequencing and clinical datasets from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). Our preliminary analysis identified seven TAS2Rs genes associated with survival using univariate Cox regression analysis, all of which were observed to be overexpressed in colon cancer. Subsequently, based on these seven TAS2Rs prognostic genes, two colon cancer molecular subtypes (Cluster A and Cluster B) were defined. These subtypes exhibited distinct prognostic and immune characteristics, with Cluster A characterized by low immune cell infiltration and less favorable outcomes, while Cluster B was associated with high immune cell infiltration and better prognosis. Finally, we developed a robust scoring system using a gradient boosting machine (GBM) approach, integrated with the gene-pairing method, to predict the prognosis of colon cancer patients. This machine learning model could improve our predictive accuracy for colon cancer outcomes, underscoring its value in the precision oncology framework. Full article

Glioblastoma (GBM) is the most common yet uniformly fatal adult brain cancer. Intra-tumoral molecular and cellular heterogeneities are major contributory factors to therapeutic refractoriness and futility in GBM. Molecular heterogeneity is represented through molecular subtype clusters whereby the proneural (PN) subtype is associated with significantly increased long-term survival compared to the highly resistant mesenchymal (MES) subtype. Furthermore, it is universally recognized that a small subset of GBM cells known as GBM stem cells (GSCs) serve as reservoirs for tumor recurrence and progression. The clonal evolution of GSC molecular subtypes in response to therapy drives intra-tumoral heterogeneity and remains a critical determinant of GBM outcomes. In particular, the intra-tumoral MES reprogramming of GSCs using current GBM therapies has emerged as a leading hypothesis for therapeutic refractoriness. Preventing the intra-tumoral divergent evolution of GBM toward the MES subtype via new treatments would dramatically improve long-term survival for GBM patients and have a significant impact on GBM outcomes. In this review, we examine the challenges of the role of MES reprogramming in the malignant clonal evolution of glioblastoma and provide future perspectives for addressing the unmet therapeutic need to overcome resistance in GBM. Full article

Background: Glioblastoma multiforme (GBM) is a highly aggressive brain cancer known for its challenging survival rates; it is characterized by distinct subtypes, such as the proneural and mesenchymal states. The development of targeted therapies is critically dependent on a thorough understanding of these subtypes. Advances in single-cell RNA-sequencing (scRNA-seq) have opened new avenues for identifying subtype-specific gene biomarkers, which are essential for innovative treatments. Methods: This study introduces a genetic optimization algorithm designed to select a precise set of genes that clearly differentiate between the proneural and mesenchymal GBM subtypes. By integrating differential gene expression analysis with gene variability assessments, our dual-criterion strategy ensures the selection of genes that are not only differentially expressed between subtypes but also exhibit consistent variability patterns. This approach enhances the biological relevance of identified biomarkers. We applied this algorithm to scRNA-seq data from GBM samples, focusing on the discovery of subtype-specific gene biomarkers. Results: The application of our genetic optimization algorithm to scRNA-seq data successfully identified significant genes that are closely associated with the fundamental characteristics of GBM. These genes show a strong potential to distinguish between the proneural and mesenchymal subtypes, offering insights into the molecular underpinnings of GBM heterogeneity. Conclusions: This study introduces a novel approach for biomarker discovery in GBM that is potentially applicable to other complex diseases. By leveraging scRNA-seq data, our method contributes to the development of targeted therapies, highlighting the importance of precise biomarker identification in personalized medicine. Full article

Urokinase plasminogen activator receptor (uPAR) encoded by the PLAUR gene is known as a clinical marker for cell invasiveness in glioblastoma multiforme (GBM). It is additionally implicated in various processes, including angiogenesis and inflammation within the tumor microenvironment. However, there has not been a comprehensive study that depicts the overall functions and molecular cooperators of PLAUR with respect to intra-tumoral subtypes of GBM. Using single-cell RNA sequencing data from 37 GBM patients, we identified PLAUR as a marker gene for two distinct subtypes in GBM. One subtype is featured by inflammatory activities and the other subtype is marked by ECM remodeling processes. Using the whole-transcriptome data from single cells, we are able to uncover the molecular cooperators of PLAUR for both subtypes without presuming biological pathways. Two protein networks comprise the molecular context of PLAUR, with each of the two subtypes characterized by a different dominant network. We concluded that targeting PLAUR directly influences the mechanisms represented by these two protein networks, regardless of the subtype of the targeted cell. Full article