Search Results (1,492)

Glioblastoma multiforme (GBM) is characterized by aggressive growth, extensive vascularization, high metabolic malleability, and a striking capacity for therapy resistance. Current treatments involve surgical resection and concomitant radiation therapy and chemotherapy, prolonging survival times marginally due to the therapy resistance that is built up by the tumor cells. A growing body of research has identified exosomes as critical enablers of therapy resistance. These nanoscale vesicles enable GBM cells to disseminate oncogenic proteins, nucleic acids, and lipids that collectively promote angiogenesis, maintain autophagy under metabolic pressure, and suppress apoptosis. As interest grows in targeting tumor communication networks, exosome-based therapeutic strategies have emerged as promising avenues for improving therapeutic outcomes in GBM. This review integrates current insights into two complementary therapeutic strategies: inhibiting exosome biogenesis and secretion, and engineering exosomes as precision vehicles for the delivery of anti-tumor molecular cargo. Key molecular regulators of exosome formation—including the endosomal sorting complex required for transport (ESCRT) machinery, tumor susceptibility gene 101 (TSG101) protein, ceramide-driven pathways, and Rab GTPases—govern the sorting and release of factors that enhance GBM survival. Targeting these pathways through pharmacological or genetic means has shown promise in suppressing angiogenic signaling, disrupting autophagic flux via modulation of autophagy-related gene (ATG) proteins, and sensitizing tumor cells to apoptosis by destabilizing mitochondria and associated survival networks. In parallel, advances in exosome engineering—encompassing siRNA loading, miRNA enrichment, and small-molecule drug packaging—offer new routes for delivering therapeutic agents across the blood–brain barrier with high cellular specificity. Engineered exosomes carrying anti-angiogenic, autophagy-inhibiting, or pro-apoptotic molecules can reprogram the tumor microenvironment and activate both the intrinsic mitochondrial and extrinsic ligand-mediated apoptotic pathways. Collectively, current evidence underscores the potential of strategically modulating endogenous exosome biogenesis and harnessing exogenous engineered therapeutic exosomes to interrupt the angiogenic and autophagic circuits that underpin therapy resistance, ultimately leading to the induction of apoptotic cell death in GBM. Full article

Background and Objectives: Glioblastoma (GBM) is the most aggressive primary tumor of the central nervous system, characterized by high invasiveness and poor prognosis. Inflammation in the tumor microenvironment, including the presence of immunosuppressive M2-macrophages (CD163+), plays a key role in disease progression. The aim of this study was to evaluate serum levels of interleukin-22 (IL-22) in Bulgarian patients with GBM and to analyze its diagnostic role, its relationship with systemic inflammatory markers (NLR), metabolic parameters, and the infiltration of CD163+ cells. Materials and Methods: The study included 41 newly diagnosed patients with GBM and 46 healthy controls. Serum IL-22 levels were measured by ELISA, and the density of CD163+ cells in the tumor tissue was analyzed immunohistochemically. Statistical analysis included Mann–Whitney test, ROC analysis, binary logistic regression, and Kaplan–Meier survival analysis. Results: GBM patients showed significantly higher levels of IL-22 compared to healthy controls (p = 0.001). ROC analysis demonstrated moderate diagnostic ability of IL-22 (AUC = 0.713), with high levels being a potential risk factor for the disease (OR= 2.51). A weak inverse correlation was found between IL-22 and neutrophil-to-lymphocyte ratio (NLR) (p = 0.048). Although IL-22 levels alone did not affect overall survival, patients with high levels of the cytokine and dense stromal infiltration of CD163+ macrophages tended to have shorter overall survival (p = 0.080). Conclusions: IL-22 is a potential diagnostic biomarker, probably reflecting the systemic inflammatory response in GBM. Its prognostic value might be contextually dependent on the tumor microenvironment, as high levels of IL-22 in combination with immunosuppressive macrophages may contribute to a more aggressive course of the disease. Full article

Glioblastoma (GBM) shows extensive epigenetic heterogeneity. In IDH-wildtype (IDH-WT) GBM, promoter DNA methylation may regulate lineage programs influencing tumor evolution and prognosis; here, we systematically profiled promoter-level methylation dynamics across longitudinal tumors. Genome-wide DNA methylation data were obtained from the publicly available Gene Expression Omnibus (GEO; GSE279073) dataset, comprising a longitudinal cohort of 226 IDH-wildtype glioblastomas profiled on the Illumina Infinium EPIC 850K array across primary and recurrent stages at the University of California, San Francisco. From 333 Gene Ontology gliogenesis-annotated genes (GO:0042063), a 48-gene promoter panel was derived, with ≥2 probes per gene. Promoter methylation was summarized as the median β-value and tested using one-sample Wilcoxon with FDR correction. Functional enrichment, longitudinal variation, and patient-level methylation burden were assessed. Validation analyses were performed using independent IDH-wildtype GBM datasets from The Cancer Genome Atlas (RNA-seq and 450K methylation; n = 347). Promoter hypomethylation predominated across all stages, with 25 genes consistently hypomethylated and 7 hypermethylated. Functional enrichment highlighted gliogenesis, glial cell differentiation, neurogenesis, and Notch-related signaling. In TCGA, promoter methylation inversely correlated with expression for 11 of 33 genes (FDR < 0.05). An Expression Score contrasting hypomethylated and hypermethylated genes was positively associated with improved overall survival, where higher scores predicted better outcome (HR = 0.87, p = 0.016; Q4 vs. Q1 HR = 0.68, p = 0.025), and a complementary Methylation Score showed that higher promoter hypermethylation predicted poorer outcome (HR = 1.73, p < 0.001). CNTN2 and TSPAN2 were adverse prognostic genes (FDR < 0.05). The Expression Score was highest in Proneural tumors and lowest in Mesenchymal tumors (p < 0.001), reflecting a proneural-like state associated with better prognosis. Promoter methylation within gliogenesis genes defines a stable yet prognostically informative epigenetic signature in IDH-WT GBM. Hypomethylation promotes transcriptional activation and a favorable outcome, whereas hypermethylation represses lineage programs and predicts poorer survival. Full article

Cachexia is a muscle-wasting syndrome that has a 50% overall prevalence across all cancers and is known to affect both survival and quality of life. However, its measurement, classification, and impact in individuals with primary brain tumors is unclear. Now, evidence is emerging that cachexia has a direct effect on both clinical and physical function outcomes for individuals with glioblastoma multiforme (GBM). Herein, we outline a standardized approach to the diagnosis of cachexia in the GBM population, incorporating several available clinical tools to ensure the link between clinical prognosis and quality of life. Full article

Glioblastoma multiforme (GBM) is the most aggressive primary brain cancer (with a median survival time of 14.5 months), characterized by heterogeneity. Identifying prognostic molecular subtypes could provide a deeper exposition of GBM biology with potential therapeutic implications. In this study, we classified GBM into two prognostic subtypes, C1-GBM (n = 57; OS: 313 days) and C2-GBM (n = 109; OS: 452 days), using pathway-based signatures derived from RNA-seq data. Unsupervised consensus clustering revealed that only binary classification (cluster number, CN = 2; mean cluster consensus score = 0.84) demonstrated statistically prognostic differences. We characterized C1 and C2 based on oncogenic pathway and immune signatures. Specifically, C1-GBM was categorized as an immune-infiltrated “hot” tumor, with high infiltration of immune cells, particularly macrophages and CD4⁺ T cells, while C2-GBM as an “inherent driving” subtype, showing elevated activity in G2/M checkpoint genes. To predict the C1 or C2 classification and explore therapeutic interventions, we developed a neural network model. By using Weighted Correlation Network Analysis (WGCNA), we obtained the gene co-expression module based on both gene expression pattern and distribution among patients in TCGA dataset (n = 166) and identified nine hub genes as potentially prognostic biomarkers for the neural network. The model showed strong accuracy in predicting C1/C2 classification and prognosis, validated by the external CGGA-GBM dataset (n = 85). Based on the classification of the BP neural network model, we constructed a Cox nomogram prognostic prediction model for the TCGA-GBM dataset. We predicted potential therapeutic small molecular drugs by targeting subtype-specific oncogenic pathways and validated drug sensitivity (C1-GBM: Methotrexate and Cisplatin; C2-GBM: Cytarabine) by assessing IC₅₀ values against GBM cell lines (divided into C1/C2 subtypes based on the nine hub genes) from the Genomics of Drug Sensitivity in Cancer database. This study introduces a pathway-based prognostic molecular classification of GBM with “hot” (C1-GBM) and “inherent driving” (C2-GBM) tumor subtypes, providing a prediction model based on hub biomarkers and potential therapeutic targets for treatments. Full article

Metastasis is still the leading cause of cancer-related death. It happens when disseminated tumor cells (DTCs) successfully navigate a series of steps and adapt to the unique conditions of distant organs. In this review, key molecular and immune mechanisms that shape metastatic spread, long-term survival, and eventual outgrowth are examined, with a focus on how tumor-intrinsic programs interact with extracellular matrix (ECM) remodeling, angiogenesis, and immune regulation. Gene networks that sustain tumor-cell plasticity and invasion are described, including EMT-linked transcription factors such as SNAIL and TWIST, as well as broader transcriptional regulators like SP1. Also, how epigenetic mechanisms, such as EZH2 activity, DNA methylation, chromatin remodeling, and noncoding RNAs, lock in pro-metastatic states and support adaptation under therapeutic pressure. Finally, proteases and matrix-modifying enzymes that physically and biochemically reshape tissues, including MMPs, uPA, cathepsins, LOX/LOXL2, and heparinase, are discussed for their roles in releasing stored growth signals and building permissive niches that enable seeding and colonization. In parallel, immune-evasion strategies that protect circulating and newly seeded tumor cells are discussed, including platelet-mediated shielding, suppressive myeloid populations, checkpoint signaling, and stromal barriers that exclude effector lymphocytes. A major focus is metastatic dormancy, cellular, angiogenic, and immune-mediated, framed as a reversible survival state regulated by stress signaling, adhesion cues, metabolic rewiring, and niche constraints, and as a key determinant of late relapse. Tumor-specific metastatic programs across mesenchymal malignancies (osteosarcoma, chondrosarcoma, and liposarcoma) and selected high-burden cancers (melanoma, hepatocellular carcinoma, glioblastoma, and breast cancer) are highlighted, emphasizing shared principles and divergent organotropisms. Emerging therapeutic strategies that target both the “seed” and the “soil” are also discussed, including immunotherapy combinations, stromal/ECM normalization, chemokine-axis inhibition, epigenetic reprogramming, and liquid-biopsy-enabled minimal residual disease monitoring, to prevent reactivation and improve durable control of metastatic disease. Full article

Background: The prognostic relevance of surgical timing at glioblastoma recurrence remains uncertain, and definitions of early versus delayed reoperation vary widely. Whether earlier surgery provides meaningful survival or functional benefit has not been clearly established. Methods: Databases including PubMed, Embase, Scopus, and Web of Science were searched from inception to May 2025. Eighteen observational studies met the inclusion criteria, fourteen of which provided extractable hazard ratios for survival. The primary outcome was overall survival after reoperation; secondary outcomes included functional status (ΔKPS or discharge home) and major postoperative complications. Random-effects models with Hartung–Knapp adjustment were used, with subgroup analyses stratified by KPS, extent of resection, and eloquence. Results: Across 2267 reoperated patients from 14 survival studies, earlier reoperation was associated with significantly longer survival (pooled HR 0.86; 95% CI 0.78–0.95). Subgroup analyses showed stronger effects in patients with KPS ≥ 70 (HR 0.81; 95% CI 0.72–0.92), non-eloquent tumors (HR 0.84; 95% CI 0.75–0.94), and near-total/gross-total resection (HR 0.79; 95% CI 0.68–0.93). Functional outcomes were pooled from 9 studies (n = 1182), demonstrating higher odds of postoperative stability or improvement with early surgery (OR 1.28; 95% CI 1.12–1.46). Major complications were reported in 9 studies (n = 1344) and did not differ between groups (OR 0.98; 95% CI 0.81–1.19). Sensitivity analyses and influence diagnostics showed consistent effect estimates and no undue single-study influence. Conclusions: Earlier reoperation for recurrent glioblastoma is associated with improved survival and better functional outcomes without increased morbidity in appropriately selected patients. Surgical timing should be incorporated into multidisciplinary planning. Prospective studies with standardized timing definitions and time-dependent modeling are needed to validate these findings. Full article

Glioblastoma, isocitrate dehydrogenase (IDH1/2) wild-type (IDH-wildtype), is one of the most aggressive and malignant tumors of the central nervous system, characterized by rapid growth, pronounced cellular heterogeneity, and an exceptionally poor prognosis. The median survival time for patients with glioblastoma, IDH-wildtype, is approximately 15 months after diagnosis, and current multimodal treatment strategies remain largely ineffective. This review focuses on contemporary pharmacotherapeutic approaches used in the management of glioblastoma, IDH-wildtype, including temozolomide-based chemotherapy, corticosteroids for edema control, and antiangiogenic therapy in recurrent disease, with particular emphasis on their clinical efficacy and limitations. In addition, the review discusses emerging targeted therapeutic strategies developed for IDH-mutant diffuse gliomas, which represent a biologically distinct disease entity. Particular attention is given to ivosidenib, a selective inhibitor of mutant IDH1, currently evaluated for the treatment of astrocytoma, IDH-mutant, grade 4. Its epigenetic mechanism of action, involving inhibition of the oncometabolite 2-hydroxyglutarate (2-HG), is outlined, along with preliminary clinical evidence suggesting potential to delay disease progression. Finally, innovative drug-delivery technologies designed to overcome the blood–brain barrier are briefly discussed as complementary strategies that may enhance the efficacy of both conventional and targeted therapies. Overall, future advances in the treatment of diffuse gliomas will likely depend on the integration of molecularly targeted agents, predictive biomarkers, and advanced delivery platforms aimed at improving patient survival and quality of life. Full article

Glioblastoma (GBM) is the most prevalent and devastating form of primary brain tumors in adults, with dismal survival despite advancements in treatment modalities. The current study sought to develop clinically significant prognostic models for GBM patients by comprehensively profiling MGMT, NUPR1, NDRG2, and GLI1 gene promoter methylation in GBM tissues vs. non-neurooncological disease (NND) and their association with clinical characteristics and therapeutic outcome. This was further evaluated by in silico functional enrichment analysis. NUPR1, NDRG2, and GLI1 gene promoter methylation were significant epigenetic discriminators between GBM and NND. However, NDRG2 methylation was the sole independent predictor for neoplastic lesions (OR = 1.71, 95% CI [1.25–3.57], p = 0.028). Multivariable Cox regression analysis revealed that NUPR1 promoter hypermethylation was significantly correlated with a lower risk of mortality (HR = 0.96, 95% CI [0.96–0.99], p = 0.002), while multiple tumor sites were linked to an increased risk of mortality in the univariate model (HR = 4.44, 95% CI [1.42–13.88], p = 0.01). A heatmap correlation matrix identified a robust positive correlation among the MGMT and NUPR1 methylation status (r = 0.93, p < 0.001). NUPR1 and MGMT promoter hypermethylation was associated with a favorable response to temozolomide therapy. Patients with NUPR1 and MGMT hypermethylation exhibited extended OS and PFS compared to those with hypomethylation levels, whereas GLI1 and NDRG2 hypermethylation were linked to shorter PFS. In conclusion, the multi-faceted epigenetic panel adopted in the current study captures different aspects of GBM biology and moves towards a more comprehensive model that reflects the molecular heterogeneity of GBM as insights for personalized therapy. Full article

Background: Glioblastoma multiforme (GBM), the most aggressive primary brain malignancy in adults, is associated with poor prognosis and recurrence despite standard of care and newer immunotherapies. This warrants exploration of synergistic approaches such as combination immunotherapy for improved tumor control. Methods: We initiated a systematic review of articles from 2015–2025 in PubMed, Embase, Scopus, Cochrane, and Web of Science if they assessed immunotherapy for GBM. Results: We included 49 studies (n = 3002 patients) with no significant demographic differences across publications. Combination immunotherapy regimens demonstrated higher pooled ORRs in limited comparative analyses, though findings were driven by a small number of studies. Single-arm analysis for overall survival (OS), progression-free survival (PFS), treatment-related adverse events (TRAEs), and ORR showed no significant differences among the groups. However, treatment–control arm analysis showed pooled ORs of 9.51 for combination immunotherapies and 0.44 in the control group. Conclusions: Combining immunotherapeutics across mechanisms may potentiate immune response effectiveness against GBM. Full article

Brain tumors, particularly glioblastoma, remain among the most lethal cancers, with limited survival benefits from current genetic and molecular-targeted approaches. Emerging evidence reveals that beyond oncogenes and mutations, neuronal plasticity, long-term potentiation, synaptic remodeling, and neurotransmitter-driven signaling play a pivotal role in shaping tumor progression and therapeutic response. This convergence of neuroscience and oncology has given rise to the field of cancer neuroscience, which explores the bidirectional interactions between neurons and malignant cells. In this review, we summarize fundamental principles of neuronal plasticity, contrasting physiological roles with pathological reprogramming in brain tumors. We highlight how tumor cells exploit synaptic input, particularly glutamatergic signaling, to enhance proliferation, invasion, and integration into neural circuits. We further discuss how neuronal-driven feedback loops contribute to therapy resistance, including chemoresistance, radioresistance, and immune evasion, mediated through pathways such as mitogen-activated protein kinase (MAPK), phosphoinositide 3-kinase/protein kinase B (PI3K/AKT), and calcium influx. The tumor microenvironment, including astrocytes, microglia, and oligodendrocyte-lineage cells, emerges as an active participant in reinforcing this neuron-tumor ecosystem. Finally, this review explores therapeutic opportunities targeting neuronal plasticity, spanning pharmacological interventions, neuromodulation approaches (transcranial magnetic stimulation (TMS), deep brain stimulation (DBS), optogenetics), and computational/artificial intelligence frameworks that model neuron tumor networks to predict personalized therapy. Also, we propose future directions integrating connect omics, neuroinformatics, and brain organoid models to refine translational strategies. Full article

Background: Glioblastoma (GB) carries a dismal prognosis, with survival outcomes particularly poor in older patients. With the fastest-growing global demographic being those aged over 65, the incidence of GB is expected to rise. Objective: To evaluate predictors of survival in patients aged ≥70 years with histologically confirmed GB, focusing on surgical resection, adjuvant therapy, and comorbidities. Methods: A retrospective review was performed of all patients aged ≥70 undergoing index surgery for GB between January 2021 and March 2025 at a single tertiary neurosurgical centre. Demographics, pre-operative fitness scores (Karnofsky Performance Status [KPS]., Charlson Comorbidity Index [CCI].), tumour characteristics, extent of resection, adjuvant treatment, and survival were analysed. Tumour volume was estimated using the ABC/2 method. Survival outcomes were assessed using Kaplan–Meier curves and multivariable Cox proportional hazards regression. Results: A total of 124 patients aged ≥70 years (median 74 years, range 70–86) were included. Median overall survival was 8 months (IQR 4–15). On multivariable analysis, adjuvant chemoradiotherapy (HR = 0.30, 95% CI 0.17–0.52; p < 0.001) and gross total resection (GTR) (HR = 0.41, 95% CI 0.20–0.86; p = 0.019) were independently associated with improved survival. Smoking history was associated with increased hazard of death (HR = 2.02, 95% CI 1.07–3.81; p = 0.029), an effect robust to multiple sensitivity analyses. No significant associations were found for age, pre-operative KPS, comorbidity index, tumour volume, or methylation status (all p > 0.10). Tests for non-proportional hazards indicated that the survival benefit of adjuvant therapy diminished over time (interaction p = 0.0002), with early post-operative benefit (HR ≈ 0.35 at 1 month) that attenuated towards unity by 6–12 months. The effects of GTR and smoking were time-invariant. RMST analysis suggested a modest, non-significant absolute survival advantage of GTR over STR (mean difference = 2.0 months at 18 months; p = 0.11). After exclusion of early post-operative deaths (<6 weeks), adjuvant therapy (HR = 0.34; p < 0.001) and GTR (HR = 0.33; p = 0.005) remained independent predictors of improved survival. Conclusions: Among patients aged ≥70 years with glioblastoma, adjuvant therapy and extent of resection remain key independent predictors of survival, while smoking is associated with poorer outcomes. The survival benefit of adjuvant chemoradiotherapy is strongest in the early post-operative period and diminishes over time, underscoring the importance of early multidisciplinary intervention. These findings highlight that aggressive multimodal treatment may confer survival advantage even in older patients. Full article

The challenges of glioblastoma multiforme treatment are related to limitations in tumor removal surgery, its high heterogeneity and aggressiveness, development of resistance to standard therapy, the blood–brain barrier, and the side and toxic effects of the conventional antitumor agents used in clinical practice. Although new treatment strategies continue to emerge, progress remains slow and has not resulted in substantial improvements in patient survival. The main goal of research in recent years has been aimed at developing ways to deal with all these challenges. One of the ways to improve the control of glioblastomas is the introduction of effective new antitumor agents. Metal complexes represent a particularly promising class of compounds in this context. This is why the aim of this study was to assess the effects of six homo- and heterometallic coordination compounds bearing Schiff base ligands—[Zn₂(Ampy)(µ-OH)(H₂O)₂](ClO₄)₂ (ZnAmpy), [Zn₂(Dmen)(µ-OH)(H₂O)₂](ClO₄)₂ (ZnDmen), ¹_∞[{Zn₂(Ampy)(μ₃-OH)}₂(H₂O){μ-[Au(CN)₂]}](ClO₄)₃·THF·H₂O (ZnAmpyAu), [{Zn₂(Dmen)(μ-OH)}₂{μ-[Au(CN)₂]}{[Au(CN)₂]₂}](ClO₄)·H₂O (ZnDmenAu), ¹_∞[Zn(Salampy){μ-Au(CN)₂}] (ZnSalampyAu), and ¹_∞[Zn(Saldmen)(μ-Au(CN)₂}] (ZnSaldmenAu)—on the viability and proliferation of 8MGBA and U251MG human glioblastoma multiforme cells (HDmen and HAmpy are bicompartmental Schiff base ligands resulting from the condensation of 2,6-diformyl-p-cresol with N,N-dimethylethylenediamine and 2-(aminomethyl)pyridine, respectively, while HSaldmen and HSalampy are tridentate Schiff base ligands obtained via condensation of salicylaldehyde with N,N-dimethylethylenediamine and 2-(aminomethyl)pyridine, respectively). Among these compounds, ZnSaldmenAu is a new compound and is reported here for the first time. Cytotoxicity of the compounds was evaluated through analysis of cell viability, 2D/3D growth, cytopathological alterations, and induction of cell death. The results obtained by methods with different targets in cells and the associated mechanisms of action revealed that the compounds investigated show promising cytotoxic/potential antitumor activity in treated cells. Full article

Background/Objectives: Glioblastoma (GBM) exhibits heterogeneous, nonlinear invasion patterns that challenge conventional modeling and radiomic prediction. Most deep learning approaches describe the morphology but rarely capture the dynamical stability of tumor evolution. We propose an AI framework that approximates a latent attractor landscape of GBM morphodynamics—stable basins in a continuous manifold that are consistent with reproducible morphologic regimes. Methods: Multimodal MRI scans from BraTS 2020 (n = 494) were standardized and embedded with a 3D autoencoder to obtain 128-D latent representations. Unsupervised clustering identified latent basins (“attractors”). A neural ordinary differential equation (neural-ODE) approximated latent dynamics. All dynamics were inferred from cross-sectional population variability rather than longitudinal follow-up, serving as a proof-of-concept approximation of morphologic continuity. Voxel-level perturbation quantified local morphodynamic sensitivity, and proof-of-concept control was explored by adding small inputs to the neural-ODE using both a deterministic controller and a reinforcement learning agent based on soft actor–critic (SAC). Survival analyses (Kaplan–Meier, log-rank, ridge-regularized Cox) assessed associations with outcomes. Results: The learned latent manifold was smooth and clinically organized. Three dominant attractor basins were identified with significant survival stratification (χ² = 31.8, p = 1.3 × 10⁻⁷) in the static model. Dynamic attractor basins derived from neural-ODE endpoints showed modest and non-significant survival differences, confirming that these dynamic labels primarily encode the morphodynamic structure rather than fixed prognostic strata. Dynamic basins inferred from neural-ODE flows were not independently prognostic, indicating that the inferred morphodynamic field captures geometric organization rather than additional clinical risk information. The latent stability index showed a weak but borderline significant negative association with survival (ρ = −0.13 [−0.26, −0.01]; p = 0.0499). In multivariable Cox models, age remained the dominant covariate (HR = 1.30 [1.16–1.45]; p = 5 × 10⁻⁶), with overall C-indices of 0.61–0.64. Voxel-level sensitivity maps highlighted enhancing rims and peri-necrotic interfaces as influential regions. In simulation, deterministic control redirected trajectories toward lower-risk basins (≈57% success; ≈96% terminal distance reduction), while a soft actor–critic (SAC) agent produced smoother trajectories and modest additional reductions in terminal distance, albeit without matching the deterministic controller’s success rate. The learned attractor classes were internally consistent and clinically distinct. Conclusions: Learning a latent attractor landscape links generative AI, dynamical systems theory, and clinical outcomes in GBM. Although limited by the cross-sectional nature of BraTS and modest prognostic gains beyond age, these results provide a mechanistic, controllable framework for tumor morphology in which inferred dynamic attractor-like flows describe latent organization rather than a clinically predictive temporal model, motivating prospective radiogenomic validation and adaptive therapy studies. Full article

Background/Objectives: Combined chromosome 7 gain and chromosome 10 loss (+7/−10) is the most frequent cytogenetic alteration and a defining diagnostic criterion for isocitrate dehydrogenase wild-type (IDHwt) glioblastoma. Despite the association with poor prognosis, its clinical and therapeutic significance remains unclear. We aim to systematically review its clinical significance, focusing on prevalence, prognostic value, and potential association with therapeutic resistance in adult patients. Methods: PubMed, Embase, CENTRAL, Scopus, EBSCOhost, and Web of Science were searched from inception to April 2025, using controlled vocabulary and free-text terms. Eligible studies included adult glioblastoma with molecular confirmation of combined chromosome 7 gain and chromosome 10 loss and reported survival or treatment response. Quality was assessed qualitatively, and findings were synthesized descriptively. Results: Of 3249 records, 5 observational studies (523 patients) were included. The signature was present in 60% to 70% of glioblastoma cases and frequently co-occurred with epidermal growth factor receptor amplification and telomerase reverse transcriptase promoter mutations. This alteration was consistently associated with shorter survival (mean, 8–70 weeks) compared with tumors lacking the alteration (19–170 weeks). In one study, the signature was more common in radioresistant tumors (9/20 vs. 1/10). Molecular evidence suggests that this alteration arises early in tumorigenesis. Conclusions: The +7/−10 cytogenetic alteration, common in glioblastoma, is frequently associated with aggressive clinical behavior. While exploratory data suggest a possible association with radiotherapy response, current evidence is insufficient to establish a predictive or therapeutic role. Its principal clinical value lies in diagnosis, molecular classification, and risk stratification. Incorporating cytogenetic testing for this alteration into routine glioblastoma workup may improve risk stratification and guide individualized management. Full article