Search Results (197)

Neuroinflammation within the tumor microenvironment (TME) of central nervous system (CNS) neoplasms, particularly glioblastoma (GBM), is no longer viewed merely as a reactive phenomenon but rather as a major driver of gliomagenesis and malignant transformation. This process involves a shift from acute immune activation to a chronic, sterile state that reshapes the CNS borders and immune niches to favor tumor evasion. This narrative review provides a comprehensive mechanistically focused analysis of the mechanisms governing the inflammatory stroma in primary and metastatic brain neoplasms. It critically examines the ontogeny and transcriptomic profile of myeloid and glial populations, dismantling the binary M1/M2 polarization model in favor of a continuum of functional states determined by metabolic and oxygenation gradients. It also analyzes intracellular signaling cascades, the subversion of innate immunity sensors such as the cGAS-STING pathway, the epigenetic reprogramming of stromal cells, and the role of extracellular vesicles. The electrochemical integration of tumor cells into neuronal circuits via glutamatergic synapses and connexin 43 gap junction coupling is addressed in detail, defining the mitogenic impact of neuronal activity on the tumor. The inflammatory profiles of IDH-wildtype and IDH-mutant gliomas and of secondary brain metastases are contrasted. Finally, the correlates of functional neuroimaging, liquid biopsies, and resistance mechanisms to conventional therapies are analyzed, including the GIANT and SENIPERA clinical trials, CARv3-TEAM-E bivalent cellular immunotherapy preconditioned with the LDC + R regimen, and the accelerated approval of dordaviprone (Modeyso) in H3 K27M-mutant diffuse midline gliomas. Full article

Objective: The glioma prognostic literature contains a large number of transcriptomic risk signatures, yet whether these signatures add measurable information beyond a clinical model containing grade and molecular markers is rarely tested. We pursued three objectives jointly: to evaluate a leakage-controlled signature in terms of both discrimination and calibration; to test it against a clinical reference model and against a null distribution of random signatures; and to quantify the reporting practice of the field. Methods: The CGGA mRNAseq_693 cohort (n = 404, 209 deaths) served as development, the CGGA mRNAseq_325 cohort (n = 222, 138 deaths) as independent internal validation, and the TCGA lower-grade glioma and glioblastoma cohorts (n = 664, 247 deaths) as external validation. A univariate Cox score test was applied to 17,544 genes with false discovery rate control by the Benjamini–Hochberg procedure, and an elastic-net penalised Cox model was fitted on the top 200 candidate genes. Every model-building operation-imputation, scaling, candidate pool, and penalty selection was confined to the development cohort, and the final model was locked. Three arms were compared: clinical only, transcriptomic only, and combined. Calibration was quantified by the integrated calibration index derived from a smoothed calibration curve. In addition, the abstract-level reporting content of 515 glioma signature records indexed in Web of Science was analysed. Results: The signature made no measurable contribution beyond the clinical reference model. In the independent internal validation cohort the clinical model reached a concordance index of 0.800 (95% CI 0.767–0.831) and the signature 0.801 (0.769–0.832); the paired bootstrap difference was indistinguishable from zero (Δ = +0.001; 95% CI −0.032 to +0.035), and restricting the clinical model to variables known at diagnosis did not change this (Δ = +0.008; −0.024 to +0.043). Against a null distribution of 1000 random 20-gene sets drawn from the same candidate pool, the signature exceeded the null internally (p = 0.015) but was indistinguishable from it in external validation (p = 0.154); 99.2% of random sets reached a concordance index above 0.75 and 82.2% above 0.80 in the external cohort. Discrimination fell markedly within the IDH-wildtype (0.629) and WHO grade IV (0.606) strata, and the risk score correlated at 0.722 with a proliferation metagene despite containing no canonical proliferation gene. The concordance indices themselves—0.801 internally and 0.824 externally for the 17-gene subset available in TCGA, with an integrated calibration index of 0.045 at 36 months—are therefore best read as an illustration of the problem rather than as evidence of clinical utility: they sit squarely inside the range that random gene sets reach in the same data, and they fall in the range routinely presented as successful in the published literature. In the literature survey, 8.7% of the 515 records mentioned calibration, 4.5% decision curve analysis, and only 1.0% any comparison against a clinical reference model; none reported all three. Conclusions: A signature developed under a leakage-controlled protocol and well calibrated was nevertheless indistinguishable from the appropriate references on two of the three criteria we propose. Most of its discrimination rests on the IDH and grade axis that a broad range of prognostic gene sets can capture. Concordance indices reported in the glioma signature literature cannot be interpreted without a clinical reference model and a random-signature null distribution. Full article

(1) Background: Modifications to tumor classifications could fundamentally alter the foundation of research approaches. A concrete illustration of this issue is the actual WHO classification of tumors of the central nervous system, published in 2021. According to the WHO classification, GBM is an IDH wild-type tumor. However, some multi-omics databases retain the classification from the time the samples for the datasets were collected, prior to the WHO 2021 classification, including IDH mutant GBMs. We were interested in assessing the number of papers published in the biomedical literature from 2022 to 2025 that are based on these databases, to ensure the correct implementation of the WHO 2021 classification of GBM. (2) Methods: We systematically reviewed publications in the biomedical literature from 2022 to 2025 that utilized the two most widely used multi-omics databases in the glioma research field, the CGGA and TCGA databases, to assess the correct application of the classification of GBM. (3) Results: We identified 269 publications, but only 45 (14%) correctly included only IDH wild-type GBM; 83 (33%) also contained IDH mutant tumors; and 141 (53%) provided no information about the IDH status of their research material. (4) Conclusions: Using a systematic search strategy, we found that 1/3 of published papers used IDH mutant tumors, and 1/2 of the studies did not report the IDH status of the tumors. Full article

Glutamate dehydrogenase (GLUD1) links glutamine metabolism and redox regulation, yet its prognostic and functional relevance across different glioma subtypes warrants further study. Here, we show that GLUD1 expression was inversely associated with tumor grade and positively associated with survival across glioma subtypes, a relationship not fully recapitulated by broader glutaminolysis-related gene signatures. To investigate the consequences of GLUD1 inhibition, we treated endogenous IDH-mutant and IDH-wildtype glioma cell lines with the reported GLUD1 inhibitor R162. GLUD1 inhibition reduced viability in all cell lines tested. This effect was not rescued by α-ketoglutarate (α-KG) supplementation, indicating that impaired tricarboxylic acid (TCA) cycle anaplerosis was not the primary mechanism underlying GLUD1 dependency. Instead, GLUD1 inhibition caused intracellular glutamate accumulation, increased reactive oxygen species (ROS), γ-H2AX induction, and elevated intracellular calcium, while complementary in silico analyses predicted disruption of mitochondrial membrane potential following R162 exposure. Together, these findings indicate that GLUD1 inhibition induces metabolic and redox stress associated with disrupted glutamate and calcium homeostasis and DNA damage. Our findings distinguish the favorable prognostic value of GLUD1 expression from the cellular vulnerability revealed by its inhibition, supporting further investigations of GLUD1 as both a prognostic biomarker and potential therapeutic target in glioma. Full article

Background/Objectives: Neurological impairment after glioma resection is a common postoperative event, but many deficits improve during recovery. The present study investigated whether transient and persistent postoperative neurological deficits differ in their association with overall survival (OS) and progression-free survival (PFS). Methods: We retrospectively reviewed data from patients who underwent initial surgical treatment for glioma in our institution. Neurological function was evaluated using documented clinical examinations performed before surgery, in the immediate postoperative period, and during routine follow-up 3–6 months after the procedure. Results: The study cohort comprised 496 patients, of whom 44.4% were women. The mean age at surgery was 60 years (95% CI, 58–61), and the average follow-up period was 21 months (95% CI, 19–23). According to the 2021 WHO classification, 80.0% of tumors were grade 4, 11.1% were grade 3, and 7.3% were grade 2. IDH mutations were absent in 81% of cases. Median survival for the entire cohort was 34 months (95% CI, 30–38). Preoperative neurological deficits, including hemiparesis, were not significantly associated with OS. Postoperative deficits that were resolved by the follow-up assessment showed no relationship with either OS or PFS, irrespective of IDH mutation status. In contrast, neurological deficits that persisted at follow-up were independently associated with shorter OS and PFS among patients with IDH-wild-type gliomas (p < 0.001), whereas no significant association was observed in the IDH-mutant subgroup. Similarly, when new neurological deficits were present at follow-up, poorer OS and PFS were predicted only in patients with IDH-wild-type tumors (p < 0.001). Conclusions: Temporary neurological deterioration following glioma surgery does not appear to adversely influence overall or progression-free survival, regardless of IDH status. However, persistent postoperative deficits, as well as newly acquired deficits that remain evident during follow-up, are strong indicators of an unfavorable prognosis in patients with IDH-wild-type gliomas. Full article

Background: Glutamatergic neuron-to-glioma signaling mediated by α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs) has emerged as an important mechanism in glioma progression. Objectives/Methods: We analyzed the expression of the AMPAR subunit genes GRIA1, GRIA2, GRIA3, and GRIA4 in lower-grade glioma (LGG). Results: Expression of GRIA1–GRIA4 was highest in IDH-mutant/1p19q-codeleted tumors and lowest in IDH-wildtype tumors across both The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) cohorts. High expression of each GRIA gene was associated with longer overall survival (OS). Transcriptome-wide analyses identified positive correlations between an AMPAR score and genes involved in synaptic organization, neuronal connectivity, and neurotransmission. Co-expression analyses demonstrated coordinated expression between GRIA1–GRIA4 and genes encoding AMPAR auxiliary proteins. Gene Ontology (GO) enrichment revealed overrepresentation of synaptic signaling, trans-synaptic communication, and synapse organization. Although the AMPAR score was associated with favorable survival in univariate analyses, it did not retain independent prognostic significance after adjustment for key clinicomolecular variables. Elevated expression of AMPAR subunit genes in LGG was associated with favorable molecular subtypes and a synaptic transcriptional program. Conclusions: These findings suggest that GRIA1–GRIA4 expression is associated with a synaptically enriched transcriptional program in LGG, although its cellular origin remains uncertain. Full article

Postoperative radiotherapy (RT) improves survival in glioblastoma, and its role in standard management is not disputed. The randomized trials establishing this benefit, however, were conducted before computed tomography, magnetic resonance imaging (MRI), molecular classification, and temozolomide (TMZ), in heterogeneous populations of “operated malignant glioma” treated with whole-brain or large-field RT versus best supportive care. Their pooled survival benefit (risk ratio 0.81; 95% CI 0.74–0.88) robustly answers the historical question they were designed to address. Since then, advances in surgery, imaging, molecular diagnostics, and systemic therapy have created a modern best-prognosis subgroup—young patients with excellent performance status, MRI-confirmed complete or supramaximal resection of an IDH-wildtype glioblastoma, and median survival approaching or exceeding three years—for whom no clearly defined historical counterpart exists. This perspective provides a structured appraisal of the directness of the landmark randomized evidence using GRADE concepts and translates that appraisal into a graded roadmap for future de-escalation trial designs. Across population, intervention, comparator, and outcomes, the historical trials exhibit substantial indirectness, while the only randomized RT-versus-no-RT evidence from the modern era derives from elderly patients representing the opposite prognostic extreme. This is not an argument against RT. The infiltrative biology of glioblastoma, predominantly in-field recurrence, and radioresistant stem-cell populations strongly support continued benefit. Rather, the unresolved question concerns the magnitude of benefit after maximal contemporary therapy and whether selected de-escalation strategies merit prospective evaluation. Our thesis is one of collective scientific equipoise regarding an unresolved evidence question rather than individual clinician equipoise or refutation of current standard care. Full article

Background/Objectives: ¹⁸F-fluorodeoxyglucose positron emission tomography (FDG PET) reflects glucose metabolism but has limited diagnostic value for gliomas because of its high physiological uptake in the normal brain. This study visualized and characterized patterns of hypometabolism in non-contrast-enhanced gliomas using Z-score analysis and explored its potential for estimating isocitrate dehydrogenase (IDH) status. Methods: We retrospectively analyzed 116 patients with non-contrast-enhanced supratentorial gliomas, classified according to the 2021 World Health Organization classification (26 glioblastomas, IDH-wildtype; 54 astrocytomas, IDH-mutant; and 36 oligodendrogliomas, IDH-mutant and 1p/19q-codeleted). Z-score maps of FDG images were generated using a normal database. Tumor-associated hypometabolic regions (Z < −2) were analyzed, focusing on the proportion of severely hypometabolic regions (Z6–: Z < −6) and sphericity. Results: The mean Z-score differed significantly among the three subtypes, with the highest value observed in glioblastomas and the lowest in astrocytomas (p < 0.001). IDH-mutant gliomas showed a higher proportion of Z6– regions (p < 0.001) and higher sphericity (p = 0.009) than IDH-wildtype gliomas. In multivariable logistic regression, both the proportion of Z6– and sphericity were independent predictors of IDH status. Their combination demonstrated a strong discriminative performance for IDH status (area under the receiver operating characteristic curve = 0.839). On visual assessment, tumors with both small Z6– extent and low sphericity were primarily IDH-wildtype (75%), whereas the absence of both features indicated IDH-mutant status (94.8%). Conclusions: Z-score-based analysis enables the objective visualization and quantification of tumor-associated hypometabolic regions in non-contrast-enhanced gliomas, providing a potentially useful imaging biomarker for estimating IDH status. Full article

Background: Clinical outcomes in isocitrate dehydrogenase (IDH)-wildtype grade 4 diffuse glioma remain highly heterogeneous despite standard multimodal therapy. We evaluated the prognostic significance of pretreatment platelet-to-albumin ratio (PAR) and compared its performance with established inflammatory biomarkers. Methods: This retrospective cohort study included 166 patients with histopathologically confirmed IDH-wildtype grade 4 diffuse glioma treated between 2017 and 2025. Pretreatment PAR, neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), pan-immune inflammation value (PIV), C-reactive protein-to-albumin ratio (CAR), and lactate dehydrogenase-to-albumin ratio (LAR) were evaluated. Discriminative performance was assessed using classical and inverse probability of censoring weighting (IPCW)-adjusted time-dependent receiver operating characteristic (ROC) analyses. Survival outcomes were evaluated using Kaplan–Meier analyses and predefined baseline-adjusted multivariable Cox proportional hazards regression models. Internal validation was performed using 1000 bootstrap resampling iterations. Results: PAR demonstrated the highest discriminative performance for 12-month overall survival (OS), with an area under the curve of 0.853. Using an optimal cutoff value of 79.459, patients with elevated PAR experienced significantly shorter OS (median, 6.2 vs. 16.7 months; p < 0.001) and progression-free survival (PFS) (median, 5.9 vs. 12.3 months; p < 0.001). In baseline-adjusted multivariable analyses, elevated pretreatment PAR remained independently associated with inferior OS (hazard ratio [HR], 3.287; 95% confidence interval [CI], 2.196–4.921; p < 0.001) and PFS (HR, 3.791; 95% CI, 2.501–5.749; p < 0.001). These findings were supported by sensitivity analyses and bootstrap internal validation. Conclusions: Pretreatment PAR was independently associated with survival outcomes and demonstrated favorable discriminative performance relative to other inflammatory biomarkers. PAR may represent an accessible biomarker reflecting tumor–host interactions in IDH-wildtype grade 4 diffuse glioma. The proposed PAR cutoff should be considered exploratory and requires external validation before routine clinical application. Full article

Background/Objectives: Noninvasive determination of glioma molecular profiles is clinically crucial for assessing therapeutic efficacy and predicting disease outcomes. This study aimed to evaluate the potential of morphological magnetic resonance imaging (MRI), diffusion-weighted imaging (DWI), magnetic resonance spectroscopy (MRS), and dynamic contrast-enhanced perfusion-weighted imaging (DCE-PWI) in predicting TP53 gene status and X-linked alpha-thalassemia intellectual disability syndrome (ATRX) gene status in isocitrate dehydrogenase (IDH)-mutant gliomas. Methods: A retrospective analysis was performed on 106 IDH-mutant glioma patients using morphological MRI, DWI, MRS, and DCE-PWI data. Statistical comparisons of imaging parameters across molecular status groups were conducted, and logistic regression models were developed to predict molecular status, with diagnostic performance evaluated by receiver operating characteristic (ROC) curve analysis. Five-fold stratified cross-validation with 1000 bootstrap resamples was employed to assess model generalizability Results: Among 106 IDH-mutant gliomas, the TP53-mutant group showed a greater proportion of tumors with >33% enhancement (p = 0.018), higher Cho/Cr (p < 0.001), and higher Cho/NAA (p = 0.005) than the TP53-wildtype group. Multivariable analysis demonstrated that the Cho/Cr ratio was an independent predictor of TP53 mutation in IDH-mutant gliomas (odds ratio [OR] = 2.037, p = 0.021), with the model achieving an apparent AUC of 0.741. DCE-PWI parameters showed no significant differences across molecular subgroups. Ve was significantly elevated in ATRX-mutant tumors (median 57.16 vs. 30.63, p = 0.029). Ktrans, Kep, Vp, and iAUC showed no significant differences between groups (all p > 0.05). Furthermore, multivariable analysis showed that ADC values (OR = 1.005, p = 0.017) and the Cho/NAA ratio (OR = 3.073, p = 0.023) emerged as independent predictors of ATRX mutation, with the model achieving an apparent AUC of 0.863. Five-fold cross-validation demonstrated that the Cho/Cr model for TP53 prediction achieved a mean AUC of 0.717 ± 0.043 (Bootstrap 95% CI: 0.616–0.814), and the ADC + ChoNAA model for ATRX prediction achieved 0.865 ± 0.124 (95% CI: 0.780–0.953). All predictors remained significant across all five folds. Pooled confusion matrices yielded sensitivities of 0.623 and 0.757, specificities of 0.696 and 0.909, and accuracies of 0.654 and 0.840, respectively. Conclusions: Multimodal MRI techniques (morphological MRI, DWI, MRS, and DCE-PWI) can help predict TP53 and ATRX status without surgery. Higher Cho/Cr and Cho/NAA ratios were independently associated with TP53 mutation, whereas lower ADC and higher Cho/NAA independently predicted ATRX mutation. These findings suggest that a focused imaging protocol may be sufficient for preoperative molecular profiling in this tumor type. Full article

Neuropeptide Y [NPY; encoded by the NPY gene] is a widely expressed 36-amino-acid neuropeptide that regulates neuronal function, vascular regulation, and immune regulation; its role in glioblastoma [GBM] remains incompletely characterized. We performed an integrative in silico multi-scale transcriptomic analysis combining bulk RNA-sequencing of IDH-wildtype GBM [n = 169] and lower-grade glioma [n = 510] surgical resections from TCGA, normal cortical tissue from GTEx [n = 207], and four independent GEO validation cohorts of surgical GBM and non-tumor brain specimens [GSE4290, GSE50161, GSE131928 scRNA-seq of ~20,426 cells from 28 patients, and GSE194329 10X Visium spatial transcriptomics from five patients], along with survival modeling, pathway enrichment, single-cell RNA sequencing, spatial transcriptomics, and cell–cell communication analysis. NPY and its principal receptor, NPY1R, were significantly downregulated in GBM, while genes associated with hypoxia, angiogenesis, invasion, and immune suppression were upregulated. Single-cell analysis showed that NPY-axis transcript expression was elevated in neural progenitor-like populations. In contrast, hypoxia and metabolic programs were concentrated in mesenchymal tumors and stromal compartments, indicating distinct cellular contexts. Spatial analysis revealed a weak and heterogeneous relationship between NPY and hypoxia signatures, with substantial inter-patient variability and no significant global spatial cross-correlation. These findings indicate that loss of NPY signaling is a consistent feature of GBM and is associated with hypoxia-driven tumor states, while the spatial relationship between NPY and hypoxia appears weak, heterogeneous, and patient-specific. Full article

Objective: CDCA8 is frequently overexpressed in malignant tumors and linked to poor prognosis. This study evaluated the prognostic significance of CDCA8 expression in glioma patients using the CGGA and TCGA datasets. Methods: Clinical and expression data of glioma patients from CGGA and TCGA were analyzed. CDCA8 expression was compared across subgroups based on tumor grade (GBM vs. LGG) and IDH mutation status, and meta-analyses were performed to assess inter-database differences. Results: This study included 1125 glioma patients from CGGA and TCGA. CDCA8 expression was higher in TCGA GBM (p < 0.001) but comparable between databases in LGG (p = 0.501). CGGA showed lower CDCA8 in IDH-mutant gliomas (p < 0.001), with no difference in IDH-wildtype cases (p = 0.154). CGGA patients had longer overall survival in all above subgroups. Meta-analysis found no significant prognostic association of CDCA8 in GBM, IDH-wildtype and IDH-mutant gliomas. In LGG, high CDCA8 was significantly linked to reduced adverse events (p < 0.001, OR = 0.22, 95% CI [0.11–0.43]). Conclusion: CDCA8 has grade-dependent prognostic roles in gliomas. Its overexpression correlates with poor prognosis in GBM but favorable outcomes in LGG. Inter-database variations support CDCA8 as a promising prognostic biomarker for LGG, and reflect the influences of regional, therapeutic and genetic factors. Full article

Characterizing the m6A epigenetic landscape is essential for understanding glioma biology, yet transcriptome-wide mapping of these modifications at isoform resolution across specific tumor subtypes has remained limited. Conventional short-read approaches lack the capacity to resolve full-length transcript isoforms or assign m6A modifications to individual transcripts, representing a critical gap in glioma where alternative splicing is pervasive. Methods: We performed direct RNA nanopore sequencing and transcriptome-wide m6A analysis in 14 glioma tumor tissues, including IDH1-mutant astrocytoma, oligodendroglioma, and IDH1 wild-type glioblastoma, enabling isoform-resolved profiling not accessible by conventional short-read approaches. m6A sites were predicted computationally using the m6Anet deep learning framework, which has been independently benchmarked against MeRIP-seq-derived sites, and high-confidence calls were defined at a probability threshold of ≥0.9 and required detection across multiple patients within each subtype. Results: IDH1-mutant gliomas showed a higher overall burden of computationally inferred m6A-modified sites, transcripts, and genes than IDH1 wild-type glioblastoma, along with variation in transcript biotypes, regional distribution of m6A sites, and extent of isoform methylation. Differential methylation analysis identified subtype-specific patterns of m6A localization, many of which were observed without corresponding changes in gene-level expression, indicating that m6A variation represents a post-transcriptional regulatory layer not captured by gene-level analysis alone. Integration of gene expression, isoform usage, and m6A status further identified variation in isoform composition and transcript features between astrocytoma and glioblastoma. Analysis of m6A regulators showed subtype-associated expression patterns among readers, writers, and erasers, and exploratory analyses identified isoform-level associations with survival that were not apparent at the gene level. Conclusions: Overall, these data describe subtype-specific patterns of m6A marking and isoform architecture across glioma tissues, derived from computational inference using direct RNA sequencing in a modestly sized cohort and warrant validation by orthogonal methods in larger studies. These findings are consistent with concurrent independent evidence that isoform-specific m6A deposition is evolutionarily conserved across mammals and that long-read isoform resolution reveals transcript diversity in glioma not captured by gene-level analysis. While cohort size and the absence of orthogonal site-level validation suggest that the data require cautious interpretation, this work provides a hypothesis-generating resource and methodological framework for future mechanistic and translational investigation of the glioma epitranscriptome. Full article

Background/Objectives: Gliomas are among the most aggressive primary brain tumors in adults, characterized by profound molecular heterogeneity and poor response to conventional therapies. Immunotherapy has transformed outcomes in several cancers, yet glioma remains largely refractory, due in part to an immunosuppressive tumor microenvironment. Post-transcriptional regulation of gene expression is increasingly recognized as a key mechanism controlling immune cell function in tumors. Regnase-1, an endoribonuclease regulating the stability of inflammation- and immunity-related mRNAs, is a central modulator of immune responses; however, its role in glioma progression and immune modulation remains poorly understood. This study aimed to evaluate Regnase-1 expression in glioma and investigate its association with tumor grade, prognosis, and immune microenvironment characteristics. Methods: Regnase-1 transcript levels were evaluated by RT-PCR in tumor samples from 40 Moroccan glioma patients and validated using transcriptomic data from The Cancer Genome Atlas (TCGA, n = 672) and the Chinese Glioma Genome Atlas (CGGA, n = 959). Bioinformatic analyses and statistical assessments were performed using established pipelines. Results: Regnase-1 expression was significantly elevated in glioblastoma, IDH-wildtype tumors, and higher tumor grades, correlating with poorer overall survival, and emerging as an independent prognostic factor in the CGGA cohort. High Regnase-1 expression was associated with enrichment of pathways related to angiogenesis, hypoxia, invasion, and immune evasion. Tumors with elevated Regnase-1 showed reduced infiltration of effector immune cells (CD8⁺ T cells, Th1 cells) and increased presence of immunosuppressive populations, including regulatory T cells, myeloid-derived suppressor cells, and M2 macrophages. Single-cell analyses further highlighted exhausted CD8⁺ T cells and regulatory T cells as major populations linked to Regnase-1 expression. Notably, Regnase-1 expression also exhibited strong positive correlations with multiple inhibitory immune checkpoint pathways. Conclusions: Elevated Regnase-1 expression defines an aggressive, immunosuppressive glioma phenotype and is associated with poor prognosis, supporting its potential as a prognostic biomarker and a target for immunomodulatory strategies. Full article

Background: Gliomas are characterized by a high degree of molecular heterogeneity, which impairs the reproducibility of predictive biomarkers derived from bulk-based molecular profiling due to immune/stromal contamination of tumors and the high prevalence of the IDH mutation signature. Methods: In this study, we used MOFA+ to derive intrinsic molecular signatures from transcriptional, methylation, and genomic profiles of a cohort of 667 diffuse gliomas in the Cancer Genome Atlas database. Thereafter, factor scores were derived for two separate Chinese Glioma Genome Atlas batches (Batch 1, n = 325; Batch 2, n = 693) without any retraining on the model. The prognostic independence of identified molecular signatures was assessed using multivariable Cox regression adjusted for IDH mutation status and tumor purity; purity-residualized survival analyses; IDH-stratified Cox regression in each cohort; validation by concordance index against established molecular signatures; and survival extreme profiling. To characterize the biological significance of factor signatures, we projected gene set signatures corresponding to each factor signature onto a single-cell RNA-seq dataset of GBM (GSE131928). Results: MOFA+ identified 12 latent factors, of which a vascular–extracellular matrix (ECM) remodeling axis (Factor 1) explained the highest multi-omics variance (24.9%) and was the strongest independent prognostic factor. In multivariable Cox regression adjusting for IDH status and tumor purity, Factor 1 remained independently prognostic (HR = 1.67, 95% CI 1.27–2.20, p = 0.0002); in a fully-adjusted model additionally including age, WHO grade, MGMT methylation, and 1p/19q codeletion (plus radiotherapy and chemotherapy status in the CGGA cohorts), Factor 1 remained prognostic in both CGGA cohorts (CGGA1: HR = 1.50, p = 3.8 × 10⁻⁵; CGGA2: HR = 1.18, p = 0.003) but lost significance in TCGA (HR = 1.04, p = 0.83), consistent with the cohort-dependent magnitude reported in the IDH-stratified and meta-regression analyses below. Purity-residualized survival analysis showed negligible attenuation of the Factor 1 signal (raw HR = 3.57 vs. residualized HR = 3.72; concordance 96.5%). Within IDH-wildtype gliomas, Factor 1 was significant in both external validation cohorts (CGGA1: HR = 1.64, FDR = 4.6 × 10⁻⁶; CGGA2: HR = 1.20, FDR = 0.02), though the TCGA IDH-wildtype subgroup showed a trend that did not survive FDR correction (FDR = 0.060). All validation was performed without model retraining. Within IDH-mutant gliomas, Factor 1 was strongly prognostic in both CGGA cohorts but was not significant in TCGA (HR = 1.17, FDR = 0.33). These findings should therefore be interpreted as consistent in directionality across cohorts but not uniformly replicated at the FDR-adjusted significance threshold in the TCGA discovery dataset. Concordance index benchmarking on a matched subset (n = 503) showed Factor 1 achieved discrimination comparable to the Mesenchymal signature (C = 0.797 vs. 0.801; ΔC = −0.004) while outperforming four other established classifiers. Factor 1 consistently separated patients with extreme survival phenotypes (OS < 6 vs. >15 months) across all three cohorts (all log-rank p < 0.001). Projection onto a single-cell GBM atlas (GSE131928), supported by inferCNV-based malignant-cell classification, localized the Vascular–ECM program to malignant cells and the Immune–ECM axis to myeloid compartments. Conclusions: The Vascular–ECM axis is a consistent, prognostic program robust to purity adjustment for diffuse gliomas that remains relevant across IDH-defined subgroups in three independent datasets comprising 1685 patients. The Vascular–ECM axis is a reproducible, purity-robust prognostic program in diffuse glioma, with directionally consistent adverse effects across TCGA, CGGA Batch 1, and CGGA Batch 2 (pooled n = 1685). Given the strong co-loading of endothelial, ECM, and myeloid genes observed in the single-cell projection, Factor 1 is best interpreted as a vascular/ECM-associated tumor–microenvironment ecosystem program rather than a malignant-cell-autonomous signature. Its FDR-adjusted significance within IDH-stratified subgroups is cohort-dependent and robust in both CGGA cohorts but attenuated in the TCGA IDH-wildtype (FDR = 0.060) and TCGA IDH-mutant (FDR = 0.33) strata. The pooled signal should therefore be interpreted as evidence of a generalizable biological program rather than a uniformly replicated subgroup-specific biomarker. It is possible to calculate factor scores based on RNA sequencing alone using fixed loadings (Z = XWᵀ), which may have implications for future translational applications. All findings are correlative; a causal role for the Vascular–ECM program in glioma progression, invasion, or therapy resistance remains to be established through functional perturbation experiments. Full article