Journal of Neuro-Oncology

BackgroundIn an era characterized by rapid progression in neurosurgical technologies, traditional tools such as the non-navigated two-dimensional intraoperative ultrasound (nn-2D-IOUS) risk being overshadowed. Against this backdrop, this study endeavors to provide a comprehensive and rigorous assessment of the clinical efficacy and surgical relevance of nn-2D-IOUS, specifically in the context of glioma resections. MethodsThis retrospective study undertaken at a single center evaluated 99 consecutive, non-selected patients diagnosed with both high-grade and low-grade gliomas. The primary objective was to assess the proficiency of nn-2D-IOUS in generating satisfactory image quality, identifying residual tumor tissue, and its influence on the extent of resection. To validate these results, early postoperative MRI data served as the reference standard. ResultsThe nn-2D-IOUS exhibited a high level of effectiveness, successfully generating good quality images in 79% of the cases evaluated. With a sensitivity rate of 68% and a perfect specificity of 100%, nn-2D-IOUS unequivocally demonstrated its utility in intraoperative tumor detection. Notably, in cases where total tumor removal was the surgical objective, a resection exceeding 95% of the initial tumor volume was achieved in 86% of patients. Additionally, in cases where residual tumor was not detected by nn-2D-IOUS, the mean volume of undetected tumor tissue was remarkably minimal, averaging at 0.29 cm3. ConclusionOur study provides compelling evidence supporting the invaluable role and efficacy of nn-2D-IOUS in glioma surgery. The results underscore the potential of harnessing traditional, cost-effective technologies such as nn-2D-IOUS to achieve enhanced surgical outcomes, even in the face of more advanced alternatives. These insights carry significant implications, particularly for resource-constrained settings, emphasizing the importance of optimizing the use of existing tools to improve patient care in a practical and efficient manner.

IntroductionInteractions between cancer cells and their microenvironment are central to tumor formation. Regional microenvironmental variability in the brain may offer insight into essential factors in tumorigenesis. Surprisingly, a granular assessment of regional patterns of gliomagenesis has not been undertaken in the molecular era. ObjectiveTo quantitatively establish the anatomical distribution of the major molecular subtypes of adult diffuse glioma. MethodsWe retrospectively analyzed a consecutive series of 204 IDH-mutant and 200 IDH- wildtype gliomas. Tumor volumes were segmented, normalized, and assigned to a brain location using a standardized neuroanatomic atlas. An independent and external validation cohort of 190 IDH-mutant and 227 IDH-wildtype gliomas was used to assess reproducibility. Microarray expressions from the Allen Human Brain Atlas were utilized to analyze transcriptomic differences between hotspots and coldspots of IDH-mutant gliomas. Results50.5% (103/204) of IDH-mutant tumors arose with the superior and middle frontal gyri indicating a 3.1-fold regional enrichment relative to the volume of these gyri (p<0.001). Only 0.5% (1/204) of IDH-mutant tumors arose with the occipital gyri indicating a 23.4-fold regional scarcity relative to volume (p<0.001). 9.5% (19/200) of IDH-wildtype tumors arose in the superior temporal gyrus with a 2.1-fold enrichment (p=0.01) and 6% (12/200) in the hippocampus with a 6-fold enrichment (p<0.001). IDH-mutant and wildtype tumors were enriched by 4 and 4.5-fold respectively in the insula (both p<0.001). Both IDH-mutant astrocytomas and oligodendrogliomas were significantly enriched in the SFG (39.2% and 40.2% respectively; both p<0.001), but 23.5% (24/102) of astrocytomas occurred disproportionately higher in the insula compared to oligodendrogliomas (p<0.001). These enrichment patterns were reproduced in an independent validation cohort of 417 glioma patients. Transcriptomic analysis comparing the lobar hotspot (frontal lobe) to the coldspot (occipital lobe) revealed frontal enrichment of cholesterol (NES=1.78) and fatty acid (NES=1.94) metabolism pathways, paralleling the observed regional enrichment of IDH-mutant gliomas. ConclusionsThis study reveals striking regional differences in glioma incidence, identifying key hotspots in the brain for gliomagenesis that vary based on tumor molecular subtype. Metabolic differences across cortical regions raise the possibility that regional metabolic differences may contribute to the observed vulnerability of specific regions to gliomagenesis. These findings provide a framework for investigating additional microenvironmental factors that drive human glioma formation.

Background: Extent of resection remains central to meningioma management, yet Simpson grading is subjective and may not reflect measurable postoperative residual disease. We compared surgeon-reported Simpson grade, report-derived radiological grading, and residual tumour volumetry across a multicentre cohort. Methods: We performed a retrospective study across two tertiary neurosciences centres comprising four hospitals, including patients undergoing primary cranial meningioma resection from 2006 to 2025. Postoperative magnetic resonance imaging (MRI) reports were harmonised using weakly supervised natural language processing based on term frequency-inverse document frequency (TF-IDF) and a linear support vector machine classifier. Residual tumour volume was segmented from contrast-enhanced postoperative MRI and log-transformed. Concordance between Simpson and radiological gross-total/subtotal resection classification was assessed using absolute agreement and prevalence-adjusted bias-adjusted kappa (PABAK). Cox models assessed recurrence-free survival, with bootstrap validation and anatomical and scan-timing sensitivity analyses. Results: Among 912 patients, recurrence or residual progression occurred in 281. Surgical-radiological agreement was substantial but imperfect (absolute agreement 74%; PABAK 0.61), with lower agreement in skull-base and parafalcine-parasagittal tumours. In adjusted models, recurrence hazard increased with Simpson grade (hazard ratio 1.54, 95% confidence interval 1.37-1.72), radiological grade (1.92, 1.68-2.20), and log-transformed residual volume (1.20, 1.16-1.24; all p<0.0005). Optimism corrected concordance increased from Simpson grade to radiological grade and log-volumetry (0.692, 0.733, and 0.748), with this ranking preserved across sensitivity analyses. Conclusions: Imaging-based postoperative residual disease measures outperformed Simpson grade. TF-IDF-assisted report-derived grading provides a scalable bridge to volumetry, while quantitative residual volume offers the strongest prognostic representation.

BackgroundThe life expectancy of patients with diffuse IDH-mutant low-grade gliomas (IDHmt LGG) WHO grade 2 ranges from 5 to over 20 years. Tumor behavior, including spontaneous growth rate, varies even within homogeneously classified subtypes of oligodendroglioma and astrocytoma. Risk-adjusted treatment strategies are needed to avoid therapy-related toxicities, without compromising outcome. The spontaneous tumor volume growth rate (TVGR) serves as a prognostic marker and predicts response to therapy. Accurate prediction of TVGR through biomarkers would enable an improved evidence-based risk management. Patients & MethodsA cohort of 77 patients treated in Montpellier, France, for IDHmt LGG grade 2 (29 oligodendrogliomas, 48 astrocytomas) was analyzed (age >18 years; MRI scans and frozen tumor tissue available). DNA methylome profiling (Illumina, EPIC array) and RNA sequencing were established. TVGR was determined based on serial MRI collected over the "watch & wait" period from diagnosis to first treatment beyond surgery. Transcriptomic and methylome data were analyzed for signatures associated with TVGR using rank-rank regression followed by preranked gene set enrichment analysis. ResultsThe median TVGR was lower in IDHmt codeleted compared to non-codeleted LGG, (0.241 year-1 range 0.082-0.366 vs 0.424 year-1 range 0.264-0.609, p<0.001). In codeleted IDHmt LGG, TVGR was associated with deregulated gene signatures for signal transduction, neuronal systems, growth factor stimulation, and neural progenitor- and stem cells. In contrast, TVGR in noncodeleted IDHmt LGG was associated predominantly with proliferation-related signatures. ConclusionSpontaneous TVGR of codeleted and non-codeleted IDHmt LGG involve distinct biological processes, suggesting possible differences in response to therapies. Key PointsO_LIIDHmt glioma WHO grade 2 growth rate impacts outcome and response to therapy C_LIO_LIMolecular drivers of spontaneous growth rates are distinct between astrocytomas and oligodendrogliomas C_LIO_LIPossible impact on treatment response and outcome C_LI Importance of StudyThe life expectancy of patients with diffuse IDH-mutant low-grade gliomas (IDHmt LGG) WHO grade 2 ranges from 5 to over 20 years, with tumor behavior and growth rate varying even within homogeneous histo-molecular subtypes. Risk-adapted treatment strategies are needed to avoid therapy-related toxicities, without compromising outcome. The spontaneous tumor volume growth rate (TVGR) is a prognostic marker and predicts therapy response. We analyzed a cohort of 77 patients with IDHmt LGG, with available MRI and tumor tissue. DNA methylome profiling and RNA sequencing were performed. TVGR was calculated from serial MRI during the "watch & wait" period before any treatment beyond surgery. TVGR in non-codeleted LGG patients was mainly associated with gene signatures linked with proliferation, while it was associated with deregulated gene signatures for signal transduction, neuronal systems, growth factor stimulation, and neural progenitors and stem cells in codeleted tumors. These insights suggest possible differences in response to therapies.

BackgroundNRCAM, a neuronal cell adhesion molecule, has been implicated in glioma biology through splicing alterations reported by prior studies. However, the relative contributions of genomic and epigenetic mechanisms to NRCAM dysregulation in gliomas remain unclear. MethodsWe analyzed glioma datasets from The Cancer Genome Atlas (TCGA) using UCSC Xena and cBioPortal. Copy number variation (CNV), DNA methylation (Illumina 450K arrays), and mutation profiles were assessed for NRCAM. Kaplan Meier survival analyses were performed with Xena, stratifying patients by copy number status and methylation state. Correlations between mutation burden and fraction genome altered were evaluated using Spearman and Pearson methods. ResultsSomatic mutations in NRCAM were rare across TCGA gliomas. In contrast, CNV and methylation changes were frequent and clinically relevant. Copy number gains at the NRCAM locus were associated with significantly shorter overall survival, while higher methylation of NRCAM correlated with improved survival outcomes. NRCAM mutation count did not show a linear correlation with fraction genome altered (FGA), suggesting these alterations are largely independent of overall genomic instability. The findings highlight copy number imbalance and epigenetic regulation as predominant mechanisms of NRCAM dysregulation. ConclusionNRCAM is recurrently dysregulated in gliomas through copy number alterations and DNA methylation, both of which stratify patient survival. Together with previously reported splicing deregulation, these data suggest that NRCAM functions as a multilayered regulator of glioma progression. NRCAM methylation may represent a prognostic biomarker, while therapeutic modulation of NRCAM warrants further investigation.

Adult-onset craniopharyngioma (AoC) is a rare intracranial tumour associated with long-term physical and psychological difficulties. Although prior questionnaire-based studies suggest impairments in social and emotional functioning, no research has experimentally examined social interaction perception in this population. This study employed an online experimental task combined with automated linguistic analysis to explore differences in social interaction perception between AoC patients and healthy volunteers (HVs). Nineteen AoC patients and twenty matched HVs viewed 30 short, naturalistic video clips depicting everyday social interactions. After each video, participants were asked to describe what they saw in as much detail as possible. Responses were analysed using Linguistic Inquiry and Word Count (LIWC) software to assess emotional and social language use across eight pre-registered categories. AoC participants used a higher proportion of social and emotional language across six categories (e.g., affect, social behaviour) despite producing shorter responses overall. Inferential statistics found no significant differences between groups, and Bayesian analysis confirmed there were no differences in the use of pro-social or emotion words between AoC participants and HVs. Contrary to hypotheses, AoC patients did not significantly differ from HVs in their linguistic descriptions of social interactions. This may indicate preserved social interaction perception or may reflect task or sample limitations. Future studies should explore the influence of hypothalamic involvement and oxytocin in social functioning in AoC.

PurposeMaas et al. recently showed that a microenvironment-determined risk continuum, driven by the shift from microglia-like to myeloid-derived macrophage-like tumor-associated macrophages (TAMs), independently predicts meningioma progression beyond WHO grade. Whether this gradient is recoverable from bulk RNA-seq has not been tested. MethodsWe computed a microglia-to-macrophage ssGSEA ratio using expanded gene sets (15 microglia, 17 macrophage) anchored to Maas core markers across 968 meningiomas from 5 GEO datasets, validated it against pseudo-bulk profiles from the Maas snRNA-seq cohort (n=25), and tested recurrence-free survival (RFS) association by Cox regression in a 101-patient subset (73 events, median follow-up 110.2 months). ResultsThe ratio correlated with single-cell microglia proportion (overlap-controlled r=0.70, 95% CI 0.42-0.86) and discriminated WHO grades and transcriptomic clusters, confirming biological recoverability. The ratio did not predict RFS (HR 0.92, 95% CI 0.72-1.16, p=0.46). A quantitative attenuation analysis predicts the Maas IHC HR of 2.00 attenuates to HR 1.24-1.40 after proxy measurement error (r2=0.22-0.49) and NF2-wildtype dilution (30-45%), yielding only 15-40% power at 73 events. An exploratory NF2-expression proxy subgroup (uncorrected p=0.056) showed a trend in NF2-low tumors (HR 0.68, 95% CI 0.46-1.01) absent in NF2-high tumors (HR 0.98, p=0.89). The Chen 34-gene tumor-intrinsic panel also reached near-chance discrimination (C-index 0.552). ConclusionSingle-cell-anchored ssGSEA recovers the Maas gradient in bulk RNA-seq but attenuates it below detectability in moderate-sized, NF2-unselected cohorts. The prognostic component is bounded by power and NF2 stratification, not an intrinsic modality failure; NF2-annotated cohorts with approximately 480 events are required for definitive testing.

IntroductionPituitary adenomas with cavernous sinus invasion represent a challenging subset of intracranial tumors. The presence of cavernous sinus invasion complicates surgical resection and increases the risk of recurrence and postoperative complications. Endoscopic endonasal surgery (EES) has emerged as a promising alternative to traditional microscopic transsphenoidal surgery, offering enhanced visualization and reduced collateral damage. This meta-analysis aims to evaluate the efficacy and safety of EES in the treatment of pituitary adenomas with cavernous sinus invasion, focusing on remission rates, gross total resection (GTR), recurrence rates, and complications. MethodsA comprehensive literature search was conducted through PubMed, Scopus, Embase, and CENTRAL databases until August 2025, following PRISMA guidelines. Studies meeting eligibility criteria, including human studies published in English and involving adult patients with pituitary adenomas and cavernous sinus invasion treated with EES, were included. Data extraction focused on patient demographics, tumor characteristics, surgical outcomes, and complications. Statistical analysis was performed using a random-effects model, and subgroup analysis was conducted based on factors such as tumor size, Knosp grade, and hormonal subtype. ResultsA total of 27 studies involving 3,591 patients were included. The pooled remission rate was 60% (95% CI: 49% to 71%), with substantial variability across studies. The pooled residual tumor rate was 15% (95% CI: 11% to 19%), and the recurrence rate was 8% (95% CI: 6% to 11%). The incidence of cerebrospinal fluid (CSF) leaks was 9% (95% CI: 3% to 14%), while the rates of ICA injury and cranial nerve injury were extremely low (0.00% and 0.01%, respectively). Subgroup analyses revealed higher remission rates in macroadenomas (68%) compared to microadenomas (33%), and GH-secreting tumors showed higher endocrinological remission rates compared to ACTH-secreting tumors. ConclusionEndoscopic endonasal surgery demonstrates moderate efficacy in the treatment of pituitary adenomas with cavernous sinus invasion, with favorable remission and resection rates. However, substantial variability across studies emphasizes the need for further standardization of surgical techniques and patient selection criteria. The procedure is generally safe, with low rates of serious complications such as ICA injury and cranial nerve damage. Further prospective studies are needed to optimize patient management and evaluate long-term outcomes, including recurrence and quality of life.

BackgroundGlioblastoma (GBM) remains one of the most aggressive primary brain tumors, with limited survival despite maximal safe resection and chemoradiotherapy. Neoadjuvant bevacizumab (BEV) has been proposed to reduce peritumoral edema, improve functional status, and potentially enhance progression-free survival (PFS). However, its survival benefit in newly diagnosed, surgically resectable GBM remains unclear. ObjectiveTo systematically review and quantitatively synthesize the evidence on neoadjuvant BEV in adult patients with newly diagnosed, resectable GBM, focusing on survival and functional outcomes. MethodsFollowing PROSPERO registration (CRD420251078761), we searched PubMed, Embase, Scopus, Web of Science, and Cochrane Library up to July 20, 2025, without language restrictions. Eligible randomized trials, non-randomized trials, and cohort studies compared neoadjuvant BEV (alone or with other therapies) to standard care without BEV. Primary outcomes were overall survival (OS) and PFS; secondary outcomes included Karnofsky Performance Status (KPS), steroid use, radiological response, and biomarkers. Data were pooled using a random-effects model. ResultsThirteen studies (2 RCTs, 7 non-randomized trials, 4 cohorts) met the inclusion criteria; four (n=751) were eligible for meta-analysis. Pooled HR for OS was 0.72 (95% CI: 0.42-1.25, p=0.246) and for PFS was 0.72 (95% CI: 0.42-1.22, p=0.220), both with low heterogeneity (I2=0%). Functional outcomes suggested improved KPS and reduced steroid dependence, but certainty was low. Biomarker and radiological findings were inconsistent. ConclusionsNeoadjuvant BEV in resectable GBM does not significantly improve OS or PFS but may offer symptomatic and functional benefits. Current evidence is limited by small sample sizes, heterogeneous protocols, and low methodological quality. Well-designed multicenter RCTs are warranted.

PurposeTo evaluate the association between surgically acquired neurological deficits and mortality among patients who underwent surgical resection of brain metastases. MethodsPatients who underwent surgical resection of brain metastases at our institution between 2011 and 2019 were included. Surgically acquired neurological deficits were defined as dysarthria/aphasia, ataxia, hemiparesis, and visual field loss. A Cox proportional hazards model adjusting for potential confounders was constructed to evaluate whether surgically acquired neurological deficits were independently associated with a higher risk of overall mortality. ResultsA total of 153 patients were included in the analysis. 3.3% (5 patients) had a surgically acquired neurological deficit. On univariate time-to-event analysis, there was no statistically significant association between the development of a surgically acquired neurological deficit and mortality (HR=1.12; 95% CI=0.15, 8.24; p=0.910). On multivariate time-to-event analysis adjusting for potential confounders, there was also no statistically significant association between the development of a surgically acquired neurological deficit and mortality (HR=1.53; 95% CI=0.20, 11.9; p=0.683). ConclusionThe development of a surgically acquired neurological deficit was not associated with overall mortality. Although this conclusion differs from other studies in the literature, the goal of surgical resection remains unchanged - to resect as much tumor as possible while still preserving neurological function.

BackgroundBrain tumors can present as focal neurologic deficits (reflecting the tumor location) or generalized symptoms due to increased intracranial pressure. Occasionally, brain tumors can be found incidentally in asymptomatic patients or in patients with unrelated symptoms who undergo brain imaging. The term incidentaloma is used to refer to these imaging abnormalities. ObjectiveThe object of this study was to examine the prevalence and correlates of asymptomatic glioma in a large epidemiological study of brain tumors. MethodsThe analysis was based on a large series of patients with glioma (N = 1989) enrolled in a multicenter clinic-based epidemiologic study between 2005 and 2017. Patients were considered asymptomatic from the tumor, and thus as having an incidentally detected glioma (IDG), if the tumor was diagnosed during workup of injury or unrelated medical condition. ResultsA total of 32 of 1989 (1.6%) patients were asymptomatic at diagnosis. The leading indication for brain imaging in IDG was non-workplace injuries followed by medical workup for unrelated conditions. IDG was more prevalent in patients younger than 50 years of age (2.6% vs 1.0%). IDG was also more common in patients with low grade gliomas (4.7% for WHO grade II and 1.5% for WHO grade III) vs glioblastomas (0.6% in WHO grade IV). ConclusionThe present data suggest that gliomas may be found incidentally, especially among low grade gliomas. Studies of IDG may be useful as a proxy for early detection of tumor as a means to improve patient survival.

Background/ObjectivesIncreasing evidence indicates that gliomas co-opt mechanisms of excitatory synaptic transmission and plasticity to support tumor progression, yet these processes remain poorly characterized in lower-grade gliomas (LGGs). Here, we investigated whether genes associated with excitatory synaptic function are linked to patient prognosis in LGG. MethodsA curated panel of 36 synaptic genes was analyzed in LGG using RNA-sequencing and clinical data from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) datasets. Correlations among gene expression levels were analyzed using the Evergene platform. ResultsAmong the genes investigated, DLG2, DLG3, and DLG4, which encode the postsynaptic scaffolding proteins PSD-93, SAP-102, and PSD-95, respectively, showed strong associations with patient overall survival (OS). Higher expression of each gene was consistently associated with longer OS across both datasets. Expression of DLG2-DLG4 was higher in oligodendroglioma and IDH-mutant, 1p/19q co-deleted tumors, and lower in astrocytoma and IDH-wild-type tumors. Furthermore, expression of all three genes positively correlated with a broad gene signature related to excitatory synaptic transmission and synaptic plasticity, including multiple components of glutamatergic signaling and postsynaptic organization. ConclusionsThese findings suggest that elevated expression of DLG2-DLG4 is associated with a transcriptional program resembling differentiated neuronal-like features and favorable clinical outcome in LGG. Simple SummaryLower-grade gliomas are brain tumors with highly variable outcomes, and better markers are needed to predict how patients will fare. Recent research suggests that these tumors may use mechanisms normally involved in communication between brain cells, but this is not well understood in these cancer types. In this study, we analyzed large patient datasets to examine genes related to synaptic function. We found that higher expression of three genes involved in synaptic membrane organization, DLG2, DLG3, and DLG4 was consistently associated with longer patient survival. These genes were also linked to a broader pattern of gene expression suggestive of neural transmission and plasticity. Our findings suggest that some lower-grade gliomas may adopt characteristics of normal brain cells that are associated with less aggressive behavior. This work may help guide future research on prognostic markers and improve understanding of brain tumor biology.

Genome-wide DNA methylation aberrations are pervasive and associated with clinicopathological features across pituitary tumors (PT) subtypes. The feasibility to detect CpG methylation abnormalities in circulating cell-free DNA (cfDNA) has been reported in central nervous system tumors other than PT. Here, we aimed to profile and identify methylome-based signatures in the serum of patients harboring PT (n =13). Our analysis indicated that serum cfDNA methylome from patients with PT are distinct from the counterparts in patients with other tumors (gliomas, meningiomas, colorectal carcinomas, n =134) and nontumor conditions (n = 4). Furthermore, the serum methylome patterns across PT was associated with functional status and adenohypophyseal cell lineage PT subtypes, recapitulating epigenetic features reported in PT-tissue. A machine learning algorithm using serum PT-specific signatures generated a score that distinguished PT from non-PT conditions with 100% accuracy in our validation set. These preliminary results underpin the potential clinical application of a liquid biopsy-based DNA methylation profiling as a noninvasive approach to identify clinically relevant epigenetic markers that can be used in the management of PT.

Glioblastomas integrate into the brain globally, where they provoke neuronal hyperactivity to enhance tumor growth and invasion. Communication of glioblastomas with neurons is not only present locally, but has preclinically been shown to extend towards the contralateral hemisphere through white matter tracts. However, it remains unknown how the distant hyperactivity that is often found in patients relates to structural embedding of the tumor into the larger brain network. 29 newly diagnosed IDH-wildtype glioblastoma patients and 25 age and sex matched healthy controls were included. To define structural tumor embedding, we overlayed each patient-specific tumor mask with a normative structural connectome obtained from diffusion MRI. We identified the average number of streamlines intersecting the tumor, extracting the tumors average tract density ( Lesion-Tract Density Index, L-TDI). For a subgroup of patients (n = 17), we determined structural embedding directly from diffusion scans and subsequent tractography. To identify regions connecting to the tumor, we seeded from each patients tumor rim outside FLAIR hyperintensities in the white matter to the 210 cortical regions of the Brainnetome atlas. We then counted the number of tumor-connecting regions, termed PATNET hereafter. Finally, participants underwent eyes-closed resting-state magnetoencephalography. We used broadband power as a proxy for neuronal spiking activity of each cortical region. To capture deviant brain activity in tumor and non-tumor regions, we regionally standardized broadband values using controls. We then sought to establish an association of deviant peritumor activity with both L-TDI and PATNET. Subsequently, we investigated whether tumor-connected regions showed more deviant activity than unconnected regions. Finally, we explored the clinical relevance of L-TDI and PATNET. Greater structural tumor embedding significantly related to more deviant peritumor activity (rhoLTDI= 0.47, PLTDI = .010; rhoPATNET = 0.54, PPATNET = .024), with larger tumors showing greater embedding and more hyperactivity than smaller tumors. Furthermore, distant tumor-connected regions showed more hyperactivity than unconnected regions, but only in patients with peritumor hyperactivity (F(1,15) = 11.02, P =.005). Finally, higher PATNET associated with lower KPS (U = 61.5, P = .015). Glioblastomas structural embedding explains hyperactivity around the tumor and in distant cortical regions, such that distant hyperactivity occurs primarily when there is tumor hyperactivity and the region is structurally connected to the tumor. Moreover, patient-specific tumor embedding relates to functional status.

BackgroundGlioblastoma (GBM), Isocitrate dehydrogenase-wildtype (IDH-wt) is characterised by diffuse infiltration, with progression often arising from perilesional tissue and occult white-matter damage. We investigated whether radiomics from the T2/FLAIR-defined oedema and the structural disconnectome improve prediction of progression-free survival (PFS). MethodsWe retrospectively analysed 387 adults with newly diagnosed GBM, IDH-wt treated at a single tertiary centre (2005-2020). A deep-learning pipeline segmented enhancing tumour, non-enhancing tumour, and oedema on pre-operative MRI; lesion masks were propagated to normative tractography to derive disconnectome maps. 3-D shape radiomic features extracted for each segmented region underwent appropriate feature selection. Finally, 10 tumour and 9 oedema radiomics were combined with 6 clinical features to train 3 survival models (Random Survival Forest (RSF), XGBoost, Cox proportional hazards (CPH)) that were evaluated on a held-out 20% test set using Harrells C-index, Kaplan-Meier risk stratification and time-dependent ROC curves. ResultsThe best performance was achieved by RSF using all clinical and radiomic features (C-index 0.665 vs 0.595 for clinical features only, p=0.088). Models including oedema radiomics outperformed those using tumour radiomics alone, and disconnectome features, derived from both tumour and oedema regions, were repeatedly selected among the top predictors across algorithms. Combining radiomic and clinical features improved risk stratification and 12-month early-versus-late recurrence classification (AUC 0.704 vs 0.582 for clinical features alone). ConclusionsIntegrating perilesional oedema and white-matter disconnectome MR features with clinical and molecular data enhances prediction of PFS in GBM, IDH-wt. These network-aware, multimodal survival models may support personalised risk-adapted treatment strategies pending external validation. Key Points- GBM IDH-wt exhibits a high recurrence rate despite aggressive treatment. - Addition of high-dimensional oedema and disconnectome radiomic features to clinical features showed consistent improvement in the test performance of 3 ML models. - This can support informed clinical decision-making. Importance of the StudyPrediction of progression free survival (PFS) for a patient with highly recurrent glioblastoma IDH-wt traditionally relies on clinical history, demographics, and molecular markers of the tumour. Recent literature reveals the tumours disruptive nature through its invasion of white-matter tracts and identifies its microenvironment, particularly the perilesional oedema, as a harbour of treatment resistant tumour cells. This study is the first to combine high-dimensional radiomic features of the tumour, the oedema, and their disconnectome with clinical and treatment factors to predict PFS. Using 3 model architectures (XGBoost, RSF, and CoxPH), we demonstrate consistent directional improvements in performance, on addition of radiomic features to clinical baseline models. Furthermore, oedema and disconnectome radiomics are identified as top predictor features across algorithms. This proof-of-concept study provides a reproducible multimodal pipeline, reaffirms the usability of MR radiomics, and identifies features of the oedema and the structural connectome as promising biomarkers, demanding large-scale external validation.

Medical imaging is crucial for glioma management. Combined with MRI, amino acid PET may improve glioma diagnosis, biopsy targeting, and tumor delineation compared to structural MRI alone. Magnetic resonance spectroscopic imaging (MRSI) complements both structural MRI and PET by detecting metabolites such as N-acetylaspartate (NAA), creatine (Cr), and choline (Cho), which are markers for brain health and tumor malignancy, but is challenged by low spatial resolution. This study evaluates whether high-resolution MRSI enhanced by deep learning can improve diagnostic accuracy and serve as a complement or alternative to PET for glioma classification. Ten glioma patients (CNS WHO grades 2-4, ages 24-80) were included. Presurgical [18F]-FACBC PET/MRI, including proton 2D MRSI, was acquired for all patients. Thirty image-guided biopsies were sampled during surgery from the patients and classified as glioma tissue or non-tumor tissue, and according to IDH1 status. For each biopsy location, tumor-to-background ratio (TBR) and standardized uptake value (SUV) from PET, and tCho/NAA and tCho/tCr ratios from MRSI were calculated. ROC analysis was used to assess the accuracy of [18F]-FACBC PET and high-resolution MRSI, and the combinations of these in classifying glioma vs. non-tumor tissue and IDH1 status. The tCho/NAA ratio from the deep learning-based model demonstrated excellent diagnostic accuracy in classifying glioma vs. non-tumor tissue (AUC = 0.87, 95% CI: 0.66- 1.0), outperforming SUV (AUC = 0.71, 95% CI: 0.49-0.90), TBR (AUC = 0.68, 95% CI: 0.48-0.86), and tCho/tCr (AUC = 0.81, 95% CI: 0.54-1.00). Combining TBR with tCho/NAA and/or tCho/tCr improved tissue classification compared to either modality alone, where TBR + tCho/NAA + tCr/NAA showed the best results (AUC = 0.91, 95% CI: 0.71-1.0). MRSI was a poor predictor for IDH1-status (tCho/NAA: AUC = 0.67, 95% CI: 0.44-0.88 and tCho/tCr: AUC = 0.38, 95% CI: 0.17-0.60), while PET was an excellent predictor (SUV: AUC = 0.83, 95% CI: 0.66-0.85 and TBR: AUC = 0.82, 95% CI: 0.65-0.94) and the combination of SUV and tCho/tCr was an outstanding predictor (AUC = 0.96, 95% CI: 0.88-1.0). Incorporating high-resolution MRSI in combination with [18F]-FACBC PET improved the diagnostic accuracy in differentiating glioma tissue from non-tumor tissue. Significance StatementOur study highlights the importance of combining imaging methods for brain tumor characterization. MRI remains central in brain imaging but is limited, making PET a valuable molecular complement. MRSI provides insight into neurometabolic alterations associated with tumor growth, yet its clinical utility has been limited by low spatial resolution. By applying deep learning, we enhanced the resolution of MRSI and compared its performance with PET. Our findings demonstrate that High-resolution MRSI adds diagnostic value and, with PET, may enhance glioma classification and inform future clinical decision-making.

BackgroundGlioblastoma (GBM) progression is strongly influenced by its microenvironment, yet the contribution of white-matter injury-associated extracellular matrix (ECM) remodeling to human disease remains unclear. Experimental models show that glioma cells induce axonal injury and glial-scar-like ECM responses that accelerate tumor growth. MethodsWe curated an ECM Organization Signature reflecting injury-associated matrix remodeling and applied it to bulk RNA-sequencing data from TCGA-GBM. ECM scores were analyzed alongside wound-healing, microglia/TAM activation, and neuronal integrity signatures. Kaplan-Meier curves and age-adjusted Cox models assessed prognostic significance. ResultsECM organization, wound-healing, and microglia/TAM activation formed a coherent injury-response axis inversely correlated with neuronal programs. ECM-high tumors showed significantly different overall survival compared with ECM-low tumors (log-rank p = 0.023). In an age-adjusted Cox model, ECM remodeling independently predicted mortality (HR = 1.23, p = 0.0156). ConclusionWhite-matter injury-associated ECM remodeling is a prominent, clinically meaningful transcriptional state in human GBM and identifies a prognostic microenvironmental subtype.

ObjectiveThis paper seeks to quantify the normalized expression of transcripts FOXM1*3, VEGF, CD133, and MGMT and their relation with the histopathological and molecular diagnosis and with the probability of estimating tumor progression-free survival of gliomas. MethodsA cohort of patients was made up of patients aged over 18 years with a histological and molecular diagnosis of gliomas from the year 2011 to 2018. The patients had a complete tumor resection. Patients with high-grade glioma received adjuvant management (temozolamide and radiotherapy). Clinical and imaging follow-up was carried out periodically to identify the time of progression free survival (PFS). ResultsNinety-one patients (age range, 18-85 years) comprised the study cohort with a predominance of males. The expression of FOXM1*3, VEGF, and CD133 allowed the differentiation of astrocytomas grade II from GBM. ROC curves proved statistically significant in the GBM model (p < 0.05), demonstrating greatest sensitivity with FOXM1*3 (91%), and greatest specificity with VEGF (93%). The age-adjusted Cox multivariate model established that a PFS50% of 25 months corresponds to a median value of 5.3 for VEGF and 0.42 for CD133. ConclusionsThe normalized expression of transcripts FOXM1*3, VEGF, and CD133 allow us to estimate the probability of PFS, especially in gliomas grades II and IV; likewise, their overexpression defines the diagnosis of GBM. AuthorshipO_LISubstantial contributions to conception and design (IAFR, BNR, MARF, GG, IG), acquisition of data (IAFR, BNR, MARF, IFE, LCP, JCM, SOS, JAC, CRA), analysis and interpretation of data (IAFR, BNR, MARF, JCM, SOS, CEN, HMG, IG). C_LIO_LIDrafting the article (IAFR, BNR, MARF, IFE, LCP, SOS, JAC, IG), revising it critically for important intellectual content (IAFR, JCM, CEN, GG, HMG, CRA, IG) C_LIO_LIFinal approval of the version to be published (IAFR, BNR, MARF, IFE, LCP, JCM, SOS, JAC, CEN, GG, HMG, CRA, IG). C_LI

Introduction: Glioblastoma multiforme (GBM) remains the most lethal primary brain tumor with median survival of 14-15 months. Current prognostic markers inadequately stratify patient outcomes. PINK1 (PTEN-induced putative kinase 1), a mitochondrial kinase regulating mitophagy and cellular stress responses, has emerged as a promising prognostic candidate. Our preliminary analysis of 20 GBM cases demonstrated significant PINK1 expression with correlation to aggressive phenotypes (Turizo Smith et al., 2025). This multicenter study aims to prospectively validate PINK1 as a prognostic biomarker for survival and functional outcomes in a Latin American cohort. Methods and analysis: PINK1-GBM Colombia is a multicenter, observational cohort study across four tertiary hospitals in Bogota, Colombia (Hospital de Kennedy, Hospital El Tunal, Hospital Santa Clara and Hospital Universitario de la Samaritana). We will enroll at least 26-50 adults (18+ years) with newly diagnosed IDH-wild type GBM undergoing surgical resection. PINK1 expression will be quantified by immunohistochemistry (IHC) on formalin-fixed paraffin embedded (FFPE) tissue using standardized protocols. Primary outcomes: overall survival (OS) and progression-free survival (PFS). Secondary outcomes: functional status trajectories (KPS/ECOG). Follow-up extends 24 months with clinical, imaging (RANO 2.0), and telephone assessments. Survival analyses will employ Kaplan-Meier methods, log-rank tests, and Cox proportional hazards models adjusted for established prognostic factors. Ethics and dissemination: Approved by Universidad Nacional de Colombia Ethics Committee (Acta 001, February 5, 2026; Ref: 2.FM.1.002-CE-002-26), Subred Sur Occidente (P-AP-19-2025, July 11, 2025), and Subred Centro Oriente (CEI 067/2025, October 24, 2025). Conducted per Declaration of Helsinki and Colombian Resolution 8430/1993. Results will be disseminated via peer-reviewed publication, international conferences, and thesis submission.

The understanding of glioma disease has been evolving drastically with dedicated research into the genetic and molecular profiling of glioma tumour tissue. Molecular biomarkers have gained progressive and substantial importance in providing diagnostic information, leading to groundbreaking changes in the tumour classification system, criteria and taxonomy standardised by the 2016 and 2021 editions of the World Health Organization Classification of Tumours of the Central Nervous Systems guidelines (WHO-2016 and WHO-2021, respectively). Some of the insights into glioma disease derived from extensive research on open-source multi-omics databases, such as the Cancer Genome Atlas (TCGA). However, given the substantial changes in glioma classification, retrospective databases may harbour outdated diagnostic annotations, suboptimal for further research. Here we propose two methods for updating the tumour classification of TCGA glioma samples in accordance with WHO-2016 and WHO-2021 guidelines through the integration of curated molecular profiling information. Our methods allowed for the diagnostic update of 98% and 87% of evaluated TCGA glioma cases according to WHO-2016 and -2021, respectively, and highlighted changes in patient-specific diagnosis across both guidelines editions. Our reclassification pipelines are provided in software R, facilitating direct reproduction or tailoring upon new releases of WHO guidelines.