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Despite the importance of chemotherapy as a treatment option for glioma, its efficacy is often compromised by the formidable blood‐brain barrier (BBB) and drug resistance. To address these challenges, a novel cascade nanodrug system called A12‐PTX@RF‐NPs is designed with aims to penetrate the BBB and precisely target glioma. In this nanosystem, the RVG‐29 peptide facilitates the BBB penetration while Folic Acid (FA) targets glioma cells through binding to Folate Receptors (FR), followed by receptor‐mediated endocytosis subsequently. The incorporation of disulfide bond modifications enables responsive release within the reductive environment of glioma, ensuring successful delivery of chemotherapy drugs. Significantly, a co‐treatment approach involving the combination of A12 and PTX is implemented. In vitro and in vivo investigations have provided evidence that this amalgamation effectively induces apoptosis in tumor cells and inhibits their proliferation, thus synergistically eliminating both typical and drug‐resistant glioma cells. These findings suggest that the nanodrug system presents a promising therapeutic strategy for glioma treatment, surpassing the limitations of conventional chemotherapy. Specifically, A12‐PTX@RF‐NPs constructed in this research have demonstrated remarkable targeting capabilities and therapeutic effects in cellular as well as animal models, thereby proposing an innovative strategy for glioma treatment. [ABSTRACT FROM AUTHOR]

Comprehensive and non-invasive preoperative molecular diagnosis is important for prognostic and therapy decision-making in adult-type diffuse gliomas. We employed a deep learning method for automatic segmentation of brain gliomas directly from conventional magnetic resonance imaging (MRI) scans of the tumor core and peritumoral edema regions based on available glioma MRI data provided in the BraTS2021. Three-dimensional volumes of interest were segmented from 424 cases of glioma imaging data retrospectively obtained from two medical centers using the segmentation method and radiomic features were extracted. We developed a subtype prediction model based on extracted radiomic features and analyzed significance and correlations between glioma morphological characteristics and pathological features using data from patients with adult-type diffuse glioma. The automated segmentation achieved mean Dice scores of 0.884 and 0.889 for the tumor core and whole tumor, respectively. The area under the receiver operating characteristic curve for the prediction of adult-type diffuse gliomas subtypes was 0.945. "Glioblastoma, IDH-wildtype", "Astrocytoma, IDH-mutant", and "Oligodendroglioma, IDH-mutant, 1p/19q-coded" showed AUCs of 0.96, 0.914, and 0.961, respectively, for subtype prediction. Glioma morphological characteristics, molecular and pathological levels, and clinical data showed significant differences and correlations. An automatic segmentation model for gliomas based on 3D U-Nets was developed, and the prediction model for gliomas built using the parameters obtained from the automatic segmentation model showed high overall performance. [ABSTRACT FROM AUTHOR]

Dynamic contrast-enhanced MRI (DCE-MRI) is increasingly used to non-invasively image blood-brain barrier leakage, yet its clinical utility has been hampered by issues such as noise and partial volume artifacts. In this retrospective study involving 306 adult patients with diffuse glioma, we applied deep learning-based super-resolution and denoising (DLSD) techniques to enhance the signal-to-noise ratio (SNR) and resolution of DCE-MRI. Quantitative analysis comparing standard DCE-MRI (std-DCE) and DL-enhanced DCE-MRI (DL-DCE) revealed that DL-DCE achieved significantly higher SNR and contrast-to-noise ratio (CNR) compared to std-DCE (SNR, 52.09 vs 27.21; CNR, 9.40 vs 4.71; P < 0.001 for all). Diagnostic performance assessed by the area under the receiver operating characteristic curve (AUROC) showed improved differentiation of WHO grades based on a pharmacokinetic parameter (AUC, 0.88 vs 0.83, P = 0.02), while remaining comparable to std-DCE in other parameters. Analysis of arterial input function (AIF) reliability demonstrated that exhibited superior agreement compared to , as indicated by mostly higher intraclass correlation coefficients (Time to peak, 0.79 vs 0.43, P < 0.001). In conclusion, DLSD significantly enhances both the image quality and reliability of DCE-MRI in patients with diffuse glioma, while maintaining or improving diagnostic performance. [ABSTRACT FROM AUTHOR]

Background: Non-invasive brain mapping using navigated transcranial magnetic stimulation (nTMS) is a valuable tool prior to resection of malignant brain tumors. With nTMS motor mapping, it is additionally possible to analyze the function of the motor system and to evaluate tumor-induced neuroplasticity. Distinct changes in motor cortex excitability induced by certain malignant brain tumors are a focal point of research. Methods: A retrospective single-center study was conducted involving patients with malignant brain tumors. Clinical data, resting motor threshold (rMT), and nTMS-based tractography were evaluated. The interhemispheric rMT-ratio (rMTTumor/rMTControl) was calculated for each extremity and considered pathological if it was >110% or <90%. Distances between the corticospinal tract and the tumor (lesion-to-tract-distance -- LTD) were measured. Results: 49 patients were evaluated. 16 patients (32.7%) had a preoperative motor deficit. The cohort comprised 22 glioblastomas (44.9%), 5 gliomas of Classification of Tumors of the Central Nervous System (CNS WHO) grade 3 (10.2%), 6 gliomas of CNS WHO grade 2 (12.2%) and 16 cerebral metastases (32.7%). 26 (53.1%) had a pathological rMT-ratio for the upper extremity and 35 (71.4%) for the lower extremity. All patients with tumor-induced motor deficits had pathological interhemispheric rMT-ratios, and presence of tumor-induced motor deficits was associated with infiltration of the tumor to the nTMS-positive cortex (p = 0.04) and shorter LTDs (all p<0.021). Pathological interhemispheric rMT-ratio for the upper extremity was associated with cerebral metastases, but not with gliomas (p = 0.002). Conclusions: Our study underlines the diagnostic potential of nTMS motor mapping to go beyond surgical risk stratification. Pathological alterations in motor cortex excitability can be measured with nTMS mapping. Pathological cortical excitability was more frequent in cerebral metastases than in gliomas. [ABSTRACT FROM AUTHOR]

This study aims to elucidate the mechanism by which Xihuang Pill induces pyroptosis in glioma cells via the regulation of miR-21-5p. Human glioma cell lines U-87 and LN-229 were used as experimental models to assess the effects of Xihuang Pill on glioma pyroptosis. Cells were incubated with Xihuang Pill extract at concentrations of 7.5, 15, and 30 µg/mL for 24 h, alongside transfection with miR-21-5p mimic, an overexpression vector for STAT3, or incubation with 50 µg/mL of the STAT3 activator Colivelin for 4 h. Cell viability was measured using the CCK-8 assay, apoptosis was detected by flow cytometry, and expression levels of p-STAT3/STAT3 and pyroptosis-related proteins were determined by Western Blot. Additionally, cleaved caspase-1 was assessed by immunofluorescence, miR-21-5p expression by qRT-PCR, and STAT3 binding to the miR-21-5p promoter region by ChIP and dual-luciferase reporter assays. Results showed that Xihuang Pill significantly reduced cell viability, increased apoptosis, and upregulated the expression of pyroptosis-related proteins such as NLRP3, IL-1β, cleaved caspase-1, and GSDMD-N, while reducing p-STAT3/STAT3 and miR-21-5p levels (P < 0.05). Xihuang Pill inhibited STAT3 activation, which modulated miR-21-5p expression by binding to its promoter region. Co-transfection with miR-21-5p mimic reversed the effect of Xihuang Pill on glioma pyroptosis (P < 0.05). In conclusion, Xihuang Pill promotes glioma cell pyroptosis through the STAT3/miR-21-5p pathway. [ABSTRACT FROM AUTHOR]

Comprehensive and non-invasive preoperative molecular diagnosis is important for prognostic and therapy decision-making in adult-type diffuse gliomas. We employed a deep learning method for automatic segmentation of brain gliomas directly from conventional magnetic resonance imaging (MRI) scans of the tumor core and peritumoral edema regions based on available glioma MRI data provided in the BraTS2021. Three-dimensional volumes of interest were segmented from 424 cases of glioma imaging data retrospectively obtained from two medical centers using the segmentation method and radiomic features were extracted. We developed a subtype prediction model based on extracted radiomic features and analyzed significance and correlations between glioma morphological characteristics and pathological features using data from patients with adult-type diffuse glioma. The automated segmentation achieved mean Dice scores of 0.884 and 0.889 for the tumor core and whole tumor, respectively. The area under the receiver operating characteristic curve for the prediction of adult-type diffuse gliomas subtypes was 0.945. "Glioblastoma, IDH-wildtype", "Astrocytoma, IDH-mutant", and "Oligodendroglioma, IDH-mutant, 1p/19q-coded" showed AUCs of 0.96, 0.914, and 0.961, respectively, for subtype prediction. Glioma morphological characteristics, molecular and pathological levels, and clinical data showed significant differences and correlations. An automatic segmentation model for gliomas based on 3D U-Nets was developed, and the prediction model for gliomas built using the parameters obtained from the automatic segmentation model showed high overall performance. [ABSTRACT FROM AUTHOR]

Purpose Methods Results Conclusion Apparent diffusion coefficient (ADC) maps derived from diffusion weighted magnetic resonance imaging (DWI MRI) provides functional measurements about the water molecules in tissues. However, DWI is time consuming and very susceptible to image artifacts, leading to inaccurate ADC measurements. This study aims to develop a deep learning framework to synthesize ADC maps from multi‐parametric MR images.We proposed the multiparametric residual vision transformer model (MPR‐ViT) that leverages the long‐range context of vision transformer (ViT) layers along with the precision of convolutional operators. Residual blocks throughout the network significantly increasing the representational power of the model. The MPR‐ViT model was applied to T1w and T2‐fluid attenuated inversion recovery images of 501 glioma cases from a publicly available dataset including preprocessed ADC maps. Selected patients were divided into training (N = 400), validation (N = 50), and test (N = 51) sets, respectively. Using the preprocessed ADC maps as ground truth, model performance was evaluated and compared against the Vision Convolutional Transformer (VCT) and residual vision transformer (ResViT) models with the peak signal‐to‐noise ratio (PSNR), structural similarity index measure (SSIM), and mean squared error (MSE).The results are as follows using T1w + T2‐FLAIR MRI as inputs: MPR‐ViT—PSNR: 31.0 ± 2.1, MSE: 0.009 ± 0.0005, SSIM: 0.950 ± 0.015. In addition, ablation studies showed the relative impact on performance of each input sequence. Both qualitative and quantitative results indicate that the proposed MR‐ViT model performs favorably against the ground truth data.We show that high‐quality ADC maps can be synthesized from structural MRI using a MPR‐ViT model. Our predicted images show better conformality to the ground truth volume than ResViT and VCT predictions. These high‐quality synthetic ADC maps would be particularly useful for disease diagnosis and intervention, especially when ADC maps have artifacts or are unavailable. [ABSTRACT FROM AUTHOR]

The isocitrate dehydrogenase (IDH) mutation status is one of the most important markers according to the 2021 WHO classification of CNS tumors. Preoperatively, this information is usually obtained based on invasive biopsies, contrast-enhanced MR images or PET images generated using radioactive tracers. However, the completely non-invasive determination of IDH mutation status using routinely acquired preoperative native CT images has hardly been investigated to date. In our study, we show that radiomics-based machine learning allows to determine IDH mutation status based on preoperative native CT images both with very high accuracy and completely non-invasively. Based on independent test data, we are able to correctly identify 91.1% of cases with an IDH mutation. Our final model, containing only six features, exhibits a high area under the curve of 0.847 and an excellent area under the precision-recall curve of 0.945. In the future, such models may be used for a completely non-invasive prediction of important genetic markers, potentially allowing treating physicians to reduce the number of biopsies and speed up further treatment planning. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to assess the diagnostic management and follow‐up imaging for glioma patients across Belgian hospitals by calculating process indicators. Methods: Patients with newly diagnosed glioma in Belgium (2016–2019) were selected from the Belgian Cancer Registry. The National Social Security Number served as unique patient identifier, linking the Registry to vital status and reimbursement data. Nine measurable process related to diagnosis and follow‐up imaging were identified, with reformulations for 7 due to data limitations. For each indicator, technical documentation sheets, containing all required details (rationale, numerator and denominator, target, limitations, benchmarking, subgroup analyses) were developed, reviewed by a multidisciplinary expert panel, and validated in six pilot hospitals. Per indicator, patients were assigned to the most relevant hospital per indicator using allocation algorithms. Results: Results for process indicators assessing MRI use in glioma diagnosis and follow‐up aligned with predefined targets (90%), except for early postoperative MRI (48.5% vs. target 90%). Mandatory reporting of the WHO performance status (89.3% vs. target 100%) and performance of full‐spine (43.6% vs. target 90%) and follow‐up MRI (73.5% vs. target 90%) in ependymoma were suboptimal. The largest variability across centers was noted for the indicator on early postoperative MRI. Conclusion: This calculation of process indicators identified opportunities for improvement in diagnosis and follow‐up imaging for glioma patients in Belgium. Monitoring indicator results and providing individual feedback reports to the Belgian hospitals invites neuro‐oncology care teams and hospital managements to reflect on their results and to take measures to continuously improve care for glioma. [ABSTRACT FROM AUTHOR]

Background: Sialic acid-binding immunoglobulin-like lectin 15 (Siglec-15) enhances tumor immune escape and leads to tumor growth. Purpose: To investigate the expression of Siglec-15 in diffuse gliomas and its correlation with tumor magnetic resonance imaging (MRI) features. Material and Methods: This study included 57 patients with gliomas. Morphological MRI features, including the largest tumor diameter, enhancement category, location, calcification, cysts, and hemorrhage, were visually rated. Apparent diffusion coefficient (ADC) values were calculated in tumor region. MRI morphologic features and ADC were compared between patients with positive and negative Siglec-15 expression. Receiver operating characteristic (ROC) curves were further constructed to assess the diagnostic performance. Results: Siglec-15 was expressed in immunocytes, such as macrophages in the peritumoral area. Siglec-15 expression was positive in 20/57 (35.09%) patients, with higher expression in patients with IDH-mutant gliomas and lower grade gliomas. The tumor diameter was significantly smaller in patients with positive Siglec-15 expression than in those with negative expression for all patients (P = 0.017) and for patients with IDH-mutant gliomas (P = 0.020). Moreover, ADC values of the tumor were significantly higher in patients with positive Siglec-15 expression than in those with negative expression for all patients (P = 0.027). The areas under the ROC curve (AUCs) of the diameter and ADC were 0.702 and 0.686, respectively. A combination of these two parameters generated an improved AUC of 0.762. Conclusion: Siglec-15 was expressed in immunocytes such as macrophages in the peritumoral area, with a positive rate of 35.09%. Positive Siglec-15 expression in diffuse gliomas was correlated with smaller tumor size and higher ADC values. [ABSTRACT FROM AUTHOR]

Background: Distinguishing between tumor recurrence and pseudoprogression (PsP) in high-grade glioma postoperatively is challenging. This study aims to enhance this differentiation using a combination of intratumoral and peritumoral radiomics. Purpose: To assess the effectiveness of intratumoral and peritumoral radiomics in improving the differentiation between high-grade glioma recurrence and pseudoprogression after surgery. Material and Methods: A total of 109 cases were randomly divided into training and validation sets, with 1316 features extracted from intratumoral and peritumoral volumes of interest (VOIs) on conventional magnetic resonance imaging (MRI) and apparent diffusion coefficient (ADC) maps. Feature selection was performed using the mRMR algorithm, resulting in intratumoral (100 features), peritumoral (100 features), and combined (200 features) subsets. Optimal features were then selected using PCC and RFE algorithms and modeled using LR, SVM, and LDA classifiers. Diagnostic performance was compared using area under the receiver operating characteristic curve (AUC), evaluated in the validation set. A nomogram was established using radscores from intratumoral, peritumoral, and combined models. Results: The combined model, utilizing 14 optimal features (8 peritumoral, 6 intratumoral) and LR as the best classifier, outperformed the single intratumoral and peritumoral models. In the training set, the AUC values for the combined model, intratumoral model, and peritumoral model were 0.938, 0.921, and 0.847, respectively; in the validation set, the AUC values were 0.841, 0.755, and 0.705. The nomogram model demonstrated AUCs of 0.960 (training set) and 0.850 (validation set). Conclusion: The combination of intratumoral and peritumoral radiomics is effective in distinguishing high-grade glioma recurrence from pseudoprogression after surgery. [ABSTRACT FROM AUTHOR]

Background and Purpose: To develop and test a decision tree for predicting contrast enhancement quality and shape using precontrast magnetic resonance imaging (MRI) sequences in a large adult‐type diffuse glioma cohort. Methods: Preoperative MRI scans (development/optimization/test sets: n = 31/38/303, male = 17/22/189, mean age = 52/59/56.7 years, high‐grade glioma = 22/33/249) were retrospectively evaluated, including pre‐ and postcontrast T1‐weighted, T2‐weighted, fluid‐attenuated inversion recovery, and diffusion‐weighted imaging sequences. Enhancement prediction decision tree (EPDT) was developed using development and optimization sets, incorporating four imaging features: necrosis, diffusion restriction, T2 inhomogeneity, and nonenhancing tumor margins. EPDT accuracy was assessed on a test set by three raters of variable experience. True enhancement features (gold standard) were evaluated using pre‐ and postcontrast T1‐weighted images. Statistical analysis used confusion matrices, Cohen's/Fleiss' kappa, and Kendall's W. Significance threshold was p <.05. Results: Raters 1, 2, and 3 achieved overall accuracies of.86 (95% confidence interval [CI]:.81‐.90),.89 (95% CI:.85‐.92), and.92 (95% CI:.89‐.95), respectively, in predicting enhancement quality (marked, mild, or no enhancement). Regarding shape, defined as the thickness of enhancing margin (solid, rim, or no enhancement), accuracies were.84 (95% CI:.79‐.88),.88 (95% CI:.84‐.92), and.89 (95% CI:.85‐.92). Intrarater intergroup agreement comparing predicted and true enhancement features consistently reached substantial levels (≥.68 [95% CI:.61‐.75]). Interrater comparison showed at least moderate agreement (group: ≥.42 [95% CI:.36‐.48], pairwise: ≥.61 [95% CI:.50‐.72]). Among the imaging features in the EPDT, necrosis assessment displayed the highest intra‐ and interrater consistency (≥.80 [95% CI:.73‐.88]). Conclusion: The proposed EPDT has high accuracy in predicting enhancement patterns of gliomas irrespective of rater experience. [ABSTRACT FROM AUTHOR]

Background: Diffuse intrinsic pontine glioma (DIPG) primarily affects pediatric patients. Data on the global incidence of DIPG remain sparse, especially in South Asia and low-middle-income countries like Pakistan. Methods: After exemption from the Ethics Review Committee, a retrospective study was conducted. Records of patients with DIPG at the Aga Khan Hospital in Karachi, from January 2010 to December 2022, were reviewed. Results: A total of 35 pediatric patients were managed for DIPG. The median age of the patients was 9, with 19 (54.3%) males and 16 (45.7%) females. Cranial nerve palsies were the most common complaint and were present in 19 (54.3%) patients, followed by headaches in 18 (51.4%), long tract signs in 14 (40%), ataxia/cerebellar symptoms in 14 (40%), and seizures in 5 (14.3%). MRI was the primary diagnostic tool, used alone or with CT in 32 (94.1%) patients; CT alone was used in only 2 (5.7%) patients. Biopsy was performed in 10 (28.6%) patients. Primary radiation therapy was administered to 14 (40%) patients with 5400 cGy in 30 fractions. All these patients received steroids while none of them received reirradiation. VP shunt surgery for hydrocephalus was performed in 9 (25.7%) patients. Over half (54.3%) refused treatment post-diagnosis, and 71.4% were lost to follow-up. Conclusion: Providing timely, quality multi-disciplinary care to DIPG patients within resource constraints remains challenging in Pakistan. However, recent developments show promise for improving DIPG care in the country. [ABSTRACT FROM AUTHOR]

Whether use of antidepressants is related to the risk of developing lower-grade (WHO grades 2-3) and higher-grade (WHO grade 4) glioma was investigated in this study. A registry-based case–control study was performed with 1283 glioma case patients and 6400 age-, sex-, and geographically matched control participants who were diagnosed in Sweden during 2009-2013. Conditional logistic regression was used to analyze whether selective serotonin reuptake inhibitors (SSRIs) or non-SSRIs were associated with the risk of developing lower- or higher-grade glioma in the study population. Our results show that use of antidepressant medication was not associated with the risk of developing glioma. We also performed a meta-analysis in which the data set from the present study was combined with results from 2 previous epidemiologic studies to answer the same questions. The meta-analysis showed a modest risk reduction of developing glioma in relation to antidepressant treatment (odds ratio = 0.90; 95% CI, 0.83-0.97) when all glioma subgroups and all forms of antidepressant medications were combined. In conclusion, it remains possible that antidepressants may have common monoaminergic mechanism(s) that reduce the risk of developing glioma. [ABSTRACT FROM AUTHOR]

Gliomas, the most prevalent type of neurological tumor, pose a challenging prognosis for patients. Recent studies have underscored the importance of inflammatory markers such as the neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), and monocyte/lymphocyte ratio (MLR) in predicting the prognosis of gliomas. We undertook a thorough meta-analysis to elucidate the role of these inflammatory markers in forecasting the prognosis of glioma patients. We extracted hazard ratios (HR) and their corresponding 95% confidence intervals (95% CI) from each study for analysis. To assess heterogeneity and identify influential studies, we conducted sensitivity analysis. Subgroup analysis was performed to investigate sources of heterogeneity, and we employed Egger's test to evaluate publication bias in the meta-analysis. Higher NLR levels were associated with shorter overall survival (HR = 1.46, 95% CI: 1.33–1.60) and progression-free survival (HR = 1.24, 95% CI: 1.04–1.48). There was no significant correlation between PLR levels and overall survival (HR = 1.01, 95% CI: 1.00–1.01) or progression-free survival (HR = 1.00, 95% CI: 0.98–1.02) in glioma patients. Elevated MLR levels were associated with decreased overall survival in glioma patients (HR = 1.78, 95% CI: 1.36–2.34). SII levels did not show any significant association with overall or progression-free survival in glioma patients (HR = 1.00, 95% CI: 0.99–1.01).In the sensitivity analysis, two studies potentially contributed to the instability. Subgroup analyses showed patient population and area were identified as potential sources of heterogeneity. Egger's test showed that there was publication bias in the relationship between NLR and PLR and overall survival (P < 0.05).All randomized controlled models, except for these, were not affected by publication bias. NLR and MLR are two reliable indicators of inflammation in the prognosis of glioma patients; PLR and SII do not have significant value in the prognosis of glioma patients. [ABSTRACT FROM AUTHOR]

Background: Treatment of patients with low-grade and high-grade gliomas is highly variable due to the large difference in survival expectancy. New non-invasive tools are needed for risk stratification prior to treatment. The urokinase plasminogen activator receptor (uPAR) is expressed in several cancers, associated with poor prognosis and may be non-invasively imaged using uPAR-PET. We aimed to investigate the uptake of the uPAR-PET tracer [68Ga]Ga-NOTA-AE105 in primary gliomas and establish its prognostic value regarding overall survival (OS), and progression-free survival (PFS). Additionally, we analyzed the proportion of uPAR-PET positive tumors to estimate the potential number of candidates for future uPAR-PRRT. Methods: In a prospective phase II clinical trial, 24 patients suspected of primary glioma underwent a dynamic 60-min PET/MRI following the administration of approximately 200 MBq (range: 83–222 MBq) [68Ga]Ga-NOTA-AE105. Lesions were considered uPAR positive if the tumor-to-background ratio, calculated as the ratio of TumorSUVmax-to-Normal-BrainSUVmean tumor-SUVmax-to-background-SUVmean, was ≥ 2.0. The patients were followed over time to assess OS and PFS and stratified into high and low uPAR expression groups based on TumorSUVmax. Results: Of the 24 patients, 16 (67%) were diagnosed with WHO grade 4 gliomas, 6 (25%) with grade 3, and 2 (8%) with grade 2. Two-thirds of all patients (67%) presented with uPAR positive lesions and 94% grade 4 gliomas. At median follow up of 18.8 (2.1–45.6) months, 19 patients had disease progression and 14 had died. uPAR expression dichotomized into high and low, revealed significant worse prognosis for the high uPAR group for OS and PFS with HR of 14.3 (95% CI, 1.8-112.3; P = 0.011), and HR of 26.5 (95% CI, 3.3–214.0; P = 0.0021), respectively. uPAR expression as a continuous variable was associated with worse prognosis for OS and PFS with HR of 2.7 (95% CI, 1.5–4.8; P = 0.0012), and HR of 2.5 (95% CI, 1.5–4.2; P = 0.00073), respectively. Conclusions: The majority of glioma patients and almost all with grade 4 gliomas displayed uPAR positive lesions underlining the feasibility of 68Ga-NOTA-AE105 PET/MRI in gliomas. High uPAR expression is significantly correlated with worse survival outcomes for patients. Additionally, the high proportion of uPAR positive gliomas underscores the potential of uPAR-targeted radionuclide therapy in these patients. Trail Registration: EudraCT No: 2016-002417-21; the Scientific Ethics Committee: H-16,035,303; the Danish Data Protection Agency: 2012-58-0004; clinical trials registry: NCT02945826, 26Oct2016, URL: https://classic.clinicaltrials.gov/ct2/show/NCT02945826. [ABSTRACT FROM AUTHOR]

A scalable platform for cell typing in the glioma microenvironment can improve tumor subtyping and immune landscape detection as successful immunotherapy strategies continue to be sought and evaluated. DNA methylation (DNAm) biomarkers for molecular classification of tumor subtypes have been developed for clinical use. However, tools that predict the cellular landscape of the tumor are not well-defined or readily available. We developed the Glioma Immune Microenvironment Composition Calculator (GIMiCC), an approach for deconvolution of cell types in gliomas using DNAm data. Using data from 17 isolated cell types, we describe the derivation of the deconvolution libraries in the biological context of selected genomic regions and validate deconvolution results using independent datasets. We utilize GIMiCC to illustrate that DNAm-based estimates of immune composition are clinically relevant and scalable for potential clinical implementation. In addition, we utilize GIMiCC to identify composition-independent DNAm alterations that are associated with high immune infiltration. Our future work aims to optimize GIMiCC and advance the clinical evaluation of glioma. [ABSTRACT FROM AUTHOR]

Background: Nicotinamide and tryptophan metabolism play important roles in regulating tumor synthesis metabolism and signal transduction functions. However, their comprehensive impact on the prognosis and the tumor immune microenvironment of glioma is still unclear. The purpose of this study was to investigate the association of nicotinamide and tryptophan metabolism with prognosis and immune status of gliomas and to develop relevant models for predicting prognosis and sensitivity to immunotherapy in gliomas. Methods: Bulk and single-cell transcriptome data from TCGA, CGGA and GSE159416 were obtained for this study. Gliomas were classified based on nicotinamide and tryptophan metabolism, and PPI network associated with differentially expressed genes was established. The core genes were identified and the risk model was established by machine learning techniques, including univariate Cox regression and LASSO regression. Then the risk model was validated with data from the CGGA. Finally, the effects of genes in the risk model on the biological behavior of gliomas were verified by in vitro experiments. Results: The high nicotinamide and tryptophan metabolism is associated with poor prognosis and high levels of immune cell infiltration in glioma. Seven of the core genes related to nicotinamide and tryptophan metabolism were used to construct a risk model, and the model has good predictive ability for prognosis, immune microenvironment, and response to immune checkpoint therapy of glioma. We also confirmed that high expression of TGFBI can lead to an increased level of migration, invasion, and EMT of glioma cells, and the aforementioned effect of TGFBI can be reduced by FAK inhibitor PF-573,228. Conclusions: Our study evaluated the effects of nicotinamide and tryptophan metabolism on the prognosis and tumor immune microenvironment of glioma, which can help predict the prognosis and sensitivity to immunotherapy of glioma. [ABSTRACT FROM AUTHOR]

Dynamic contrast-enhanced MRI (DCE-MRI) is increasingly used to non-invasively image blood-brain barrier leakage, yet its clinical utility has been hampered by issues such as noise and partial volume artifacts. In this retrospective study involving 306 adult patients with diffuse glioma, we applied deep learning-based super-resolution and denoising (DLSD) techniques to enhance the signal-to-noise ratio (SNR) and resolution of DCE-MRI. Quantitative analysis comparing standard DCE-MRI (std-DCE) and DL-enhanced DCE-MRI (DL-DCE) revealed that DL-DCE achieved significantly higher SNR and contrast-to-noise ratio (CNR) compared to std-DCE (SNR, 52.09 vs 27.21; CNR, 9.40 vs 4.71; P < 0.001 for all). Diagnostic performance assessed by the area under the receiver operating characteristic curve (AUROC) showed improved differentiation of WHO grades based on a pharmacokinetic parameter (AUC, 0.88 vs 0.83, P = 0.02), while remaining comparable to std-DCE in other parameters. Analysis of arterial input function (AIF) reliability demonstrated that exhibited superior agreement compared to , as indicated by mostly higher intraclass correlation coefficients (Time to peak, 0.79 vs 0.43, P < 0.001). In conclusion, DLSD significantly enhances both the image quality and reliability of DCE-MRI in patients with diffuse glioma, while maintaining or improving diagnostic performance. [ABSTRACT FROM AUTHOR]

Oncostreams are self-organized structures formed by spindle-like, elongated, self-propelled cells recently described in glioblastomas and especially in gliosarcomas. Cells within these structures either move as large clusters in one main direction, flocks, or as linear, intermingling collections of cells advancing in opposite directions, streams. Round, passive cells are also observed, either inside or segregated from the oncostreams. Here we generalize a recently formulated particle-field approach to investigate the genesis and evolution of these structures, first showing that, in systems consisting only of identical self-propelled cells, both flocks and streams emerge as self-organized dynamic configurations. Flocks are the more stable configurations, while streams are transient and usually originate in collisions between flocks. Stream degradation is easier at low self-propulsion speeds. In systems consisting of both motile and passive cells, the latter block stream formation and accelerate their degradation and flock stabilization. Since the flock appears to be the most effective invasive structure, we thus argue that a phenotype mixture (motile and passive cells) may favor glioblastoma invasion. hlBy relating cellular properties to the observed outcome, our model shows that oncostreams are self-organized structures that result from the interplay between speed, shape, and steric repulsion. [ABSTRACT FROM AUTHOR]

High-grade gliomas are the most prevalent neurooncological desease in adults, their incidence increases with age, peaking in the seventh decade. This paper aims to address how to select patients for surgical resection by identifying pre-surgical predictors of 12-month mortality in newly diagnosed HGG patients aged ≥ 75 years. A prognostic score will be proposed to guide surgical decisions based on expected survival. Retrospective observational single-center cohort study was carried out at the "Città della Salute e della Scienza-Molinette" University Hospital in Turin, Italy. All consecutive patients aged ≥ 75 years newly diagnosed with HGG were included, regardless of whether they underwent surgical resection. Clinical, radiological, histological and molecular data were collected.Variables potentially available at the time of diagnosis were considered to develop a multivariable logistic regression predictive model, with 12-months overall survival as the dependent variable. 102 patients aged 75 years or older received a new diagnosis of high-grade glioma, of whom 68 underwent surgical resection. Patients undergoing surgery were slightly younger (76.9 vs 79.0 years, p = 0.007) and had better performance status (median KPS 80 vs 70). Most tumors undergoing surgery were localized in cortical or subcortical non-motor areas (p < 0.001) and less frequently deep-seated (p = 0.023) or multifocal (p < 0.001). A predictive model, the DAK-75 score, was developed: the AUROC of the final model was 0.822 (95% CI 0.741–0.902). The score includes clinical presentation, tumor location, and KPS, ranging from 0 to 20, categorizing risk scores into low-risk and high-risk groups (< or > 8). Higher scores corresponded to fewer surgical patients and higher one-year mortality rates (92.2% vs 47.1%, p < 0.001). DAK-75 score may represent a valuable tool in the decision-making process for neurosurgical intervention in elderly patients diagnosed with HGG. Further studies are needed to externally and prospectively validate the scoring system. [ABSTRACT FROM AUTHOR]

Interleukin-18, a member of the interleukin − 1 family of cytokines, is upregulated in glioma. However, its effects on glioma remain unclear. This study aimed to explore the role and underlying mechanisms of interleukin-18 expression in glioma. Here, we demonstrated that interleukin-18 enhanced resistance to temozolomide by increasing proliferation and inhibiting apoptosis in cultured glioma cells. Further in vivo studies revealed that interleukin-18 promoted temozolomide resistance in BALB/c nude mice bearing tumor. Mechanical exploration indicated that interleukin-18 stimulation could activate the PI3K/AKT signaling pathway in glioma cells, and PI3K inhibition could reduce the temozolomide resistance promoted by interleukin-18. We found that interleukin-18 upregulated CD274 expression in glioma, revealing its potential effects on the microenvironment. Furthermore, we established a tumor xenograft model and explored the therapeutic efficacy of anti-interleukin-18 monoclonal antibody. Targeting interleukin-18 prolonged survival and attenuated CD274 expression in the mice bearing tumor. Combined treatment with anti-interleukin-18 and anti-PD-1 monoclonal antibody showed better efficacy in suppressing tumor growth than either treatment alone in mice bearing tumor. Collectively, these data present that interleukin-18 promotes temozolomide chemoresistance in glioma cells via PI3K/Akt activation and establishes an immunosuppressive milieu by modulating CD274. This study highlights the therapeutic value of interleukin-18 in glioma. [ABSTRACT FROM AUTHOR]

Pilocytic astrocytoma (PA) is classified as a Grade I benign neuroglial tumor. The extent of surgical resection is a critical factor influencing the prognosis for patients with PA. In prior researches of PA, the extent of surgical resection is generally categorized into GTR, STR and biopsy. In some researches on brain tumor surgeries, the extent of resection also includes GTL. There is no existing research specifically comparing the efficacy of GTR versus GTL in PA treatment. In this study, the data we used are from the SEER database. We categorized the extent of resection into GTL, GTR, STL, STR, biopsy, and no surgery based on SEER classification of surgical procedures, to investigate the impact of extent of resection on PA patient survival. A multivariate logistic regression model was utilized to acquire odds ratios (OR) for different extent of resection. Survival outcomes across different extent of resection (GTL, GTR, STL, STR, biopsy, no surgery) were assessed using Kaplan–Meier survival curve analysis, with curve comparisons conducted via log-rank tests. The impact of various risk factors on survival was assessed using the Cox proportional hazards model. The hazard ratio (HR) was employed to quantify the influence of one or more factors on overall survival throughout the follow-up period. Multivariate Cox analysis revealed that age, tumor location, extent of resection, as well as the application of radiotherapy and chemotherapy, all significantly impacted prognosis. Compared to GTL, GTR did not significantly increase the risk of mortality (HR 1.17; 95% CI 0.73–1.86, p = 0.5). Furthermore, there was no statistically significant difference between the Kaplan–Meier survival curves of the two groups (p = 0.18). We employed propensity score matching (PSM) to balance the differences in baseline characteristics of patients receiving chemotherapy or radiotherapy. A total of 4429 patients were included in this study. Age, diagnosis period, race, tumor size, and tumor location as influential on the extent of resection. Age, tumor location, extent of resection, and application of radiotherapy and chemotherapy influenced the survival of PA patients. The Kaplan–Meier survival curves revealed that the long-term survival rate for GTR is slightly higher than that for GTL. The PSM analysis revealed that the application of radiotherapy and chemotherapy was associated with the reduction of overall survival in PA patients. In conclusion, there was no significant difference in survival between GTR and GTL, so GTR with less damage was preferred. The application of radiotherapy and chemotherapy can reduce overall survival of patients with PA. [ABSTRACT FROM AUTHOR]

In recent years, CD9 has been extensively studied as a potential biomarker for cancer. However, the biological role of CD9 in gliomas remains unclear. This study investigates the function of CD9 in gliomas and its molecular mechanisms. Utilizing pan-cancer analysis with TCGA, CGGA, and GEO databases, differential expression of CD9 was observed in 11 tumor types within the TCGA cohort, and it was associated with patient survival rates. Analysis of the CGGA glioma database revealed that patients with high CD9 expression had lower survival rates. The area under the ROC curve (AUC) for GSE16011 was greater than 0.7, indicating a high discriminative ability. Through gene set enrichment analysis (GSEA), immune-related analysis, and CD9 mutation detection, CD9 was found to have the strongest correlation with neutrophil involvement (cor = 0.30, P < 0.05), and the high CD9 expression group exhibited higher rejection responses and TIDE scores, suggesting a lower likelihood of successful immunotherapy. The high CD9 expression group was more sensitive to 81 drugs, indicating potential therapeutic effects for gliomas. Furthermore, overexpression of CD9 in gliomas may be associated with gene mutations. Down-regulation or up-regulation of CD9 expression in the glioblastoma cell line LN229 showed that CD9 could positively regulate the migratory ability of LN229 cells. Further, several marker genes, such as VEGFR-2, TGF-β1, CASP1 and PI3K, were down regulated in CD9 knockdown cell lines and up regulated in CD9 overexpression cell lines, compared with control cell line. This study preliminarily explores the role of CD9 in gliomas and its prognostic value, providing new insights for personalized treatment strategies in glioma therapy. [ABSTRACT FROM AUTHOR]

Astrocytomas that harbor recurrent genomic alterations in MYB or MYBL1 are a group of Pediatric-type diffuse low-grade gliomas that were newly recognized in the 2021 WHO Classification of Tumors of the Central Nervous System. These tumors are described in the WHO classification as harboring fusions in MYB or MYBL1. In this report, we examine 14 consecutive cases in which a MYB or MYBL1 alteration was identified, each with diagnostic confirmation by genome-wide DNA methylation profiling (6 Angiocentric gliomas and 8 Diffuse astrocytomas, MYB- or MYBL1-altered), for their specific genomic alterations in these genes. Using RNA sequencing, we find productive in-frame fusions of the MYB or MYBL1 genes in only 5/14 cases. The remaining 9 cases show genomic alterations that result in truncation of the gene, without evidence of an in-frame fusion partner. Gene expression analysis showed overexpression of the MYB(L1) genes, regardless of the presence of a productive fusion. In addition, QKI, a recognized fusion partner common in angiocentric glioma, was generally up-regulated in these 14 cases, compared to a cohort comprising >1000 CNS tumors of various types, regardless of whether a genomic alteration in QKI was present. Overall, the results show that truncations, in the absence of a productive fusion, of the MYB(L1) genes can likely drive the tumors and have implications for the analysis and diagnosis of Angiocentric glioma and Diffuse astrocytoma, MYB- or MYBL1-altered, especially for cases that are tested on panels designed to focus on fusion detection. [ABSTRACT FROM AUTHOR]

The role of long non-coding RNAs (lncRNAs) in malignant cell transformation remains elusive. We previously identified an enhancer-associated lncRNA, LINC01116 (named HOXDeRNA), as a transformative factor converting human astrocytes into glioma-like cells. Employing a combination of CRISPR editing, chromatin isolation by RNA purification coupled with sequencing (ChIRP-seq), in situ mapping RNA-genome interactions (iMARGI), chromatin immunoprecipitation sequencing (ChIP-seq), HiC, and RNA/DNA FISH, we found that HOXDeRNA directly binds to CpG islands within the promoters of 35 glioma-specific transcription factors (TFs) distributed throughout the genome, including key stem cell TFs SOX2, OLIG2, POU3F2, and ASCL1, liberating them from PRC2 repression. This process requires a distinct RNA quadruplex structure and other segments of HOXDeRNA, interacting with EZH2 and CpGs, respectively. Subsequent transformation activates multiple oncogenes (e.g., EGFR, miR-21, and WEE1), driven by the SOX2- and OLIG2-dependent glioma-specific super enhancers. These results help reconstruct the sequence of events underlying the process of astrocyte transformation, highlighting HOXDeRNA's central genome-wide activity and suggesting a shared RNA-dependent mechanism in otherwise heterogeneous and multifactorial gliomagenesis. [Display omitted] • HOXDeRNA transforms astrocytes into glioma-like stem cells • HOXDeRNA directly binds to PRC2-covered CpG islands in the promoters of glioma driver genes • HOXDeRNA removes EZH2 through its RNA quadruplex sequences Deforzh et al. demonstrate the ability of the lncRNA HOXDeRNA to transform astrocytes into glioma-like stem cells by sequestering and protecting key glioma genes from Polycomb2 repression in an RNA quadruplex-dependent manner. [ABSTRACT FROM AUTHOR]

Aging is an important risk factor for tumorigenesis. Metabolic reprogramming is a hallmark of both aging and tumor initiation. However, the manner in which the crosstalk between aging and metabolic reprogramming affects the tumor microenvironment (TME) to promote tumorigenesis was poorly explored. We utilized a computational approach proposed by our previous work, MMP3C (Modeling Metabolic Plasticity by Pathway Pairwise Comparison), to characterize aging-related metabolic plasticity events using pan-cancer bulk RNA-seq data. Our analysis revealed a high degree of metabolically organized heterogeneity across 17 aging-related cancer types. In particular, a higher degree of several energy generation pathways, i.e., glycolysis and impaired oxidative phosphorylation, was observed in older patients. Similar phenomena were also found via single-cell RNA-seq analysis. Furthermore, those energy generation pathways were found to be weakened in activated T cells and macrophages, whereas they increased in exhausted T cells, immunosuppressive macrophages, and Tregs in older patients. It was suggested that aging-induced metabolic switches alter glucose utilization, thereby influencing immune function and resulting in the remodeling of the TME. This work offers new insights into the associations between tumor metabolism and the TME mediated by aging, linking with novel strategies for cancer therapy. [ABSTRACT FROM AUTHOR]

Simple Summary: This study explored the current practices in the real world for grade 2 glioma, an uncommon primary brain cancer. Leveraging the prospective BRAIN registry, this study demonstrates that whilst sequential radiotherapy and chemotherapy improve progression-free survival in high-risk grade 2 glioma, the majority of patients are observed following surgery. In high-risk patients who are observed, 61% remain progression-free at 12 months, with 10% being progression-free at 5 years. This clinically meaningful progression-free survival suggests that validated biomarkers beyond the usual definition of high-risk are required to better inform patient management. Factors contributing to decision-making are underway. Background: Grade-2 gliomas (G2-glioma) are uncommon. In 2016, RTOG9802 established the addition of chemotherapy after radiation (CRT) as a new standard of care for patients with high-risk G2-glioma, defined as subtotal resection or age ≥40 yrs. Here, we report current practices using real-world data. Methods: Patients diagnosed with G2-glioma from 1 January 2016 to 31 December 2022 were identified in BRAIN, a prospective clinical registry collecting data on patients with brain tumours. High- and low-risk were defined as per RTOG9802. Two time periods, January 2016–December 2019 (TP1) and January 2020–December 2022 (TP2), were defined. Survival was estimated using the Kaplan–Meier method. Results: 224 patients were identified. Overall, 38 (17%) were low-risk, with 35 (91%) observed without further treatment. A total of 186 (83%) were high-risk, with 96 (52%) observed, 63 (34%) receiving CRT, and 19 (10%) receiving radiation. Over time, CRT use increased (TP1 vs. TP2: 22% vs. 36%, p = 0.004), and the rate of biopsy (TP1 vs. TP2: 35% vs. 20%, p = 0.02) and radiotherapy alone (TP1 vs. TP2: 14% vs. 4%, p = 0.01) decreased. Median progression-free survival (PFS) was significantly longer in high-risk patients who received CRT (NR) over observation (39 months) (HR 0.49, p = 0.007). In high-risk patients who were observed, 59 (61%) were progression-free at 12 months and 10 (10%) at 5 years. OS data remains immature. Conclusion: Congruent with RTOG9802, real-world BRAIN data shows CRT is associated with improved PFS compared to observation in high-risk G2-glioma. Whilst CRT use has increased over time, observation after surgery remains the most common strategy, with some high-risk patients achieving clinically meaningful PFS. Validated biomarkers are urgently required to better inform patient management. [ABSTRACT FROM AUTHOR]

Background/Objectives: High-grade gliomas are the most common primary malignant brain tumors in adults. These neoplasms remain predominantly incurable due to the genetic diversity within each tumor, leading to varied responses to specific drug therapies. With the advent of new targeted and immune therapies, which have demonstrated promising outcomes in clinical trials, there is a growing need for image-based techniques to enable early prediction of treatment response. This study aimed to evaluate the potential of radiomics and artificial intelligence implementation in predicting progression-free survival (PFS) in patients with highest-grade glioma (CNS WHO 4) undergoing a standard treatment plan. Methods: In this retrospective study, prediction models were developed in a cohort of 51 patients with pathologically confirmed highest-grade glioma (CNS WHO 4) from the authors' institution and the repository of the Cancer Imaging Archive (TCIA). Only patients with confirmed recurrence after complete tumor resection with adjuvant radiotherapy and chemotherapy with temozolomide were included. For each patient, 109 radiomic features of the tumor were obtained from a preoperative magnetic resonance imaging (MRI) examination. Four clinical features were added manually—sex, weight, age at the time of diagnosis, and the lobe of the brain where the tumor was located. The data label was the time to recurrence, which was determined based on follow-up MRI scans. Artificial intelligence algorithms were built to predict PFS in the training set (n = 75%) and then validate it in the test set (n = 25%). The performance of each model in both the training and test datasets was assessed using mean absolute percentage error (MAPE). Results: In the test set, the random forest model showed the highest predictive performance with 1-MAPE = 92.27% and a C-index of 0.9544. The decision tree, gradient booster, and artificial neural network models showed slightly lower effectiveness with 1-MAPE of 88.31%, 80.21%, and 91.29%, respectively. Conclusions: Four of the six models built gave satisfactory results. These results show that artificial intelligence models combined with radiomic features could be useful for predicting the progression-free survival of high-grade glioma patients. This could be beneficial for risk stratification of patients, enhancing the potential for personalized treatment plans and improving overall survival. Further investigation is necessary with an expanded sample size and external multicenter validation. [ABSTRACT FROM AUTHOR]

Background: For glioma patients, the long-term advantages of dendritic cells (DCs) immunization remain unknown. It is extremely important to develop new treatment strategies that enhance the immunotherapy effect of DC-based vaccines. DCs exposed to glioma stem cells (GSCs) are considered promising vaccines against glioma. Methods: Glioma stem cells were isolated from mouse glioma GL261 cells (GCs). Both were subjected to severe (47°C) and mild (42°C) heat shock to induce immunogenic cell death (ICD). Membrane mobilization of calreticulin (CRT) and release of heat shock proteins (HSPs) were detected by flow cytometry. Dendritic cells were then exposed to heat-inactivated cells and co-culturing of T cells tested for immunotherapeutic efficacy in vitro. In vivo, we investigated the GSC targeting effect of the GSC-DC vaccine combined with CD47 blockade. Results: Heat shock induced ICD in GCs and GSCs, as indicated by significant release of calreticulin, HSP70, and HSP90. Heat shock condition ICD lysates induce maturation and activation-associated marker expression on monocyte-derived DCs. Accordingly, DCs pulsed with GCs and GSCs inactivated reduced colony formation, sphere formation, migration, and invasion of glioma and GSCs in vitro. Glioma stem cell-DC vaccine in combination with anti-CD47 antibody significantly enhanced survival in mice with glioma, induced production of interferon (IFN)-γ, and enhanced T-cell expansion in vivo. Of note, DCs pulsed with inactivated GSCs were more effective to control tumor growth than DCs pulsed with inactive GCs. Conclusions: Severe heat shock induces ICD in vitro. These data showed that administration of anti-CD47 antibody combined with GSC-DC vaccine may represent an effective immunotherapeutic strategy for cancer patients in clinical. [ABSTRACT FROM AUTHOR]

Background: Exosomes (EXO) play crucial roles in intercellular communication and glioma microenvironment modulation. Tumor-associated macrophages are more likely to become M2-like type macrophages in the immunosuppressive microenvironment. Here, we aimed to investigate the effects and molecular mechanisms of hypoxic glioma-derived exosomes mediated M2-like macrophage polarization. Methods: Highly expressed miRNAs in exosomes derived from glioma cells cultured under hypoxia condition compared to normoxic condition were identified through microRNA sequencing. The polarization status of macrophages was determined using qRT-PCR, Western blotting, flow cytometry, and immunohistochemistry. By using RNA-seq, we aimed to identify the downstream target genes regulated by miR-25-3p in macrophages and investigate the mechanistic pathways through which it exerts its effects. The proliferation and migration capabilities of glioma cells were assessed through EdU, Transwell assays, and in vivo experiments. Results: We found that miR-25-3p was upregulated in the exosomes derived from hypoxic glioma cells and can be transferred to the macrophage. In macrophages, miR-25-3p downregulates the expression of PHLPP2, thereby activating the PI3K-AKT-mTOR signaling pathway, ultimately leading to macrophage M2 polarization. As part of a feedback loop, M2-polarized macrophages can, in turn, promote malignant glioma progression. Conclusion: Our study reveals that miR-25-3p from hypoxic glioma cells is delivered to macrophages via exosomes as a mediator, promoting M2 polarization of macrophages through the miR-25-3p/PHLPP2/PI3K-AKT signaling pathway. This study suggests that targeted interventions to modulate miR-25-3p expression, transmission, or inhibition of PI3K-AKT pathway activation can disrupt the immune-suppressive microenvironment, providing a novel approach for immunotherapy in gliomas. [ABSTRACT FROM AUTHOR]

Glioma cells hijack developmental programs to control cell state. Here, we uncover a glioma cell state-specific metabolic liability that can be therapeutically targeted. To model cell conditions at brain tumor inception, we generated genetically engineered murine gliomas, with deletion of p53 alone (p53) or with constitutively active Notch signaling (N1IC), a pathway critical in controlling astrocyte differentiation during brain development. N1IC tumors harbored quiescent astrocyte-like transformed cell populations while p53 tumors were predominantly comprised of proliferating progenitor-like cell states. Further, N1IC transformed cells exhibited increased mitochondrial lipid peroxidation, high ROS production and depletion of reduced glutathione. This altered mitochondrial phenotype rendered the astrocyte-like, quiescent populations more sensitive to pharmacologic or genetic inhibition of the lipid hydroperoxidase GPX4 and induction of ferroptosis. Treatment of patient-derived early-passage cell lines and glioma slice cultures generated from surgical samples with a GPX4 inhibitor induced selective depletion of quiescent astrocyte-like glioma cell populations with similar metabolic profiles. Collectively, these findings reveal a specific therapeutic vulnerability to ferroptosis linked to mitochondrial redox imbalance in a subpopulation of quiescent astrocyte-like glioma cells resistant to standard forms of treatment. Synopsis: The interdependence of oncogenic drivers, cell proliferation and energy metabolism in glioma resistance remains unclear. This study uncovers a unique, targetable metabolic vulnerability of quiescent astrocyte-like glioma cells otherwise resistant to standard forms of treatment. Activating Notch at early stages of gliomagenesis in a retrovirus-induced mouse model drives tumors with an astrocyte-like phenotype. Astrocyte-like glioma cells show decreased mitochondrial respiration and altered complex I function, but increased lipid peroxidation and ROS production. Astrocyte-like glioma cells are specifically vulnerable to the inhibition of the lipid hydroperoxidase GPX4 and induction of ferroptosis. Treating acute slices generated from human glioma surgical samples with GPX4 inhibitors selectively depletes the quiescent astrocyte-like tumor cells. Quiescent astrocyte-like glioma cells show abnormal energy metabolism, which renders them sensitive to ferroptosis-inducing drugs. [ABSTRACT FROM AUTHOR]

Background Methods Results Conclusions Procollagen C‐proteinase enhancer (PCOLCE) promotes tumor progression in multiple cancers. However, the specific role of PCOLCE in gliomas remains enigmatic. In this study, we focused on analyzing PCOLCE expression and its correlation with clinicopathological parameters in glioma specimens; moreover, we explored the effects of PCOLCE in glioma proliferation in vitro and in vivo.A tissue microarray containing 159 human glioma specimens was pressed to explore the correlation between PCOLCE expression and the survival of glioma patients. Cell Counting Kit‐8 (CCK8), colony formation, and immunoblot assays were used to detect the role of PCOLCE on cell proliferation in glioma. Furthermore, the in vivo role of PCOLCE was investigated using a subcutaneous glioma xenograft model.The expression of PCOLCE was higher in grade III and IV gliomas than in grade I and II gliomas. High PCOLCE expression was related to a remarkably worse prognosis in glioma patients. Additionally, PCOLCE downregulation impeded glioma cell proliferation. Furthermore, PCOLCE knockdown markedly abrogated p‐ERK expression in glioma cells, whereas, it negligibly influenced p38 and JNK signaling.These results indicate that PCOLCE is a feasible prognostic biomarker for glioma, and PCOLCE‐induced activation of ERK signaling may be a pro‐growth mechanism in glioma cells. [ABSTRACT FROM AUTHOR]

Prior studies have described the complex interplay that exists between glioma cells and neurons; however, the electrophysiological properties endogenous to glioma cells remain obscure. To address this, we employed Patch-sequencing (Patch-seq) on human glioma specimens and found that one-third of patched cells in IDH mutant (IDHmut) tumors demonstrate properties of both neurons and glia. To define these hybrid cells (HCs), which fire single, short action potentials, and discern if they are of tumoral origin, we developed the single cell rule association mining (SCRAM) computational tool to annotate each cell individually. SCRAM revealed that HCs possess select features of GABAergic neurons and oligodendrocyte precursor cells, and include both tumor and non-tumor cells. These studies characterize the combined electrophysiological and molecular properties of human glioma cells and describe a cell type in human glioma with unique electrophysiological and transcriptomic properties that may also exist in the non-tumor brain. [Display omitted] • Patch-seq identifies spiking tumor cells in human glioma • Spiking glioma cells exhibit GABAergic and glial properties in IDH mutant gliomas • SCRAM algorithm accurately annotates tumor and non-tumor cells from Patch-seq data • Spiking glioma cells confer increased survival in IDH mutant glioma Curry et al. employ simultaneous electrophysiological and genomic profiling of single cells from human glioma to identify glioma cells that fire action potentials (APs). This study introduces single cell rule association mining (SCRAM), a computational tool that provides integrated genomic and transcriptomic profiles for each single cell. [ABSTRACT FROM AUTHOR]

Malignant (high-grade) gliomas are aggressive intrinsic brain tumors that diffusely infiltrate the brain parenchyma. They comprise of World Health Organization (WHO) grade III and IV gliomas. Ionizing radiation or irradiation (IR) is frequently utilized in the treatment of both primary as well as metastatic brain tumors. On the contrary, macrophages (MΦ) are the most copious infiltrating immune cells of all the different cell types colonizing glioma. MΦ at tumor milieu are referred to as tumor-associated macrophages (TAMΦ). In malignant gliomas milieu, TAMΦ are also polarized into two distinct phenotypes such as M1 TAMΦ or M2 TAMΦ, which are capable of inhibiting or promoting tumor growth, respectively. Cranial-IR such as x- and γ-IR are sufficient to induce the migration of peripherally derived MΦ into the brain parenchyma. The IR facilitate a more immunosuppressive milieu via the stimulation of efferocytosis in TAMΦ, and an upsurge of tumor cell engulfment by TAMΦ exhibited detrimental effect of the anti-tumoral immune response in glioma. The MΦ inside the tumor mass are associated with multiple phenomena that include IR resistance and enrichment of the M2 MΦ after IR is able to facilitate glioblastoma multiforme (GBM) recurrence. Reviews on the role of cranial IR-induced peripheral and brain-engrafting macrophages (BeMΦ) in glioma are lacking. Specifically, most studies on peripheral, intrinsic as well as beMΦ on IR focus on WHO grade III and IV. Thus, this review precisely focuses primary on WHO grade III as well as IV gliomas. [ABSTRACT FROM AUTHOR]

This study investigates the prognostic significance of SH3 and multiple ankyrin repeat domains 2 (SHANK2) gene expression in glioma patients, using data from The Cancer Genome Atlas (TCGA), the Genotype‐Tissue Expression (GTEx) project, and the Gene Expression Omnibus (GEO). Through comprehensive analysis, we found a significant association between higher SHANK2 expression and improved survival outcomes across various glioma subtypes. To further validate the clinical relevance of SHANK2, we conducted cellular experiments involving siRNA‐mediated knockdown of SHANK2 in U87 and A172 glioma cell lines. Quantitative real‐time PCR (qPCR) and Western blot analyses confirmed the successful knockdown of SHANK2, and subsequent MTT assays revealed that silencing SHANK2 significantly promoted glioma cell proliferation. These findings underscore the potential role of SHANK2 as a tumor suppressor in glioma. The study also introduces a multivariate prognostic model incorporating SHANK2, providing a novel perspective on glioma prognosis. While the retrospective nature of the study presents limitations, our results suggest that SHANK2 expression could serve as a valuable biomarker for glioma prognosis and inform future therapeutic strategies. [ABSTRACT FROM AUTHOR]

Background: Our previous study found that tumor suppressor nitrogen permease regulator like-2(NPRL2) is frequently downregulated in glioma, leading to malignant growth. However, NPRL2-mediated crosstalk between tumor cells and immune cells remains unclear. Methods: The regulatory effects of NPRL2 on tripartite motif–containing protein 16(TRIM16) dependent ubiquitination degradation of Galectin-3(Gal-3) were explored. The effects of Gal-3 on copper uptake, immunocompetence and cuproptosis were investigated in CD8+T lymphocytes(CD8+T cells). The ability of NPRL2 to protect CD8+T cells from Gal-3 damage was evaluated. Furthermore, the correlations among NPRL2, TRIM16, Gal-3 and CD8+T cell accumulation were analyzed in glioma clinical specimens. Results: NPRL2 increased the TRIM16 expression via inactivation of ERK1/2, which in turn promoted the ubiquitination-mediated degradation of Gal-3 and diminished Gal-3 release from glioma cells. Moreover, Gal-3 accelerated copper uptake and triggered cuproptosis in CD8+T cells, whereas NPRL2 increased CD8+T cell recruitment and prevented impairment of CD8+T cells by Gal-3. Clinical samples revealed that NPRL2 expression was positively associated with TRIM16 expression and negatively correlated with Gal-3, but Gal-3 expression was negatively associated with CD8+T cell accumulation. Conclusion: Glioma-derived NPRL2/TRIM16/Gal-3 axis participates in the regulation of CD8+T cell cuproptosis, which provides a promising strategy to rescue the immune activity of CD8+T cells and reverse immunosuppression in glioma. [ABSTRACT FROM AUTHOR]

Brain tumor volumes as assessed by magnetic resonance imaging (MRI) do not always spatially overlap with biological tumor volumes (BTV) measured by [18F]Fluoroethyltyrosine positron emission tomography ([18F]FET PET). We prospectively investigated volumetric patterns based on the extent of tumor volume overlap between the two modalities. Eighty-six patients with newly diagnosed glioma who had undergone MRI and [18F]FET PET between 2007 and 2009 were included in this prospective study and (re-)classified according to CNS WHO 2021 (Classification of Tumors of the Central Nervous System by the World Health Organization). Four different patterns of volume overlap were defined mathematically according to the extent of overlap between MRI-based T2 tumor volume (non-enhancing tumor volume, nCEV) and BTVs. Progression-free (PFS) and overall survival (OS) were determined. Seventy patients were diagnosed with isocitrate dehydrogenase wildtype (IDHwt) glioblastoma and 16 with IDH-mutant glioma, respectively. The most common pattern was characterized by a larger non-contrast-enhancing tumor volume (nCEV) that enclosed all or most of the BTV and was observed in 46 patients (54%) (pattern 1). This pattern was more frequent in IDH-mutant gliomas than in IDH-wildtype glioblastoma (81% versus 47%, p = 0.02). In multivariate analyses, pattern 1 was associated with prolonged PFS (HR 0.59; 95 CI 0.34-1.0; p = 0.05), but not OS (HR 0.66; 95 CI 0.4–1.08; p = 0.1). For OS, presence of an IDH mutation (p = 0.05) and lower age (p = 0.03) were associated with prolonged OS. The spatial relation between nCEV and BTV varies within and between glioma entities. Most frequently, a larger nCEV encases the BTV. Some patients show spatially dissociated nCEVs and BTVs. Not accounting for this phenomenon in surgery or radiotherapy planning might lead to undertreatment. [ABSTRACT FROM AUTHOR]

(1) Background: Clinical aspects like sex, age, Karnofsky Performance Scale (KPS) and psychosocial distress can affect the health-related quality of life (HR-QoL) and treatment satisfaction of patients with malignant isocitrate dehydrogenase wild-type (IDHwt) gliomas and caregivers. (2) Methods: We prospectively investigated the HR-QoL and patient/caregiver treatment satisfaction in a cross-sectional study with univariable and multiple regression analyses. Questionnaires were applied to investigate the HR-QoL (EORTC QLQ-C30, QLQ-BN20) and treatment satisfaction (EORTC PATSAT-C33). (3) Results: A cohort of 61 patients was investigated. A higher KPS was significantly associated with a better HR-QoL regarding the functional scales of the EORTC QLQ-C30 (p < 0.004) and a lower symptom burden regarding the EORTC QLQ-BN20 (p < 0.001). The patient treatment satisfaction was significantly poorer in the patients older than 60 years in the domain of family involvement (p = 0.010). None of the investigated aspects showed a significant impact on the treatment satisfaction of caregivers. (4) Conclusions: We demonstrated that in patients with IDHwt gliomas, the KPS was the most important predictor for a better HR-QoL in functional domains. Data on the HR-QoL and treatment satisfaction in patients with IDHwt gliomas and their caregivers are rare; therefore, further efforts should be made to improve supportive care in this highly distressed cohort. [ABSTRACT FROM AUTHOR]

Simple Summary: Gliomas are diverse types of tumors originating from glial cells. Among these tumors, glioblastoma multiforme (GBM) is the most aggressive form and has a poor prognosis and high mortality rate, with treatment success largely influenced by patient age, tumor location, and genetic mutations. Glioma cells can reprogram their tumor microenvironment (TME) to support tumor proliferation and survival, interacting with other cells through cytokines and growth factors. The TME of gliomas is highly heterogeneous, complex, and often immunosuppressive, interfering with treatment strategies. Current therapeutic strategies focus on modulating immune cell activities and enhancing anti-tumor responses. T-cell-based immunotherapies are being explored to target glioma cells. These include chimeric antigen receptor (CAR) T-cell therapy and T-cell receptor (TCR) therapy, which involve engineering T cells to recognize tumor antigens. However, these therapies face multiple challenges including tumor heterogeneity, immunosuppression by T cell exhaustion, and altered antigen presentation, etc. Future research should focus on boosting T cell functions, targeting immune checkpoints, and developing more effective delivery methods to improve treatment outcomes for glioma patients. Glioma is known for its immunosuppressive microenvironment, which makes it challenging to target through immunotherapies. Immune cells like macrophages, microglia, myeloid-derived suppressor cells, and T lymphocytes are known to infiltrate the glioma tumor microenvironment and regulate immune response distinctively. Among the variety of immune cells, T lymphocytes have highly complex and multifaceted roles in the glioma immune landscape. T lymphocytes, which include CD4+ helper and CD8+ cytotoxic T cells, are known for their pivotal roles in anti-tumor responses. However, these cells may behave differently in the highly dynamic glioma microenvironment, for example, via an immune invasion mechanism enforced by tumor cells. Therefore, T lymphocytes play dual roles in glioma immunity, firstly by their anti-tumor responses, and secondly by exploiting gliomas to promote immune invasion. As an immunosuppression strategy, glioma induces T-cell exhaustion and suppression of effector T cells by regulatory T cells (Tregs) or by altering their signaling pathways. Further, the expression of immune checkpoint inhibitors on the glioma cell surface leads to T cell anergy and dysfunction. Overall, this dynamic interplay between T lymphocytes and glioma is crucial for designing more effective immunotherapies. The current review provides detailed knowledge on the roles of T lymphocytes in the glioma immune microenvironment and helps to explore novel therapeutic approaches to reinvigorate T lymphocytes. [ABSTRACT FROM AUTHOR]

Low-grade gliomas are a cause of severe and often life-long disability in children. Pathology plays a key role in their management by establishing the diagnosis, excluding malignant alternatives, predicting outcomes and identifying targetable genetic alterations. Molecular diagnosis has reshaped the terrain of pathology, raising the question of what part traditional histology plays. In this review, we consider the classification and pathological diagnosis of low-grade gliomas and glioneuronal tumours in children by traditional histopathology enhanced by the opportunities afforded by access to comprehensive genetic and epigenetic characterisation. [ABSTRACT FROM AUTHOR]

Introduction: The goal of surgical management in pediatric low-grade gliomas (pLGGs) is gross total resection (GTR), as it is considered curative with favorable long-term outcomes. Achieving GTR can be challenging in the setting of eloquent-region gliomas, in which resection may increase risk of neurological deficits. Awake craniotomy (AC) with intraoperative neurofunctional mapping (IONM) offers a promising approach to achieve maximal resection while preserving neurological function. However, its adoption in pediatric cases has been hindered, and barriers to its adoption have not previously been elucidated. Findings: This review includes two complementary investigations. First, a survey study was conducted querying pediatric neurosurgeons on their perceived barriers to the procedure in children with pLGG. Next, these critical barriers were analyzed in the context of existing literature. These barriers included the lack of standardized IONM techniques for children, inadequate surgical and anesthesia experience, concerns regarding increased complication risks, doubts about children's ability to tolerate the procedure, and perceived non-indications due to alternative monitoring tools. Conclusion: Efforts to overcome these barriers include standardizing IONM protocols, refining anesthesia management, enhancing patient preparation strategies, and challenging entrenched beliefs about pediatric AC. Collaborative interdisciplinary efforts and further studies are needed to establish safety guidelines and broaden the application of AC, ultimately improving outcomes for children with pLGG. [ABSTRACT FROM AUTHOR]

Low-grade gliomas are the most common brain tumor of childhood, and complete resection offers a high likelihood of cure. However, in many instances, tumors may not be surgically accessible without substantial morbidity, particularly in regard to gliomas arising from the optic or hypothalamic regions, as well as the brainstem. When gross total resection is not feasible, alternative treatment strategies must be considered. While conventional chemotherapy and radiation therapy have long been the backbone of adjuvant therapy for low-grade glioma, emerging techniques and technologies are rapidly changing the landscape of care for patients with this disease. This article seeks to review the current and emerging modalities of treatment for pediatric low-grade glioma. [ABSTRACT FROM AUTHOR]

Background: Gliomas, the most prevalent type of primary brain tumor, stand out as one of the most aggressive and lethal types of human cancer. Methods & Results: To uncover potential prognostic markers, we employed the weighted correlation network analysis (WGCNA) on the Chinese Glioma Genome Atlas (CGGA) 693 dataset to reveal four modules significantly associated with glioma clinical traits, primarily involved in immune function, cell cycle regulation, and ribosome biogenesis. Using the least absolute shrinkage and selection operator (LASSO) regression algorithm, we identified 11 key genes and developed a prognostic risk score model, which exhibits precise prognostic prediction in the CGGA 325 dataset. More importantly, we also validated the model in 12 glioma patients with overall survival (OS) ranging from 4 to 132 months using mRNA sequencing and immunohistochemical analysis. The analysis of immune infiltration revealed that patients with high-risk scores exhibit a heightened immune infiltration, particularly immune suppression cells, along with increased expression of immune checkpoints. Furthermore, we explored potentially effective drugs targeting 11 key genes for gliomas using the library of integrated network-based cellular signatures (LINCS) L1000 database, identifying that in vitro, both torin-1 and clofarabine exhibit promising anti-glioma activity and inhibitory effect on the cell cycle, a significant pathway enriched in the identified glioma modules. Conclusions: In conclusion, our study provides valuable insights into molecular mechanisms and identifying potential therapeutic targets for gliomas. [ABSTRACT FROM AUTHOR]

Background: Deep learning reconstruction (DLR) with denoising has been reported as potentially improving the image quality of magnetic resonance imaging (MRI). Multi-modal MRI is a critical non-invasive method for tumor detection, surgery planning, and prognosis assessment; however, the DLR on multi-modal glioma imaging has not been assessed. Purpose: To assess multi-modal MRI for glioma based on the DLR method. Material and Methods: We assessed multi-modal images of 107 glioma patients (49 preoperative and 58 postoperative). All the images were reconstructed with both DLR and conventional reconstruction methods, encompassing T1-weighted (T1W), contrast-enhanced T1W (CE-T1), T2-weighted (T2W), and T2 fluid-attenuated inversion recovery (T2-FLAIR). The image quality was evaluated using signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and edge sharpness. Visual assessment and diagnostic assessment were performed blindly by neuroradiologists. Results: In contrast with conventionally reconstructed images, (residual) tumor SNR for all modalities and tumor to white/gray matter CNR from DLR images were higher in T1W, T2W, and T2-FLAIR sequences. The visual assessment of DLR images demonstrated the superior visualization of tumor in T2W, edema in T2-FLAIR, enhanced tumor and necrosis part in CE-T1, and fewer artifacts in all modalities. Improved diagnostic efficiency and confidence were observed for preoperative cases with DLR images. Conclusion: DLR of multi-modal MRI reconstruction prototype for glioma has demonstrated significant improvements in image quality. Moreover, it increased diagnostic efficiency and confidence of glioma. [ABSTRACT FROM AUTHOR]

Background: Measuring non‐parametric intravoxel mean diffusivity distributions (MDDs) using magnetic resonance imaging (MRI) is a sensitive method for detecting intracellular diffusivity changes during physiological alterations. Histological and molecular glioma classifications are essential for prognosis and treatment, with distinct water diffusion dynamics among subtypes. Purpose: We developed a data‐driven approach using a fully connected network (FCN) to enhance the speed and stability of calculating MDDs across varying SNRs, enable tumor microstructural mapping, and test its reliability in identifying MIB‐1 labeling index (LI) levels and molecular status of gliomas. Methods: An FCN was trained to learn the mapping between the simulated diffusion decay curves and the ground truth MDDs. We performed 5 000 000 simulation curves with various diffusivity components and random SNR ∈[30,300]$ \in [ {30,\ 300} ]$. Eighty percent of simulation curves were used for the FCN training, 10% for validation, and the others were external tests for the FCN performance evaluation. In vivo data were collected to evaluate its clinical reliability. One hundred one patients (44 years ±$ \pm $ 14, 67 men) with gliomas and six healthy controls underwent a 3.0 T MRI examination with a spin echo–echo planar imaging (SE‐EPI) diffusion‐weighted imaging (DWI) sequence. The trained FCN was employed to calculate MDDs of each brain voxel by voxel. We used the Fuzzy C‐means algorithm to cluster the MDDs of tumor voxels, facilitating the characterization of distinct glioma tissues. Quantitative assessments were conducted through sectional integrals of the MDDs, demarcated by six bands to derive signal fractions (fn,n=1−6${{f}_n},\ n = 1 -6$) and diffusivities of the maximum peaks (Dpeak${{D}_{peak}}$). Cosine similarity scores (CSS) were used for MDD similarity. ANOVA and Mann–Whitney U test were used for difference analysis. Logistic regression and area under the receiver operator characteristic curve (AUC) were used for classification evaluation. Results: The simulation results showed that the FCN‐based MDD approach (FCN‐MDD) achieved higher CSS than non‐negative least squares‐based MDD (NNLS‐MDD). For in vivo data, the spectra of ET and NET obtained by FCN‐MDD are more distinguishable than NNLS‐MDD. Fraction maps delineate the characteristics of different tumor tissues (enhancing and non‐enhancing tumor, edema, and necrosis). f3,f4,Dpeak${{f}_3},\ {{f}_4},{{D}_{peak}}$ showed a positive and negative correlation with MIB‐1 respectively (r=0.568,r=−0.521,r=−0.654$r = 0.568,\ r = - 0.521,\ r = - 0.654$, all p<0.001$p < 0.001$). The AUC of Dpeak${{D}_{peak}}$ for predicting MIB‐1 LI levels was 0.900 (95% CI, 0.826–0.974), versus 0.781 (0.677–0.886) of ADC. The highest AUC of isocitrate dehydrogenase (IDH) mutation status, assessed by a logistic regression model (f1+f3${{f}_1} + {{f}_3}$) was 0.873 (95% CI, 0.802–0.944). Conclusion: The proposed FCN‐MDD method was more robust to variations in SNR and less reliant on empirically set regularization values than the NNLS‐MDD method. FCN‐MDD also enabled qualitative and quantitative evaluation of the composition of gliomas. [ABSTRACT FROM AUTHOR]

The serotonin 5-HT6 receptor (5-HT6R), expressed almost exclusively in the brain, affects the Cdk5 signaling as well as the mTOR pathway. Due to the association of 5-HT6R signaling with pathways involved in cancer progression, we decided to check the usefulness of 5-HT6R ligands in the treatment of CNS tumors. For this purpose, a new group of low-base 5-HT6R ligands was developed, belonging to arylsulfonamide derivatives of cyclic arylguanidines. The selected group of molecules was also tested for their antiproliferative activity on astrocytoma (1321N1) and glioblastoma (U87MG, LN-229, U-251) cell lines. Some of the molecules were subjected to ADMET tests in vitro, including lipophilicity, drug binding to plasma proteins, affinity for phospholipids, drug–drug interaction (DDI), the penetration of the membrane (PAMPA), metabolic stability, and hepatotoxicity as well as in vivo cardiotoxicity in the Danio rerio model. Two antagonists with an affinity constant Ki < 50 nM (PR 68 Ki = 37 nM) were selected. These compounds were characterized by very high selectivity. An analysis of pharmacokinetic parameters for the lead compound PR 68 confirmed favorable properties for administration, including passive diffusion and acceptable metabolic stability (metabolized in 49%, MLMs). The compound did not exhibit the potential for drug–drug interactions. [ABSTRACT FROM AUTHOR]

Objective: Identification of driver mutations in tumors is an extremely important task in oncology for the choice of treatment strategy and assessment of therapy efficacy. In many cases, especially in disease monitoring, there is a need to detect a small number of copies of the mutant allele against the background of excessive content of wild-type DNA. Methods: Genomic DNA was isolated from tumor tissue in paraffine blocks and amplified using polymerase-chain reaction (PCR) with blocking of wild-type DNA amplification via addition of locked-nucleic acid (LNA) oligonucleotides. Fluorescently labelled PCR-product enriched by IDH-mutant alleles was hybridized on a biochip with immobilized oligonucleotide probes which was able to determine 5 mutations in the IDH1 gene and 2 mutations in the IDH2 gene. Results and Discussion: The method was developed and tested on a collection of 26 samples of paraffinized tumor tissue (glioma, glioblastoma, chondrosarcoma). In three cases, R132C, R132L, and R132H mutations in the IDH1 gene were detected in tumor samples with low representation of the mutant allele. The limit of detection of mutant DNA was determined to be 0.1% in the wild-type DNA background. The advantages of the method are simultaneous analysis of multiple targets, simplicity, reliability, and cost-effectiveness. Conclusions: A highly sensitive method for detecting somatic mutations in the IDH1/2 genes by LNA-mediated blocking of amplification of wild-type alleles and hybridization in a biological microchip was developed. We believe that the method may be useful for detecting low-abundance mutations in tumor samples, as well as in circular tumor DNA. [ABSTRACT FROM AUTHOR]

Glioma, a formidable form of brain cancer, poses significant challenges in terms of treatment and prognosis. Circular RNA nucleoporin 98 (circNUP98) has emerged as a potential regulator in various cancers, yet its role in glioma remains unclear. Here, we elucidate the functional role of circNUP98 in glioma cell proliferation, invasion, and migration, shedding light on its therapeutic implications. Glioma cells were subjected to si‐NUP98 transfection, followed by assessments of cell viability, proliferation, invasion, and migration. Subcellular localization of circNUP98 was determined, and its downstream targets were identified. We delineated the binding relationships between circNUP98 and microRNA (miR)‐520f‐3p, as well as between miR‐520f‐3p and ETS transcription factor ELK4 (ELK4). The expression levels of circNUP98/miR‐520f‐3p/ELK4 were quantified. Our findings demonstrated that circNUP98 was upregulated in glioma cells, and its inhibition significantly attenuated glioma cell proliferation, invasion, and migration. Mechanistically, circNUP98 functioned as a sponge for miR‐520f‐3p, thereby relieving the inhibitory effect of miR‐520f‐3p on ELK4. Moreover, inhibition of miR‐520f‐3p or overexpression of ELK4 partially rescued the suppressive effect of circNUP98 knockdown on glioma cell behaviors. In summary, our study unveils that circNUP98 promotes glioma cell progression via the miR‐520f‐3p/ELK4 axis, offering novel insights into the therapeutic targeting of circNUP98 in glioma treatment. [ABSTRACT FROM AUTHOR]

Background: As part of stress-triggered molecules, immediate early response 3 (IER3) dysregulation has been reported to sustain pro-oncogenic pathways and precede malignant transformation. However, the role of IER3 in glioma pathology is ill-defined. Methods: Immunohistochemistry (IHC) assay and publicly available glioma datasets were used to calculate the IER3 expression level in glioma. Wound healing, invasion and cell counting kit-8 (CCK8) assays were applied to measure the cell viability and capacities of migration and invasion of glioma cells in vitro. The immunofluorescence (IF) assay was used to assess the expression associations of IER3 with CCL2 and TGFBI. Cox regression analysis and Kaplan-Meier (K-M) curve were introduced to compute the prognosis-predicting value of IER3. Variations in copy number (CNVs), single nucleotide (SNVs), and methylation profiles were analyzed to illustrate the epigenetic modifications of IER3. Gliomas were divided into two subgroups using the restricted cubic spline (RCS) method. Results IER3: was overexpressed and hypomethylated in gliomas and significantly associated with the dismal prognosis of glioma samples. Samples in the high IER3 subgroup were characterized by increased infiltration of tumor-associated monocytes/macrophages (TAMMs), as well as the elevated sensitivity to Dabrafenib, an inhibitor of BRAF. In addition, this subgroup demonstrated a low mutation rate of IDH, high gain rates of BRAF, ELTD1, and PDGFA. Gliomas with relatively low IER3 expression demonstrated a less invasive subtype and were featured by favorable prognosis, increased response to immunotherapy, and adjuvant chemotherapy plus radiotherapy. The IF assay revealed that IER3 was co-localized and co-expressed with TGFBI. The glioma cells with small interfering RNA (siRNA)-silenced IER3 displayed lower migration, invasion, proliferation, and cell viability than the control group. Conclusions: In this study, we identified IER3 upregulation as an essential biomarker that could assist in adjuvant therapy and prognosis prediction for gliomas. [ABSTRACT FROM AUTHOR]