Grade Gliomas Research Articles

Targeted Metabolic Profiling in Determining the Metabolic Heterogeneity in Human Biopsies of Different Grades of Glioma.

Gliomas are intricate tumors with numerous metabolic and genetic abnormalities contributing to their aggressive phenotypes and poor prognoses. The study aims at identifying the key molecular metabolic as well as gene expressional variations that could be used to differentiate between different grades of glioma to obtain deeper insights theabout metabolic status of glioma that may serve as good candidates of diagnosis in future. In the present study, the metabolomic profiling along with clinical and expressional analyses of glioma biopsies (n = 52; patients comprising both of benign and malignant lesions) was analyzed. The biopsies were subjected to gene/protein expressional analysis using RT-PCR and western blotting and also were subjected to metabolite analyses. The results of the gene/protein expressional analysis exhibited elevated levels of carnitine palmitoyltransferase, monoglyceride lipase, human phosphofructokinase, and isocitrate dehydrogenase in higher grades of glioma when compared to those of control. Our study suggested that the metabolites and gene/protein expressional levels were found to be discriminative among the grades of glioma. The study is deemed as a provider of deeper insights that are essential for differential therapeutic approaches that specifically target the dysregulated metabolome to the benefit of patients.

Correlation of Pre-Operative Myo-Inositol/Creatine Ratio with Histopathological Grade of Glioma

Background: Introduction: Gliomas are the most frequent primary intracerebral tumors in adults & constitute 35–50% of all intracranial neoplasms. In determining a treatment plan, tumor grade is a key consideration for minimizing the risk of unnecessary morbidity and mortality. Objective: To evaluate Correlation of pre-operative Myo-inositol/Creatine ratio with histopathological grade of glioma. Materials and method: This was a cross sectional experimental study. Total 33 patients consistent with selection criteria were enrolled in this study. Myo-inositol/ Creatine ratio was obtained from MRS. Histopathological grade of glioma was obtained from biopsy (hematoxylin and eosin stain or HE stain) report. The obtained results were then grouped categorically. Result: Out of 33 patients, 22 were male and 11 were female. According to histopathology, 14 gliomas were confirmed as high grade and 19 gliomas were confirmed as low grade. Spearman Rank Correlation Test showed a moderate negative association between Myo-inositol/Creatine ratio with glioma grading with coefficient value of r = -0.611 with a statistically significant p-value (p<0.001). We were able to differentiate between low grade (II) and high grade (III + IV) gliomas using the Myoinositol/ Creatine ratio. The levels of MI/Cr were higher (e”0.48) in patients with lowgrade glioma, and lower (<0.48) in patients high grade glioma Conclusion: This study has shown a significant correlation between pre-operative Myo-inositol/Creatine ratio with histopathological grade of glioma. It may help neurosurgeons in taking clinical decisions about patient management and counselling. Bang. J Neurosurgery 2024; 13(2): 57-63

Association between Fat-Soluble Vitamin Metabolic Process and Glioma Progression.

Although multimodality therapy has recently advanced, patients with glioblastoma, one of the most aggressive and deadly types of central nervous system cancer, have a very poor prognosis and rare long-term survival. Vitamins are essential organic nutrients that play a pivotal role in maintaining homeostasis, and various studies have demonstrated the implication of vitamins in the pathophysiology of gliomas. Herein, we aimed to investigate the association of the vitamin metabolic pathway and the corresponding candidate genes for the malignancy, aggressiveness, and poor prognosis of gliomas using The Cancer Genome Atlas database of patients with gliomas. We demonstrated that fat-soluble vitamin metabolic processes are prominently associated with glioma grade, molecular biomarkers, molecular subtypes, and clinical outcomes. Moreover, we identified the key genes related to the fat-soluble metabolic pathway in gliomas using differentially expressed gene analysis. Among them, the expression of the vitamin K epoxide reductase complex subunit 1 (VKORC1), encoding VKOR essential for the vitamin K-dependent γ-carboxylation of target proteins, was prominently associated with not only malignancy, aggressiveness, and poor prognosis of gliomas but also the representative signal pathways related to glioma pathogenesis. Moreover, the inactivation of Vkorc1 by RNA interference decreased the proliferation and migration potential of glioma cells in vitro. Collectively, these findings reveal the pivotal role of fat-soluble vitamin and vitamin K metabolic processes in the pathophysiology of gliomas, thereby identifying a potential target for drug development for the treatment of malignant gliomas.

Preoperative prediction of diffuse glioma type and grade in adults: a gadolinium-free MRI-based decision tree.

To develop a gadolinium-free MRI-based diagnosis prediction decision tree (DPDT) for adult-type diffuse gliomas and to assess the added value of gadolinium-based contrast agent (GBCA)enhanced images. This study included preoperative grade 2-4 adult-type diffuse gliomas (World Health Organization 2021) scanned between 2010 and 2021. The DPDT, incorporating eleven GBCA-free MRI features, was developed using 18% of the dataset based on consensus readings. Diagnosis predictions involved grade (grade 2 vs. grade 3/4) and molecular status (isocitrate dehydrogenase (IDH) and 1p/19q). GBCA-free diagnosis was predicted using DPDT, while GBCA-enhanced diagnosis included post-contrast images. The accuracy of these predictions was assessed by three raters with varying experience levels in neuroradiology using the test dataset. Agreement analyses were applied to evaluate the prediction performance/reproducibility. The test dataset included 303 patients (age (SD): 56.7 (14.2) years, female/male: 114/189, low-grade/high-grade: 54/249, IDH-mutant/wildtype: 82/221, 1p/19q-codeleted/intact: 34/269). Per-rater GBCA-free predictions achieved ≥ 0.85 (95%-CI: 0.80-0.88) accuracy for grade and ≥ 0.75 (95%-CI: 0.70-0.80) for molecular status, while GBCA-enhanced predictions reached ≥ 0.87 (95%-CI: 0.82-0.90) and ≥ 0.77 (95%-CI: 0.71-0.81), respectively. No accuracy difference was observed between GBCA-free and GBCA-enhanced predictions. Group inter-rater agreement was moderate for GBCA-free (0.56 (95%-CI: 0.46-0.66)) and substantial for GBCA-enhanced grade prediction (0.68 (95%-CI: 0.58-0.78), p = 0.008), while substantial for both GBCA-free (0.75 (95%-CI: 0.69-0.80) and GBCA-enhanced (0.77 (95%-CI: 0.71-0.82), p = 0.51) molecular status predictions. The proposed GBCA-free diagnosis prediction decision tree performed well, with GBCA-enhanced images adding little to the preoperative diagnostic accuracy of adult-type diffuse gliomas. Question Given health and environmental concerns, is there a gadolinium-free imaging protocol to preoperatively evaluate gliomas comparable to the gadolinium-enhanced standard practice? Findings The proposed gadolinium-free diagnosis prediction decision tree for adult-type diffuse gliomas performed well, and gadolinium-enhanced MRI demonstrated only limited improvement in diagnostic accuracy. Clinical relevance Even inexperienced raters effectively classified adult-type diffuse gliomas using the gadolinium-free diagnosis prediction decision tree, which, until further validation, can be used alongside gadolinium-enhanced images to respect standard practice, despite this study showing that gadolinium-enhanced images hardly improved diagnostic accuracy.

"Navigating the complexities of low-Grade glioma treatment: insights into SBT I-125 and novel assessment tools".

Central nervous system tumors, classified by the WHO into four grades based on their aggressiveness, present significant challenges in treatment, particularly low-grade gliomas (LGGs) which, despite their slower growth, can progress to high-grade gliomas. Lucca B. Palavani and colleagues evaluated the efficacy and safety of SBT I-125 brachytherapy for LGMs in a systematic review and meta-analysis of 20 studies involving 988 patients. The analysis revealed an overall complication rate of 10%, with headaches and cyst formation being the most frequent issues. The five-year progression-free survival (PFS) rate was 66%, while the ten-year PFS rate was 30%, and the rate of malignant transformation was 26%. The mortality rate was 33%. Despite these findings, significant limitations were noted, including data insufficiencies, study heterogeneity, lack of randomized controlled trials, and potential publication bias. Inconsistencies in follow-up durations further hindered the evaluation of long-term efficacy and safety. Recent advancements in automated tumor assessment, such as Cheng et al.'s deep learning-based pipeline, are revolutionizing glioma management by enhancing the accuracy and consistency of tumor volume and RANO measurements. These innovations facilitate improved glioma grading, genetic mutation prediction, surgical planning, real-time intraoperative guidance, and histopathological analysis. Integrating such advanced tools into clinical practice can significantly enhance the precision and efficiency of glioma management. In conclusion, while SBT I-125 brachytherapy shows promise, concerns regarding safety and efficacy underscore the need for further research with standardized methodologies. Incorporating advanced automated assessment tools could improve treatment evaluation and patient outcomes.

Epigenetic landscape reorganisation and reactivation of embryonic development genes are associated with malignancy in IDH-mutant astrocytoma

Accurate grading of IDH-mutant gliomas defines patient prognosis and guides the treatment path. Histological grading is challenging, and aside from CDKN2A/B homozygous deletions in IDH-mutant astrocytomas, there are no other objective molecular markers used for grading. RNA-sequencing was conducted on primary IDH-mutant astrocytomas (n = 138) included in the prospective CATNON trial, which was performed to assess the prognostic effect of adjuvant and concurrent temozolomide. We integrated the RNA-sequencing data with matched DNA-methylation and NGS data. We also used multi-omics data from IDH-mutant astrocytomas included in the TCGA dataset and validated results on matched primary and recurrent samples from the GLASS-NL study. Since discrete classes do not adequately capture grading of these tumours, we utilised DNA-methylation profiles to generate a Continuous Grading Coefficient (CGC) based on classification scores from a CNS-tumour classifier. CGC was an independent predictor of survival outperforming current WHO-CNS5 and methylation-based classification. Our RNA-sequencing analysis revealed four distinct transcription clusters that were associated with (i) upregulation of cell cycling genes; (ii) downregulation of glial differentiation genes; (iii) upregulation of embryonic development genes (e.g. HOX, PAX, and TBX) and (iv) upregulation of extracellular matrix genes. The upregulation of embryonic development genes was associated with a specific increase of CpG island methylation near these genes. Higher grade IDH-mutant astrocytomas have DNA-methylation signatures that, on the RNA level, are associated with increased cell cycling, tumour cell de-differentiation and extracellular matrix remodelling. These combined molecular signatures can serve as an objective marker for grading of IDH-mutant astrocytomas.

-New frontiers in domain-inspired radiomics and radiogenomics: increasing role of molecular diagnostics in CNS tumor classification and grading following WHO CNS-5 updates.

Gliomas and Glioblastomas represent a significant portion of central nervous system (CNS) tumors associated with high mortality rates and variable prognosis. In 2021, the World Health Organization (WHO) updated its Glioma classification criteria, most notably incorporating molecular markers including CDKN2A/B homozygous deletion, TERT promoter mutation, EGFR amplification, + 7/-10 chromosome copy number changes, and others into the grading and classification of adult and pediatric Gliomas. The inclusion of these markers and the corresponding introduction of new Glioma subtypes has allowed for more specific tailoring of clinical interventions and has inspired a new wave of Radiogenomic studies seeking to leverage medical imaging information to explore the diagnostic and prognostic implications of these new biomarkers. Radiomics, deep learning, and combined approaches have enabled the development of powerful computational tools for MRI analysis correlating imaging characteristics with various molecular biomarkers integrated into the updated WHO CNS-5 guidelines. Recent studies have leveraged these methods to accurately classify Gliomas in accordance with these updated molecular-based criteria based solely on non-invasive MRI, demonstrating the great promise of Radiogenomic tools. In this review, we explore the relative benefits and drawbacks of these computational frameworks and highlight the technical and clinical innovations presented by recent studies in the landscape of fast evolving molecular-based Glioma subtyping. Furthermore, the potential benefits and challenges of incorporating these tools into routine radiological workflows, aiming to enhance patient care and optimize clinical outcomes in the evolving field of CNS tumor management, have been highlighted.

Fractal dimension and lacunarity measures of glioma subcomponents are discriminative of the grade of gliomas and IDH status.

Since the overall glioma mass and its subcomponents-enhancing region (malignant part of the tumor), non-enhancing (less aggressive tumor cells), necrotic core (dead cells), and edema (water deposition)-are complex and irregular structures, non-Euclidean geometric measures such as fractal dimension (FD or "fractality") and lacunarity are needed to quantify their structural complexity. Fractality measures the extent of structural irregularity, while lacunarity measures the spatial distribution or gaps. The complex geometric patterns of the glioma subcomponents may be closely associated with the grade and molecular landscape. Therefore, we measured FD and lacunarity in the glioma subcomponents and developed machine learning models to discriminate between tumor grades and isocitrate dehydrogenase (IDH) gene status. 3D fractal dimension (FD3D) and lacunarity (Lac3D) were measured for the enhancing, non-enhancing plus necrotic core, and edema-subcomponents using preoperative structural-MRI obtained from the The Cancer Genome Atlas (TCGA) and University of California San Francisco Preoperative Diffuse Glioma MRI (UCSF-PDGM) glioma cohorts. The FD3D and Lac3D measures of the tumor-subcomponents were then compared across glioma grades (HGGs: high-grade gliomas vs. LGGs: low-grade gliomas) and IDH status (mutant vs. wild type). Using these measures, machine learning platforms discriminative of glioma grade and IDH status were developed. Kaplan-Meier survival analysis was used to assess the prognostic significance of FD3D and Lac3D measurements. HGG exhibited significantly higher fractality and lower lacunarity in the enhancing subcomponent, along with lower fractality in the non-enhancing subcomponent compared to LGG. This suggests that a highly irregular and complex geometry in the enhancing-subcomponent is a characteristic feature of HGGs. A comparison of FD3D and Lac3D between IDH-wild type and IDH-mutant gliomas revealed that mutant gliomas had ~2.5-fold lower FD3D in the enhancing-subcomponent and higher FD3D with lower Lac3D in the non-enhancing subcomponent, indicating a less complex and smooth enhancing subcomponent, and a more continuous non-enhancing subcomponent as features of IDH-mutant gliomas. Supervised ML models using FD3D from both the enhancing and non-enhancing subcomponents together demonstrated high-sensitivity in discriminating glioma grades (~97.9%) and IDH status (~94.4%). A combined fractal estimation of the enhancing and non-enhancing subcomponents using MR images could serve as a non-invasive, precise, and quantitative measure for discriminating glioma grade and IDH status. The combination of 2-hydroxyglutarate-magnetic resonance spectroscopy (2HG-MRS) with FD3D and Lac3D quantification may be established as a robust imaging signature for glioma subtyping.

148 - The application of magnetic resonance MAGIC technique in preoperative grading of brain gliomas

148 - The application of magnetic resonance MAGIC technique in preoperative grading of brain gliomas

The prognostic significance of androgen receptor expression in gliomas

Androgen receptor (AR) overexpression has been identified in gliomas and its stem cells, suggesting that AR plays an important role in tumor carcinogenesis. The prognostic significance of AR overexpression in gliomas remains unknown. AR mRNA expression in gliomas and relevant clinical data were obtained from The Cancer Genome Atlas and Chinese Glioma Genome Atlas databases. AR expression levels were compared across gliomas of different histopathologic grades and molecular subtypes. Kaplan–Meier analyses in patients with different AR expression levels were investigated for the potential prognostic values of AR. Compared with normal brain tissue, gliomas show significantly higher AR mRNA expression (p < 0.01). AR mRNA expression was more prominent in higher grade disease and in worse prognostic molecular subtypes (p < 0.01). AR protein is more abundant in glioblastoma than in lower grade gliomas (LGG) (grade 2/3) (p < 0.0001). This is corroborated by a linear association between AR mRNA and protein expression (r = 0.65). In LGG, both higher AR mRNA and protein expression was associated with significantly worse overall survival (OS). Five-year OS for LGG patients with high versus low AR expression were 59.1% and 73.3%, respectively (p < 0.0001). AR expression is not prognostic for OS within glioblastoma patients. Gender was not associated with AR expression or prognosis. Higher AR expression levels are associated with higher grade disease and histopathologic features predicting poorer prognosis in lower grade gliomas. Higher gene expression in LGG patients is correlated with poor prognosis but not in the glioblastoma cohort suggesting saturated expression/functions of AR in glioblastoma.

ResMT: A hybrid CNN-transformer framework for glioma grading with 3D MRI

Accurate grading of gliomas is crucial for treatment strategies and prognosis. While convolutional neural networks (CNNs) have proven effective in classifying medical images, they struggle with capturing long-range dependencies among pixels. Transformer-based networks can address this issue, but CNN-based methods often perform better when trained on small datasets. Additionally, tumor segmentation is essential for classification models, but training an additional segmentation model significantly increases workload. To address these challenges, we propose ResMT, which combines CNN and transformer architectures for glioma grading, extracting both local and global features efficiently. Specifically, we designed a spatial residual module (SRM) where a 3D CNN captures glioma's volumetric complexity, and Swin UNETR, a pre-trained segmentation model, enhances the network without extra training. Our model also includes a multi-plane channel and spatial attention module (MCSA) to refine the analysis by focusing on critical features across multiple planes (axial, coronal, and sagittal). Transformer blocks establish long-range relationships among planes and slices. We evaluated ResMT on the BraTs19 dataset, comparing it with baselines and state-of-the-art models. Results demonstrate that ResMT achieves the highest prediction performance with an AUC of 0.9953, highlighting hybrid CNN-transformer models' potential for 3D MRI classification.

Is the voltage-gated sodium channel β3 subunit (SCN3B) a biomarker for glioma?

Recent studies suggest a need for reliable biomarkers enhancing prognosis prediction and treatment strategies in cancer. Here, we performed a data analysis bearing on the expression of SCN3B, voltage-gated sodium channel (VGSC) β3 subunit, as a possible candidate for the development of a glioma biomarker for the first time. This extends our previous review article that mentioned the potential of SCN3B as a prognostic biomarker for glioma survival, further examining its association with existing indicators and immune responses. We utilized clinical and genomic data from multiple glioma cohorts. These include the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). We employed analytical techniques including time-dependent receiver operating characteristic (ROC) analysis, decision curves analysis (DCA), and correlation studies with immune checkpoint markers. Our findings indicate a differential SCN3B expression between glioma grades, and that this significantly correlates with patient survival, particularly in oligodendroglioma subtypes. The DCA curves suggested that the inclusion of SCN3B in the prognostic model would improve decision-making in these subtypes. Moreover, SCN3B expression positively correlated with the presence of key immune cells and negatively correlated with several immune checkpoint inhibitors. This suggests potential roles in modulating immune responses in glioma. Thus, SCN3B emerges as a promising potential prognostic biomarker for glioma, especially for oligodendroglioma. Its dual correlations with prognosis and immune regulation present a compelling case for further experimental and clinical investigations to establish its utility in enhancing glioma management strategies. These findings underscore the importance of integrating novel biomarkers with traditional prognostic models to refine treatment paradigms and improve patient outcomes.

Bmal1 regulates the stemness and tumorigenesis of gliomas with the Wnt/β-catenin signaling pathway

BackgroundThe circadian rhythm gene Brain and Muscle Arnt-like1 (Bmal1) acts as a transcription factor and plays a crucial role in oncogenesis and embryonic development. Bmal1 is notably overexpressed in various tumors, including glioma. However, the precise mechanisms underlying the elevated Bmal1 expression in glioma malignancy remain unclear. MethodsThis study employed multiple databases, including The Cancer Genome Atlas (TCGA), GTEx, and cBioportal, to analyze Bmal1 mRNA expression in gliomas, evaluate its prognostic significance, investigate transcriptome alterations, identify key signaling pathways associated with Bmal1, and examine its interaction with tumor stem cells. Additionally, experimental validation was performed to confirm Bmal1′s regulatory effects on glioma stem cells. ResultsOur analysis revealed differential Bmal1 expression across glioma grades and molecular subtypes. Moreover, Bmal1 significantly influences several tumor-related signaling pathways, notably the Mapk, Met, and Wnt pathways, and is actively involved with stem cells. A strong positive correlation was observed between Bmal1 and glioma stem cell markers, such as Nestin, Sox2, and Cd133. Experimental validation confirmed that Bmal1 promotes stem cell expansion and tumor progression via the Wnt/β-catenin pathway. ConclusionThis study underscores the critical regulatory function of Bmal1 in glioma development. The interaction between Bmal1 and glioma stem cells appears to significantly impact glioma initiation and progression.

FAM109B plays a tumorigenic role in low-grade gliomas and is associated with tumor-associated macrophages (TAMs)

BackgroundFamily with sequence similarity 109, member B (FAM109B) is involved in endocytic transport and affects genetic variation in brain methylation. It is one of the important genes related to immune cell-associated diseases. In the tumor immune system, methylation can regulate tumor immunity and influence the maturation and functional response of immune cells. Whether FAM109B is involved in tumor progression and its correlation with the tumor immune microenvironment has not yet been disclosed.MethodsA comprehensive pan-cancer analysis of FAM109B expression, prognosis, immunity, and TMB was conducted. The expression, clinical features, and prognostic value of FAM109B in low-grade gliomas (LGG) were evaluated using TCGA, CGGA, and Gravendeel databases. The expression of FAM109B was validated by qRT-PCR, immunohistochemistry (IHC), and Western blotting (WB). The relationship between FAM109B and methylation, Copy Number Variation (CNV), prognosis, immune checkpoints (ICs), and common chemotherapy drug sensitivity in LGG was explored through Cox regression, Kaplan–Meier curves, and Spearman correlation analysis. FAM109B levels and their distribution were studied using the TIMER database and single-cell analysis. The potential role of FAM109B in gliomas was further investigated through in vitro and in vivo experiments.ResultsFAM109B was significantly elevated in various tumor types and was associated with poor prognosis. Its expression was related to aggressive progression and poor prognosis in low-grade glioma patients, serving as an independent prognostic marker for LGG. Glioma grade was negatively correlated with FAM109B DNA promoter methylation. Immune infiltration and single-cell analysis showed significant expression of FAM109B in tumor-associated macrophages (TAMs). The expression of FAM109B was closely related to gene mutations, immune checkpoints (ICs), and chemotherapy drugs in LGG. In vitro studies showed increased FAM109B expression in LGG, closely related to cell proliferation. In vivo studies showed that mice in the sh-FAM109B group had slower tumor growth, slower weight loss, and longer survival times.ConclusionsFAM109B, as a novel prognostic biomarker for low-grade gliomas, exhibits specific overexpression in TAMs and may be a potential therapeutic target for LGG patients.

Super-resolution reconstruction improves multishell diffusion: using radiomics to predict adult-type diffuse glioma IDH and grade.

Multishell diffusion scanning is limited by low spatial resolution. We sought to improve the resolution of multishell diffusion images through deep learning-based super-resolution reconstruction (SR) and subsequently develop and validate a prediction model for adult-type diffuse glioma, isocitrate dehydrogenase status and grade 2/3 tumors. A simple diffusion model (DTI) and three advanced diffusion models (DKI, MAP, and NODDI) were constructed based on multishell diffusion scanning. Migration was performed with a generative adversarial network based on deep residual channel attention networks, after which images with 2x and 4x resolution improvements were generated. Radiomic features were used as inputs, and diagnostic models were subsequently constructed via multiple pipelines. This prospective study included 90 instances (median age, 54.5 years; 39 men) diagnosed with adult-type diffuse glioma. Images with both 2x- and 4x-improved resolution were visually superior to the original images, and the 2x-improved images allowed better predictions than did the 4x-improved images (P<.001). A comparison of the areas under the curve among the multiple pipeline-constructed models revealed that the advanced diffusion models did not have greater diagnostic performance than the simple diffusion model (P>.05). The NODDI model constructed with 2x-improved images had the best performance in predicting isocitrate dehydrogenase status (AUC_validation=0.877; Brier score=0.132). The MAP model constructed with the original images performed best in classifying grade 2 and grade 3 tumors (AUC_validation=0.806; Brier score=0.168). SR improves the resolution of multishell diffusion images and has different advantages in achieving different goals and creating different target diffusion models.

Multi-pool chemical exchange saturation transfer MRI in glioma grading, molecular subtyping and evaluating tumor proliferation.

To evaluate the performance of multi-pool Chemical exchange saturation transfer (CEST) MRI in prediction of glioma grade, isocitrate dehydrogenase (IDH) mutation, alpha-thalassemia/mental retardation syndrome X-linked (ATRX) loss and Ki-67 labeling index (LI), based on the fifth edition of the World Health Organization classification of central nervous system tumors (WHO CNS5). 95 patients with adult-type diffuse gliomas were analyzed. The amide, direct water saturation (DS), nuclear Overhauser enhancement (NOE), semi-solid magnetization transfer (MT) and amine signals were derived using Lorentzian fitting, and asymmetry-based amide proton transfer-weighted (APTwasym) signal was calculated. The mean value of tumor region was measured and intergroup differences were estimated using student-t test. The receiver operating curve (ROC) and area under the curve (AUC) analysis were used to evaluate the diagnostic performance of signals and their combinations. Spearman correlation analysis was performed to evaluate tumor proliferation. The amide and DS signals were significantly higher in high-grade gliomas compared to low-grade gliomas, as well as in IDH-wildtype gliomas compared to IDH-mutant gliomas (all p < 0.001). The DS, MT and amine signals showed significantly differences between ATRX loss and retention in grade 2/3 IDH-mutant gliomas (all p < 0.05). The combination of signals showed the highest AUC in prediction of grade (0.857), IDH mutation (0.814) and ATRX loss (0.769). Additionally, the amide and DS signals were positively correlated with Ki-67 LI (both p < 0.001). Multi-pool CEST MRI demonstrated good potential to predict glioma grade, IDH mutation, ATRX loss and Ki-67 LI.

Stanniocalcin-1 promotes temozolomide resistance of glioblastoma through regulation of MGMT

Temozolomide (TMZ) resistance is a major challenge in the treatment of glioblastoma (GBM). Tumour reproductive cells (TRCs) have been implicated in the development of chemotherapy resistance. By culturing DBTRG cells in three-dimensional soft fibrin gels to enrich GBM TRCs and performing RNA-seq analysis, the expression of stanniocalcin-1 (STC), a gene encoding a secreted glycoprotein, was found to be upregulated in TRCs. Meanwhile, the viability of TMZ-treated TRC cells was significantly higher than that of TMZ-treated 2D cells. Analysis of clinical data from CGGA (Chinese Glioma Genome Atlas) database showed that high expression of STC1 was closely associated with poor prognosis, glioma grade and resistance to TMZ treatment, suggesting that STC1 may be involved in TMZ drug resistance. The expression of STC1 in tissues and cells was examined, as well as the effect of STC1 on GBM cell proliferation and TMZ-induced DNA damage. The results showed that overexpression of STC1 promoted and knockdown of STC1 inhibited TMZ-induced DNA damage. These results were validated in an intracranial tumour model. These data revealed that STC1 exerts regulatory functions on MGMT expression in GBM, and provides a rationale for targeting STC1 to overcome TMZ resistance.

The Role of Amide Proton Transfer (APT)-Weighted Imaging in Glioma: Assessment of Tumor Grading, Molecular Profile and Survival in Different Tumor Components.

Amide Proton Transfer-weighted (APTw) imaging is a molecular MRI technique used to quantify protein concentrations in gliomas, which have heterogeneous components with varying cellularity and metabolic activity. This study aimed to assess the correlation between the component-specific APT signal of the neoplasm and WHO grade, molecular profile and survival status. Sixty-one patients with adult-type diffuse gliomas were retrospectively analyzed. APT values were semi-automatically extracted from tumor solid and, whenever present, necrotic components. APT values were compared between groups stratified by WHO grade, IDH-mutation, MGMT promoter methylation and 1- and 2-year survival status using Wilcoxon rank-sum test, adjusting for multiple comparisons. Overall survival (OS) was analyzed in the subgroup of 48 patients with grade 4 tumors using Cox proportional-hazards models. Random-effects models were used to assess inter-subject heterogeneity of the mean APT values in each tumor component. APT values of the solid component significantly differed between patients with grades 2-3 and 4 tumors (mean 1.58 ± 0.50 vs. 2.04 ± 0.56, p = 0.028) and correlated with OS after 1 year (1.81 ± 0.58 in survivors vs. 2.17 ± 0.51 in deceased patients, p = 0.030). APT values did not differ by IDH-mutation, MGMT methylation, and 2-year survival status. Within grade 4 glioma patients, higher APT kurtosis of the solid component was a negative prognostic factor (hazard ratio = 1.60, p = 0.040). Mean APT values of the necrosis showed high inter-subject variability, although most necrotic tumors were grade 4 and IDH wildtype. In conclusion, APTw imaging in the solid component provided metrics associated with glioma grade and survival status but showed weak correlation with IDH-mutation and MGMT promoter methylation status, in contrast to previous works. Further research is needed to understand APT signal variability within the necrotic component of high-grade gliomas.

Single-cell and spatial transcriptome assays reveal heterogeneity in gliomas through stress responses and pathway alterations.

Glioma is a highly heterogeneous malignancy of the central nervous system. This heterogeneity is driven by various molecular processes, including neoplastic transformation, cell cycle dysregulation, and angiogenesis. Among these biomolecular events, inflammation and stress pathways in the development and driving factors of glioma heterogeneity have been reported. However, the mechanisms of glioma heterogeneity under stress response remain unclear, especially from a spatial aspect. This study employed single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) to explore the impact of oxidative stress response genes in oligodendrocyte precursor cells (OPCs). Our analysis identified distinct pathways activated by oxidative stress in two different types of gliomas: high- and low- grade (HG and LG) gliomas. In HG gliomas, oxidative stress induced a metabolic shift from oxidative phosphorylation to glycolysis, promoting cell survival by preventing apoptosis. This metabolic reprogramming was accompanied by epithelial-to-mesenchymal transition (EMT) and an upregulation of stress response genes. Furthermore, SCENIC (Single-Cell rEgulatory Network Inference and Clustering) analysis revealed that oxidative stress activated the AP1 transcription factor in HG gliomas, thereby enhancing tumor cell survival and proliferation. Our findings provide a novel perspective on the mechanisms of oxidative stress responses across various grades of gliomas. This insight enhances our comprehension of the evolutionary processes and heterogeneity within gliomas, potentially guiding future research and therapeutic strategies.

L’utilité du facteur d’épissage SRSF1 dans le grading des tumeurs gliales: Une méta-analyse

The grading of glial tumors is based on morphological and sometimes on molecular features. Many markers have been assessed in order to grade the glial tumours without a real consensus. Some authors reported that SRSF1, a spiling factor, presents an expression correlated to the tumours grades. In this study, we aimed to assess the utility of the SRSF1 into the grading of gliomas based on its immunohistochemical expression. The authors conducted a meta-analysis under the PRISMA guidelines during a 10-year-period (2013-2023). The Meta-Disc software 5.4 (free version) was used. Q test and I2 statistics were carried out to explore the heterogeneity among studies. Meta-regression was performed in case of significant heterogeneity. Publication bias was assessed using the funnel plot test and the Egger's test (free version JASP). According to the inclusion criteria, 4 studies from 193 articles were included. The pooled SEN, SPE and DOR accounted respectively for 0.592, 0.565 and 1.852. The AUC was estimated to 0.558 suggesting a bad diagnostic accuracy. The heterogeneity in the pooled SEN and SPE was statistically significant. The meta-regression analysis focusing on the technique used, the clones, the dilution, the interpretation technique revealed no covariate factors (P>0.05). Even if this meta-analysis highlighted the absence of a real diagnostic utility of the SRSF1 in grading the glial tumours, the heterogeneity revealed reinforces the need for more prospective studies performed according to the quality assessment criteria.