Glioma Grade and Molecular Markers: Comparing Machine-Learning Approaches Using VASARI (Visually AcceSAble Rembrandt Images) Radiological Assessment.

OBJECTIVES: This study aimed to leverage Visually AcceSAble Rembrandt Images (VASARI) radiological features, extracted from magnetic resonance imaging (MRI) scans, and machine-learning techniques to predict glioma grade, isocitrate dehydrogenase (IDH) mutation status, and O6-methylguanine-DNA methyltransferase (MGMT) methylation. METHODOLOGY: A retrospective evaluation was undertaken, analyzing MRI and molecular data from 107 glioma patients treated at a tertiary hospital. Patients underwent MRI scans using established protocols and were evaluated based on VASARI criteria. Tissue samples were assessed for glioma grade and underwent molecular testing for IDH mutations and MGMT methylation. Four machine learning models, namely, Random Forest, Elastic-Net, multivariate adaptive regression spline (MARS), and eXtreme Gradient Boosting (XGBoost), were trained on 27 VASARI features using fivefold internal cross-validation. The models' predictive performances were assessed using the area under the curve (AUC), sensitivity, and specificity. RESULTS: For glioma grade prediction, XGBoost exhibited the highest AUC (0.978), sensitivity (0.879), and specificity (0.964), with f6 (proportion of non-enhancing) and f12 (definition of enhancing margin) as the most important predictors. In predicting IDH mutation status, XGBoost achieved an AUC of 0.806, sensitivity of 0.364, and specificity of 0.880, with f1 (tumor location), f12, and f30 (perpendicular diameter to f29) as primary predictors. For MGMT methylation, XGBoost displayed an AUC of 0.580, sensitivity of 0.372, and specificity of 0.759, highlighting f29 (longest diameter) as the key predictor. CONCLUSIONS: This study underscores the robust potential of combining VASARI radiological features with machine learning models in predicting glioma grade, IDH mutation status, and MGMT methylation. The best and most balanced performance was achieved using the XGBoost model. While the prediction of glioma grade showed promising results, the sensitivity in discerning IDH mutations and MGMT methylation still leaves room for improvement. Follow-up studies with larger datasets and more advanced artificial intelligence techniques can further refine our understanding and management of gliomas.

Unveiling hierarchy and spatial distribution of O6-methylguanine-DNA methyltransferase promoter methylation in World Health Organization grade 2-3 gliomas.

This study investigated the role of O6-methylguanine-DNA methyltransferase promoter (MGMTp) methylation hierarchy and heterogeneity in grade 2-3 gliomas, focusing on variations in chemotherapy benefits and resection dependency. A cohort of 668 newly diagnosed grade 2-3 gliomas, with comprehensive clinical, radiological, and molecular data, formed the basis of this analysis. The extent of resection was categorized into gross total resection (GTR ≥100%), subtotal resection (STR >90%), and partial resection (PR ≤90%). MGMTp methylation levels were examined using quantitative pyrosequencing. Our findings highlighted the critical role of GTR in improving the prognosis for astrocytomas (IDH1/2-mutant and 1p/19q non-codeleted), contrasting with its lesser significance for oligodendrogliomas (IDH1/2 mutation and 1p/19q codeletion). Oligodendrogliomas demonstrated the highest average MGMTp methylation levels (median: 28%), with a predominant percentage of methylated cases (average methylation levels >20%). Astrocytomas were more common in the low-methylated group (10%-20%), while IDH wild-type gliomas were mostly unmethylated (<10%). Spatial distribution analysis revealed a decrement in frontal lobe involvement from methylated, low-methylated to unmethylated cases (72.8%, 59.3%, and 47.8%, respectively). In contrast, low-methylated and unmethylated cases were more likely to invade the temporal-insular region (19.7%, 34.3%, and 40.4%, respectively). Astrocytomas with intermediate MGMTp methylation were notably associated with temporal-insular involvement, potentially indicating a moderate response to temozolomide and underscoring the importance of aggressive resection strategies. In conclusion, our study elucidates the complex interplay of MGMTp methylation hierarchy and heterogeneity among grade 2-3 gliomas, providing insights into why astrocytomas and IDH wild-type lower-grade glioma might derive less benefit from chemotherapy.

A multivariate retrospective analysis of high-grade gliomas: Survival and prognostic factors.

OBJECTIVES: High-grade gliomas (HGGs) are highly malignant, aggressive, and have a high incidence and mortality rate. The aim of this study was to investigate survival outcomes and prognostic factors in patients with HGGs. METHODS: In this retrospective study, a total of 159 patients with histologically confirmed HGGs were included. The recruitment period was from January 2011 to December 2019. We evaluated patient demographic data, tumor characteristics, treatment methods, immunocytochemistry results, overall survival (OS) time, and progression-free survival (PFS) time using Kaplan-<>Meier survival analysis with log-rank testing. Additionally, we employed Cox regression analysis to identify independent factors associated with survival outcomes. RESULTS: Kaplan-Meier survival analysis revealed that the 1-, 2-, and 5-years OS rates were 81.8%, 50.3%, and 12.6%, respectively. Similarly, the 1-, 2-, and 5-years PFS rates were 50.9%, 22.4%, and 3.1%, respectively. The median OS duration was 35.0 months. The univariate analysis indicated that postoperative pathological classification, grade, and age were significantly associated with patient outcomes (p < 0.01). Among the patients, 147 received concurrent chemoradiotherapy, while 12 did not. The immunohistochemical markers of ki-67, MGMT, IDH1R132H, and p53 demonstrated statistically significant differences in their prognostic impact (p = 0.001, p = 0.020, p = 0.003, and p = 0.021, respectively). In conclusion, we found that grades, age, pathological classification, ki-67, MGMT, and IDH1R132H expression were statistically significantly associated with PFS (p < 0.01, p = 0.004, p = 0.003, p = 0.001, p = 0.036, and p = 0.028). Additionally, immunohistochemical expressions of TRIB3 and AURKA were significantly higher in patients with shorter survival (p = 0.015 and p = 0.023). CONCLUSIONS: Tumor grade and the use of concurrent chemoradiotherapy after surgery were independent prognostic factors that significantly influenced patient survival. Additionally, tumor grade and MGMT expression were found to be independent factors affecting progression-free survival (PFS). Notably, the expression of TRIB3 and AURKA was higher in patients with poor survival outcomes.

Advances in the Treatment of Pediatric Low-Grade Gliomas.

PURPOSE OF REVIEW: Pediatric low-grade gliomas (pLGGs) often result in significant long-term morbidities despite high overall survival rates. This review aims to consolidate the current understanding of pLGG biology and molecular features and provide an overview of current and emerging treatment strategies. RECENT FINDINGS: Surgical resection remains a primary treatment modality, supplemented by chemotherapy and radiotherapy in specific cases. However, recent advances have elucidated the molecular underpinnings of pLGGs, revealing key genetic abnormalities such as BRAF fusions and mutations and the involvement of the RAS/MAPK and mTOR pathways. Novel targeted therapies, including MEK, BRAF and pan-RAF inhibitors, have shown promise in clinical trials, demonstrating significant efficacy and manageable toxicity. Understanding of pLGGs has significantly improved, leading to more personalized treatment approaches. Targeted therapies have emerged as effective alternatives, potentially reducing long-term toxicities. Future research should focus on optimizing therapy sequences, understanding long-term impacts, and ensuring global accessibility to advanced treatments.

Connectomic insights into the impact of 1p/19q co-deletion in dominant hemisphere insular glioma patients.

Objectives: This study aimed to elucidate the influences of 1p/19q co-deletion on structural connectivity alterations in patients with dominant hemisphere insular diffuse gliomas. Methods: We incorporated 32 cases of left insular gliomas and 20 healthy controls for this study. Using diffusion MRI, we applied correlational tractography, differential tractography, and graph theoretical analysis to explore the potential connectivity associated with 1p/19q co-deletion. Results: The study revealed that the quantitative anisotropy (QA) of key deep medial fiber tracts, including the anterior thalamic radiation, superior thalamic radiation, fornix, and cingulum, had significant negative associations with 1p/19q co-deletion (FDR = 4.72 × 10-5). These tracts are crucial in maintaining the integrity of brain networks. Differential analysis further supported these findings (FWER-corrected p < 0.05). The 1p/19q non-co-deletion group exhibited significantly higher clustering coefficients (FDR-corrected p < 0.05) and reduced betweenness centrality (FDR-corrected p < 0.05) in regions around the tumor compared to HC group. Graph theoretical analysis indicated that non-co-deletion patients had increased local clustering and decreased betweenness centrality in peritumoral brain regions compared to co-deletion patients and healthy controls (FDR-corrected p < 0.05). Additionally, despite not being significant through correction, patients with 1p/19q co-deletion exhibited lower trends in weighted average clustering coefficient, transitivity, small worldness, and global efficiency, while showing higher tendencies in weighted path length compared to patients without the co-deletion. Conclusion: The findings of this study underline the significant role of 1p/19q co-deletion in altering structural connectivity in insular glioma patients. These alterations in brain networks could have profound implications for the neural functionality in patients with dominant hemisphere insular gliomas.

Significance of Nestin and CD133 as cancer stem cell markers in diffuse glioma and association with p53 expression and IDH status.

BACKGROUND: Recent evidence suggests that the tumor stem cells that are responsible for the pathogenesis of gliomas have similar properties to those of neural stem cells. We have studied two of the most consistently expressed stem cell markers in gliomas, i.e., CD133 and Nestin, and compared them with respect to p53 expression and IDH status. OBJECTIVES: To assess the level of expression of Nestin and CD133, and identify a correlation among various grades of diffuse glioma with IDH status and expression of p53. MATERIALS AND METHODS: A cross-sectional retrospective study with 102 subjects for the expression of cancer stem cell markers; CD133 and Nestin and the correlation of their expression with that of p53 and IDH1 status in adult diffuse glioma. The study was conducted in the Departments of Pathology and Neurosurgery. The expression was assessed by immunohistochemistry on formalin-fixed paraffin-embedded sections. The scoring of expression of CD133 and Nestin was adapted from Zhang et al. The scoring for p53 was adopted from Aruna et al. Results: The diffuse gliomas were graded based on WHO into grade II (30.3%), grade III (28.4%), and grade IV (41.3%). Among WHO grade IV, 59.4% were primary, and 40.4% were secondary glioblastomas. 73% of the diffuse gliomas were IDH mutant, and p53 showed an overall expression of 76.4%. The expression of CD133 and Nestin were compared with the increasing grades of diffuse gliomas, which, when plotted on ROC curves, had AUCs of 0.6806 and 0.6119, respectively. Their expression showed a positive correlation with the IDH status of the tumor. CONCLUSIONS: Cancer stem cell markers CD133 and Nestin are expressed in diffuse glioma and have a higher expression with increasing WHO grade of malignancy. These cancer stem cell markers have shown significant association with the IDH-1 mutant status of diffuse gliomas. Hence, it can be inferred that diffuse gliomas with a higher expression of CD133 and Nestin have a poorer prognosis. Further, these cancer stem cell markers may be used as therapeutic targets in the future.

Analysis of visual evoked potentials in patients with neurofibromatosis type 1: new concepts.

Introduction: Neurofibromatosis type 1 (NF type 1) is an autosomal dominant disease with typical clinical manifestations, such as skin lesions, Lisch nodules, optic pathway gliomas, and neurofibromas, caused by the mutation of the NF1 gene. Visual evoked potentials (VEP) present a measure of the electrophysiological response of visual cortex to a visual stimulus. The role of VEP in the pathophysiology of NF type 1 is very complex and requires additional research. The Aim: We examined the differences between NF type 1 patients with normal and altered VEP and analyzed the correlation between the prolongation of P100 latency and disease severity. Materials and methods: Two groups were formed: a control group and a study group with NF type 1 patients. Based on the control group analysis, a threshold value for a normal VEP finding of 116 ms was obtained, and it was used to divide the study group into subgroups with normal and altered VEP. We proceeded with examining the differences in clinical manifestations of the disease between the subgroups, after which we checked if there is a correlation between the prolongation of the P100 latency and the severity of the clinical picture according to the Riccardi scale. Statistical analysis was performed using the Pearson chi-square test and the Spearman correlation test in the program SPSS 28.0, with levels of statistical significance p = 0.05 and p = 0.001. Results: In the group with the abnormal VEP we found a statistically significant more frequent occurrence of optic tract glioma (p = 0.008), tumors (p = 0.032), epilepsy (p = 0.043), and cognitive disorders (p = 0.028), while the other clinical signs had an equal prevalence in both groups. A moderately strong correlation (r s = 0.665) was observed between the prolongation of P100 latency and the severity of the clinical picture. Conclusion: Our results showed the important role of VEP in the description of clinical phenotypes of NF type 1. The authors of the study propose VEP to be included in the diagnostic algorithms designed for patients with NF type 1.

Deep learning models for rapid discrimination of high-grade gliomas from solitary brain metastases using multi-plane T1-weighted contrast-enhanced (T1CE) images.

Background: High-grade gliomas (HGG) and solitary brain metastases (SBM) are two common types of brain tumors in middle-aged and elderly patients. HGG and SBM display a high degree of similarity on magnetic resonance imaging (MRI) images. Consequently, differential diagnosis using preoperative MRI remains challenging. This study developed deep learning models that used pre-operative T1-weighted contrast-enhanced (T1CE) MRI images to differentiate between HGG and SBM before surgery. Methods: By comparing various convolutional neural network models using T1CE image data from The First Medical Center of the Chinese PLA General Hospital and The Second People's Hospital of Yibin (Data collection for this study spanned from January 2016 to December 2023), it was confirmed that the GoogLeNet model exhibited the highest discriminative performance. Additionally, we evaluated the individual impact of the tumoral core and peritumoral edema regions on the network's predictive performance. Finally, we adopted a slice-based voting method to assess the accuracy of the validation dataset and evaluated patient prediction performance on an additional test dataset. Results: The GoogLeNet model, in a five-fold cross-validation using multi-plane T1CE slices (axial, coronal, and sagittal) from 180 patients, achieved an average patient accuracy of 92.78%, a sensitivity of 95.56%, and a specificity of 90.00%. Moreover, on an external test set of 29 patients, the model achieved an accuracy of 89.66%, a sensitivity of 90.91%, and a specificity of 83.33%, with an area under the curve of 0.939 [95% confidence interval (CI): 0.842-1.000]. Conclusions: GoogLeNet performed better than previous methods at differentiating HGG from SBM, even for core and peritumoral edema in both. HGG and SBM could be fast screened using this end-to-end approach, improving workflow for both tumor treatments.

Assessing the prognostic role of panimmune inflammation in high-grade gliomas.

OBJECTIVE: High-grade gliomas are aggressive brain tumors with poor prognoses. Understanding the factors that influence their progression is crucial for improving treatment outcomes. This study investigates the prognostic significance of panimmune inflammation in patients diagnosed with high-grade gliomas. MATERIALS-METHODS: Data from 89 high-grade glioma patients were analysed retrospectively. The Panimmune inflammation Value (PIV) of each patient meeting the eligibility criteria was calculated on the basis of platelet, monocyte, neutrophil, and lymphocyte counts obtained from peripheral blood samples taken on the first day of treatment. PIV is calculated using the following formula: PIV = T × M × N ÷ L. A receiver operating characteristic (ROC) analysis was employed to identify the optimal cut-off value for PIV about progression-free survival (PFS) and overall survival (OS) outcomes. The primary and secondary endpoints were the differences in OS and PFS between the PIV groups. The Kaplan‒Meier method was used for survival analyses. RESULTS: The ROC analysis indicated that the optimal PIV threshold was 545.5, which exhibited a significant interaction with PFS and OS outcomes. Patients were subsequently divided into two groups based on their PIV levels: a low PIV (L-PIV) group comprising 45 patients and a high PIV (H-PIV) group comprising 44 patients. A comparative analysis of survival rates indicated that patients with elevated PIV had a shorter median PFS of 4.0 months compared to 8.0 months in the low PIV group (P = 0.797), as well as a reduced median OS of 19.0 months versus not available (NA) in the low PIV group (P = 0.215). CONCLUSION: Our study results did not reveal a statistically significant association between H-PIV measurements and reduced PFS or OS. However, PIV effectively stratified newly diagnosed high-grade glioma patients into two distinct groups with significantly different PFS and OS outcomes.

Fluorescence-Guided Surgical Techniques in Adult Diffuse Low-Grade Gliomas: State-of-the-Art and Emerging Techniques: A Systematic Review.

Diffuse low-grade gliomas are infiltrative tumors whose margins are not distinguishable from the adjacent healthy brain parenchyma. The aim was to precisely examine the results provided by the intraoperative use of macroscopic fluorescence in diffuse low-grade gliomas and to describe the new fluorescence-based techniques capable of guiding the resection of low-grade gliomas. Only about 20% and 50% of low-grade gliomas are macroscopically fluorescent after 5-amino-levulinic acid (5-ALA) or fluorescein sodium intake, respectively. However, 5-ALA is helpful for detecting anaplastic foci, and thus choosing the best biopsy targets in diffuse gliomas. Spectroscopic detection of 5-ALA-induced fluorescence can detect very low and non-macroscopically visible concentrations of protoporphyrin IX, a 5-ALA metabolite, and, consequently, has excellent performances for the detection of low-grade gliomas. Moreover, these tumors have a specific spectroscopic signature with two fluorescence emission peaks, which is useful for distinguishing them not only from healthy brain but also from high-grade gliomas. Confocal laser endomicroscopy can generate intraoperative optic biopsies, but its sensitivity remains limited. In the future, the coupled measurement of autofluorescence and induced fluorescence, and the introduction of fluorescence detection technologies providing a wider field of view could result in the development of operator-friendly tools implementable in the operative routine.

Trans-temporal trans-choroidal resection of thalamic and thalamopeduncular tumors: how I do it.

BACKGROUND:  Surgical resection is the cornerstone of treatment for low-grade tumors, albeit total excision is beneficial. As the thalamus is surrounded by vital neurovascular system, lesions here present a surgical challenge. METHOD: This article aims to demonstrate the trans-temporal, trans-choroidal fissure approach's effective surgical therapy on patients with thalamic lesions. With this approach, we were able to remove the tumor completely in three patients and almost completely in six more. Here we discuss a few technical details and potential hazards of the procedure with an operative video. CONCLUSION: This approach  provides excellent access to the deep areas of brain.

Single Nucleus Total RNA Sequencing of Formalin-Fixed Paraffin-Embedded Gliomas.

Gliomas, the predominant form of brain cancer, comprise diverse malignant subtypes with limited curative therapies available. The insufficient understanding of their molecular diversity and evolutionary processes hinders the advancement of new treatments. Technical complexities associated with formalin-fixed paraffin-embedded (FFPE) clinical samples hinder molecular-level analyses of gliomas. Current single-cell RNA sequencing (scRNA-seq) platforms are inadequate for large-scale clinical applications. In this study, automated snRandom-seq is developed, a high-throughput single-nucleus total RNA sequencing platform optimized for archival FFPE samples. This platform integrates automated single-nucleus isolation and droplet barcoding systems with the random primer-based scRNA-seq chemistry, accommodating a broad spectrum of sample types. The automated snRandom-seq is applied to analyze 116 492 single nuclei from 17 FFPE samples of various glioma subtypes, including rare clinical samples and matched primary-recurrent glioblastomas (GBMs). The study provides comprehensive insights into the molecular characteristics of gliomas at the single-cell level. Abundant non-coding RNAs (ncRNAs) with distinct expression profiles across different glioma clusters and uncovered promising recurrence-related targets and pathways in primary-recurrent GBMs are identified. These findings establish automated snRandom-seq as a robust tool for scRNA-seq of FFPE samples, enabling exploration of molecular diversities and tumor evolution. This platform holds significant implications for large-scale integrative and retrospective clinical research.

Enhanced Multimodal Brain Tumor Classification in MR Images using 2D ResNet as backbone with Explicit Tumor Size Information.

It's a major public health problem of global concern that malignant gliomas tend to grow rapidly and infiltrate surrounding tissues. Accurate grading of the tumor can determine the degree of malignancy to formulate the best treatment plan, which can eliminate the tumor or limit widespread metastasis of the tumor, saving the patient's life and improving their prognosis. To more accurately predict the grading of gliomas, we proposed a novel method of combining the advantages of 2D and 3D Convolutional Neural Networks for tumor grading by multimodality on Magnetic Resonance Imaging. The core of the innovation lies in our combination of tumor 3D information extracted from multimodal data with those obtained from a 2D ResNet50 architecture. It solves both the lack of temporal-spatial information provided by 3D imaging in 2D convolutional neural networks and avoids more noise from too much information in 3D convolutional neural networks, which causes serious overfitting problems. Incorporating explicit tumor 3D information, such as tumor volume and surface area, enhances the grading model's performance and addresses the limitations of both approaches. By fusing information from multiple modalities, the model achieves a more precise and accurate characterization of tumors. The model I s trained and evaluated using two publicly available brain glioma datasets, achieving an AUC of 0.9684 on the validation set. The model's interpretability is enhanced through heatmaps, which highlight the tumor region. The proposed method holds promise for clinical application in tumor grading and contributes to the field of medical diagnostics for prediction.

Multicenter integration analysis of TRP channels revealed potential mechanisms of immunosuppressive microenvironment activation and identified a machine learning-derived signature for improving outcomes in gliomas.

AIM: This study aimed to explore the mechanisms of transient receptor potential (TRP) channels on the immune microenvironment and develop a TRP-related signature for predicting prognosis, immunotherapy response, and drug sensitivity in gliomas. METHODS: Based on the unsupervised clustering algorithm, we identified novel TRP channel clusters and investigated their biological function, immune microenvironment, and genomic heterogeneity. In vitro and in vivo experiments revealed the association between TRPV2 and macrophages. Subsequently, based on 96 machine learning algorithms and six independent glioma cohorts, we constructed a machine learning-based TRP channel signature (MLTS). The performance of the MLTS in predicting prognosis, immunotherapy response, and drug sensitivity was evaluated. RESULTS: Patients with high expression levels of TRP channel genes had worse prognoses, higher tumor mutation burden, and more activated immunosuppressive microenvironment. Meanwhile, TRPV2 was identified as the most essential regulator in TRP channels. TRPV2 activation could promote macrophages migration toward malignant cells and alleviate glioma prognosis. Furthermore, MLTS could work independently of common clinical features and present stable and superior prediction performance. CONCLUSION: This study investigated the comprehensive effect of TRP channel genes in gliomas and provided a promising tool for designing effective, precise treatment strategies.

The role of lactate-induced protein lactylation in gliomas: implications for preclinical research and the development of new treatments.

The most prevalent primary brain tumors in adults are gliomas. In addition to insufficient therapeutic alternatives, gliomas are fatal mostly due to the rapid proliferation and continuous infiltration of tumor cells into the surrounding healthy brain tissue. According to a growing body of research, aerobic glycolysis, or the Warburg effect, promotes glioma development because gliomas are heterogeneous cancers that undergo metabolic reprogramming. Therefore, addressing the Warburg effect might be a useful therapeutic strategy for treating cancer. Lactate plays a critical role in reprogramming energy metabolism, allowing cells to rapidly access large amounts of energy. Lactate, a byproduct of glycolysis, is therefore present in rapidly proliferating cells and tumors. In addition to the protumorigenesis pathways of lactate synthesis, circulation, and consumption, lactate-induced lactylation has been identified in recent investigations. Lactate plays crucial roles in modulating immune processes, maintaining homeostasis, and promoting metabolic reprogramming in tumors, which are processes regulated by the lactate-induced lactylation of the lysine residues of histones. In this paper, we discuss the discovery and effects of lactylation, review the published studies on how protein lactylation influences cancer growth and further explore novel treatment approaches to achieve improved antitumor effects by targeting lactylation. These findings could lead to a new approach and guidance for improving the prognosis of patients with gliomas.

Oligodendroglioma: a neurological perspective in Sub-saharan Africa.

Gliomas are a kind of brain cancer that develops from glial cells. Glial cells provide nourishment and energy to nerve cells, and they also preserve the blood-brain barrier. A primary cancer of the central nervous system (CNS) is oligodendroglioma. This suggests that it originates in the brain or spinal cord. While oligodendrogliomas can strike anyone at any age, the age range of 35 to 44 is when they most commonly occur. Oligodendrogliomas are rare in young people and more common in men than women. Based on anecdotal data, patients with oligodendroglioma may present management challenges in Africa. There are delays in diagnosis and referrals due to the scarcity of neuroimaging facilities. A wide range of strategies have been put forth to improve pathology services in low- and middle-income nations. Adequate mentorship, short-term visitor programs, overcoming supply chain constraints, establishing training standards, and establishing the role of pathologists in cancer screening and early diagnosis have all been proposed as solutions to this problem. To sum up, oligodendroglioma is one of the low-grade gliomas this study looked at. Brain cancer is a serious public health concern in Africa. Improved options for screening and therapy are required to better address this problem.

Controversies in neuro-oncology: Focal proton versus photon radiation therapy for adult brain tumors.

Radiation therapy (RT) plays a fundamental role in the treatment of malignant and benign brain tumors. Current state-of-the-art photon- and proton-based RT combines more conformal dose distribution of target volumes and accurate dose delivery while limiting the adverse radiation effects. PubMed was systematically searched from from 2000 to October 2023 to identify studies reporting outcomes related to treatment of central nervous system (CNS)/skull base tumors with PT in adults. Several studies have demonstrated that proton therapy (PT) provides a reduced dose to healthy brain parenchyma compared with photon-based (xRT) radiation techniques. However, whether dosimetric advantages translate into superior clinical outcomes for different adult brain tumors remains an open question. This review aims at critically reviewing the recent studies on PT in adult patients with brain tumors, including glioma, meningiomas, and chordomas, to explore its potential benefits compared with xRT.

Noninvasive prediction of CCL2 expression level in high-grade glioma patients.

BACKGROUND: Gliomas are recognized as the most frequent type of malignancies in the central nervous system, and efficacious prognostic indicators are essential to treat patients with gliomas and improve their clinical outcomes. The chemokine (C-C motif) ligand 2 (CCL2) is a promising predictor for glioma malignancy and progression. However, at present, the methods to evaluate CCL2 expression level are invasive and operator-dependent. OBJECTIVE: It was expected to noninvasively predict CCL2 expression levels in malignant glioma tissues by magnetic resonance imaging (MRI)-based radiomics and assess the association between the developed radiomics model and prognostic indicators and related genes. METHODS: MRI-based radiomics was used to predict CCL2 expression level using data obtained from The Cancer Imaging Archive (TCIA) and The Cancer Genome Atlas (TCGA) databases. A support vector machine (SVM)-based radiomics model and a logistic regression (LR)-based radiomics model were used to predict the radiomics score, and its correlation with CCL2 expression level was analyzed. RESULTS: The results revealed that there was an association between CCL2 expression level and the overall survival of cases with gliomas, and bioinformatics correlation analysis showed that CCL2 expression level was highly correlated with disease-related pathways, such as mTOR signaling pathway, cGMP-PKG signaling pathway, and MAPK signaling pathway. Both SVM- and LR-based radiomics data robustly predicted CCL2 expression level, and radiomics scores could also be used to predict the overall survival of patients. Moreover, the high/low radiomics scores were highly correlated with the known glioma-related genes, including CD70, CD27, and PDCD1. CONCLUSION: An MRI-based radiomics model was successfully developed, and its clinical benefits were confirmed, including the prediction of CCL2 expression level and patients' prognosis.

Forms of Non-Apoptotic Cell Death and Their Role in Gliomas-Presentation of the Current State of Knowledge.

In addition to necrosis and apoptosis, the two forms of cell death that have been known for many decades, other non-apoptotic forms of cell death have been discovered, many of which also play a role in tumors. Starting with the description of autophagy more than 60 years ago, newer forms of cell death have become important for the biology of tumors, such as ferroptosis, pyroptosis, necroptosis, and paraptosis. In this review, all non-apoptotic and oncologically relevant forms of programmed cell death are presented, starting with their first descriptions, their molecular characteristics, and their role and their interactions in cell physiology and pathophysiology. Based on these descriptions, the current state of knowledge about their alterations and their role in gliomas will be presented. In addition, current efforts to therapeutically influence the molecular components of these forms of cell death will be discussed. Although research into their exact role in gliomas is still at a rather early stage, our review clarifies that all these non-apoptotic forms of cell death show significant alterations in gliomas and that important insight into understanding them has already been gained.

MGMT promoter methylation is a strong prognostic factor for survival after progression in high-grade gliomas.

BACKGROUND: High-grade gliomas (HGGs) have a rapid relapse and short survival. Studies have identified many clinical characteristics and biomarkers associated with progression-free survival (PFS) and over-survival (OS). However, there has not yet a comprehensive study on survival after the first progression (SAP). METHODS: From CGGA and TCGA, 319 and 308 HGGs were confirmed as the first progression. The data on clinical characteristics and biomarkers were analyzed in accordance with OS, PFS, and SAP. RESULTS: Analysis of 319 patients from CGGA, significant predictors of improved OS/PFS/SAP were WHO grade, MGMT promoter methylation, and Ki-67 expression in univariate analysis. Further multivariate analysis showed MGMT promoter methylation and Ki-67 expression were independent predictors. However, an analysis of 308 patients from TCGA found MGMT promoter methylation is the only prognostic marker. A longer SAP was observed in patients with methylated MGMT promoter after standard chemoradiotherapy. In our data, HGGs could be divided into low, intermediate, and high-risk groups for SAP by MGMT methylation and Ki-67 expression. CONCLUSIONS: Patients with MGMT promoter methylation have a prolonger SAP after standard chemoradiotherapy. HGGs could be divided into low, intermediate, and high-risk groups for SAP according to MGMT status and Ki-67 expression.