Type Of Glioma Research Articles

Priority-Elastic net for binary disease outcome prediction based on multi-omics data

BackgroundHigh-dimensional omics data integration has emerged as a prominent avenue within the healthcare industry, presenting substantial potential to improve predictive models. However, the data integration process faces several challenges, including data heterogeneity, priority sequence in which data blocks are prioritized for rendering predictive information contained in multiple blocks, assessing the flow of information from one omics level to the other and multicollinearity.MethodsWe propose the Priority-Elastic net algorithm, a hierarchical regression method extending Priority-Lasso for the binary logistic regression model by incorporating a priority order for blocks of variables while fitting Elastic-net models sequentially for each block. The fitted values from each step are then used as an offset in the subsequent step. Additionally, we considered the adaptive elastic-net penalty within our priority framework to compare the results.ResultsThe Priority-Elastic net and Priority-Adaptive Elastic net algorithms were evaluated on a brain tumor dataset available from The Cancer Genome Atlas (TCGA), accounting for transcriptomics, proteomics, and clinical information measured over two glioma types: Lower-grade glioma (LGG) and glioblastoma (GBM).ConclusionOur findings suggest that the Priority-Elastic net is a highly advantageous choice for a wide range of applications. It offers moderate computational complexity, flexibility in integrating prior knowledge while introducing a hierarchical modeling perspective, and, importantly, improved stability and accuracy in predictions, making it superior to the other methods discussed. This evolution marks a significant step forward in predictive modeling, offering a sophisticated tool for navigating the complexities of multi-omics datasets in pursuit of precision medicine’s ultimate goal: personalized treatment optimization based on a comprehensive array of patient-specific data. This framework can be generalized to time-to-event, Cox proportional hazards regression and multicategorical outcomes. A practical implementation of this method is available upon request in R script, complete with an example to facilitate its application.

Correlation of degree and pattern of contrast enhancement on Magnetic Resonance Imaging with histopathological grade of intracranial astrocytoma

Background/Objective: Astrocytomas, a type of glioma, require accurate grading to guide treatment. This study evaluates the correlation between MRI contrast enhancement and histopathological grades of astrocytomas. Methods: A cross-sectional study of 37 patients with biopsy-confirmed astrocytomas was conducted. Non-probability or purposive sampling was carried out. MRI scans assessed contrast enhancement characteristics, and tumors were classified radiologically and histopathologically. Results: The age range of the patients was 11 to 74 years and mean age was 40.25±16.04 years. The male to female ratio was 4:1. Headache was the most common presenting symptoms (95%). Most of the tumors were located at the cerebral hemispheres (78%). None or slight contrast enhancement was found in 17 (46%) and the pattern of contrast enhancement was heterogeneous in 24 (65%) patients. Maximum 20 (54%) patients had high grade astrocytoma. In the present study, 85% high grade astrocytoma showed moderate to marked whereas 82.4% low grade astrocytoma showed none or slight contrast enhancement. Sensitivity & specificity of contrast enhanced MRI was 82.4% and 85% respectively. The overall accuracy was 83.78%. Conclusion: MRI is a reliable non-invasive tool for grading astrocytomas, with strong correlation between contrast enhancement and tumor grade, supporting its use in clinical decision-making. J Shaheed Suhrawardy Med Coll 2023; 15(1): 13-19

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.

Role of Advanced Magnetic Resonance Imaging in Differentiating among Glioma Subtypes and Predicting Tumor-Proliferative Behavior

Abstract Objective Gliomas are a devastating and heterogeneous group of primary brain tumors. Previously, the source of glioma was undetermined. Recent literature indicates that neural stem cells, or progenitors, are proposed to be the source of glioma. The prognosis of different types of gliomas differs due to their various biological tissue types. Besides the histological grade, the two useful immunohistochemistry markers that show the tumor's biological behavior are isocitrate dehydrogenase (IDH) labeling and the Ki-67 labeling index. We sought to determine the magnetic resonance imaging (MRI) characteristics associated with IDH mutational status and ascertain whether MRI combined with IDH mutational status, can better predict the clinical outcomes of gliomas. Materials and Methods This period study was conducted in the Department of Radiology, Sri Ramachandra Institute of Higher Education and Research, Chennai, Tamil Nadu, India for 5 years (May 2016–May 2021). The study cohort included 30 patients diagnosed with gliomas who underwent preoperative MRI followed by surgical resection and histopathological examination. Preoperative MRI images were done to assess qualitative tumor characteristics such as location, margin of tumor, extent, cortical involvement, cystic component, mineralization or hemorrhage, and contrast enhancement. Discussion Differences in MRI features between IDH-mutant (MT) and IDH-wild-type (WT) groups were analyzed using the chi-square test for categorical variables and the Mann–Whitney U test for continuous variables. Statistical analysis was conducted using SPSS software. Results Among the 30 patients evaluated, 18 had IDH-WT and 12 had IDH-MT type gliomas. Male predominance (73.33%) was noted in our study. Brainstem location, indistinct borders (83.33%), less cortical involvement (72.22%), less cystic changes (88.89%), more area of necrotic component (44.44%), significantly increased choline/creatine (Cho/Cr) ratio, and choline/N-acetyl aspartate (Cho/NAA) ratio favors IDH-WT tumors. Positive T2-fluid-attenuated inversion recovery mismatch sign is more frequently seen in IDH-MT (7/12; 58.33%) tumors than in IDH-WT (4/18; 22.22%) tumors. Whereas well-defined contours (66.67%), more cortical involvement (83.33%), more cystic changes (58.33%), and less area of necrotic component favor IDH-MT type tumors. Conclusion MRI is a very promising and valuable tool for differentiating among glioma subtypes and predicting tumor-proliferative behavior in glioma cases. The combination of MRI characteristics with IDH mutation status enhances the predictive accuracy for clinical outcomes in glioma patients. This approach could potentially guide treatment planning and improve prognostic assessments.

Region-based analyses of existing genome-wide association studies identifies novel potential genetic susceptibility regions for glioma.

Glioma is a rare and debilitating brain cancer with one of the lowest cancer survival rates. Genome-wide association studies have identified 34 genetic susceptibility regions. We sought to discover novel susceptibility regions using approaches which test groups of contiguous genetic markers simultaneously. We analyzed data from three independent glioma studies of European ancestry, GliomaScan (1,316 cases/1,293 controls), AGOG (560 cases/2,237 controls), and GICC (4,000 cases/2,411 controls), using the machine-learning algorithm DEPTH and a region-based regression method based on the generalized Berk-Jones (GBJ) statistic, to assess the association of glioma with genomic regions by glioma type and sex. Summary statistics from the UCSF/Mayo Clinic study were used for independent validation. We conducted a meta-analysis using GliomaScan, AGOG, GICC and UCSF/Mayo. We identified 11 novel candidate genomic regions for glioma risk common to multiple studies. Two of the 11 regions, 16p13.3 containing RBFOX1 and 1p36.21 containing PRDM2, were significantly associated with female and male glioma risk respectively, based on results of the meta-analysis. Both regions have been previously linked to glioma tumor progression. Three of the 11 regions contain neurotransmitter receptor genes (7q31.33 GRM8, 5q35.2 DRD1, 15q13.3 CHRNA7). Our region-based approach identified 11 genomic regions that suggest association with glioma risk of which two regions, 16p13.3 and 1p36.21, warrant further investigation as genetic susceptibility regions for female and male risk respectively. Our analyses suggest that genetic susceptibility to glioma may differ by sex and highlights the possibility that synapse-related genes play a role in glioma susceptibility.

Relationship between radiofrequency-electromagnetic radiation from cellular phones and brain tumor: meta-analyses using various proxies for RF-EMR exposure-outcome assessment

IntroductionThe authors conducted meta-analyses regarding the association between cellular and mobile phone use and brain tumor development by applying various radiofrequency-electromagnetic radiation (RF-EMR) exposure subcategories. With changing patterns of mobile phone use and rapidly developing Wireless Personal Area Network (WPAN) technology (such as Bluetooth), this study will provide insight into the importance of more precise exposure subcategories for RF-EMR.MethodsThe medical librarian searched MEDLINE (PubMed), EMBASE, and the Cochrane Library until 16 December 2020.ResultsIn these meta-analyses, 19 case-control studies and five cohort studies were included. Ipsilateral users reported a pooled odds ratio (OR) of 1.40 (95% CI 1.21–1.62) compared to non-regular users. Users with years of use over 10 years reported a pooled OR of 1.27 (95% CI 1.08–1.48). When stratified by each type of brain tumor, only meningioma (OR 1.20 (95% CI 1.04–1.39)), glioma (OR 1.45 (95% CI 1.16–1.82)), and malignant brain tumors (OR 1.93 (95% CI 1.55–2.39)) showed an increased OR with statistical significance for ipsilateral users. For users with years of use over 10 years, only glioma (OR 1.32 (95% CI 1.01–1.71)) showed an increased OR with statistical significance. When 11 studies with an OR with cumulative hours of use over 896 h were synthesized, the pooled OR was 1.59 (95% CI 1.25–2.02). When stratified by each type of brain tumor, glioma, meningioma, and acoustic neuroma reported the pooled OR of 1.66 (95% CI 1.13–2.44), 1.29 (95% CI 1.08–1.54), and 1.84 (95% CI 0.78–4.37), respectively. For each individual study that considered cumulative hours of use, the highest OR for glioma, meningioma, and acoustic neuroma was 2.89 (1.41–5.93) (both side use, > 896 h), 2.57 (1.02–6.44) (both side use, > 896 h), and 3.53 (1.59–7.82) (ipsilateral use, > 1640 h), respectively. For five cohort studies, the pooled risk ratios (RRs) for all CNS tumors, glioma, meningioma, and acoustic neuroma, were statistically equivocal, respectively. However, the point estimates for acoustic neuroma showed a rather increased pooled RR for ever-use (1.26) and over 10 years of use (1.61) compared to never-use, respectively.DiscussionIn this meta-analysis, as the exposure subcategory used became more concrete, the pooled ORs demonstrated higher values with statistical significance. Although the meta-analysis of cohort studies yielded statistically inconclusive pooled effect estimates, (i) as the number of studies included grows and (ii) as the applied exposure subcategories become more concrete, the pooled RRs could show a different aspect in future research. Additionally, future studies should thoroughly account for changing patterns in mobile phone use and the growing use of earphones or headphones with WPAN technology.

Attenuation coefficient as a tool to detect changes in the white matter of the rat brain caused by different types of gliomas and irradiation

In the present work, we carried out a comparative study of the attenuation coefficient of the white matter of the rat brain during the growth of glial tumors characterized by different degrees of malignancy (glioblastoma 101/8, astrocytoma 10-17-2, glioma C6) and during irradiation. We demonstrated that some tumor models cause a pronounced decrease in white matter attenuation coefficient values due to infiltration of tumor cells, myelinated fiber destruction, and edema. In contrast, other tumors cause compression of the myelinated fibers of the corpus callosum without their ruptures and prominent invasion of tumor cells, which preserved the attenuation coefficient values changeless. In addition, for the first time, the possibility of using the attenuation coefficient to detect late radiation-induced changes in white matter characterized by focal development of edema, disruption of the integrity of myelinated fibers, and a decrease in the amount of oligodendrocytes and differentiation of these areas from tumor tissue and healthy white matter has been demonstrated. The results indicate the promise of using the attenuation coefficient estimated from OCT data for in vivo assessment of the degree of destruction of peritumoral white matter or its compression, which makes this method useful not only in primary resections but also in repeated surgical interventions for recurrent tumors.

PDOC-03 CASE SERIES ON PEDIATRIC PATIENTS WITH LEPTOMENINGEAL METASTASES FROM VARIOUS PRIMARY BRAIN TUMORS: FROM CLINICAL PRESENTATIONS TO OUTCOMES

Abstract Leptomeningeal disease (LMD), also known as carcinomatous meningitis, is when cancer cells are found in the thin layers covering the brain and spinal cord, in the spaces between these layers, or in the fluid surrounding the brain and spinal cord. In children with brain tumors, LMD is rare, occurring in about 1% to 2% of cases. It’s most commonly seen in certain types of tumors like medulloblastoma and primary central nervous system lymphoma, but it can also occur in other types such as pineoblastoma, Atypical Teratoid Rhabdoid Tumor, and both low-grade and high-grade gliomas. Although pilocytic astrocytomas, a type of low-grade glioma, seldom spread, there have been a few reported cases of them spreading to the leptomeninges. The exact prevalence of LMD in pediatric brain tumors isn’t well-documented due to differences in how it’s screened for across different types of tumors and at different stages of the disease. Improved surgical methods and various treatments targeting specific areas or affecting the whole body have resulted in better survival rates for patients with LMD. Detecting LMD early is important for treatment options. It can be found either at the same time as the primary brain tumor, when the tumor comes back, or as LMD without an initial tumor. There’s concern that procedures to divert cerebrospinal fluid might spread cancer cells. MRI scans are important for diagnosing LMD, but it can still be challenging to diagnose based on these scans alone. Usually, confirmation is done by analyzing the fluid around the brain and spinal cord for cancer cells. Given that LMD is a complex and rare complication of pediatric brain tumors, more research is needed to improve diagnosis and treatment. In this article, we’ll discuss three cases of pediatric brain tumors with LMD, including how they were diagnosed, treated, and their clinical outcomes.

Metabotropic Glutamate Receptors Type 3 and 5 Feature the "NeuroTransmitter-type" of Glioblastoma: A Bioinformatic Approach.

Glioblastoma (GBM) represents an aggressive and common tumor of the central nervous system. The prognosis of GBM is poor, and despite a refined genetic and molecular characterization, pharmacological treatment is largely suboptimal. Contribute to defining a therapeutic line in GBM targeting the mGlu3 receptor in line with the principles of precision medicine. Here, we performed a computational analysis focused on the expression of type 3 and 5 metabotropic glutamate receptor subtypes (mGlu3 and mGlu5, respectively) in high- and low-grade gliomas. The analysis allowed the identification of a particular high-grade glioma type, characterized by a high expression level of both receptor subtypes and by other markers of excitatory and inhibitory neurotransmission. This so-called neurotransmitter-GBM (NT-GBM) also shows a distinct immunological, metabolic, and vascularization gene signature. Our findings might lay the groundwork for a targeted therapy to be specifically applied to this putative novel type of GBM.

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.

Application of U-Net Network Utilizing Multiattention Gate for MRI Segmentation of Brain Tumors.

Studies have shown that the type of low-grade glioma is associated with its shape. The traditional diagnostic method involves extraction of the tumor shape from MRIs and diagnosing the type of glioma based on corresponding relationship between the glioma shape and type. This method is affected by the MRI background, tumor pixel size, and doctors' professional level, leading to misdiagnoses and missed diagnoses. With the help of deep learning algorithms, the shape of a glioma can be automatically segmented, thereby assisting doctors to focus more on the diagnosis of glioma and improving diagnostic efficiency. The segmentation of glioma MRIs using traditional deep learning algorithms exhibits limited accuracy, thereby impeding the effectiveness of assisting doctors in the diagnosis. The primary objective of our research is to facilitate the segmentation of low-grade glioma MRIs for medical practitioners through the utilization of deep learning algorithms. In this study, a UNet glioma segmentation network that incorporates multiattention gates was proposed to address this limitation. The UNet-based algorithm in the coding part integrated the attention gate into the hierarchical structure of the network to suppress the features of irrelevant regions and reduce the feature redundancy. In the decoding part, by adding attention gates in the fusion process of low- and high-level features, important feature information was highlighted, model parameters were reduced, and model sensitivity and accuracy were improved. The network model performed image segmentation on the glioma MRI dataset, and the accuracy and average intersection ratio (mIoU) of the algorithm segmentation reached 99.7%, 87.3%, 99.7%, and 87.6%. Compared with the UNet, PSPNet, and Attention UNet network models, this network model has obvious advantages in accuracy, mIoU, and loss convergence. It can serve as a standard for assisting doctors in diagnosis.

Evaluating the impact of tubular retractors in glioma surgery: A systematic review and meta-analysis

BackgroundAchieving safe, maximal tumor resection in gliomas can be challenging due to the tumor’s intricate relationship with surrounding structures. Tubular retractors offer a minimally invasive approach, preserving functional pathways and reducing complications. To assess their efficacy and safety, we conducted a systematic review and meta-analysis. MethodsA search across databases identified 26 studies meeting inclusion criteria, encompassing 106 patients with various glioma types and tumor locations. ResultsAmong 26 eligible studies, 15 provided sufficient data on 106 patients (median age: 50.5 years). Glioblastoma multiforme constituted 52.4 % of tumors, followed by IDH-mutant astrocytomas at 31.0 %. Tumor locations varied, with intraventricular and thalamic involvement in 16.3 % (16/98) of cases, followed by temporal (12.2 %), frontal and occipital (each 8.16 %), basal ganglia (8.16 %), parietal (7.14 %), optic pathway (2.04 %), and caudate nucleus (1.02 %) involvement. VyCor and Brainpath retractors were most used (22.6 % and 21.7 %, respectively). Tubular retractors were often combined with the exoscope (35.9 %). Gross total resection (GTR) was achieved in 69.4 % of cases, near-total resection (NTR) in 5.1 %, and subtotal resection/partial resection (STR/PR) in 25.5 %. Mean extent of resection (EOR) significantly differed between GTR and STR/NTR/PR groups (p<0.001). Postoperative complications included visual deficits (6.38 %), hemiparesis or weakness (2.13 %), multiple complications (1.06 %), and other unspecified complications (3.19 %). ConclusionTubular retractors are a valuable intraoperative adjunct and component of the surgical armamentarium for glioma surgery allowing bimanual operative techniques to manage hemostasis directly with excellent surgical outcomes and an acceptable complication profile.

AB091. Establishment and application of brainstem glioma organoids.

Traditional preclinical experiments on brainstem gliomas mainly rely on patient-derived primary cell lines, but there are problems such as low success rate in establishment and inability to preserve tumor heterogeneity, which limit the clinical transformation. As a new type of in vitro tumor model, organoids have similar structure and function to the original tumor, requiring less tissue for cultivation, with short cycle and high success rate, which is particularly suitable for brainstem glioma biopsy. There is currently no precedent for the successful construction of brainstem glioma organoid models. This new established organoid provides us a more robust preclinical tool for comprehending the pathogenesis and conducting drug screening for this kind of disease. Cultivate patient-derived brainstem glioma organoids in vitro, verify the genetic fidelity and consistency of the organoids through morphological experiments as well as sequencing technology. Then explore the evolutionary direction of multiple types of brainstem gliomas through pseudo-time series analysis. Complete drug screening, natural killer (NK) cell co-culture, oncolytic virus therapy, and other treatments based on organoids in vitro, and evaluate the efficacy. Complete co-culture of organoids and Institute of Cancer Research (ICR) mouse brain slices in vitro. Establish patient-derived organoid xenograft (PDOX) mouse models derived from organoids in vivo. The establishment of organoids of all types of brainstem gliomas was completed for the first time in the world, with a total of 41/48 organoid models derived from patients, with a success rate of 85.4%, covering all segments and pathological types. The results of morphological experiments and sequencing showed that the genetic characteristics of organoids were highly consistent with those of tumor tissues. Drug screening tests for temozolomide and panobinostat were completed in vitro, and NK cell co-culture and oncolytic virus therapy testing were achieved. Co-culture of brainstem glioma organoids and mouse brain slices was achieved in vitro. Furthermore, a PDOX model of brainstem glioma was established. Brainstem glioma organoids can be established maturely, stably, and reliably, and can be used for preclinical drug testing for patients. Animal models derived from brainstem glioma organoids have broad preclinical experimental value.

Evaluation of Single and Combined Temozolomide and Doxorubicin Treatment Responses in Low- and High-Grade Glioma In Vitro.

Astrocytoma, the most common type of glioma, can histologically be low or high grade. Treatment recommendations for astrocytic tumors are based on the histopathological and molecular phenotype. For grade 2 astrocytoma, the combination of radiotherapy and adjuvant chemotherapy with procarbazine, lomustine, and vincristine (PCV) is better than radiotherapy alone. Temozolomide (TMZ) is being increasingly recognized as a replacement for PCV in brain tumor therapy, due to the lower myelotoxicity. TMZ is currently a well-established first-line treatment for grade 3 astrocytoma, grade 4 astrocytoma, and glioblastoma and it is also sporadically used for grade 2 astrocytoma. However, TMZ faces multiple challenges such as adverse effects and drug resistance. In this study, we compared the cytotoxic effect induced by TMZ and doxorubicin (DOXO), alone and in combination, on a low-grade astrocytoma cell line (AC1B) and a high-grade glioma cell line (GB1B). We found that TMZ and DOXO, each produced a cytotoxic effect in monotherapy. GB1B cell line was more sensitive to the treatment than AC1B cells, at a 7- and 10-day exposure to the DOXO. However, when the duration of the treatment was extended to 14 days, GB1B cells became more resistant to DOXO treatment, compared to AC1B cells. Regarding the treatment with TMZ, GB1B exhibited greater resistance to TMZ compared to AC1B, across all studied intervals and the resistance to treatment of GB1B increased with longer exposure time. However, in combined therapy, the drugs did not exert a synergistic effect on any astrocytic cell line. The current data suggest that both TMZ and DOXO exhibit efficient therapeutic effects on low- and high-grade glioma cells. However, no synergistic effect was observed for combined therapy.

Glioma Type Prediction with Dynamic Contrast-Enhanced MR Imaging and Diffusion Kurtosis Imaging-A Standardized Multicenter Study.

The aim was to explore the performance of dynamic contrast-enhanced (DCE) MRI and diffusion kurtosis imaging (DKI) in differentiating the molecular subtypes of adult-type gliomas. A multicenter MRI study with standardized imaging protocols, including DCE-MRI and DKI data of 81 patients with WHO grade 2-4 gliomas, was performed at six centers. The DCE-MRI and DKI parameter values were quantitatively evaluated in ROIs in tumor tissue and contralateral normal-appearing white matter. Binary logistic regression analyses were performed to differentiate between high-grade (HGG) vs. low-grade gliomas (LGG), IDH1/2 wildtype vs. mutated gliomas, and high-grade astrocytic tumors vs. high-grade oligodendrogliomas. Receiver operating characteristic (ROC) curves were generated for each parameter and for the regression models to determine the area under the curve (AUC), sensitivity, and specificity. Significant differences between tumor groups were found in the DCE-MRI and DKI parameters. A combination of DCE-MRI and DKI parameters revealed the best prediction of HGG vs. LGG (AUC = 0.954 (0.900-1.000)), IDH1/2 wildtype vs. mutated gliomas (AUC = 0.802 (0.702-0.903)), and astrocytomas/glioblastomas vs. oligodendrogliomas (AUC = 0.806 (0.700-0.912)) with the lowest Akaike information criterion. The combination of DCE-MRI and DKI seems helpful in predicting glioma types according to the 2021 World Health Organization's (WHO) classification.

Histopathological Spectrum of Gliomas and Its Immunohistochemical Correlation in a Tertiary Care Setup.

Introduction Central nervous system (CNS) tumors pose significant diagnostic challenges due to their varied morphological and differentiating characteristics. Modern advancements in immunohistochemistry (IHC) and molecular pathology have greatly enhanced prognostication, screening, and therapeutic management. Gliomas, a type of tumor originating from glial cells in the CNS, can develop from astrocytes, oligodendrocytes, or ependymal cells. According to the 2021 update, the classification of diffuse gliomas is primarily based on the presence or absence of isocitrate dehydrogenase (IDH1/2) mutations. IDH-wildtype gliomas (glioblastomas) have a significantly poorer prognosis compared to IDH-mutant gliomas (astrocytomas and oligodendrogliomas). Gliomas are highly infiltrative and resistant to treatment, making them largely incurable regardless of their grade and prognosis. Objective This study aimed to determine the histopathological diversity of gliomas and its correlation with protein expressions of IDH, ATRX gene (α-thalassemia/mental retardation syndrome X-linked), Ki-67, and p53 mutations (tumor suppressor gene-53), according to the 2021 World Health Organization (WHO) Classification of CNS Tumors, Fifth Edition. Methods This descriptive cross-sectional study was carried out in the Department of Pathology at a tertiary care center, focusing on various types of gliomas received over a two-year period. A total of 54 specimens of gliomas received from the Department of Neurosurgery were subjected to histopathological examination. Sections were stained using hematoxylin and eosin (H&E), and IHC was performed using four markers (IDH, ATRX, p53, Ki-67) in each case. Results were analyzed according to the 2021 WHO Classification of CNS Tumors, Fifth Edition. Results The majority of individuals were between the age group of 40 and 60 years, showing a male predominance (65%). The most common site was the frontal lobe. Glioblastoma constituted the largest proportion (46.2%) of the total cases, followed by astrocytoma (20.3%), oligodendroglioma (18.5%), pilocytic astrocytoma (7.4%), and ependymoma (7.4%). All 11 cases of astrocytoma exhibited IDH mutation and ATRX loss, with p53 positive in the majority of cases. Strong nuclear p53 immunohistochemical positivity in >10% of tumor nuclei correlates with TP53 mutations. Among 25 cases of glioblastoma, IDH was negative, ATRX was retained in all cases, and 11 cases were positive for p53 mutation. For oligodendroglioma, out of 10 cases, IDH mutation was positive, and ATRX was retained in all cases. p53 mutation was not seen in any case. All cases of pilocytic astrocytoma were negative for IDH and p53 mutations, with ATRX retained in all cases. In all cases of ependymoma, IDH and p53 mutations were negative, and ATRX was retained in all cases. Glioblastomas exhibited the highest Ki-67 expression. Conclusion The 2021 WHO Classification of CNS Tumors, Fifth Edition, was updated, building on previously established concepts and continuing to evolve. The final diagnosis of gliomas relies on a comprehensive combination of clinical evaluation, neuroimaging, pathological examination, and molecular analysis. Nonetheless, histopathological examination, along with IHC, remains the cornerstone of diagnosis.

Apatinib combined with temozolomide in diffuse midline glioma: a novel and effective therapy

PurposeDiffuse midline glioma (DMG), H3 K27M-mutant is a type of diffuse high-grade glioma that occurs in the brain midline carrying an extremely poor prognosis under the best efforts of surgery, radiation, and other therapies. For better therapy, we explored the efficacy and toxicity of a novel therapy that combines apatinib and temozolomide in DMG.MethodsA retrospective analysis of 32 patients with DMG who underwent apatinib plus temozolomide treatment was performed. Apatinib was given 500 mg in adults, 250 mg in pediatric patients once daily. Temozolomide was administered at 200 mg/m2/d according to the standard 5/28 days regimen. The main clinical data included basic information of patients, radiological and pathological characteristics of tumors, treatment, adverse reactions, prognosis.ResultsThe objective response rate was 24.1%, and the disease control rate was 79.3%. The median PFS of all patients was 5.8 months, and median OS was 10.3 months. A total of 236 cycles of treatment were available for safety assessment and the toxicity of the combination therapy was relatively well tolerated. The most common grade 3 toxicities were myelosuppression including leukopenia (5.08%), neutropenia (4.24%), lymphopenia (2.12%), thrombocytopenia (1.69%) and anemia (1.27%). Grade 4 toxicities included neutropenia (2.12%), thrombocytopenia (2.12%) and proteinuria (1.69%). All the adverse events were relieved after symptomatic treatment or dose reduction.ConclusionsApatinib plus temozolomide could be an effective regimen with manageable toxicities and favorable efficacy and may outperform temozolomide monotherapy, particularly in newly diagnosed adults with tumors located outside the pons. The novel therapy deserves further investigation in adult DMG patients.

Diffusion kurtosis imaging-based habitat analysis identifies high-risk molecular subtypes and heterogeneity matching in diffuse gliomas.

High-risk types of diffuse gliomas in adults include isocitrate dehydrogenase (IDH) wild-type glioblastomas and grade 4 astrocytomas. Achieving noninvasive prediction of high-risk molecular subtypes of gliomas is important for personalized and precise diagnosis and treatment. We retrospectively collected data from 116 patients diagnosed with adult diffuse gliomas. Multiple high-risk molecular markers were tested, and various habitat models and whole-tumor models were constructed based on preoperative routine and diffusion kurtosis imaging (DKI) sequences to predict high-risk molecular subtypes of gliomas. Feature selection and model construction utilized Least absolute shrinkage and selection operator (LASSO) and support vector machine (SVM). Finally, the Wilcoxon rank-sum test was employed to explore the correlation between habitat quantitative features (intra-tumor heterogeneity score，ITH score) and heterogeneity, as well as high-risk molecular subtypes. The results showed that the habitat analysis model based on DKI performed remarkably well (with AUC values reaching 0.977 and 0.902 in the training and test sets, respectively). The model's performance was further enhanced when combined with clinical variables. (The AUC values were 0.994 and 0.920, respectively.) Additionally, we found a close correlation between ITH score and heterogeneity, with statistically significant differences observed between high-risk and non-high-risk molecular subtypes. The habitat model based on DKI is an ideal means for preoperatively predicting high-risk molecular subtypes of gliomas, holding significant value for noninvasively alerting malignant gliomas and those with malignant transformation potential.

HGG-17. DECIPHERING GENETICS AND EPIGENETICS OF HIGH-GRADE GLIOMAS WITH BRAF ACTIVATING ALTERATION IS SUPPORTING THE DISCOVERY OF A NEW INTRACRANIAL SARCOMA-LIKE BRAF POSITIVE ENTITY

Abstract BACKGROUND The current WHO classification of Central Nervous System tumors recognizes several glioma types driven by the BRAFV600E mutation. These tumors mostly encompass pediatric low-grade gliomas. Nevertheless, a subset of them behaves as anaplastic gliomas and, currently, the unique predictive criterion linked to anaplasia is an elevated mitotic index (more than 2.5 mitoses/mm2). Histologically, the high-grade gliomas harboring BRAFV600E alteration mostly correspond to WHO grade 3 pleomorphic xanthoastrocytoma, IDH wild-type glioblastoma, entering the WHO grade 4 subset like the epithelioid subtype, and the rarer high-grade gliomas with piloïd features. These tumor types share their histomolecular features making differential diagnoses difficult. In this setting, DNA methylation profiling may be very useful to precise the integrative diagnosis. However, some of those high-grade forms failed in our experience to be classified in any methylation class with v11b4 version of the Heidelberg classifier. METHODS To understand the reasons explaining this standard classification failure, we investigated with multi-omics approaches (epigenetics, next-generation sequencing, RNAseq, proteomics and metabolomics) a well clinical characterized cohort of 17 high-grade pediatric intracranial tumors harboring this mutation. RESULTS Interestingly, almost all tumors show similar morphological features and associated passenger molecular alterations mostly CDKN2A homozygous deletion. When using the new v12.5 brain tumor classifier, the methylation profiling of the 2/17 unclassified tumors was clustering with a new MPNST (Malignant Peripheral Nerve Sheath Tumor) methylation entity. The RNAseq and proteomics analyses were showing a different molecular pattern from standard BRAF-mutated high-grade gliomas, even the clinical, radiological and histomolecular characteristics were comparable. CONCLUSION So, methylation profiling should be part of the mandatory molecular assessments to perform when a BRAF-mutated tumor is seen by neuropathologists. Furthermore, the multiomics analyses helped us to define a specific molecular pattern of this new BRAF-driven entity, where frequency and prognosis need to be determined on another larger series.

The molecular signature and prognosis of glioma with preoperative intratumoral hemorrhage: a retrospective cohort analysis

BackgroundIntratumoral hemorrhage, though less common, could be the first clinical manifestation of glioma and is detectable via MRI; however, its exact impacts on patient outcomes remain unclear and controversial. The 2021 WHO CNS 5 classification emphasised genetic and molecular features, initiating the necessity to establish the correlation between hemorrhage and molecular alterations. This study aims to determine the prevalence of intratumoral hemorrhage in glioma subtypes and identify associated molecular and clinical characteristics to improve patient management.MethodsIntegrated clinical data and imaging studies of patients who underwent surgery at the Department of Neurosurgery at Peking Union Medical College Hospital from January 2011 to January 2022 with pathological confirmation of glioma were retrospectively reviewed. Patients were divided into hemorrhage and non-hemorrhage groups based on preoperative magnetic resonance imaging. A comparison and survival analysis were conducted with the two groups. In terms of subgroup analysis, we classified patients into astrocytoma, IDH-mutant; oligodendroglioma, IDH-mutant, 1p/19q-codeleted; glioblastoma, IDH-wildtype; pediatric-type gliomas; or circumscribed glioma using integrated histological and molecular characteristics, according to WHO CNS 5 classifications.Results457 patients were enrolled in the analysis, including 67 (14.7%) patients with intratumoral hemorrhage. The hemorrhage group was significantly older and had worse preoperative Karnofsky performance scores. The hemorrhage group had a higher occurrence of neurological impairment and a higher Ki-67 index. Molecular analysis indicated that CDKN2B, KMT5B, and PIK3CA alteration occurred more in the hemorrhage group (CDKN2B, 84.4% vs. 62.2%, p = 0.029; KMT5B, 25.0% vs. 8.9%, p = 0.029; and PIK3CA, 81.3% vs. 58.5%, p = 0.029). Survival analysis showed significantly worse prognoses for the hemorrhage group (hemorrhage 18.4 months vs. non-hemorrhage 39.1 months, p = 0.01). In subgroup analysis, the multivariate analysis showed that intra-tumoral hemorrhage is an independent risk factor only in glioblastoma, IDH-wildtype (162 cases of 457 overall, HR = 1.72, p = 0.026), but not in other types of gliomas. The molecular alteration of CDK6 (hemorrhage group p = 0.004, non-hemorrhage group p < 0.001), EGFR (hemorrhage group p = 0.003, non-hemorrhage group p = 0.001), and FGFR2 (hemorrhage group p = 0.007, non-hemorrhage group p = 0.001) was associated with shorter overall survival time in both hemorrhage and non-hemorrhage groups.ConclusionsGlioma patients with preoperative intratumoral hemorrhage had unfavorable prognoses compared to their nonhemorrhage counterparts. CDKN2B, KMT5B, and PIK3CA alterations were associated with an increased occurrence of intratumoral hemorrhage, which might be future targets for further investigation of intratumoral hemorrhage.