Risk factors for nausea and vomiting requiring the daily administration of 5-HT3 receptor antagonists in radiotherapy combined with temozolomide for high-grade glioma.

Radiotherapy combined with temozolomide (TMZ+RT) is the primary treatment for high-grade glioma. TMZ is classified as a moderate emetic risk agent and, thus, supportive care for nausea and vomiting is important. In Nagoya University Hospital, all patients are treated with a 5-hydroxy-tryptamine 3 receptor antagonist (5-HT3RA) for the first 3 days. The daily administration of 5-HT3RA is resumed after the 4th day based on the condition of patients during TMZ+RT. Therefore, the present study investigated risk factors for nausea and vomiting in patients requiring the daily administration of 5-HT3RA. Patients with high-grade glioma who received TMZ+RT between January 2014 and December 2019 at our hospital were included. Patients were divided into two groups: a control group (patients who did not resume 5-HT3RA) and resuming 5-HT3RA group (patients who resumed 5-HT3RA after the 4th day), and both groups were compared to identify risk factors for nausea and vomiting during TMZ+RT. There were 78 patients in the control group (68%) and 36 in the resuming 5-HT3RA group (32%). A multivariate analysis of patient backgrounds in the two groups identified age <18 years, PS 2 or more, and occipital lobe tumors as risk factors for nausea and vomiting. Nausea and vomiting were attenuated in 30 patients (83%) in the resuming 5-HT3RA group following the resumption of 5-HT3RA. The results obtained highlight the importance of extracting patients with these risk factors before the initiation of therapy and the early resumption or daily administration of 5-HT3RA according to the condition of each patient.

Inhibition of the TCF12/VSIG4 axis by palbociclib diminishes the proliferation and migration of glioma cells and decreases the M2 polarization of glioma-associated microglia.

The CDK4/CDK6 inhibitor palbociclib has shown the encouraging promise in the treatment of glioma. Here, we elucidated how palbociclib exerts suppressive functions in the M2 polarization of glioma-related microglia and the progression of glioma. Xenograft experiments were used to evaluate the function in vivo. The mRNA levels of transcription factor 12 (TCF12) and VSIG4 were detected by RT-qPCR, and their protein levels were assessed by immunoblotting. Cell migration was tested by wound-healing assay. Cell cycle distribution and M1/M2 microglia phenotype analysis were performed by flow cytometry. The levels of IFN-γ, TNF-α, IL-6，and TGF-ß were measured by ELISA. The TCF12/VSIG4 association was verified by luciferase reporter and chromatin immunoprecipitation (ChIP) assays. In U251 and LN229 glioma cells, TCF12 and VSIG4 were overexpressed, and palbociclib reduced their expression levels. TCF12 upregulation enhanced the proliferation and migration of glioma cells and the M2 polarization of glioma-associated microglia in vitro as well as the tumorigenicity of U251 glioma cells in vivo, which could be reversed by palbociclib. Mechanistically, TCF12 could enhance VSIG4 transcription and expression by binding to the VSIG4 promoter. TCF12 deficiency led to repression in glioma cell proliferation and migration as well as microglia M2 polarization, which could be abolished by increased VSIG4 expression. Our study reveals the novel TCF12/VSIG4 axis responsible for the efficacy of palbociclib in combating glioma, offering a rationale for the application of palbociclib in glioma treatment.

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.

Characterizing the Linkage of Systemic Hypoxia and Angiogenesis in High-Grade Glioma to Define the Changes in Tumor Microenvironment for Predicting Prognosis.

High-grade gliomas (HGG) comprising WHO grades 3 and 4 have a poor overall survival (OS) that has not improved in the past decade. Herein, markers representing four components of the tumor microenvironment (TME) were identified to define their linked expression in TME and predict the prognosis in HGG, namely, interleukin6 (IL6, inflammation), inducible nitric oxide synthase(iNOS), heat shock protein-70 (HSP70, hypoxia), vascular endothelial growth receptor (VEGF), and endothelin1 (ET1) (angiogenesis) and matrix metalloprotease-14 (MMP14) and intercellular adhesion molecule1 (ICAM1, extracellular matrix). To establish a non-invasive panel of biomarkers for precise prognostication in HGG. Eighty-six therapy-naive HGG patients with 45 controls were analyzed for the defined panel. Systemic expression of extracellular/secretory biomarkers was screened dot-immune assay (DIA), quantified by ELISA, and validated by immunocytochemistry (ICC). Expression of iNOS, HSP70, IL-6, VEGF, ET1, MMP14, and ICAM1 was found to be positively associated with grade. Quantification of circulating levels of the markers by ELISA and ICC presented a similar result. The biomarkers were observed to negatively correlate with OS (p < 0.0001). Cox-regression analysis yielded all biomarkers as good prognostic indicators and independent of confounders. On applying combination statistics, the biomarker panel achieved higher sensitivity than single markers to define survival. The intra-association of all seven biomarkers was significant, hinting of a cross-talk between the TME components and a hypoxia driven systemic inflammation upregulating the expression of other components. This is a first ever experimental study of a marker panel that can distinguish between histopathological grades and also delineate differential survival using liquid biopsy, suggesting that markers of hypoxia can be a cornerstone for personalized therapy. The panel of biomarkers of iNOS, HSP70, IL-6, VEGF, ET1, MMP14, and ICAM1 holds promise for prognostication in HGG.

Diffusion tensor imaging in detecting gliomas sub-regions of infiltration, local and remote recurrences: a systematic review.

Given that glioma cells tend to infiltrate and migrate along WM tracts, leading to demyelination and axonal injuries, Diffusion Tensor Imaging (DTI) emerged as a promising tool for identifying major "high-risk areas" of recurrence within the peritumoral brain zone (PBZ) or at a distance throughout the adjacents white matter tracts. Of our systematic review is to answer the following research question: In patients with brain tumor, is DTI able to recognizes within the peri-tumoral brain zone (PBZ) areas more prone to local (near the surgical cavity) or remote recurrence compared to the conventional imaging techniques?. We conducted a comprehensive literature search to identify relevant studies in line with the PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) guidelines. 15 papers were deemed compatible with our research question and included. To enhance the paper's readability, we have categorized our findings into two distinct groups: the first delves into the role of DTI in detecting PBZ sub-regions of infiltration and local recurrences (n = 8), while the second group explores the feasibility of DTI in detecting white matter tract infiltration and remote recurrences (n = 7). DTI values and, within a broader framework, radiomics investigations can provide precise, voxel-by-voxel insights into the state of PBZ and recurrences. Better defining the regions at risk for potential recurrence within the PBZ and along WM bundles will allow targeted therapy.

Utilizing human cerebral organoids to model breast cancer brain metastasis in culture.

BACKGROUND: Metastasis, the spread, and growth of malignant cells at secondary sites within a patient's body, accounts for over 90% of cancer-related mortality. Breast cancer is the most common tumor type diagnosed and the leading cause of cancer lethality in women in the United States. It is estimated that 10-16% breast cancer patients will have brain metastasis. Current therapies to treat patients with breast cancer brain metastasis (BCBM) remain palliative. This is largely due to our limited understanding of the fundamental molecular and cellular mechanisms through which BCBM progresses, which represents a critical barrier for the development of efficient therapies for affected breast cancer patients. METHODS: Previous research in BCBM relied on co-culture assays of tumor cells with rodent neural cells or rodent brain slice ex vivo. Given the need to overcome the obstacle for human-relevant host to study cell-cell communication in BCBM, we generated human embryonic stem cell-derived cerebral organoids to co-culture with human breast cancer cell lines. We used MDA-MB-231 and its brain metastatic derivate MDA-MB-231 Br-EGFP, other cell lines of MCF-7, HCC-1806, and SUM159PT. We leveraged this novel 3D co-culture platform to investigate the crosstalk of human breast cancer cells with neural cells in cerebral organoid. RESULTS: We found that MDA-MB-231 and SUM159PT breast cancer cells formed tumor colonies in human cerebral organoids. Moreover, MDA-MB-231 Br-EGFP cells showed increased capacity to invade and expand in human cerebral organoids. CONCLUSIONS: Our co-culture model has demonstrated a remarkable capacity to discern the brain metastatic ability of human breast cancer cells in cerebral organoids. The generation of BCBM-like structures in organoid will facilitate the study of human tumor microenvironment in culture.

Illuminating the dark space of neutral glycosphingolipidome by selective enrichment and profiling at multi-structural levels.

Glycosphingolipids (GSLs) are essential components of cell membranes, particularly enriched in the nervous system. Altered molecular distributions of GSLs are increasingly associated with human diseases, emphasizing the significance of lipidomic profiling. Traditional GSL analysis methods are hampered by matrix effect from phospholipids and the difficulty in distinguishing structural isomers. Herein, we introduce a highly sensitive workflow that harnesses magnetic TiO2 nanoparticle-based selective enrichment, charge-tagging Paternò-Büchi reaction, and liquid chromatography-tandem mass spectrometry. This approach enables mapping over 300 distinct GSLs in brain tissues by defining sugar types, long chain bases, N-acyl chains, and the locations of desaturation and hydroxylation. Relative quantitation of GSLs across multiple structural levels provides evidence of dysregulated gene and protein expressions of FA2H and CerS2 in human glioma tissue. Based on the structural features of GSLs, our method accurately differentiates human glioma with/without isocitrate dehydrogenase genetic mutation, and normal brain tissue.

Comprehensive application of AI algorithms with TCR NGS data for glioma diagnosis.

T-cell receptor (TCR) detection can examine the extent of T-cell immune responses. Therefore, the article analyzed characteristic data of glioma obtained by DNA-based TCR high-throughput sequencing, to predict the disease with fewer biomarkers and higher accuracy. We downloaded data online and obtained six TCR-related diversity indices to establish a multidimensional classification system. By comparing actual presence of the 602 correlated sequences, we obtained two-dimensional and multidimensional datasets. Multiple classification methods were utilized for both datasets with the classification accuracy of multidimensional data slightly less to two-dimensional datasets. This study reduced the TCR ß sequences through feature selection methods like RFECV (Recursive Feature Elimination with Cross-Validation). Consequently, using only the presence of these three sequences, the classification AUC value of 96.67% can be achieved. The combination of the three correlated TCR clones obtained at a source data threshold of 0.1 is: CASSLGGNTEAFF_TRBV12_TRBJ1-1, CASSYSDTGELFF_TRBV6_TRBJ2-2, and CASSLTGNTEAFF_TRBV12_TRBJ1-1. At 0.001, the combination is: CASSLGETQYF_TRBV12_TRBJ2-5, CASSLGGNQPQHF_TRBV12_TRBJ1-5, and CASSLSGNTIYF_TRBV12_TRBJ1-3. This method can serve as a potential diagnostic and therapeutic tool, facilitating diagnosis and treatment of glioma and other cancers.

Brain tumor classification in VIT-B/16 based on relative position encoding and residual MLP.

Brain tumors pose a significant threat to health, and their early detection and classification are crucial. Currently, the diagnosis heavily relies on pathologists conducting time-consuming morphological examinations of brain images, leading to subjective outcomes and potential misdiagnoses. In response to these challenges, this study proposes an improved Vision Transformer-based algorithm for human brain tumor classification. To overcome the limitations of small existing datasets, Homomorphic Filtering, Channels Contrast Limited Adaptive Histogram Equalization, and Unsharp Masking techniques are applied to enrich dataset images, enhancing information and improving model generalization. Addressing the limitation of the Vision Transformer's self-attention structure in capturing input token sequences, a novel relative position encoding method is employed to enhance the overall predictive capabilities of the model. Furthermore, the introduction of residual structures in the Multi-Layer Perceptron tackles convergence degradation during training, leading to faster convergence and enhanced algorithm accuracy. Finally, this study comprehensively analyzes the network model's performance on validation sets in terms of accuracy, precision, and recall. Experimental results demonstrate that the proposed model achieves a classification accuracy of 91.36% on an augmented open-source brain tumor dataset, surpassing the original VIT-B/16 accuracy by 5.54%. This validates the effectiveness of the proposed approach in brain tumor classification, offering potential reference for clinical diagnoses by medical practitioners.

Classification of brain tumor types through MRIs using parallel CNNs and firefly optimization.

Image segmentation is a critical and challenging endeavor in the field of medicine. A magnetic resonance imaging (MRI) scan is a helpful method for locating any abnormal brain tissue these days. It is a difficult undertaking for radiologists to diagnose and classify the tumor from several pictures. This work develops an intelligent method for accurately identifying brain tumors. This research investigates the identification of brain tumor types from MRI data using convolutional neural networks and optimization strategies. Two novel approaches are presented: the first is a novel segmentation technique based on firefly optimization (FFO) that assesses segmentation quality based on many parameters, and the other is a combination of two types of convolutional neural networks to categorize tumor traits and identify the kind of tumor. These upgrades are intended to raise the general efficacy of the MRI scan technique and increase identification accuracy. Using MRI scans from BBRATS2018, the testing is carried out, and the suggested approach has shown improved performance with an average accuracy of 98.6%.

Matrix metalloproteinase 9 expression and glioblastoma survival prediction using machine learning on digital pathological images.

This study aimed to apply pathomics to predict Matrix metalloproteinase 9 (MMP9) expression in glioblastoma (GBM) and investigate the underlying molecular mechanisms associated with pathomics. Here, we included 127 GBM patients, 78 of whom were randomly allocated to the training and test cohorts for pathomics modeling. The prognostic significance of MMP9 was assessed using Kaplan-Meier and Cox regression analyses. PyRadiomics was used to extract the features of H&E-stained whole slide images. Feature selection was performed using the maximum relevance and minimum redundancy (mRMR) and recursive feature elimination (RFE) algorithms. Prediction models were created using support vector machines (SVM) and logistic regression (LR). The performance was assessed using ROC analysis, calibration curve assessment, and decision curve analysis. MMP9 expression was elevated in patients with GBM. This was an independent prognostic factor for GBM. Six features were selected for the pathomics model. The area under the curves (AUCs) of the training and test subsets were 0.828 and 0.808, respectively, for the SVM model and 0.778 and 0.754, respectively, for the LR model. The C-index and calibration plots exhibited effective estimation abilities. The pathomics score calculated using the SVM model was highly correlated with overall survival time. These findings indicate that MMP9 plays a crucial role in GBM development and prognosis. Our pathomics model demonstrated high efficacy for predicting MMP9 expression levels and prognosis of patients with GBM.

MicroRNAs as the pivotal regulators of Temozolomide resistance in glioblastoma.

Glioblastoma (GBM) is an aggressive nervous system tumor with a poor prognosis. Although, surgery, radiation therapy, and chemotherapy are the current standard protocol for GBM patients, there is still a poor prognosis in these patients. Temozolomide (TMZ) as a first-line therapeutic agent in GBM can easily cross from the blood-brain barrier to inhibit tumor cell proliferation. However, there is a high rate of TMZ resistance in GBM patients. Since, there are limited therapeutic choices for GBM patients who develop TMZ resistance; it is required to clarify the molecular mechanisms of chemo resistance to introduce the novel therapeutic targets. MicroRNAs (miRNAs) regulate chemo resistance through regulation of drug metabolism, absorption, DNA repair, apoptosis, and cell cycle. In the present review we discussed the role of miRNAs in TMZ response of GBM cells. It has been reported that miRNAs mainly induced TMZ sensitivity by regulation of signaling pathways and autophagy in GBM cells. Therefore, miRNAs can be used as the reliable diagnostic/prognostic markers in GBM patients. They can also be used as the therapeutic targets to improve the TMZ response in GBM cells.

The cuproptosis-related signature predicts the prognosis and immune microenvironments of primary diffuse gliomas: a comprehensive analysis.

BACKGROUND: Evidence has revealed a connection between cuproptosis and the inhibition of tumor angiogenesis. While the efficacy of a model based on cuproptosis-related genes (CRGs) in predicting the prognosis of peripheral organ tumors has been demonstrated, the impact of CRGs on the prognosis and the immunological landscape of gliomas remains unexplored. METHODS: We screened CRGs to construct a novel scoring tool and developed a prognostic model for gliomas within the various cohorts. Afterward, a comprehensive exploration of the relationship between the CRG risk signature and the immunological landscape of gliomas was undertaken from multiple perspectives. RESULTS: Five genes (NLRP3, ATP7B, SLC31A1, FDX1, and GCSH) were identified to build a CRG scoring system. The nomogram, based on CRG risk and other signatures, demonstrated a superior predictive performance (AUC of 0.89, 0.92, and 0.93 at 1, 2, and 3 years, respectively) in the training cohort. Furthermore, the CRG score was closely associated with various aspects of the immune landscape in gliomas, including immune cell infiltration, tumor mutations, tumor immune dysfunction and exclusion, immune checkpoints, cytotoxic T lymphocyte and immune exhaustion-related markers, as well as cancer signaling pathway biomarkers and cytokines. CONCLUSION: The CRG risk signature may serve as a robust biomarker for predicting the prognosis and the potential viability of immunotherapy responses. Moreover, the key candidate CRGs might be promising targets to explore the underlying biological background and novel therapeutic interventions in gliomas.

Lysyl oxidase-like 1 predicts the prognosis of patients with primary glioblastoma and promotes tumor invasion via EMT pathway.

Background: Lysyl oxidase enzymes (LOXs), as extracellular matrix (ECM) protein regulators, play vital roles in tumor progression by remodeling the tumor microenvironment. However, their roles in glioblastoma (GBM) have not been fully elucidated. Methods: The genetic alterations and prognostic value of LOXs were investigated via cBioPortal. The correlations between LOXs and biological functions/molecular tumor subtypes were explored in The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). After Kaplan‒Meier and Cox survival analyses, a Loxl1-based nomogram and prognostic risk score model (PRSM) were constructed and evaluated by time-dependent receiver operating characteristic curves, calibration curves, and decision curve analyses. Tumor enrichment pathways and immune infiltrates were explored by single-cell RNA sequencing and TIMER. Loxl1-related changes in tumor viability/proliferation and invasion were further validated by CCK-8, western blot, wound healing, and Transwell invasion assays. Results: GBM patients with altered LOXs had poor survival. Upregulated LOXs were found in IDH1-wildtype and mesenchymal (not Loxl1) GBM subtypes, promoting ECM receptor interactions in GBM. The Loxl1-based nomogram and the PRSM showed high accuracy, reliability, and net clinical benefits. Loxl1 expression was related to tumor invasion and immune infiltration (B cells, neutrophils, and dendritic cells). Loxl1 knockdown suppressed GBM cell proliferation and invasion by inhibiting the EMT pathway (through the downregulation of N-cadherin/Vimentin/Snai1 and the upregulation of E-cadherin). Conclusion: The Loxl1-based nomogram and PRSM were stable and individualized for assessing GBM patient prognosis, and the invasive role of Loxl1 could provide a promising therapeutic strategy.

Multi-scale signaling and tumor evolution in high-grade gliomas.

Although genomic anomalies in glioblastoma (GBM) have been well studied for over a decade, its 5-year survival rate remains lower than 5%. We seek to expand the molecular landscape of high-grade glioma, composed of IDH-wildtype GBM and IDH-mutant grade 4 astrocytoma, by integrating proteomic, metabolomic, lipidomic, and post-translational modifications (PTMs) with genomic and transcriptomic measurements to uncover multi-scale regulatory interactions governing tumor development and evolution. Applying 14 proteogenomic and metabolomic platforms to 228 tumors (212 GBM and 16 grade 4 IDH-mutant astrocytoma), including 28 at recurrence, plus 18 normal brain samples and 14 brain metastases as comparators, reveals heterogeneous upstream alterations converging on common downstream events at the proteomic and metabolomic levels and changes in protein-protein interactions and glycosylation site occupancy at recurrence. Recurrent genetic alterations and phosphorylation events on PTPN11 map to important regulatory domains in three dimensions, suggesting a central role for PTPN11 signaling across high-grade gliomas.

Unraveling morphology, methylation profiling, and diagnostic challenges in BRAF-Mutant pediatric glial and glioneuronal tumors.

OBJECTIVES: To elucidate the relationship between DNA methylation profiling (DMP) and pathological diagnosis (PD) in pediatric glial and glioneuronal tumors with B-Raf proto-oncogene, serine/threonine kinase (BRAF) mutations, addressing their diagnostic challenges. METHODS: This retrospective study, conducted in Saudi Arabia, analyzed 47 cases from the Children's Brain Tumor Network online database using scanned images, next-generation sequencing data, and methylation profiles processed using the Heidelberg methylation brain tumor classifiers v12.5 and v12.8. The data was last access on 10 November 2023. RESULTS: The highest prevalence of BRAF mutations was observed in pilocytic astrocytoma and ganglioglioma. The DMP was consistent with PD in 23 cases, but discrepancies emerged in others, including diagnostic changes in diffuse leptomeningeal glioneuronal tumor and polymorphous low-grade neuroepithelial tumor of the young. A key inconsistency appeared between a pilocytic astrocytoma MC and a glioneuronal tumor PD. Two high-grade astrocytomas were misclassified as pleomorphic xanthoastrocytomas. Additionally, low variant allelic frequency in gangliogliomas likely contributed to misclassifications as control in 5 cases. CONCLUSION: This study emphasized the importance of integrating DMP with PD in diagnosing pediatric glial and glioneuronal tumors with BRAF mutations. Although DMP offers significant diagnostic insights, its limitations, particularly in cases with low tumor content, necessitate cautious interpretation, as well as its use as a complementary diagnostic tool, rather than a definitive method.

Decision making for health-related research outcomes that alter diagnosis: A model from paediatric brain tumours.

AIMS: The question of how to handle clinically actionable outcomes from retrospective research studies is poorly explored. In neuropathology, this problem is exacerbated by ongoing refinement in tumour classification. We sought to establish a disclosure threshold for potential revised diagnoses as determined by the neuro-oncology speciality. METHODS: As part of a previous research study, the diagnoses of 73 archival paediatric brain tumour samples were reclassified according to the WHO 2016 guidelines. To determine the disclosure threshold and clinical actionability of pathology-related findings, we conducted a result-evaluation approach within the ethical framework of BRAIN UK using a surrogate clinical multidisciplinary team (MDT) of neuro-oncology specialists. RESULTS: The MDT identified key determinants impacting decision-making, including anticipated changes to patient management, time elapsed since initial diagnosis, likelihood of the patient being alive and absence of additional samples since cohort inception. Ultimately, none of our research findings were considered clinically actionable, largely due to the cohort's historic archival and high-risk nature. From this experience, we developed a decision-making framework to determine if research findings indicating a change in diagnosis require reporting to the relevant clinical teams. CONCLUSIONS: Ethical issues relating to the use of archival tissue for research and the potential to identify actionable findings must be carefully considered. We have established a structured framework to assess the actionability of research data relating to patient diagnosis. While our specific findings are most applicable to the pathology of poor prognostic brain tumour groups in children, the model can be adapted to a range of disease settings, for example, other diseases where research is dependent on retrospective tissue cohorts, and research findings may have implications for patients and families, such as other tumour types, epilepsy-related pathology, genetic disorders and degenerative diseases.

Single-cell transcriptomic analysis identifies downregulated phosphodiesterase 8B as a novel oncogene in IDH-mutant glioma.

Introduction: Glioma, a prevalent and deadly brain tumor, is marked by significant cellular heterogeneity and metabolic alterations. However, the comprehensive cell-of-origin and metabolic landscape in high-grade (Glioblastoma Multiforme, WHO grade IV) and low-grade (Oligoastrocytoma, WHO grade II) gliomas remains elusive. Methods: In this study, we undertook single-cell transcriptome sequencing of these glioma grades to elucidate their cellular and metabolic distinctions. Following the identification of cell types, we compared metabolic pathway activities and gene expressions between high-grade and low-grade gliomas. Results: Notably, astrocytes and oligodendrocyte progenitor cells (OPCs) exhibited the most substantial differences in both metabolic pathways and gene expression, indicative of their distinct origins. The comprehensive analysis identified the most altered metabolic pathways (MCPs) and genes across all cell types, which were further validated against TCGA and CGGA datasets for clinical relevance. Discussion: Crucially, the metabolic enzyme phosphodiesterase 8B (PDE8B) was found to be exclusively expressed and progressively downregulated in astrocytes and OPCs in higher-grade gliomas. This decreased expression identifies PDE8B as a metabolism-related oncogene in IDH-mutant glioma, marking its dual role as both a protective marker for glioma grading and prognosis and as a facilitator in glioma progression.

Liposomal Nanomaterials: A Rising Star in Glioma Treatment.

Glioma is a primary malignant tumor in the central nervous system. In recent years, the treatment of glioma has developed rapidly, but the overall survival of glioma patients has not significantly improved. Due to the presence of the blood-brain barrier and intracranial tumor barrier, many drugs with good effects to cure glioma in vitro cannot be accurately transported to the corresponding lesions. In order to enable anti-tumor drugs to overcome the barriers and target glioma, nanodrug delivery systems have emerged recently. It is gratifying that liposomes, as a multifunctional nanodrug delivery carrier, which can be compatible with hydrophilic and hydrophobic drugs, easily functionalized by various targeted ligands, biodegradable, and hypoimmunogenic in vivo, has become a quality choice to solve the intractable problem of glioma medication. Therefore, we focused on the liposome nanodrug delivery system, and summarized its current research progress in glioma. Hopefully, this review may provide new ideas for the research and development of liposome-based nanomaterials for the clinical treatment of glioma.

Intracerebral benign fibrous histiocytoma.

Benign fibrous histiocytoma (BFH) within the intracerebral region is remarkably rare. Our report details 2 cases of unusual BFH instances that exhibit no adhesion to the dura mater or cerebral falx, accompanied by a comprehensive literature review. While magnetic resonance imaging demonstrates specific characteristics for BFH, it does not readily differentiate BFH from more common brain neoplasms like gliomas and metastatic tumors. The definitive diagnosis of BFH depends primarily on histopathological and immunohistochemical examinations. Total surgical resection is considered an efficacious therapeutic approach, emphasizing the necessity for prolonged postoperative surveillance to detect any potential tumor recurrence or metastasis.