Epidemiology of Brain Tumors

Advancing brain tumor therapy: unveiling the potential of PROTACs for targeted protein degradation

The long-term treatment of malignancies, particularly brain tumors, is challenged by abnormal protein expression and drug resistance. In terms of potency, selectivity, and overcoming drug resistance, Proteolysis Targeting Chimeras (PROTACs), a cutting-edge method used to selectively degrade target proteins, beats traditional inhibitors. This review summarizes recent research on using PROTACs as a therapeutic strategy for brain tumors, focusing on their mechanism, benefits, limitations, and the need for optimization. The review draws from a comprehensive search of peer-reviewed literature, scientific databases, and clinical trial databases. Articles published up to the knowledge cutoff date up to 14 April 2023 were included. Inclusion criteria covered PROTAC-based brain tumor therapies, including preclinical and early clinical studies, with no restrictions on design or publication type. We included studies using in vitro, in vivo brain tumor models, and human subjects. Eligible treatments involved PROTACs targeting proteins linked to brain tumor progression. We evaluated the selected studies for methodology, including design, sample size, and data analysis techniques. A narrative synthesis summarized key outcomes and trends in PROTAC-based brain tumor therapy. Recent research shows PROTACs selectively degrade brain tumor-related proteins with minimal off-target effects. They offer enhanced potency, selectivity, and the ability to combat resistance compared to traditional inhibitors. PROTACs hold promise for brain tumor treatment offering advantages over traditional inhibitors, but more research is needed to refine their mechanisms, efficacy, and safety. Larger-scale trials and translational studies are essential for assessing their clinical utility.

Exosome-based drug delivery systems for enhanced neurological therapeutics

Exosomes are small extracellular vesicles naturally secreted by cells into body fluids, enriched with bioactive molecules such as RNAs, proteins, and lipids. These nanosized vesicles play a crucial role in physiological and pathological processes by facilitating intercellular communication and modulating cellular responses, particularly within the central nervous system (CNS). Their ability to cross the blood-brain barrier and reflect the characteristics of their parent cells makes exosomal cargo a promising candidate for biomarkers in the early diagnosis and clinical assessment of neurological conditions. This review offers a comprehensive overview of current knowledge on the characterization of mammalian-derived exosomes, their application as drug delivery systems for neurological disorders, and ongoing clinical trials involving exosome-loaded cargo. Despite their promising attributes, a significant challenge remains the lack of standardized isolation methods, as current techniques are often complex, costly, and require sophisticated equipment, affecting the scalability and affordability of exosome-based therapies. The review highlights the engineering potential of exosomes, emphasizing their ability to be customized for targeted therapeutic delivery through surface modification or conjugation. Future advancements in addressing these challenges and leveraging the unique properties of exosomes could lead to innovative and effective therapeutic strategies in neurology.

Transforming agents: The power of structural modifications in glioblastoma multiforme therapy

Glioblastoma (GBM) is a very deadly type of brain tumor with a poor prognosis and a short survival rate. Recent advancements in understanding GBM's molecular and genetic characteristics have led to the development of various therapeutic and diagnostic strategies. Key elements such as microRNAs, lncRNAs, exosomes, angiogenesis, and chromatin modifications are highlighted, alongside significant epigenetic alterations that impact therapy and diagnosis. Despite these advancements, molecular classifications have not improved patient outcomes due to intratumoral diversity complicating targeted therapies. In this article, it is tried to emphasize the potential of investigating the epigenetic landscape of GBM, particularly identifying patients with diffuse hypermethylation at gene promoters associated with better outcomes. Integrating epigenetic and genetic data has enhanced the identification of glioma subtypes with high diagnostic precision. The reversibility of epigenetic changes offers promising therapeutic prospects, as recent insights into the "epigenetic orchestra" suggest new avenues for innovative treatment modalities for this challenging cancer. In this review article, we focus on the roles of translational elements and their alterations in the context of GBM diagnosis and therapy.

Radiogenomics and machine learning predict oncogenic signaling pathways in glioblastoma

BACKGROUND

Glioblastoma (GBM) is a highly aggressive brain tumor associated with a poor patient prognosis. The survival rate remains low despite standard therapies, highlighting the urgent need for novel treatment strategies. Advanced imaging techniques, particularly magnetic resonance imaging (MRI), are crucial in assessing GBM. Disruptions in various oncogenic signaling pathways, such as Receptor Tyrosine Kinase (RTK)-Ras-Extracellular signal-regulated kinase (ERK) signaling, Phosphoinositide 3- Kinases (PI3Ks), tumor protein p53 (TP53), and Neurogenic locus notch homolog protein (NOTCH), contribute to the development of different tumor types, each exhibiting distinct morphological and phenotypic features that can be observed at a microscopic level. However, identifying genetic abnormalities for targeted therapy often requires invasive procedures, prompting exploration into non-invasive approaches like radiogenomics. This study explores the utility of radiogenomics and machine learning (ML) in predicting these oncogenic signaling pathways in GBM patients.

METHODS

We collected post-operative MRI scans (T1w, T1c, FLAIR, T2w) from the BRATS-19 dataset, including scans from patients with both GBM and LGG, linked to genetic and clinical data via TCGA and CPTAC. Signaling pathway data was manually extracted from cBioPortal. Radiomic features were extracted from four MRI modalities using PyRadiomics. Dimensionality reduction and feature selection were applied and Data imbalance was addressed with SMOTE. Five ML models were trained to predict signaling pathways, with Grid Search optimizing hyperparameters and 5-fold cross-validation ensuring unbiased performance. Each model's performance was evaluated using various metrics on test data.

RESULTS

Our results showed a positive association between most signaling pathways and the radiomic features derived from MRI scans. The best models achieved high AUC scores, namely 0.7 for RTK-RAS, 0.8 for PI3K, 0.75 for TP53, and 0.4 for NOTCH, and therefore, demonstrated the potential of ML models in accurately predicting oncogenic signaling pathways from radiomic features, thereby informing personalized therapeutic approaches and improving patient outcomes.

CONCLUSION

We present a novel approach for the non-invasive prediction of deregulation in oncogenic signaling pathways in glioblastoma (GBM) by integrating radiogenomic data with machine learning models. This research contributes to advancing precision medicine in GBM management, highlighting the importance of integrating radiomics with genomic data to understand tumor behavior and treatment response better.

Computed Tomography-Image-Based Glioma Grading Using Radiomics and Machine Learning: A Proof-of-Principle Study

BACKGROUND/OBJECTIVES

In recent years, numerous studies have been published on determining the WHO grade of central nervous system (CNS) tumors using machine learning algorithms. These studies are usually based on magnetic resonance imaging (MRI) and sometimes also on positron emission tomography (PET) images. To date, however, there are virtually no corresponding studies based on routinely generated computed tomography (CT) images. The aim of our proof-of-concept study is to investigate whether machine learning-based tumor diagnosis is also possible using CT images.

METHODS

We investigate the differentiability of histologically confirmed low-grade and high-grade gliomas. Three conventional machine learning algorithms and a neural net are tested. In addition, we analyze which of the common imaging methods (MRI or CT) appears to be best suited for the diagnostic question under investigation when machine learning algorithms are used. For this purpose, we compare our results based on CT images with numerous studies based on MRI scans.

RESULTS

Our best-performing model includes six features and is obtained using univariate analysis for feature preselection and a Naive Bayes approach for model construction. Using independent test data, this model yields a mean AUC of 0.903, a mean accuracy of 0.839, a mean sensitivity of 0.807 and a mean specificity of 0.864.

CONCLUSIONS

Our results demonstrate that low-grade and high-grade gliomas can be differentiated with high accuracy using machine learning algorithms, not only based on the usual MRI scans, but also based on CT images. In the future, such CT-image-based models can help to further accelerate brain tumor diagnostics and to reduce the number of necessary biopsies.

Efficacy and safety of anesthetic agents in awake craniotomy using monitored anesthesia care protocol: a systematic review and meta-analysis

Awake craniotomy (AC) facilitates real-time brain mapping, maximizing tumor resection while preserving critical neurological functions. This study systematically reviews the efficacy of several anesthetic protocols under Monitored Anesthesia Care (MAC) during AC, focusing on clinical outcomes. A systematic review and meta-analysis were conducted using data from observational studies and randomized trials involving AC under MAC. Databases searched included PubMed, Embase, and Web of Science. The analysis employed mixed-effects models to assess both the overall rate of the outcomes and the impact of anesthetic agents on clinical outcomes. The primary outcome was the rate of postoperative neurological deficits. Of 468 studies initially identified, 26 met the inclusion criteria. The overall adverse event rate was 23.7%. The pooled proportion of patients with postoperative neurological deficits and intraoperative seizures was 10.45% and 8.8%, respectively. Remifentanil use was associated with a lower risk of neurological deficits in mixed effects meta-analysis (6.9% vs 16.5%), while intraoperative seizure rate was slightly lower with propofol use (7.1% vs. 11.8%). Midazolam use was also associated with lower agitation (5.5% vs. 10.9%). The rate of secondary adverse outcomes other than hypertension (10.2%) and tense brain (10%) were below 10% and comparable to the previous literature. The findings highlight the variability in anesthetic protocols used in MAC for AC. Despite limited evidence regarding safety concerns and potential confounders, Remifentanil, Propofol, and Midazolam appear to be superior to other agents evaluated in these procedures. However, further research is required to draw definitive conclusions.

Machine learning algorithms for predicting delayed hyponatremia after transsphenoidal surgery for patients with pituitary adenoma

This study aimed to develop and validate machine learning (ML) models to predict the occurrence of delayed hyponatremia after transsphenoidal surgery for pituitary adenoma. We retrospectively collected clinical data on patients with pituitary adenomas treated with transsphenoidal surgery between January 2010 and December 2020. From January 2021 to December 2022, patients with pituitary adenomas were prospectively enrolled. We trained seven ML models to predict delayed hyponatremia using the clinical variables in the training set. The final model was internally validated using a test set and a prospective dataset. The SHapley Additive exPlanations (SHAP) algorithm was used to determine the significance of each variable in the occurrence of delayed hyponatremia. In the training dataset, the best predictive performance was observed for XGBoost (area under the ROC curve; AUC = 0.821), followed by Random Forest (AUC = 0.8), Logistic Regression (AUC = 0.793), Support Vector Machine (AUC = 0.776), naïve Bayes (AUC = 0.774), K-Nearest Neighbors (AUC = 0.742), and Decision Tree (AUC = 0.717). The AUC of the XGBoost model for the test and prospective datasets are 0.831 and 0.785, respectively. The differences in pituitary stalk deviation angle, the "measurable pituitary stalk" length before and after surgery, and blood sodium concentration between preoperative and postoperative day 2 were important variables for predicting delayed hyponatremia as determined by the SHAP algorithm. The XGBoost model was best able to predict delayed hyponatremia after transsphenoidal surgery for pituitary adenomas. The differences in pituitary stalk deviation angle, pre- versus postoperative "measurable pituitary stalk" length, and pre- versus postoperative day 2 blood sodium concentrations were important variables for predicting delayed hyponatremia.

Epidemiology of glioblastoma in Pakistan: a secondary analysis of the Pakistan Brain Tumor Epidemiology Study (PBTES)

PURPOSE

The incidence and outcomes of glioblastoma (GBM) patients in Pakistan remain unassessed owing to a lack of cancer registries and the absence of population-based studies. For any specific population-based oncological intervention, epidemiology must be studied. Therefore, this study aims to examine the epidemiological characteristics of glioblastoma patients in Pakistan, as part of a secondary analysis of a nationwide epidemiological study.

METHODS

Data comprising of sociodemographic, tumor and treatment characteristics of 2750 patients from the Pakistan Brain Tumor Epidemiology Study were extracted and analyzed for cases between January 1, 2019, and December 31, 2019. Chi-square tests identified outcome and treatment differences. Data analysis was performed using SPSS version 26.

RESULTS

A total of 260 GBM cases were analyzed, with a mean diagnosis age of 45 years. Males accounted for 68.8%. Most patients were from a middle- (39.6%) or lower-income (42.7%) socioeconomic background and received care from a public institution (63.8%). GBM tumors were mainly located in the frontal lobe with similar proportions of right and left laterality. A median distance of 119 km was traveled for oncological care, and the mean time to surgery from the initial radiological diagnosis was 72 days. Gross total resection was achieved in 47.3% of first surgeries, with 23 reoperations for recurrence. At the end of the study period, 33% of the GBM cohort was recorded as alive with 47% being lost to follow-up.

CONCLUSION

Our analysis is the first population-based analysis of GBM in Pakistan. This epidemiologic study can serve as a basis for future research in etiology, treatment, and outcomes for glioblastoma in the Pakistani population.

Enhancing brain tumor classification by integrating radiomics and deep learning features: A comprehensive study utilizing ensemble methods on MRI scans

BACKGROUND AND OBJECTIVE

This study aims to assess the effectiveness of combining radiomics features (RFs) with deep learning features (DFs) for classifying brain tumors-specifically Glioma, Meningioma, and Pituitary Tumor-using MRI scans and advanced ensemble learning techniques.

METHODS

A total of 3064 T1-weighted contrast-enhanced brain MRI scans were analyzed. RFs were extracted using Pyradiomics, while DFs were obtained from a 3D convolutional neural network (CNN). These features were used both individually and together to train a range of machine learning models, including Support Vector Machines (SVM), Decision Trees (DT), Random Forests (RF), AdaBoost, Bagging, k-Nearest Neighbors (KNN), and Multi-Layer Perceptrons (MLP). To enhance the accuracy of these models, ensemble approaches such as Stacking, Voting, and Boosting were employed. LASSO feature selection and five-fold cross-validation were utilized to ensure the models' robustness.

RESULTS

The results demonstrated that combining RFs and DFs significantly improved the model's performance compared to using either feature set alone. The best performance was achieved using the combined RF + DF approach with ensemble methods, particularly Boosting, which resulted in an accuracy of 95.0%, an AUC of 0.92, a sensitivity of 88%, and a specificity of 90%. Conversely, models utilizing only RFs or DFs showed lower performance, with RFs reaching an AUC of 0.82 and DFs achieving an AUC of 0.85.

CONCLUSION

The integration of RFs and DFs, along with advanced ensemble methods, significantly improves the accuracy and reliability of brain tumor classification using MRI. This approach shows strong clinical potential, with opportunities for further enhancing generalizability and precision through additional MRI sequences and advanced machine learning techniques.

Brain Tumor Assessment: Integrating PET/Computed Tomography and MR Imaging Modalities

While MR imaging is the main imaging modality to assess brain tumors, PET imaging has a specific role. Among the many tracers that have been proposed and are still being developed, 2-[18F]fluoro-2-deoxy-d-glucose ([18F]FDG) and O-(2-[18F]-fluoroethyl)-l-tyrosine ([18F]FET) PET remain the most solidly established in the clinics. In particular, [18F]FET has gained increased acceptance due to its higher sensitivity. In this paper, we present an overview of the current clinical status of brain tumor imaging, with emphasis on PET imaging.

Genetic variants in mitochondrial sirtuins associated with brain tumor risk: a case-control study

BACKGROUND

Previous studies on brain tumors have been performed on the nuclear genome, but limited studies have been reported on the mitochondrial genome. The mitochondrial sirtuin (SIRT3/SIRT4/SIRT5) has been mutated in different cancers. Limited studies have been performed on brain tumors. Isocitrate dehydrogenase (IDH) is an important marker, and polymorphism in the IDH gene has been reported to differentiate the brain tumor subtypes.

AIM

The present study was designed to screen mitochondrial sirtuins and IDH polymorphisms in brain tumor patients.

METHODOLOGY

One thousand blood samples were collected (500 brain tumor patients and 500 controls). Two SNPs for each gene SIRT3 (rs12226697, rs570591), SIRT4 (rs184496260, 1925909), SIRT5 (rs2841522, rs2841523), and one SNP for IDH (rs11554137) was screened using Tetra-ARMS PCR.

RESULTS

Logistic regression showed that the mutant genotype of selected SNPs was associated with increased disease incidence compared to wild type. Haplotype analysis and linkage disequilibrium (LD) showed a strong LD in brain tumor patients. Kaplan-Meier analysis showed that mutant allele frequency was found to be associated with a significant decrease in the survival of brain tumor patients.

CONCLUSION

The present study showed that the mutant allele of selected mitochondrial sirtuins' SNP was associated with increased brain tumor risk.

Imaging features of pediatric meningiomas: emphasis on unusual locations

PURPOSE

This article aims to analyze pediatric meningioma's imaging characteristics, especially those in unusual locations.

METHODS

Pediatric patients with pathologically confirmed meningiomas at our hospital from January 2010 to January 2024 were enrolled. Meningiomas located in the cerebral convexity, parasagittal falcine region, anterior skull base, middle skull base, sphenoid ridge, cerebellopontine angle (CPA), olfactory groove, or juxtasella were considered in usual locations. Meningiomas found in other areas were considered in unusual locations. Clinical information, pathology results, and imaging features of pediatric meningiomas in usual and usual locations were analyzed and compared.

RESULTS

A total of 18 patients (19 meningiomas) were enrolled, including 14 males and 4 females, with an average age of 14 years (ranging from 6 to 18 years). A total of 12 (63.2%) meningiomas were in the unusual location, including four (33.3%) were intraparenchymal, four (33.3%) were intraventricular, two (16.7%) were intraosseous, one (8.3%) case was in the paranasal sinus, and one (8.3%) was intraspinal. The meningiomas in unusual locations usually lacked the meningeal tail sign, and the misdiagnosis rate on preoperative imaging was significantly higher than that of meningiomas in usual locations.

CONCLUSION

Pediatric meningiomas are prone to occur in unusual locations. When they occur in usual locations, they often lack typical radiographic features of meningiomas, leading to potential misdiagnosis before surgery. Recognition of the imaging characteristics of meningiomas in unusual locations in children may facilitate accurate preoperative imaging diagnosis.

A comparative study of PEO-PBO content on the targeting and anti-glioma activity of annonaceous acetogenins-loaded nanomicelles

Annonaceous acetogenins (ACGs) have great potential in the treatment of gliomas, but are extremely insoluble and difficult for delivery in vivo. Poly(ethylene oxide)-b-poly(butylene oxide) (PEO-PBO) is an amphiphilic polymer and can reduce the clearance of nanoparticles by mononuclear phagocyte system. To explore an efficient and safe nanomedicine for glioma, ACGs-loaded nanomicelles (ACGs/EB-NCs) was constructed using PEO-PBO as a carrier, and the effect of PEO-PBO content on the targeting and anti-glioma activity were also compared. ACGs/EB5-NCs, ACGs/EB10-NCs and ACGs/EB20-NCs, the three nanomicellels prepared with different ACGs/EB feeding ratios, had average particle sizes of 148.8±0.5 nm, 32.7±4.1 nm, and 27.1±0.3 nm, respectively. The three ACGs/EB-NCs were spherical in shape, with drug loading content close to the theoretical drug loading content, encapsulation efficiency greater than 97 %, and good stability in physiological media. The cumulative release rates of ACGs/EB5-NCs, ACGs/EB10-NCs and ACGs/EB20-NCs were 78.2 %, 63.4 %, and 56.3 % within 216 hours, respectively. The inhibitory effects of three ACGs/EB-NCs on U87 MG cells were similar and stronger than free ACGs (P<0.05), with half inhibitory concentration of 0.17, 0.18, and 0.16 ng/mL (P>0.05), respectively. In U87 MG tumor‑bearing mice, ACGs/EB5-NC, ACGs/EB10-NCs and ACGs/EB20-NCs showed a similar tumor inhibition rate of 61.1±5.9 %, 56.2±8.6 % and 64.3±9.4 % (P>0.05), with good safety. Three ACGs/EB-NCs exhibited excellent liver escape ability and tumor targeting ability, with the tumor targeting index greater than 1.5. Three ACGs/EB-NCs were successfully prepared with strong anti-glioma activity and tumor targeting properties, which are expected to provide new options for the clinical treatment of gliomas. The content of PEO-PBO in micelles did not have a significant effect on the tumor targeting and anti-glioma activity of ACGs/EB-NCs.

Exosomes in Central Nervous System Diseases: A Comprehensive Review of Emerging Research and Clinical Frontiers

Exosomes, nano-sized lipid bilayer vesicles, have garnered significant attention as mediators of cell communication, particularly within the central nervous system (CNS). Their unique properties, including high stability, low immunogenicity, and the ability to traverse the blood-brain barrier (BBB), position them as promising tools for understanding and addressing CNS diseases. This comprehensive review delves into the biogenesis, properties, composition, functions, and isolation of exosomes, with a particular focus on their roles in cerebrovascular diseases, neurodegenerative disorders, and CNS tumors. Exosomes are involved in key pathophysiological processes in the CNS, including angiogenesis, inflammation, apoptosis, and cellular microenvironment modification. They demonstrate promise in mitigating ischemic injury, regulating inflammatory responses, and providing neuroprotection across various CNS conditions. Furthermore, exosomes carry distinct biomolecules, offering a novel method for the early diagnosis and monitoring of CNS diseases. Despite their potential, challenges such as complex extraction processes, the heterogeneity of exosomal contents, and targeted delivery limitations hinder their clinical application. Nevertheless, exosomes hold significant promise for advancing our understanding of CNS diseases and developing novel therapeutic strategies. This manuscript significantly contributes to the field by highlighting exosomes' potential in advancing our understanding of CNS diseases, underscoring their unique value in developing novel therapeutic strategies and mediating cellular communication.

The dural attachment length predict prognosis in patients with recurrent meningiomas

To investigate the prognostic factors of recurrent meningioma patients who underwent reoperation, so as to make relevant recommendations for the treatment. A retrospective analysis was performed on 73 patients with recurrent meningioma. Patients' clinical data were obtained from their medical records. Progression-free Survival (PFS) was defined as the interval from the date of surgery to the date of tumor recurrence, or to the date of the last imaging review. Overall survival (OS) was defined as the time from the date of surgery to death from any cause, or to the date of the last follow-up. The multivariate COX regression showed that dural attachment length (HR = 1.238, 95%CI1.011-1.516, P = 0.039) and WHO grade (HR = 2.184, 95%CI1.135-4.203, P = 0.019) were independent risk factors for tumor progression. The factors associated with survival in multivariate regression analysis were preoperative Karnofsky Performance Scale (KPS) (HR = 0.951, 95%CI0.923-0.979, P = 0.001), dural attachment length (HR = 1.520, 95%CI1.124-2.057, P = 0.007) and WHO grade (HR = 4.829, 95%CI1.891-12.331, P = 0.001). The dural attachment length (OR = 1.843, 95%CI1.236-2.748, P = 0.003) was the only risk factor associated with postoperative pulmonary infection. No correlation was observed between Simpson's grade and either PFS or OS. The dural attachment length is closely related to the prognosis of recurrent meningioma, which should be given importance during the perioperative assessment.

The apparent diffusion coefficient can serve as a predictor of survival in patients with gliomas

BACKGROUND AND PURPOSE

Magnetic resonance imaging is indispensable for the preoperative diagnosis of glioma. This study aimed to investigate the role of the apparent diffusion coefficient values as predictors of survival in patients with gliomas.

METHODS AND MATERIALS

A retrospective analysis was conducted on 101 patients with gliomas who underwent surgery between 2015 and 2020. Diffusion-weighted MRI was performed before the surgery. The regions of interest were categorized into parenchymal area, non-enhancing peritumoral area, and necrotic or cystic area. All the patients were divided into three subgroups: the parenchyma group, the non-enhancing peritumoral signal abnormality group, and the necrosis or cyst group. Univariate and multivariate analyses were performed using COX regression.

RESULTS

In the parenchymal group, Ki67, P53, IDH, and the high or low ADC values were identified as independent prognosticators for disease-free survival, while Ki67, IDH, and the high or low ADC values for overall survival. In the non-enhancing peritumoral signal abnormality group, Ki67, P53, IDH, and the ADC parenchymal area/ADC non-enhancing peritumoral area ratio were identified as independent prognostic factors for disease-free survival, while Ki67, IDH, and the ADC parenchymal area/ADC non-enhancing peritumoral area ratio for overall survival. In the necrosis or cyst group, Ki67 was significantly associated with disease-free survival, while Ki67 and the ADC value of the necrotic or cystic area for overall survival.

CONCLUSIONS

The ADC values, including the ADC value in the parenchymal area, the ADC parenchymal area/ADC non-enhancing peritumoral area ratio, and the ADC value in the necrotic or cystic area, can serve as an efficient and potential index for predicting the survival of patients with glioma.

Concomitant gut dysbiosis and defective gut barrier serve as the bridges between hypercortisolism and chronic systemic inflammation in Cushing's disease

OBJECTIVE

The aim of this study was to investigate the gut microbial signatures and related pathophysiological implications in patients with Cushing's disease (CD).

DESIGN AND METHODS

Twenty-seven patients with CD and 45 healthy controls were enrolled. Based on obtained metagenomics data, we performed correlation, network study, and genome interaction group (GIG) analysis. Fecal metabolomics and serum enzyme linked immunosorbent assay (ELISA) analysis were conducted in dichotomized CD patients. Caco-2 cells were incubated with gradient concentrations of cortisol for subsequent transepithelial electrical resistance (TEER) measurement, FITC-dextran transwell permeability assay, qPCR, and western blot analysis.

RESULTS

Gut microbial composition in patients with CD was notably different from that in healthy controls. Network analysis revealed that Eubacterium siraeum might serve as the core specie in the gut microbial system of CD patients. Subsequent GIG analysis identified the positive correlations between GIG9 and UFC. Further serum ELISA and fecal metabolomics uncovered that CD patients with elevated UFC levels were characterized with increased lipopolysaccharide binding protein (LBP). Moreover, remarkable positive association was found between LBP level and relative abundance of E. siraeum. TEER and FITC-dextran transwell assays demonstrated that hypercortisolism induced increased gut permeability. Further qPCR and western blot analysis suggested that dysregulated AhR/Claudin 2 axis might be involved in the development of hypercortisolism-induced defective gut barrier function.

CONCLUSIONS

Disease activity associated dysbiosis and defective gut barrier might jointly facilitate the development of systemic inflammation in patients with CD.

The Implication of Photodynamic Therapy Applied to the Level of Tumor Resection on Postoperative Cerebral Edema and Intracranial Pressure Changes in Gliomas

AIM

The aim of our study was to explore the factors influencing cerebral edema and intracranial pressure in glioblastoma multiforme (GBM) patients who undergo photodynamic therapy (PDT) after resection.

APPROACH

This was a retrospective controlled study of GBM patients treated with PDT-assisted resections of varying scope from May 2021 to August 2023. The baseline clinical data, cerebral edema volumes, intracranial pressure values, and imaging data of the GBM patients were collected for statistical analysis.

RESULTS

A total of 56 GBM patients were included. Thirty of the patients underwent gross total resection (GTR), and the other 26 patients underwent subtotal resection (STR). We found that the cerebral edema volume and the mean intracranial pressure in patients who underwent GTR were lower than those in patients who underwent STR. Moreover, univariate analysis showed that the scope of tumor resection was an independent factor affecting cerebral edema and intracranial pressure after PDT.

CONCLUSIONS

Compared with STR, PDT combined with GTR significantly reduced postoperative brain edema volume and intracranial pressure in GBM patients.

Symptomatic spinal metastasis of a supratentorial glioblastoma in a pediatric patient: a case report and comprehensive review of the literature

Spinal metastasis of Glioblastoma is a rare occurrence, especially in pediatric patients, and extremely rare to become symptomatic. The pathology is poorly understood and remains with unclear dissemination mechanisms. The treatment approaches are varied and multimodal therapy (surgery, chemotherapy, and radiotherapy) can be employed to manage this type of metastasis. We report a case of a 17-year-old female who underwent a gross-total resection of a right frontal glioblastoma and had adjuvant therapy with chemo- and radiotherapy. In the sixth month of follow-up, the patient presented a paraparesis, and a distant recurrence at T7-T8 was detected. The patient was treated with gross-total resection of the tumor through a laminectomy. The histopathological results were consistent with an isocitrate dehydrogenase (IDH) wildtype GBM metastasis. The patient was treated with multimodal therapy, including surgery, radiotherapy, and chemotherapy. A complementary comprehensive review of current available literature on this topic is also presented.

Practical Nomograms and Risk Stratification System for Predicting the Overall and Cancer-specific Survival in Patients with Anaplastic Astrocytoma

OBJECTIVE

Anaplastic astrocytoma (AA) is an uncommon primary brain tumor with highly variable clinical outcomes. Our study aimed to develop practical tools for clinical decision-making in a population-based cohort study.

METHODS

Data from 2997 patients diagnosed with AA between 2004 and 2015 were retrospectively extracted from the Surveillance, Epidemiology, and End Results database. The Least Absolute Shrinkage and Selection Operator and multivariate Cox regression analyses were applied to select factors and establish prognostic nomograms. The discriminatory ability of these nomogram models was evaluated using the concordance index and receiver operating characteristic curve. Risk stratifications were established based on the nomograms.

RESULTS

Selected 2997 AA patients were distributed into the training cohort (70%, 2097) and the validation cohort (30%, 900). Age, household income, tumor site, extension, surgery, radiotherapy, and chemotherapy were identified as independent prognostic factors for both overall survival (OS) and cancer-specific survival (CSS). In the training cohort, our nomograms for OS and CSS exhibited good predictive accuracy with concordance index values of 0.752 (95% CI: 0.741-0.764) and 0.753 (95% CI: 0.741-0.765), respectively. Calibration and decision curve analyses curves showed that the nomograms demonstrated considerable consistency and satisfactory clinical utilities. With the establishment of nomograms, we stratified AA patients into high- and low-risk groups, and constructed risk stratification systems for OS and CSS.

CONCLUSIONS

We constructed two predictive nomograms and risk classification systems to effectively predict the OS and CSS rates in AA patients. These models were internally validated with considerable accuracy and reliability and might be helpful in future clinical practices.

Technological Frontiers in Brain Cancer: A Systematic Review and Meta-Analysis of Hyperspectral Imaging in Computer-Aided Diagnosis Systems

Brain cancer is a substantial factor in the mortality associated with cancer, presenting difficulties in the timely identification of the disease. The precision of diagnoses is significantly dependent on the proficiency of radiologists and neurologists. Although there is potential for early detection with computer-aided diagnosis (CAD) algorithms, the majority of current research is hindered by its modest sample sizes. This meta-analysis aims to comprehensively assess the diagnostic test accuracy (DTA) of computer-aided design (CAD) models specifically designed for the detection of brain cancer utilizing hyperspectral (HSI) technology. We employ Quadas-2 criteria to choose seven papers and classify the proposed methodologies according to the artificial intelligence method, cancer type, and publication year. In order to evaluate heterogeneity and diagnostic performance, we utilize Deeks' funnel plot, the forest plot, and accuracy charts. The results of our research suggest that there is no notable variation among the investigations. The CAD techniques that have been examined exhibit a notable level of precision in the automated detection of brain cancer. However, the absence of external validation hinders their potential implementation in real-time clinical settings. This highlights the necessity for additional studies in order to authenticate the CAD models for wider clinical applicability.

Revealing the link between gut microbiota and brain tumor risk: a new perspective from Mendelian randomization

Background

Recent studies have shown that gut microbiota may be related to the occurrence of brain tumors, but direct evidence is lacking. This study used the Mendelian randomization study (MR) method to explore the potential causal link between gut microbiota and brain tumors.

Method

We analyzed the genome-wide association data between 211 gut microbiota taxa and brain tumors, using the largest existing gut microbiota Genome-Wide Association Studies meta-analysis data (n=13266) and combining it with brain tumor data in the IEU OpenGWAS database. We use inverse-variance weighted analysis, supplemented by methods such as Mendelian randomization-Egger regression, weighted median estimator, simple mode, and weighted mode, to assess causality. In addition, we also conducted the Mendelian randomization-Egger intercept test, Cochran's Q test, and Mendelian randomization Steiger directionality test to ensure the accuracy of the analysis. Quality control includes sensitivity analysis, horizontal gene pleiotropy test, heterogeneity test, and MR Steiger directionality test.

Result

Our study found that specific gut microbial taxa, such as order Lactobacillales and family Clostridiaceae1, were positively correlated with the occurrence of brain tumors, while genus Defluviitaleaceae UCG011 and genus Flavonifractor were negatively correlated with the occurrence of brain tumors. The Mendelian randomization-Egger intercept test showed that our analysis was not affected by pleiotropy (P>0.05).

Conclusion

This study reveals for the first time the potential causal relationship between gut microbiota and brain tumors, providing a new perspective for the prevention and treatment of early brain tumors. These findings may help develop new clinical intervention strategies and point the way for future research.

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.

Clinical Utility of Optical Genome Mapping for Improved Cytogenomic Analysis of Gliomas

A glioma is a solid brain tumor which originates in the brain or brain stem area. The diagnosis of gliomas based on standard-of-care (SOC) techniques includes karyotyping, fluorescence in situ hybridization (FISH), and chromosomal microarray (CMA), for detecting the pathogenic variants and chromosomal abnormalities. But these techniques do not reveal the complete picture of genetic complexity, thus requiring an alternative technology for better characterization of these tumors. The present study aimed to evaluate the clinical performance and feasibility of using optical genome mapping (OGM) for chromosomal characterization of gliomas. Herein, we evaluated 10 cases of gliomas that were previously characterized by CMA. OGM analysis showed concordance with the results of CMA in identifying the characterized Structural Variants (SVs) in these cases. More notably, it also revealed additional clinically relevant aberrations, demonstrating a higher resolution and sensitivity. These clinically relevant SVs included cryptic translocation, and SVs which are beyond the detection capabilities of CMA. Our analysis highlights the unique capability of OGM to detect all classes of SVs within a single assay, thereby unveiling clinically significant data with a shorter turnaround time. Adopting this diagnostic tool as a standard of care for solid tumors like gliomas shows potential for improving therapeutic management, potentially leading to more personalized and timely interventions for patients.

tRNA Modifications and Dysregulation: Implications for Brain Diseases

Transfer RNAs (tRNAs) are well-known for their essential function in protein synthesis. Recent research has revealed a diverse range of chemical modifications that tRNAs undergo, which are crucial for various cellular processes. These modifications are necessary for the precise and efficient translation of proteins and also play important roles in gene expression regulation and cellular stress response. This review examines the role of tRNA modifications and dysregulation in the pathophysiology of various brain diseases, including epilepsy, stroke, neurodevelopmental disorders, brain tumors, Alzheimer's disease, and Parkinson's disease. Through a comprehensive analysis of existing research, our study aims to elucidate the intricate relationship between tRNA dysregulation and brain diseases. This underscores the critical need for ongoing exploration in this field and provides valuable insights that could facilitate the development of innovative diagnostic tools and therapeutic approaches, ultimately improving outcomes for individuals grappling with complex neurological conditions.

CBTRUS Statistical Report: American Brain Tumor Association & NCI Neuro-Oncology Branch Adolescent and Young Adult Primary Brain and Other Central Nervous System Tumors Diagnosed in the United States in 2016-2020

Recent analyses have shown that, whereas cancer survival overall has been improving, it has not improved for adolescents and young adults ages 15-39 years (AYA). The clinical care of AYA with primary brain and other central nervous system (CNS) tumors (BT) is complicated by the fact that the histopathologies of such tumors in AYA differ from their histopathologies in either children (ages 0-14 years) or older adults (ages 40+ years). The present report, as an update to a 2016 publication from the Central Brain Tumor Registry of the United States and the American Brain Tumor Association, provides in-depth analyses of the epidemiology of primary BT in AYA in the United States and is the first to provide biomolecular marker-specific statistics and prevalence by histopathology for both primary malignant and non-malignant BT in AYA. Between 2016 and 2020, the annual average age-specific incidence rate (AASIR) of primary malignant and non-malignant BT in AYA was 12.00 per 100,000 population, an average of 12,848 newly diagnosed cases per year. During the same period, an average of 1,018 AYA deaths per year were caused by primary malignant BT, representing an annual average age-specific mortality rate of 0.96 per 100,000 population. When primary BT were categorized by histopathology, pituitary tumors were the most common (36.6%), with an AASIR of 4.34 per 100,000 population. Total incidence increased with age overall; when stratified by sex, the incidence was higher in females than males at all ages. Incidence rates for all primary BT combined and for non-malignant tumors only were highest for non-Hispanic American Indian/Alaska Native individuals, whereas malignant tumors were more frequent in non-Hispanic White individuals, compared with other racial/ethnic groups. On the basis of histopathology, the most common molecularly defined tumor was diffuse glioma (an AASIR of 1.51 per 100,000). Primary malignant BT are the second most common cause of cancer death in the AYA population. Incidence rates of primary BT overall, as well as specific histopathologies, vary significantly by age. Accordingly, an accurate statistical assessment of primary BT in the AYA population is vital for better understanding the impact of these tumors on the US population and to serve as a reference for afflicted individuals, for researchers investigating new therapies, and for clinicians treating these patients.

Insights into Targeted and Stimulus-Responsive Nanocarriers for Brain Cancer Treatment

Brain cancers, especially glioblastoma multiforme, are associated with poor prognosis due to the limited efficacy of current therapies. Nanomedicine has emerged as a versatile technology to treat various diseases, including cancers, and has played an indispensable role in combatting the COVID-19 pandemic as evidenced by the role that lipid nanocarrier-based vaccines have played. The tunability of nanocarrier physicochemical properties -including size, shape, surface chemistry, and drug release kinetics- has resulted in the development of a wide range of nanocarriers for brain cancer treatment. These nanocarriers can improve the pharmacokinetics of drugs, increase blood-brain barrier transfer efficiency, and specifically target brain cancer cells. These unique features would potentially allow for more efficient treatment of brain cancer with fewer side effects and better therapeutic outcomes. This review provides an overview of brain cancers, current therapeutic options, and challenges to efficient brain cancer treatment. The latest advances in nanomedicine strategies are investigated with an emphasis on targeted and stimulus-responsive nanocarriers and their potential for clinical translation.

Proposing a sphenoid bone quality score: a novel concept for transsphenoidal surgery

Transsphenoid surgery is a common procedure for removing pituitary and other sellar tumors. The quality and density of the sphenoid bone, which serves as the access route to the sellar region, can affect the surgical outcomes and complications. However, there is no standardized method to assess sphenoid bone quality. I propose a sphenoid bone quality score, based on criteria and parameters derived from preoperative imaging techniques. This score could provide information on the bone characteristics and challenges of each case, and help to select the optimal surgical approach, instruments, grafts, and measures. This score could also enable a consistent evaluation of the surgery and the outcomes, and facilitate the communication and collaboration among different medical disciplines.

Chronic hyperglycemia and intracranial meningiomas

Meningiomas are among the most common primary tumors of the central nervous system. Previous research into the meningioma histological appearance, genetic markers, transcriptome and epigenetic landscape has revealed that benign meningiomas significantly differ in their glucose metabolism compared to aggressive lesions. However, a correlation between the systemic glucose metabolism and the metabolism of the tumor hasn't yet been found. We hypothesized that chronic levels of glycaemia (approximated with glycated hemoglobin (HbA1c)) are different in patients with aggressive and benign meningiomas. The study encompassed 71 patients with de novo intracranial meningiomas, operated on in three European hospitals, two in Croatia and one in Spain. Our results show that patients with WHO grade 2 meningiomas had significantly higher HbA1c values compared to patients with grade 1 lesions (P = 0.0290). We also found a significant number of patients (19/71; 26.7%) being hyperglycemic, harboring all the risks that such a condition entails. Finally, we found a significant correlation between our patients' age and their preoperative HbA1c levels (P = 0.0008, ρ(rho) = 0.388), suggesting that older meningioma patients are at a higher risk of having their glycaemia severely dysregulated. These findings are especially important considering the current routine and wide-spread use of corticosteroids as anti-edematous treatment. Further research in this area could lead to better understanding of meningiomas and have immediate clinical impact.

Progress in the Treatment of Central Nervous System Diseases Based on Nanosized Traditional Chinese Medicine

Traditional Chinese Medicine (TCM) is widely used in clinical practice to treat diseases related to central nervous system (CNS) damage. However, the blood-brain barrier (BBB) constitutes a significant impediment to the effective delivery of TCM, thus substantially diminishing its efficacy. Advances in nanotechnology and its applications in TCM (also known as nano-TCM) can deliver active ingredients or components of TCM across the BBB to the targeted brain region. This review provides an overview of the physiological and pathological mechanisms of the BBB and systematically classifies the common TCM used to treat CNS diseases and types of nanocarriers that effectively deliver TCM to the brain. Additionally, drug delivery strategies for nano-TCMs that utilize in vivo physiological properties or in vitro devices to bypass or cross the BBB are discussed. This review further focuses on the application of nano-TCMs in the treatment of various CNS diseases. Finally, this article anticipates a design strategy for nano-TCMs with higher delivery efficiency and probes their application potential in treating a wider range of CNS diseases.

Deciphering Glioblastoma: Fundamental and Novel Insights into the Biology and Therapeutic Strategies of Gliomas

Gliomas constitute a diverse and complex array of tumors within the central nervous system (CNS), characterized by a wide range of prognostic outcomes and responses to therapeutic interventions. This literature review endeavors to conduct a thorough investigation of gliomas, with a particular emphasis on glioblastoma (GBM), beginning with their classification and epidemiological characteristics, evaluating their relative importance within the CNS tumor spectrum. We examine the immunological context of gliomas, unveiling the intricate immune environment and its ramifications for disease progression and therapeutic strategies. Moreover, we accentuate critical developments in understanding tumor behavior, focusing on recent research breakthroughs in treatment responses and the elucidation of cellular signaling pathways. Analyzing the most novel transcriptomic studies, we investigate the variations in gene expression patterns in glioma cells, assessing the prognostic and therapeutic implications of these genetic alterations. Furthermore, the role of epigenetic modifications in the pathogenesis of gliomas is underscored, suggesting that such changes are fundamental to tumor evolution and possible therapeutic advancements. In the end, this comparative oncological analysis situates GBM within the wider context of neoplasms, delineating both distinct and shared characteristics with other types of tumors.

Risk Factors of the Totally Implantable Venous Access Device-Related Infection in Patients With Brain Tumors Undergoing Chemotherapy After Surgery

Background: The complication of totally implantable venous access device (TIVAD) is an infection, which causes the death of patients. Therefore, it is critical to identify risk factors for TIVAD infection to prevent death. Patients and Methods: The enrolled patients were divided into two groups and subsequently divided into subgroups according to various factors in which the correlation between infection and risk factors was analyzed. Multivariable logistic analysis of odds ratios (ORs) for seven risk factors was performed, meanwhile, the receiver operating characteristic (ROC) curve analysis of neutrophil and serum albumin was conducted for the prediction of TIVAD infection occurrence. Results: Catheter-related blood stream infection was the common infection type, which was dominantly caused by Staphylococcus aureus. Removal of TIVAD and antibiotic therapy were the preferred approaches for the treatment of infection. Seven risk factors were closely associated with the TIVAD infection, however, two risk factors, including age and outpatient, were excluded according to the multivariate logistic analysis of ORs. Receiver operating characteristic curve analysis revealed neutrophil count and serum albumin could predict the occurrence of TIVAD infection. Conclusions: Five risk factors were positively related to TIVAD infection; neutrophil and serum albumin could be used to predict the occurrence of TIVAD infection.

Nose-to-brain delivery of nanotherapeutics: Transport mechanisms and applications

The blood-brain barrier presents a key limitation to the administration of therapeutic molecules for the treatment of brain disease. While drugs administered orally or intravenously must cross this barrier to reach brain targets, the unique anatomical structure of the olfactory system provides a route to deliver drugs directly to the brain. Entering the brain via receptor, carrier, and adsorption-mediated transcytosis in the nasal olfactory and trigeminal regions has the potential to increase drug delivery. In this review, we introduce the physiological and anatomical structures of the nasal cavity, and summarize the possible modes of transport and the relevant receptors and carriers in the nose-to-brain pathway. Additionally, we provide examples of nanotherapeutics developed for intranasal drug delivery to the brain. Further development of nanoparticles that can be applied to intranasal delivery systems promises to improve drug efficacy and reduce drug resistance and adverse effects by increasing molecular access to the brain. This article is categorized under: Therapeutic Approaches and Drug Discovery > Nanomedicine for Neurological Disease.

Bisphenol A: Unveiling Its Role in Glioma Progression and Tumor Growth

Gliomas represent the most common and lethal category of primary brain tumors. Bisphenol A (BPA), a widely recognized endocrine disruptor, has been implicated in the progression of cancer. Despite its established links to various cancers, the association between BPA and glioma progression remains to be clearly defined. This study aimed to shed light on the impact of BPA on glioma cell proliferation and overall tumor progression. Our results demonstrate that BPA significantly accelerates glioma cell proliferation in a time- and dose-dependent manner. Furthermore, BPA has been found to enhance the invasive and migratory capabilities of glioma cells, potentially promoting epithelial-mesenchymal transition (EMT) characteristics within these tumors. Employing bioinformatics approaches, we devised a risk assessment model to gauge the potential glioma hazards associated with BPA exposure. Our comprehensive analysis revealed that BPA not only facilitates glioma invasion and migration but also inhibits apoptotic processes. In summary, our study offers valuable insights into the mechanisms by which BPA may promote tumorigenesis in gliomas, contributing to the understanding of its broader implications in oncology.

Ocular Motor Cranial Nerve Palsies and Increased Risk of Primary Malignant Brain Tumors: South Korean National Health Insurance Data

The aim of this study was to investigate the association between ocular motor cranial nerve palsies (OMCNP) and the occurrence of primary malignant brain tumors in a Korean population, using the national sample cohort database from Korea National Health Insurance Service (KNHIS). KNHIS data between 2010 and 2017 were analyzed. Our sample encompassed 118,686 participants, including 19,781 from a recently diagnosed OMCNP cohort and 98,905 from a matched control cohort through a 1:5 propensity score matching based on age and gender. To counteract the issue of reverse causation, we integrated a one-year time lag in our sensitivity analysis. Study participants were followed up until 31 December 2019. Cox proportional hazard regression analysis was used to compute the adjusted hazard ratio (HR) for primary malignant brain tumors according to the OMCNP diagnosis. Additionally, we performed a subgroup analysis to discern effects of various factors on the association between OMCNP and primary malignant brain tumors. HR for primary malignant brain tumors was 3.272 (95% confidence interval [CI]: 2.294 to 4.665) in the OMCNP cohort compared to the control cohort in a fully adjusted model for age, sex, socio-economic status, smoking, drinking, regular physical exercise, hypertension, diabetes, dyslipidemia, obesity, chronic kidney disease, and human immunodeficiency virus infection. Further subgroup analysis revealed that the risk of primary malignant brain tumors was significantly increased in women with OMCNP compared to men with OMCNP (HR: 5.118 in women vs. 2.441 in men, p = 0.0440), and in those aged <65 years than in those aged ≥65 years (HR: 6.951 in age < 65 years vs. 1.899 in age ≥ 65 years, p = 0.0006). Our population-based cohort study demonstrated a significantly increased risk of subsequent primary malignant brain tumors in patients with OMCNP. Particularly, OMCNP-afflicted women aged below 65 manifested a heightened probability of developing primary malignant brain tumors compared to those devoid of OMCNP.

Brain tumors in United States military veterans

BACKGROUND

Comprehensive analysis of brain tumor incidence and survival in the Veteran population has been lacking.

METHODS

Veteran data were obtained from the Veterans Health Administration (VHA) Medical Centers via VHA Corporate Data Warehouse. Brain tumor statistics on the overall US population were generated from the Central Brain Tumor Registry of the US data. Cases were individuals (≥18 years) with a primary brain tumor, diagnosed between 2004 and 2018. The average annual age-adjusted incidence rates (AAIR) and 95% confidence intervals were estimated per 100 000 population and Kaplan-Meier survival curves evaluated overall survival outcomes among Veterans.

RESULTS

The Veteran population was primarily white (78%), male (93%), and between 60 and 64 years old (18%). Individuals with a primary brain tumor in the general US population were mainly female (59%) and between 18 and 49 years old (28%). The overall AAIR of primary brain tumors from 2004 to 2018 within the Veterans Affairs cancer registry was 11.6. Nonmalignant tumors were more common than malignant tumors (AAIR:7.19 vs 4.42). The most diagnosed tumors in Veterans were nonmalignant pituitary tumors (AAIR:2.96), nonmalignant meningioma (AAIR:2.62), and glioblastoma (AAIR:1.96). In the Veteran population, survival outcomes became worse with age and were lowest among individuals diagnosed with glioblastoma.

CONCLUSIONS

Differences between Veteran and US populations can be broadly attributed to demographic composition differences of these groups. Prior to this, there have been no reports on national-level incidence rates and survival outcomes for Veterans. These data provide vital information that can drive efforts to understand disease burden and improve outcomes for individuals with primary brain tumors.

Impact of prior cancer history on survival in brain malignancy: A propensity score-adjusted, population-based study

BACKGROUND

Individuals with a Prior Cancer History (PCH) are often excluded from clinical trials. However, a growing body of evidence suggests that prior cancer history does not present adverse outcomes on cancer patients. The evidence on the survival of brain cancer patients in this regard remains widely unknown.

METHODS

We conducted a retrospective cohort study to estimate the prevalence and impact of prior cancer on survival of patients diagnosed with brain cancer. Data of patients who were diagnosed with brain cancer as their first or second primary malignancy between 2000 and 2019 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Propensity Score Matching (PSM) was used to ensure comparable baseline characteristics among the patients. Survival analysis was conducted using the Kaplan-Meier method, as well as multivariate Cox proportional hazard and multivariate competing risk models.

RESULTS

Out of 42 726 patients, 1189 (2.78%) had PCH. Genitourinary (40.4%), Breast (13.6%), Hematologic and Lymphatic (11.4%), and Gastrointestinal malignancies (11.3%) were the most common types of prior cancer. PCH served as a significant risk factor for Overall Survival (OS) (Adjusted Hazard Ratio [AHR] 1.26; 95% CI [1.15-1.39]; p < .001) but did not have a statistically significant impact on Brain Cancer-Specific Survival (BCSS) (AHR 0.97; 95% CI [0.88-1.07]; p = .54). Glioblastoma exhibited the most substantial and statistically significant impact on survival as compared to other histological types. Of all the organs systems, only prior Gastrointestinal and Hematologic and Lymphatic malignancies had a statistically significant impact on OS of patients.

CONCLUSION

Our findings indicate that PCH does not exert a substantial impact on the survival of brain cancer patients, except in cases involving gastrointestinal or hematologic and lymphatic PCH, or when the brain cancer is glioblastoma.

Distinguishing brain tumors by Label-free confocal micro-Raman spectroscopy

BACKGROUND

Brain tumors have serious adverse effects on public health and social economy. Accurate detection of brain tumor types is critical for effective and proactive treatment, and thus improve the survival of patients.

METHODS

Four types of brain tumor tissue sections were detected by Raman spectroscopy. Principal component analysis (PCA) has been used to reduce the dimensionality of the Raman spectra data. Linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) methods were utilized to discriminate different types of brain tumors.

RESULTS

Raman spectra were collected from 40 brain tumors. Variations in intensity and shift were observed in the Raman spectra positioned at 721, 854, 1004, 1032, 1128, 1248, 1449 cm-1 for different brain tumor tissues. The PCA results indicated that glioma, pituitary adenoma, and meningioma are difficult to differentiate from each other, whereas acoustic neuroma is clearly distinguished from the other three tumors. Multivariate analysis including QDA and LDA methods showed the classification accuracy rate of the QDA model was 99.47 %, better than the rate of LDA model was 95.07 %.

CONCLUSIONS

Raman spectroscopy could be used to extract valuable fingerprint-type molecular and chemical information of biological samples. The demonstrated technique has the potential to be developed to a rapid, label-free, and intelligent approach to distinguish brain tumor types with high accuracy.

Presentation and Management of Cerebral Venous Sinus Thrombosis After Supratentorial Craniotomy

BACKGROUND AND OBJECTIVES

Cerebral venous sinus thrombosis (CVST) after supratentorial craniotomy is a poorly studied complication, for which there are no management guidelines. This study assessed the incidence, associated risk factors, and management of postoperative CVST after awake craniotomy.

METHODS

This is an observational, retrospective, monocentric analysis of patients who underwent a supratentorial awake craniotomy. Postoperative CVST was defined as a flow defect on the postoperative contrast-enhanced 3D T1-weighted sequence and/or as a T2* hypointensity within the sinus.

RESULTS

In 401 supratentorial awake craniotomies (87.3% of diffuse glioma), the incidence of postoperative CVST was 4.0% (95% CI 2.5-6.4): 14/16 thromboses located in the superior sagittal sinus and 12/16 located in the transverse sinus. A venous sinus was exposed during craniotomy in 45.4% of cases, and no intraoperative injury to a cerebral venous sinus was reported. All thromboses were asymptomatic, and only two cases were diagnosed at the time of the first postoperative imaging (0.5%). Postoperative complications, early postoperative Karnofsky Performance Status score, and duration of hospital stay did not significantly differ between patients with and without postoperative CVST. Adjusted independent risk factors of postoperative CVST were female sex (adjusted Odds Ratio 4.00, 95% CI 1.24-12.91, P = .021) and a lesion ≤1 cm to a venous sinus (adjusted Odds Ratio 10.58, 95% CI 2.93-38.20, P < .001). All patients received standard prophylactic-dose anticoagulant therapy, and none received treatment-dose anticoagulant therapy. No thrombosis-related adverse event was reported. All thromboses presented spontaneous sinus recanalization radiologically at a mean of 89 ± 41 days (range, 7-171).

CONCLUSION

CVST after supratentorial awake craniotomy is a rare event with satisfactory clinical outcomes and spontaneous sinus recanalization under conservative management without treatment-dose anticoagulant therapy. These findings are comforting to neurosurgeons confronted with postoperative MRI reports suggesting CVST.

Comparison of Resection Assisting Devices in the Process of Collecting Brain Tumor Tissue for Basic Research: Microdebrider Versus Ultrasonic Aspirator

INTRODUCTION

Brain tumors display significant inter and intratumoral heterogeneity, impacting disease progression and outcomes. Preserving surgically resected tissue is vital for ensuring accurate research results to enhance understanding of tumor pathophysiology. This study evaluates tissue integrity and viability of tissue resected using 2 surgical devices for tumor resection: a mechanical microdebrider (MD) and an ultrasonic aspirator (UA).

METHODS

Tumor samples were obtained from patients undergoing surgical resection of primary and secondary intracranial tumors. Cell viability was assessed, and histopathological analysis of Hematoxylin and Eosin -stained tissues was performed. Adherent monolayer and neurospheres cell cultures were established from paired samples. RNA isolation and quantitative polymerase chain reaction of housekeeping genes were conducted to compare genetic integrity.

RESULTS

The cellular viability was comparable between samples obtained using both the MD and the UA, with a mean viability of 75.2% ± 15.6 and 70.7% ± 16.8, respectively (P = 0.318). Histopathological evaluation indicated no discernible differences in cellular integrity between the devices. Cell culture success rates and growth characteristics were similar for both devices. RNA concentration and integrity were well-maintained in both MD and UA samples, with no significant differences (P = 0.855). Quantitative polymerase chain reaction analysis of housekeeping genes showed consistent results across matched tissues from both devices and different tumor pathologies.

CONCLUSIONS

Surgical handheld devices provide valuable, high-quality tissue samples for research. Surgeon preference, tumor pathology, and anatomical location dictate device choice. Both MD and UA devices are reliable for obtaining quality tissue specimens, facilitating translational neuro-oncology research.

[Retrocochlear diagnostics for acute hearing loss and successful therapy]

A 41-year-old female patient presented due to acute onset of unilateral hearing loss 3 months previously and persistent since then. Systemic therapy with oral glucocorticoids in decreasing doses had been performed beforehand, but did not lead to any improvement. In the course of audiological diagnostics, based on subjective and objective methods, a retrocochlear hearing disorder was suspected. A meningioma was diagnosed by diagnostic imaging. Subsequent surgical removal achieved a significant hearing improvement.

Role of Phytoconstituents in Cancer Treatment: A Review

Over the years, natural compounds have become a significant advancement in cancer treatment, primarily due to their effectiveness, safety, bio-functionality, and wide range of molecular structures. They are now increasingly preferred in drug discovery due to these attributes. These compounds, whether occurring naturally or with synthetic modifications, find applications in various fields like biology, medicine, and engineering. While chemotherapy has been a successful method for treating cancer, it comes with systemic toxicity. To address this issue, researchers and medical practitioners are exploring the concept of combinational chemotherapy. This approach aims to reduce toxicity by using a mix of natural substances and their derivatives in clinical trials and prescription medications. Among the most extensively studied natural anticancer compounds are quercetin, curcumin, vincristine, and vinblastine. These compounds play crucial roles as immunotherapeutics and chemosensitizers, both as standalone treatments and in combination therapies with specific mechanisms. This review article provides a concise overview of the functions, potentials, and combinations of natural anticancer compounds in cancer treatment, along with their mechanisms of action and clinical applications.

Automated volumetric assessment of pituitary adenoma

PURPOSE

Assessment of pituitary adenoma (PA) volume and extent of resection (EOR) through manual segmentation is time-consuming and likely suffers from poor interrater agreement, especially postoperatively. Automated tumor segmentation and volumetry by use of deep learning techniques may provide more objective and quick volumetry.

METHODS

We developed an automated volumetry pipeline for pituitary adenoma. Preoperative and three-month postoperative T1-weighted, contrast-enhanced magnetic resonance imaging (MRI) with manual segmentations were used for model training. After adequate preprocessing, an ensemble of convolutional neural networks (CNNs) was trained and validated for preoperative and postoperative automated segmentation of tumor tissue. Generalization was evaluated on a separate holdout set.

RESULTS

In total, 193 image sets were used for training and 20 were held out for validation. At validation using the holdout set, our models (preoperative / postoperative) demonstrated a median Dice score of 0.71 (0.27) / 0 (0), a mean Jaccard score of 0.53 ± 0.21/0.030 ± 0.085 and a mean 95th percentile Hausdorff distance of 3.89 ± 1.96./12.199 ± 6.684. Pearson's correlation coefficient for volume correlation was 0.85 / 0.22 and -0.14 for extent of resection. Gross total resection was detected with a sensitivity of 66.67% and specificity of 36.36%.

CONCLUSIONS

Our volumetry pipeline demonstrated its ability to accurately segment pituitary adenomas. This is highly valuable for lesion detection and evaluation of progression of pituitary incidentalomas. Postoperatively, however, objective and precise detection of residual tumor remains less successful. Larger datasets, more diverse data, and more elaborate modeling could potentially improve performance.

Chlorpromazine affects glioblastoma bioenergetics by interfering with pyruvate kinase M2

Glioblastoma (GBM) is the most frequent and lethal brain tumor, whose therapeutic outcome - only partially effective with current schemes - places this disease among the unmet medical needs, and effective therapeutic approaches are urgently required. In our attempts to identify repositionable drugs in glioblastoma therapy, we identified the neuroleptic drug chlorpromazine (CPZ) as a very promising compound. Here we aimed to further unveil the mode of action of this drug. We performed a supervised recognition of the signal transduction pathways potentially influenced by CPZ via Reverse-Phase Protein microArrays (RPPA) and carried out an Activity-Based Protein Profiling (ABPP) followed by Mass Spectrometry (MS) analysis to possibly identify cellular factors targeted by the drug. Indeed, the glycolytic enzyme PKM2 was identified as one of the major targets of CPZ. Furthermore, using the Seahorse platform, we analyzed the bioenergetics changes induced by the drug. Consistent with the ability of CPZ to target PKM2, we detected relevant changes in GBM energy metabolism, possibly attributable to the drug's ability to inhibit the oncogenic properties of PKM2. RPE-1 non-cancer neuroepithelial cells appeared less responsive to the drug. PKM2 silencing reduced the effects of CPZ. 3D modeling showed that CPZ interacts with PKM2 tetramer in the same region involved in binding other known activators. The effect of CPZ can be epitomized as an inhibition of the Warburg effect and thus malignancy in GBM cells, while sparing RPE-1 cells. These preclinical data enforce the rationale that allowed us to investigate the role of CPZ in GBM treatment in a recent multicenter Phase II clinical trial.

Engineered exosomes: a promising vehicle in cancer therapy

During the past few decades, researchers have attempted to discover an effective treatment for cancer. Exosomes are natural nanovesicles released by various cells and play a role in communication between cells. While natural exosomes have high clinical potential, their inherent limitations have prompted researchers to design exosomes with improved therapeutic properties. To achieve this purpose, researchers have undertaken exosome engineering to modify the surface properties or internal composition of exosomes. After these modifications, engineered exosomes can be used as carriers for delivery of chemotherapeutic agents, targeted drug delivery or development of cancer vaccines. The present study provides an overview of exosomes, including their biogenesis, biological functions, isolation techniques, engineering methods, and potential applications in cancer therapy.

Current and Future Perspectives of Microscopic and Endoscopic Transsphenoidal Surgery for Pituitary Adenomas: A Narrative Review

Transsphenoidal resection remains the standard treatment for most pituitary adenomas. However, the ideal surgical approach to safely access these lesions, either microsurgical or endoscopic, continues to be debated. Since the introduction of endoscopic transsphenoidal surgery, centers around the world have increasingly adopted this technique, experiencing a shift away from the conventional microsurgical approach. Large series reporting the efficacy and safety of endoscopic surgery have fueled a growing interest in comparing clinical outcomes between both approaches. Still, proving superiority of either surgical approach remains an elusive task due to the inherent drawbacks of surgical observational studies, as we are still faced with a growing body of evidence reporting conflicting results. Thus, a comprehensive discussion regarding the reach and limitations of both techniques becomes necessary. In this narrative review, we perform a critical appraisal of the literature and provide an expert opinion on the state-of-the-art in transsphenoidal surgery for pituitary adenomas. The advantages and limitations of each approach are assessed and compared from a technical standpoint, and their reported outcomes evaluated in the framework of this transition phase. Available evidence should be interpreted in light of individual patient characteristics and within the context of each medical center, taking into consideration the known impact that surgical expertise and multidisciplinary management hold on clinical outcomes.

Advances in oncolytic herpes simplex virus and adenovirus therapy for recurrent glioma

Recurrent glioma treatment is challenging due to molecular heterogeneity and treatment resistance commonly observed in these tumors. Researchers are actively pursuing new therapeutic strategies. Oncolytic viruses have emerged as a promising option. Oncolytic viruses selectively replicate within tumor cells, destroying them and stimulating the immune system for an enhanced anticancer response. Among Oncolytic viruses investigated for recurrent gliomas, oncolytic herpes simplex virus and oncolytic adenovirus show notable potential. Genetic modifications play a crucial role in optimizing their therapeutic efficacy. Different generations of replicative conditioned oncolytic human adenovirus and oncolytic HSV have been developed, incorporating specific modifications to enhance tumor selectivity, replication efficiency, and immune activation. This review article summarizes these genetic modifications, offering insights into the underlying mechanisms of Oncolytic viruses' therapy. It also aims to identify strategies for further enhancing the therapeutic benefits of Oncolytic viruses. However, it is important to acknowledge that additional research and clinical trials are necessary to establish the safety, efficacy, and optimal utilization of Oncolytic viruses in treating recurrent glioblastoma.

Co-occurrence of glioma and multiple sclerosis: Prevailing theories and emerging therapies

Though the concurrence of primary brain tumors and multiple sclerosis (MS) is exceedingly rare, instances have been noted in the literature as early as 1949. Given these observations, researchers have proposed various ideas as to how these malignancies may be linked to MS. Due to insufficient data, none have gained traction or been widely accepted amongst neurologists or neuro-oncologists. What is abundantly clear, however, is the mounting uncertainty faced by clinicians when caring for these individuals. Concerns persist about the potential for disease modifying therapies (DMTs) to initiate or promote tumor growth and progression, and to date, there are no approved treatments capable of mitigating both MS disease activity and tumor growth, let alone established guidelines that clinicians may refer to. Collectively, these gaps in the literature impose limitations to optimizing the care and management of this population. As such, our hope is to stimulate further discussion of this topic and prompt future investigations to explore novel treatment options and advance our understanding of these concurrent disease processes. To this end, the chief objective of this article is to evaluate proposed ideas of how the diseases may be linked, outline emerging therapies for both MS and brain tumors, and describe evidence-based approaches to diagnosing and treating this patient population.

The Mediating Effect of Uncertainty in Illness on Cancer Coping in Patients With Primary Malignant Brain Tumors

BACKGROUND

Patients with primary malignant brain tumors (PMBTs) experience uncertainty in illness (UI) because of the high recurrence rate and symptoms that occur during treatment.

OBJECTIVE

To develop and test a model based on the Uncertainty in Illness Theory to predict the UI and cancer coping experienced by PMBT patients.

METHODS

This was a cross-sectional study using path analysis. The participants were adults diagnosed with PMBT who completed a questionnaire about demographic and disease-related characteristics, UI, cancer coping, brain tumor symptoms, and social support. Clinical data (eg, the diagnosis, tumor location, and grade) were obtained from electronic health records. Data were analyzed using SPSS 26.0 and the MVN , psych , and lavaan packages in R 4.1.0.

RESULTS

This study included 203 PMBT patients. The hypothesized model satisfied all statistical criteria (comparative fit index = 0.998, root mean square error of approximation = 0.044, standardized root mean square residual = 0.016). The indirect and direct associations of UI in the path from social support to cancer coping were all significant with a 95% bootstrapping confidence interval. Although the indirect and direct associations of UI in the path of brain tumor symptoms and cancer coping did not have direct or total effects, the indirect effect was statistically significant.

CONCLUSIONS

Uncertainty in illness mediated brain tumor symptoms and social support to predict cancer coping.

IMPLICATIONS FOR PRACTICE

A nurse-led intervention for cancer coping among PMBT patients can be developed by considering symptoms and social support and UI as a mediator.