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Background: Cerebral syphilitic gumma is a rare intracranial infectious disorder. Without a clear history of syphilis and comprehensive serological examinations, it's challenging to diagnose it accurately prior to surgery through routine magnetic resonance imaging (MRI). Advanced neuroimaging techniques have been widely used in diagnosing brain tumors, yet there's limited report on their application in cerebral syphilitic gumma. This report presents a case of an elderly male patient with cerebral syphilitic gumma and analyzes its characteristics of advanced neuroimaging. Case presentation: A 68-year-old male patient was admitted to our institution presenting with bilateral hearing loss complicated with continuing headaches without obvious cause. Laboratory tests indicated positive treponema pallidum. Conventional MRI showed nodules closely related to the adjacent meninges in bilateral temporal lobes. The patient underwent surgical resection of the nodule in the right temporal lobe due to the mass effect and the final pathological diagnosis revealed cerebral syphilitic gumma. Conclusions: With the return of syphilis in recent years, accurate diagnosis of cerebral syphilitic gumma is a matter of great urgency. Advanced neuro-MRI can serve as a significant complement to conventional MRI examination. [ABSTRACT FROM AUTHOR]

Background and purpose: Stereotactic radiosurgery (SRS) of brain metastases (BM) and resection cavities is a widely used and effective treatment modality. Based on target lesion size and anatomical location, single fraction SRS (SF-SRS) or multiple fraction SRS (MF-SRS) are applied. Current clinical recommendations conditionally recommend either reduced dose SF-SRS or MF-SRS for medium-sized BM (2--2.9 cm in diameter). Despite excellent local control rates, SRS carries the risk of radionecrosis (RN). The purpose of this study was to assess the 12- months local control (LC) rate and 12-months RN rate of this specific patient population. Materials and methods: This single-center retrospective study included 54 patients with medium-sized intact BM (n=28) or resection cavities (n=30) treated with either SF-SRS or MF-SRS. Follow-up MRI was used to determine LC and RN using a modification of the "Brain Tumor Reporting and Data System" (BT-RADS) scoring system. Results: The 12-month LC rate following treatment of intact BM was 66.7% for SF-SRS and 60.0% for MF-SRS (p=1.000). For resection cavities, the 12-month LC rate was 92.9%% after SF-SRS and 46.2% after MF-SRS (p=0.013). For intact BM, RN rate was 17.6% for SF-SRS and 20.0% for MF-SRS (p=1.000). For resection cavities, RN rate was 28.6% for SF-SRS and 20.0% for MF-SRS (p=1.000). Conclusion: Patients with intact BM showed no statistically significant differences in 12-months LC and RN rate following SF-SRS or MF-SRS. In patients with resection cavities the 12-months LC rate was significantly better following SF-SRS, with no increase in the RNFS. [ABSTRACT FROM AUTHOR]

Background: Meningioma is the most common primary brain tumor, with a clear preponderance in women. Obesity is considered a risk factor for the development of meningioma. Obesity is also the clinical hallmark of metabolic syndrome, characterized by glucose intolerance, dyslipidemia, and hypertension. Lifestyle and metabolic factors directly impact overweight and obesity and are therefore potential risk factors for meningioma development. The aim of this study is to assess lifestyle and metabolic factors for meningioma risk in women. Methods: The Cohort of Norway (CONOR) is a nationwide health survey, conducted between 1994 and 2003, including anthropometric measures, blood tests, and health questionnaires. Linkage to the National Cancer Registry enabled the identification of intracranial meningioma during follow-up until December 2018. Results: A total of 81,652 women were followed for a combined total of 1.5 million years, and 238 intracranial meningiomas were identified. Increasing levels of physical activity (HR 0.81; 95% CI 0.68-0.96; p trend <0.02) and parity (HR 0.83; 95% CI 0.71-0.97; p trend <0.03) were negatively associated with meningioma risk. Diabetes mellitus or glucose intolerance increased the risk for meningioma (HR 2.54; 95% CI 1.60-4.05). Overweight and obesity were not associated with meningioma risk, nor was metabolic syndrome. However, participants without metabolic dysfunction had a reduced meningioma risk, while participants with all five metabolic factors present had a 4-fold risk increase for meningioma (HR 4.28; 95% CI 1.34-13.68). Conclusion: Lifestyle factors seem to significantly influence meningioma risk. However, disentangling the complex associations and interactions between factors for meningioma risk will be a challenging task for future studies. [ABSTRACT FROM AUTHOR]

Brain tumor detection and segmentation from multi-parametric magnetic resonance (MR) scans are crucial for the prognosis and treatment planning of brain tumor patients in current clinical practice. With recent technological advancements, artificial intelligence-based deep learning has proven its indispensable image analysis capability in the most challenging tasks. This study proposes an automated WU-Net + + deep learning model for brain tumor segmentation using multiparametric structural MR scans obtained from the BraTS 2018 dataset. The model was validated through cross-dataset testing for intracranial hemorrhage (ICH) classification (ATLAS V2.1 dataset) and multi-organ segmentation from abdominal images of TCIA and BTCV datasets. The WU-Net++ model, a novel version of U-Net, was developed by adjusting its pooling operation as a weighted function of max and average pooling for brain tumor segmentation. The proposed model (WU-Net + +) achieved an F1 score of 0.94 ± 0.124, a dice score of 0.91 ± 0.132, and an AUC value of 0.915 for whole tumor segmentation. The model also achieved a high accuracy of 0.9949 ± 0.121 in ICH classification and dice scores of 0.912 ± 0.21, 0.844 ± 0.25, and 0.893 ± 0.17 for spleen, esophagus, and portal and splenic vein segmentation, respectively. Our study revealed that WU-Net + + has significant potential to improve the accuracy of segmentation and could be an effective method in the era of precision medicine. [ABSTRACT FROM AUTHOR]

Introduction: The literature lacks a concise neurocognitive test for assessing primary cognitive domains in neuro-oncological patients. This study aims to describe and assess the feasibility of the Ohy-Maldaun Fast Track Cognitive Test (OMFTCT), used to pre- and post-operatively evaluate patients undergoing brain tumor surgery in language eloquent areas. The cognitive diagnosis was used to safely guide intraoperative language assessment. Methods: This is a prospective longitudinal observational clinical study conducted on a cohort of 50 glioma patients eligible for awake craniotomies. The proposed protocol assesses multiple cognitive domains, including language, short-term verbal and visual memories, working memory, praxis, executive functions, and calculation ability. The protocol comprises 10 different subtests, with a maximum score of 50 points, and was applied at three time points: preoperative, immediately postoperative period, and 30 days after surgery. Results: Among the initial 50 patients enrolled, 36 underwent assessment at all three designated time points. The mean age of the patients was 45.3 years, and they presented an average of 15 years of education. The predominant tumor types included Glioblastoma, IDH-wt (44.1%), and diffuse astrocytoma, IDH-mutant (41.2%). The tumors were located in the left temporal lobe (27.8%), followed by the left frontal lobe (25%). The full test had an average application time of 23 min. Conclusion: OMFTCT provided pre- and postoperative assessments of different cognitive domains, enabling more accurate planning of intraoperative language testing. Additionally, recognition of post-operative cognitive impairments played a crucial role in optimizing patient care. [ABSTRACT FROM AUTHOR]

Background: The Hippo pathway is a conserved tumour suppressor signalling pathway, and its dysregulation is often associated with abnormal cell growth and tumorigenesis. We previously revealed that the transcriptional coactivator Yes-associated protein (YAP), the key effector of the Hippo pathway, is a molecular target for glioblastoma (GBM), the most common malignant brain tumour. Inhibiting YAP with small interfering RNA (siYAP) or the specific inhibitor verteporfin (VP) can diminish GBM growth to a certain degree. Results: In this study, to enhance the anti-GBM effect of siYAP and VP, we designed stepwise-targeting and hypoxia-responsive liposomes (AMVY@NPs), which encapsulate hypoxia-responsive polymetronidazole-coated VP and DOTAP adsorbed siYAP, with angiopep-2 (A2) modification on the surface. AMVY@NPs exhibited excellent blood‒brain barrier crossing, GBM targeting, and hypoxia-responsive and efficient siYAP and VP release properties. By inhibiting the expression and function of YAP, AMVY@NPs synergistically inhibited both the growth and stemness of GBM in vitro. Moreover, AMVY@NPs strongly inhibited the growth of orthotopic U87 xenografts and improved the survival of tumour-bearing mice without adverse effects. Conclusion: Specific targeting of YAP with stepwise-targeting and hypoxia-responsive liposome AMVY@NPs carrying siYAP and VP efficiently inhibited GBM progression. This study provides a valuable drug delivery platform and creative insights for molecular targeted treatment of GBM in the future. [ABSTRACT FROM AUTHOR]

Glioblastoma (GBM), an aggressive primary brain tumor originating from glial cells, poses significant treatment challenges due to its rapid growth and invasiveness. The exact mechanisms of GBM's brain damage remain unclear. This study examines primary molecular markers commonly assessed in GBM patients, including brain‐derived neurotrophic factor (BDNF), platelet‐derived growth factor receptor A (PDGFRA), O6‐methylguanine DNA methyltransferase (MGMT), epidermal growth factor receptor (EGFR), and vascular endothelial growth factor A (VEGFA) using computational approaches. The study revealed significant differences (p ≤ 0.05) in PDGFRA, EGFR, and VEGFA expression rates, which are particularly interesting. Additionally, MGMT and VEGFA showed higher hazard ratios. Expression levels of MGMT and VEGFA were visualized in immune and malignant cells using single‐cell RNA datasets GSE103224 and GSE148842. From a total of 48 compounds in Gracilaria edulis and 86 in Gracilaria salicornia, we identified 15 compounds capable of crossing the blood‐brain barrier. Notably, 2‐tridecanone (binding affinity [BA] = −4.2 kcal/mol; root mean square deviation [RMSD] = 1.479 Å) and decanoic acid, ethyl ester (BA = −4.2 kcal/mol; RMSD = 1.702 Å) from G. edulis interacted with MGMT via hydrogen bonds. The compound alpha‐terpineol interacted with MGMT (BA = −5.7 kcal/mol; RMSD = 0.501 Å) and VEGFA (BA = −4.7 kcal/mol; RMSD = 2.483 Å). Ethanolic and methanolic extracts from G. edulis and G. salicornia demonstrated mild anti‐cell proliferation properties in the GBM LN‐229 cell line, suggesting potential therapeutic benefits. This study highlights the significance of molecular markers and natural compounds in understanding and potentially treating GBM. [ABSTRACT FROM AUTHOR]

Background: This study aimed to develop a novel positron emission tomography (PET) tracer, [68Ga]Ga-TD-01, for CXCR4 imaging. To achieve this goal, the molecular scaffold of TIQ15 was tuned by conjugation with the DOTA chelator to make it suitable for 68Ga radiolabeling. Methods: A bifunctional chelator was prepared by conjugating the amine group of TIQ15 with p-NCS-Bz-DOTA, yielding TD-01, with a high yield (68.92%). TD-01 was then radiolabeled with 68Ga using 0.1 M ammonium acetate at 60 °C for 10 min. A 1-h dynamic small animal PET/MRI study of the labeled compound in GL261-luc2 tumor-bearing mice was performed, and brain tumor uptake was assessed. Blocking studies involved pre-administration of TIQ15 (10 mg/kg) 10 min before the PET procedure started. Results: [68Ga]Ga-TD-01 exhibited a radiochemical yield (RCY) of 36.33 ± 1.50% (EOS), with a radiochemical purity > 99% and a molar activity of 55.79 ± 1.96 GBq/µmol (EOS). The radiotracer showed in vitro stability in PBS and human plasma for over 4 h. Biodistribution studies in healthy animals revealed favorable kinetics for subsequent PET pharmacokinetic modeling with low uptake in the brain and moderate uptake in lungs, intestines and spleen. Elimination could be assigned to a renal-hepatic pathway as showed by high uptake in kidneys, liver, and urinary bladder. Importantly, [68Ga]Ga-TD-01 uptake in glioblastoma (GBM)-bearing mice significantly decreased upon competition with TIQ15, with a baseline tumor-to-background ratios > 2.5 (20 min p.i.), indicating high specificity. Conclusion: The newly developed CXCR4 PET tracer, [68Ga]Ga-TD-01, exhibited a high binding inhibition for CXCR4, excellent in vitro stability, and favorable pharmacokinetics, suggesting that the compound is a promising candidate for full in vivo characterization of CXCR4 expression in GBM, with potential for further development as a tool in cancer diagnosis. [ABSTRACT FROM AUTHOR]

MR-guided Laser Interstitial Thermal Therapy (MRgLITT) is a minimally invasive neurosurgical technique increasingly used for the treatment of drug-resistant epilepsy and brain tumors. Utilizing near-infrared light energy delivery guided by real-time MRI thermometry, MRgLITT enables precise ablation of targeted brain tissues, resulting in limited corridor-related morbidity and expedited postoperative recovery. Since receiving CE marking in 2018, the adoption of MRgLITT has expanded to more than 40 neurosurgical centers across Europe. In epilepsy treatment, MRgLITT can be applied to various types of focal lesional epilepsy, including mesial temporal lobe epilepsy, hypothalamic hamartoma, focal cortical dysplasias, periventricular heterotopias, cavernous malformations, dysembryoplastic neuroepithelial tumors (DNET), low-grade gliomas, tuberous sclerosis, and in disconnective surgeries. In neuro-oncology, MRgLITT is used for treating newly diagnosed and recurrent primary brain tumors, brain metastases, and radiation necrosis. This comprehensive review presents an overview of the current evidence and technical considerations for the use of MRgLITT in treating various pathologies associated with drug-resistant epilepsy and brain tumors. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Nowadays, segmentation and classification is most essential process to analyse the brain tumor disease. Moreover, Magnetic Resonance Imaging (MRI) scan images are used to helps the radiologist to diagnosis the tumor region using an efficient medical imaging techniques. In manual, it requires higher time to process each stage and image size is varied due to large amount of dataset. Several computer vision strategies are introduced in the literature for brain tumor segmentation and classification however, due to lower accuracy as well as ineffective decision making failed to provide the enhanced results. Therefore, this article develops the innovative hybrid Aquila coyote optimization algorithm is used to extract important elements that will be used in the classification process. Then, Deep Convolutional Neural Network (DCNN) classifier used as classification task while the weights are being modified and the suggested approach plays a significant role in improving the classification accuracy. With regard to the evaluation metrics, accuracy, sensitivity, and specificity, the suggested model's effectiveness is assessed. The performance is attained to be 97.3017%, 96.8194%, and 96.4079%, individually. This demonstrates how the suggested technique is better to those already in use for the efficient segmentation and categorization of brain tumours. [ABSTRACT FROM AUTHOR]

Background: Glioblastoma (GB) is recognized as one of the most aggressive brain tumors, with a median survival of 14.6 months. However, there are still some patients whose survival time was greater than 3 years, and the biological reasons behind this clinical phenomenon arouse our research interests. By conducting proteomic analysis on tumor tissues obtained from GB patients who survived over 3 years compared to those who survived less than 1 year, we identified a significant upregulation of SelK in patients with shorter survival times. Therefore, we hypothesized that SelK may be an important indicator related to the occurrence and progression of GBM. Methods: Proteomics and immunohistochemistry from GB patients were analyzed to investigate the correlation between SelK and clinical prognosis. Cellular phenotypes were evaluated by cell cycle analysis, cell viability assays, and xenograft models. Immunoblots and co-immunoprecipitation were conducted to verify SelK-mediated ubiquitin-dependent degradation of CDK4. Results: SelK was found to be significantly upregulated in GB samples from short-term survivors (≤ 1 year) compared to those from long-term survivors (≥ 3 years), and its expression levels were negatively correlated with clinical prognosis. Knocking down of SelK expression reduced GB cell viability, induced G0/G1 phase arrest, and impaired the growth of transplanted glioma cells in nude mice. Down-regulation of SelK-induced ER stress leads to a reduction in the expression of SKP2 and an up-regulation of β-TrCP1 expression. Up-regulation of β-TrCP1, thereby accelerating the ubiquitin-dependent degradation of CDK4 and ultimately inhibiting the malignant proliferation of the GB cells. Conclusion: This study discovered a significant increase in SelK expression in GB patients with poor prognosis, revealing a negative correlation between SelK expression and patient outcomes. Further mechanistic investigations revealed that SelK enhances the proliferation of GB cells by targeting the endoplasmic reticulum stress/SKP2/β-TrCP1/CDK4 axis. [ABSTRACT FROM AUTHOR]

Chromosome Region Maintenance 1 (CRM1), also known as Exportin 1 (XPO1), is a protein that is critical for transport of proteins and RNA to the cytoplasm through the nuclear pore complex. CRM1 inhibition with small molecule inhibitors is currently being studied in many cancers, including leukemias, solid organ malignancies and brain tumors. We review the structure of CRM1, its role in nuclear export, the current availability of CRM1 inhibitors, and the role of CRM1 in a number of distinct cellular processes. A deeper understanding of how CRM1 functions in nuclear export as well as other cellular processes may allow for the development of additional novel CRM1 inhibitors. [ABSTRACT FROM AUTHOR]

Background: Glioblastoma (GBM) is the most common brain tumor with the worst prognosis. Temozolomide is the only first-line drug for GBM. Unfortunately, the resistance issue is a classic problem. Therefore, it is essential to develop new drugs to treat GBM. As an oncogene, Skp2 is involved in the pathogenesis of various cancers including GBM. In this study, we investigated the anticancer effect of AAA237 on human glioblastoma cells and its underlying mechanism. Methods: CCK-8 assay was conducted to evaluate IC50 values of AAA237 at 48, and 72 h, respectively. The Cellular Thermal Shift Assay (CETSA) was employed to ascertain the status of Skp2 as an intrinsic target of AAA237 inside the cellular milieu. The EdU-DNA synthesis test, Soft-Agar assay and Matrigel assay were performed to check the suppressive effects of AAA237 on cell growth. To identify the migration and invasion ability of GBM cells, transwell assay was conducted. RT-qPCR and Western Blot were employed to verify the level of BNIP3. The mRFP-GFP-LC3 indicator system was utilized to assess alterations in autophagy flux and investigate the impact of AAA237 on the dynamic fusion process between autophagosomes and lysosomes. To investigate the effect of compound AAA237 on tumor growth in vivo, LN229 cells were injected into the brains of mice in an orthotopic model. Results: AAA237 could inhibit the growth of GBM cells in vitro. AAA237 could bind to Skp2 and inhibit Skp2 expression and the degradation of p21 and p27. In a dose-dependent manner, AAA237 demonstrated the ability to inhibit colony formation, migration, and invasion of GBM cells. AAA237 treatment could upregulate BNIP3 as the hub gene and therefore induce BNIP3-dependent autophagy through the mTOR pathway whereas 3-MA can somewhat reverse this process. In vivo, the administration of AAA237 effectively suppressed the development of glioma tumors with no side effects. Conclusion: Compound AAA237, a novel Skp2 inhibitor, inhibited colony formation, migration and invasion of GBM cells in a dose-dependent manner and time-dependent manner through upregulating BNIP3 as the hub gene and induced BNIP3-dependent autophagy through the mTOR pathway therefore it might be a viable therapeutic drug for the management of GBM. [ABSTRACT FROM AUTHOR]

Background: Glioblastoma, a high-grade primary brain cancer, has a median survival of approximately 14 months. Post-mortem brain donation provides insight to pathogenesis along with spatial and temporal heterogeneity. Post-mortem brain biobanking programs are increasing in number and the need to understand and improve the associated human experience is pressing. This study aims to qualitatively explore the experiences of next of kin (NOK) following the death and brain donation of a loved one and to understand the impact such programs have on NOK carers. Method: We interviewed 29 NOK following the death of their loved one and subsequent brain donation. Thematic analysis was conducted on the transcribed, qualitative interviews. Results: Four themes were identified; (1) Brain donation is a straightforward decision grounded in altruism and pragmatism; (2) Supporting donors is a source of comfort, pride and empowerment; (3) Brain donation can provide meaning for suffering and tragedy and (4) Perceptions of procedures and processes when supporting a loved one to donate. Insights into areas for improvement, for example transporting donors following a home death and the role of the body bag were also noted. Conclusion: Supporting a loved one to donate their brain can be a positive experience providing a source of hope, empowerment and purpose for NOK. Data indicating areas for consideration are broadly relevant for improving the delivery of brain donation programs for future donors and their loved ones. Plain language summary: Understanding how loved ones feel about someone close to them donating their brain to research after their death from brain cancer The act of donating brain tissue after death from brain cancer is a huge gift to medical research and may have an impact on the ability of the scientific community to improve outcomes for people diagnosed with brain cancers. While we understand how valuable these donations are for research, we need more work to understand how these donations impact the people who donate and those who love and support them. This paper explores the experiences of people who have lost someone to brain cancer who then went on to donate their brain tissue after their death. Through the use of interviews, it explores the impact that the donation has on a loved one or next of kin from providing a source of comfort, empowerment, pride or an alternative to 'senseless' suffering and tragedy. It also provides areas that should be considered by people who are facilitating brain donations to ensure that any potential, harm or upset can be minimized. [ABSTRACT FROM AUTHOR]

Glioblastoma is the most common and deadliest brain tumour in adults, with a median survival of 15 months under the current standard of care. Immunotherapies like immune checkpoint inhibitors and oncolytic viruses have been extensively studied to improve this endpoint. However, most thus far have failed. To improve the efficacy of immunotherapies to treat glioblastoma, new single-cell imaging modalities like imaging mass cytometry can be leveraged and integrated with computational models. This enables a better understanding of the tumour microenvironment and its role in treatment success or failure in this hard-to-treat tumour. Here, we implemented an agent-based model that allows for spatial predictions of combination chemotherapy, oncolytic virus, and immune checkpoint inhibitors against glioblastoma. We initialised our model with patient imaging mass cytometry data to predict patient-specific responses and found that oncolytic viruses drive combination treatment responses determined by intratumoral cell density. We found that tumours with higher tumour cell density responded better to treatment. When fixing the number of cancer cells, treatment efficacy was shown to be a function of CD4 + T cell and, to a lesser extent, of macrophage counts. Critically, our simulations show that care must be put into the integration of spatial data and agent-based models to effectively capture intratumoral dynamics. Together, this study emphasizes the use of predictive spatial modelling to better understand cancer immunotherapy treatment dynamics, while highlighting key factors to consider during model design and implementation. [ABSTRACT FROM AUTHOR]

The authors present the first reported case of MVNT in the thalamus in a 60-year-old man with a 20-year history of epilepsy and recent progressive neurological decline presented for neurosurgical evaluation for a non-enhancing mass predominantly in the right thalamus presumed to be a low-grade glioma. The tumor was subtotally resected using a left contralateral interhemispheric transcallosal approach. Histological and molecular assessment revealed an MVNT with MAPK pathway-activating mutation. The authors also conducted a systematic review of pathology-proven cases of MVNT to provide an up-to-date overview of the literature on the localization, presenting symptoms, and recurrence of this tumor. [ABSTRACT FROM AUTHOR]

Medulloblastoma (MB) stands as one of the prevalent malignant brain tumors among pediatric patients. Despite its prevalence, the intricate interplay between the regulatory program driving malignancy in MB cells and their interactions with the microenvironment remains insufficiently understood. Leveraging the capabilities of single‐cell Assay for Transposase‐Accessible Chromatin sequencing (scATAC‐seq), the chromatin accessibility landscape is unveiled across 59,015 distinct MB cells. This expansive dataset encompasses cells belonging to discrete molecular subgroups, namely SHH, WNT, Group3, and Group4. Within these chromatin accessibility profiles, specific regulatory elements tied to individual subgroups are uncovered, shedding light on the distinct activities of transcription factors (TFs) that likely orchestrate the tumorigenesis process. Moreover, it is found that certain neurotransmitter receptors (NTRs) are subgroup‐specific and can predict MB subgroup classification when combined with their associated transcription factors. Notably, targeting essential NTRs within tumors influences both the in vitro sphere‐forming capability and the in vivo tumorigenic capacity of MB cells. These findings collectively provide fresh insights into comprehending the regulatory networks and cellular dynamics within MBs. Furthermore, the significance of the TF‐NTR regulatory circuits is underscored as prospective biomarkers and viable therapeutic targets. [ABSTRACT FROM AUTHOR]

Background: Diagnosis with a brain tumor is a critical event in the lives of patients and their families due to poor medical prognoses and complex clinical care. Spiritual care interventions have been known to have meaningful effects in morbid diagnoses and palliative medicine, but their role in the neuro-oncologic patient's experience is poorly understood. This systematic review explores the role of spirituality and its relevance to patient care in the diverse setting of brain tumors. Methods: A comprehensive systematic review was conducted following PRISMA-SR guidelines. PUBMED was queried for studies on spirituality and neuro-oncology. Identified studies included RCTs, interviews, surveys, and case reports that examined spirituality in neuro-oncological clinical care, quality of life, and patient experience. Of 214 articles identified, 21 studies met the inclusion criteria, and the results were narratively synthesized. Results: Spirituality may play a significant role in mental well-being by reconciling existential questions faced by both patients and caregivers, and can serve as a valuable resource to improve mental well-being and reduce rates of palliative caregiver burnout. However, the paucity of studies examining the education and integration of spiritual awareness within the clinical literature warrants further study. Conclusions: While spiritual care interventions may improve the quality of life and mental wellness of patients and their caregivers, it is unclear how spiritual awareness and education should best be implemented. Further research is needed to better understand how key components of spiritual awareness can be integrated into medical education to deepen the patient–physician relationship and improve clinical experiences. [ABSTRACT FROM AUTHOR]

Glioblastoma multiforme (GBM) is a highly aggressive and fatal primary brain tumor. The resistance of GBM to conventional treatments is attributed to factors such as the blood–brain barrier, tumor heterogeneity, and treatment-resistant stem cells. Current therapeutic efforts show limited survival benefits, emphasizing the urgent need for novel treatments. In this context, natural anti-cancer extracts and especially animal venoms have garnered attention for their potential therapeutic benefits. Bee venom in general and that of the Middle Eastern bee, Apis mellifera syriaca in particular, has been shown to have cytotoxic effects on various cancer cell types, but not glioblastoma. Therefore, this study aimed to explore the potential of A. mellifera syriaca venom as a selective anti-cancer agent for glioblastoma through in vitro and in vivo studies. Our results revealed a strong cytotoxic effect of A. mellifera syriaca venom on U87 glioblastoma cells, with an IC50 of 14.32 µg/mL using the MTT test and an IC50 of 7.49 µg/mL using the LDH test. Cells treated with the bee venom became permeable to propidium iodide without showing any signs of early apoptosis, suggesting compromised membrane integrity but not early apoptosis. In these cells, poly (ADP-ribose) polymerase (PARP) underwent proteolytic cleavage similar to that seen in necrosis. Subsequent in vivo investigations demonstrated a significant reduction in the number of U87 cells in mice following bee venom injection, accompanied by a significant increase in cells expressing caspase-3, suggesting the occurrence of cellular apoptosis. These findings highlight the potential of A. mellifera syriaca venom as a therapeutically useful tool in the search for new drug candidates against glioblastoma and give insights into the molecular mechanism through which the venom acts on cancer cells. [ABSTRACT FROM AUTHOR]

Simple Summary: This review explores the emerging area of the therapeutic use of chimeric antigen receptor (CAR)-T cells in nervous tissue tumors. Through a detailed analysis of the existing literature, this paper highlights the most recent applications of CAR-T cells to the therapy of pediatric and adult nervous system neoplasia. Furthermore, it discusses the potential mechanisms underlying sensitivity or resistance to CAR-T cell-based therapies. Overall, this review underscores the importance of CAR-T cell therapies to the treatment of some nervous system tumors. Chimeric antigen receptor T cells (CAR-Ts) have shown a remarkable efficacy in hematological malignancies but limited responses in solid tumors. Among solid tumors, CAR-T cell therapy has been particularly explored in brain tumors. CAR-T cells have shown a limited clinical efficacy in various types of brain tumors due to several factors that have hampered their activity, including tumor antigen heterogeneity, the limited access of CAR-T cells to brain tumor cells, limited CAR-T cell trafficking and in vivo persistence and the presence of a highly immunosuppressive tumor microenvironment. Despite these considerations, some recent studies have shown promising antitumor activity of GD2-CAR-T cells on diffuse midline gliomas and neuroblastomas and of CARv3-TEAM-E cells in glioblastomas. However, strategies are required to improve the effect of CAR-T cells in brain tumors, including advanced CAR-T cell design with multiple antigenic targeting and incorporation of combination therapies. [ABSTRACT FROM AUTHOR]

Simple Summary: Conventional closed face masks (CFMs) are used in radiotherapy for head and neck cancer (HNC) and brain cancer (BC) but can cause discomfort and anxiety, affecting the patient experience. Recently, open-face masks (OFMs) have been introduced as an alternative. This study reviews and explores the application and use of OFMs in the treatment of HNC and BC, analyzing 19 relevant studies. The analysis shows heterogeneity in the type of OFMs used, especially in BC. In some cases, they are used alone, while in others, they are combined with complementary devices such as mouth bites. For both treatment sites, the review shows that OFMs, especially in combination with surface-guided radiotherapy (SGRT), offer significant advantages in terms of patient comfort and positioning accuracy. The results suggest that OFMs can achieve sub-millimeter and sub-degree reproducibility, which supports their clinical integration. Introduction: The main goal of radiotherapy (RT) is to deliver a precise dose to the target while sparing the surrounding normal tissue and minimizing side effects. Appropriate patient immobilization is crucial, especially for head and neck cancer (HNC) and Brain Cancer (BC). Conventional closed-face masks (CFMs), while effective in minimizing head motion, can cause significant discomfort, anxiety, and claustrophobia. Open-face masks (OFMs) have been developed to increase patient comfort while providing precise immobilization. Methods: Following the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) extension for scoping reviews and the Arskey and O'Malley framework, an electronic search of EMBASE, PubMed, SCOPUS, and Web of Science was conducted to identify original studies reporting the use and description of OFMs in clinical practice up to April 2024. The inclusion criteria were English-language articles focusing on OFMs for HNC and BC patients undergoing RT. Results: Of 618 titles, 19 articles fulfilled the selection criteria. Most studies were comparative (n = 13) or observational (n = 6). The articles were categorized by treatment site, resulting in three groups: BC (n = 14, 68.4%), HNC (n = 4, 21.4%), and mixed (n = 2, 10.5%), which includes both BC and HNC. Of note, 82.4% (n = 16) of the included studies were published from 2020 onwards, emphasizing the recent adoption of OFM in clinical practice. Conclusions: The reviewed studies show that OFMs, in combination with SGRT, offer significant advantages in terms of patient comfort and positioning accuracy in HNC and BC treatments. Reproducibility in the sub-millimeter and sub-degree range can be achieved, which supports the use of OFMs in clinical practice. Future research should explore innovative combinations of immobilization and monitoring to further improve RT outcomes and ensure precise treatment while increasing patient comfort. [ABSTRACT FROM AUTHOR]

Simple Summary: Glioblastoma is a highly aggressive type of brain tumor that is very difficult to treat, and surgery is crucial for improving patient survival. However, there are significant differences in access to brain tumor surgery based on factors like income, location, and available healthcare resources. People in low- and middle-income countries often struggle to receive the surgery they need due to a lack of specialized doctors, inadequate healthcare facilities, and financial challenges. As a result, patients in these regions are often diagnosed later, receive less effective treatment, and have lower survival rates compared to those in wealthier countries. This not only affects the patients but also adds economic and social burdens to their communities. The study calls for urgent actions to address these inequalities through international cooperation, better healthcare policies, and fair distribution of resources, with the goal of improving access to brain tumor surgeries for everyone, no matter where they live. Glioblastoma: a highly aggressive brain tumor, presents substantial challenges in treatment and management, with surgical intervention playing a pivotal role in improving patient outcomes. Disparities in access to brain tumor surgery arise from a multitude of factors, including socioeconomic status, geographical location, and healthcare resource allocation. Low- and middle-income countries (LMICs) often face significant barriers to accessing surgical services, such as shortages of specialized neurosurgical expertise, limited healthcare infrastructure, and financial constraints. Consequently, glioblastoma patients in LMICs experience delays in diagnosis, suboptimal treatment, and poorer clinical outcomes compared to patients in high-income countries (HICs). The clinical impact of these disparities is profound. Patients in LMICs are more likely to be diagnosed at advanced disease stages, receive less effective treatment, and have lower survival rates than their counterparts in HICs. Additionally, disparities in access to surgical care exacerbate economic and societal burdens, emphasizing the urgent need for targeted interventions and health policy reforms to address healthcare inequities. This review highlights the importance of addressing global disparities in access to brain tumor surgery for glioblastoma through collaborative efforts, policy advocacy, and resource allocation, aiming to improve outcomes and promote equity in surgical care delivery for all glioblastoma patients worldwide. [ABSTRACT FROM AUTHOR]

Simple Summary: This study explores the use of intraoperative magnetic resonance imaging (iMRI) in the surgical resection of brain metastases (BMs). The research aims to determine how iMRI can improve the precision of tumor removal, thereby enhancing patient outcomes. By providing real-time, high-resolution images during surgery, iMRI assists surgeons in achieving more complete tumor resection, potentially reducing recurrence rates and improving survival chances. Integrating iMRI into surgical protocols helps preserve neurological functions, especially for patients with BM in critical brain areas. This study highlights the safety and effectiveness of iMRI in neurosurgery and suggests its broader adoption for the better management of BMs. Intraoperative magnetic resonance imaging (iMRI) has witnessed significant growth in the field of neurosurgery, particularly in glioma surgery, enhancing image-guided neuronavigation and optimizing the extent of resection (EOR). Despite its extensive use in the treatment of gliomas, its utility in brain metastases (BMs) remains unexplored. This study examined the effect of iMRI on BM resection. This retrospective study was conducted at the neurosurgical center of the University Hospital of the Technical University of Munich and involved 25 patients with BM who underwent resection using 3-Tesla iMRI between 2018 and 2022. Volumetric measurements of the resected contrast-enhancing metastases were performed using preoperative, intraoperative, and postoperative MRI images. The Karnofsky Performance Score (KPS) and neurological status of the patients were assessed pre- and postoperatively. Local recurrence and in-brain progression were reported in patients who underwent follow-up MRI at 3 and 6 months postoperatively. In this cohort (n = 25, mean age 63.6 years), non-small-cell lung cancer (NSCLC) was the most common origin (28%). The mean surgical duration was 219.9 min, and that of iMRI was 61.7 min. Indications for iMRI were primarily associated with preoperative imaging, suggesting an unclear entity that is often suspicious for glioma. Gross total resection (GTR) was achieved in 21 patients (84%). Continued resection was pursued after iMRI in six cases (24%), resulting in an improved EOR of 100% in five cases and 97.6% in one case. Neurological status postoperatively remained stable in 60%, improved in 24%, and worsened in 16% of patients. No wound healing or postoperative complications were observed. Among the thirteen patients who underwent follow-up MRI 3 months postoperatively, one patient showed local recurrence at the site of resection, and seven patients showed in-brain progression. Of the eight patients who underwent a 6-month follow-up MRI, two showed local recurrence, while three exhibited in-brain progression. The observed favorable profiles of GTR, coupled with the notable absence of wound-healing problems and acute postoperative complications, affirm the safety and feasibility of incorporating iMRI into the neurosurgical workflow for resecting BM with specific indications. The real-time imaging capabilities of iMRI offer unparalleled precision, aiding meticulous tumor delineation and informed decision-making, ultimately contributing to improved patient outcomes. Although our experience suggests the potential benefits of iMRI as a safe tool for enhancing EOR, we acknowledge the need for larger prospective clinical trials. Comprehensive investigations on a broader scale are imperative to further elucidate the specific indications for iMRI in the context of BMs and to study its impact on survival. Rigorous prospective studies will refine our understanding of the clinical scenarios in which iMRI can maximize its impact, guiding neurosurgeons toward more informed and tailored decision-making. [ABSTRACT FROM AUTHOR]

Glioblastoma (GBM) is a primary CNS tumor that is highly lethal in adults and has limited treatment options. Despite advancements in understanding the GBM biology, the standard treatment for GBM has remained unchanged for more than a decade. Only 6.8% of patients survive beyond five years. Telomerase, particularly the hTERT promoter mutations present in up to 80% of GBM cases, represents a promising therapeutic target due to its role in sustaining telomere length and cancer cell proliferation. This review examines the biology of telomerase in GBM and explores potential telomerase-targeted therapies. We conducted a systematic review following the PRISMA-P guidelines in the MEDLINE/PubMed and Scopus databases, from January 1995 to April 2024. We searched for suitable articles by utilizing the terms "GBM", "high-grade gliomas", "hTERT" and "telomerase". We incorporated studies addressing telomerase-targeted therapies into GBM studies, excluding non-English articles, reviews, and meta-analyses. We evaluated a total of 777 records and 46 full texts, including 36 studies in the final review. Several compounds aimed at inhibiting hTERT transcription demonstrated promising preclinical outcomes; however, they were unsuccessful in clinical trials owing to intricate regulatory pathways and inadequate pharmacokinetics. Direct hTERT inhibitors encountered numerous obstacles, including a prolonged latency for telomere shortening and the activation of the alternative lengthening of telomeres (ALT). The G-quadruplex DNA stabilizers appeared to be potential indirect inhibitors, but further clinical studies are required. Imetelstat, the only telomerase inhibitor that has undergone clinical trials, has demonstrated efficacy in various cancers, but its efficacy in GBM has been limited. Telomerase-targeted therapies in GBM is challenging due to complex hTERT regulation and inadequate inhibitor pharmacokinetics. Our study demonstrates that, despite promising preclinical results, no Telomerase inhibitors have been approved for GBM, and clinical trials have been largely unsuccessful. Future strategies may include Telomerase-based vaccines and multi-target inhibitors, which may provide more effective treatments when combined with a better understanding of telomere dynamics and tumor biology. These treatments have the potential to be integrated with existing ones and to improve the outcomes for patients with GBM. [ABSTRACT FROM AUTHOR]

Demand for emergency neuroimaging is increasing. Even magnetic resonance imaging (MRI) is often performed outside office hours, sometimes revealing more uncommon entities like brain tumors. The scientific literature studying artificial intelligence (AI) methods for classifying brain tumors on imaging is growing, but knowledge about the radiologist's performance on this task is surprisingly scarce. Our study aimed to tentatively fill this knowledge gap. We hypothesized that the radiologist could classify intra-axial brain tumors at the emergency department with clinically acceptable accuracy. We retrospectively examined emergency brain MRI reports from 2013 to 2021, the inclusion criteria being (1) emergency brain MRI, (2) no previously known intra-axial brain tumor, and (3) suspicion of an intra-axial brain tumor on emergency MRI report. The tumor type suggestion and the final clinical diagnosis were pooled into groups: (1) glial tumors, (2) metastasis, (3) lymphoma, and (4) other tumors. The final study sample included 150 patients, of which 108 had histopathological tumor type confirmation. Among the patients with histopathological tumor type confirmation, the accuracy of the MRI reports in classifying the tumor type was 0.86 for gliomas against other tumor types, 0.89 for metastases, and 0.99 for lymphomas. We found the result encouraging, given the prolific need for emergency imaging. [ABSTRACT FROM AUTHOR]

Brain tumors are a leading cause of death globally, with numerous types varying in malignancy, and only 12% of adults diagnosed with brain cancer survive beyond five years. This research introduces a hyperparametric convolutional neural network (CNN) model to identify brain tumors, with significant practical implications. By fine-tuning the hyperparameters of the CNN model, we optimize feature extraction and systematically reduce model complexity, thereby enhancing the accuracy of brain tumor diagnosis. The critical hyperparameters include batch size, layer counts, learning rate, activation functions, pooling strategies, padding, and filter size. The hyperparameter-tuned CNN model was trained on three different brain MRI datasets available at Kaggle, producing outstanding performance scores, with an average value of 97% for accuracy, precision, recall, and F1-score. Our optimized model is effective, as demonstrated by our methodical comparisons with state-of-the-art approaches. Our hyperparameter modifications enhanced the model performance and strengthened its capacity for generalization, giving medical practitioners a more accurate and effective tool for making crucial judgments regarding brain tumor diagnosis. Our model is a significant step in the right direction toward trustworthy and accurate medical diagnosis, with practical implications for improving patient outcomes. [ABSTRACT FROM AUTHOR]

Glioblastoma (GBM) is the most aggressive and common malignant and CNS tumor, accounting for 47.7% of total cases. Glioblastoma has an incidence rate of 3.21 cases per 100,000 people. The regulation of autophagy, a conserved cellular process involved in the degradation and recycling of cellular components, has been found to play an important role in GBM pathogenesis and response to therapy. Autophagy plays a dual role in promoting tumor survival and apoptosis, and here we discuss the complex interplay between autophagy and GBM. We summarize the mechanisms underlying autophagy dysregulation in GBM, including PI3K/AKT/mTOR signaling, which is most active in brain tumors, and EGFR and mutant EGFRvIII. We also review potential therapeutic strategies that target autophagy for the treatment of GBM, such as autophagy inhibitors used in combination with the standard of care, TMZ. We discuss our current understanding of how autophagy is involved in TMZ resistance and its role in glioblastoma development and survival. [ABSTRACT FROM AUTHOR]

Glioblastoma is the most common primary malignant brain tumour. Despite decades of intensive research in the disease, its prognosis remains poor, with an average survival of only 14 months after diagnosis. The remarkable level of intra‐ and interpatient heterogeneity is certainly contributing to the lack of progress in tackling this tumour. Epigenetic dysregulation plays an important role in glioblastoma biology and significantly contributes to intratumour heterogeneity. However, it is becoming increasingly clear that it also contributes to intertumour heterogeneity, which historically had mainly been linked to diverse genetic events occurring in different patients. In this review, we explore how DNA methylation, chromatin remodelling, microRNA (miRNA) dysregulation, and long noncoding RNA (lncRNA) alterations contribute to intertumour heterogeneity in glioblastoma, including its implications for advanced tumour stratification, which is the essential first step for developing more effective patient‐specific therapeutic approaches. [ABSTRACT FROM AUTHOR]

We present the case of a 34‐year‐old Japanese man with anaplastic lymphoma kinase (ALK)‐positive non‐small cell lung cancer and brain metastases. After central nervous system (CNS) disease progression with alecintib and brigatinib, treatment with lorlatinib resulted in a good intracranial response. In this case, we investigated brain penetration ratio of brigatinib using cerebrospinal fluid and paired serum samples, and the ratio was 0.012. Further, we investigated resistance mechanisms via next‐generation sequencing (NGS) using lung biopsy at lung cancer diagnosis and brain biopsy sample at progressive disease of brigatinib. No apparent resistance mechanism of known ALK resistance, such as ALK mutations, amplifications, epithelial‐mesenchymal transition (EMT) and bypass pathway activation were detected. Taken together, we speculate that the low CNS penetration rate of brigatinib confers CNS progression. Further studies are warranted to reveal the resistance mechanism and propose a treatment strategy for CNS progression in ALK‐positive patients. [ABSTRACT FROM AUTHOR]

Glioblastoma (GBM) is the most aggressive and common type of malignant brain tumor diagnosed in adults. Preclinical immunocompetent mouse tumor models generated using mouse tumor cells play a pivotal role in testing the therapeutic efficacy of emerging immune-based therapies for GBMs. However, the clinical translatability of such studies is limited as mouse tumor lines do not fully recapitulate GBMs seen in inpatient settings. In this study, we generated three distinct, imageable human-GBM(hGBM)models in humanized mice using patientderived GBM cells that cover phenotypic and genetic GBM heterogeneity in primary (invasive and nodular) and recurrent tumors. We developed a pipeline to first enrich the tumor-initiating stem-like cells and then successfully established robust patient-derived GBMtumor engraftment and growth in bonemarrow-liverthymus (BLT) humanized mice. Multiplex immunofluorescence of GBM tumor sections revealed distinct phenotypic features of the patient GBM tumors, with myeloid cells dominating the immune landscape. Utilizing flow cytometry and correlative immunofluorescence, we profiled the immune microenvironment within the established human GBM tumors in the BLT mouse models and showed tumor infiltration of variable human immune cells, creating a unique immune landscape compared with lymphoid organs. These findings contribute substantially to our understanding of GBMbiologywithin the context of the human immune system in humanized mice and lay the groundwork for further translational studies aimed at advancing therapeutic strategies for GBM. [ABSTRACT FROM AUTHOR]

Despite major advances in molecular profiling and classification of primary brain tumors, personalized treatment remains limited for most patients. Here, we explored the feasibility of individual molecular profiling and the efficacy of biomarker-guided therapy for adult patients with primary brain cancers in the real-world setting within the molecular tumor board Freiburg, Germany. We analyzed genetic profiles, personalized treatment recommendations, and clinical outcomes of 102 patients with 21 brain tumor types. Alterations in the cell cycle, BRAF, and mTOR pathways most frequently led to personalized treatment recommendations. Molecularly informed therapies were recommended in 71% and implemented in 32% of patients with completed molecular diagnostics. The disease control rate following targeted treatment was 50% and the overall response rate was 30%, with a progression-free survival 2/1 ratio of at least 1.3 in 31% of patients. This study highlights the efficacy of molecularly guided treatment and the need for biomarker-stratified trials in brain cancers. [ABSTRACT FROM AUTHOR]

Deep learning models have been developed for various predictions in glioma; yet, they were constrained by manual segmentation, task-specific design, or a lack of biological interpretation. Herein, we aimed to develop an end-to-end multi-task deep learning (MDL) pipeline that can simultaneously predict molecular alterations and histological grade (auxiliary tasks), as well as prognosis (primary task) in gliomas. Further, we aimed to provide the biological mechanisms underlying the model's predictions. We collected multiscale data including baseline MRI images from 2776 glioma patients across two private (FAHZU and HPPH, n = 1931) and three public datasets (TCGA, n = 213; UCSF, n = 410; and EGD, n = 222). We trained and internally validated the MDL model using our private datasets, and externally validated it using the three public datasets. We used the model-predicted deep prognosis score (DPS) to stratify patients into low-DPS and high-DPS subtypes. Additionally, a radio-multiomics analysis was conducted to elucidate the biological basis of the DPS. In the external validation cohorts, the MDL model achieved average areas under the curve of 0.892–0.903, 0.710–0.894, and 0.850–0.879 for predicting IDH mutation status, 1p/19q co-deletion status, and tumor grade, respectively. Moreover, the MDL model yielded a C-index of 0.723 in the TCGA and 0.671 in the UCSF for the prediction of overall survival. The DPS exhibits significant correlations with activated oncogenic pathways, immune infiltration patterns, specific protein expression, DNA methylation, tumor mutation burden, and tumor-stroma ratio. Accordingly, our work presents an accurate and biologically meaningful tool for predicting molecular subtypes, tumor grade, and survival outcomes in gliomas, which provides personalized clinical decision-making in a global and non-invasive manner. [ABSTRACT FROM AUTHOR]

Introduction: Glioblastoma IDH-wildtype (GBM) is the most malignant brain tumor in adults, with a poor prognosis of approximately 15 months after diagnosis. Most patients suffer from a recurrence in <1 year, and this renders GBM a life-threatening challenge. Among molecular mechanisms driving GBM aggressiveness, angiogenesis mediated by GBM endothelial cells (GECs) deserves consideration as a therapeutic turning point. In this scenario, calpains, a family of ubiquitously expressed calcium-dependent cysteine proteases, emerged as promising targets to be investigated as a novel therapeutic strategy and prognostic tissue biomarkers. Methods: To explore this hypothesis, GECs were isolated from n=10 GBM biopsies and characterized phenotypically by immunofluorescence. The expression levels of calpains were evaluated by qRT-PCR and Western blot, and their association with patients' prognosis was estimated by Pearson correlation and Kaplan-Meier survival analysis. Calpain targeting efficacy was assessed by a time- and dose-dependent proliferation curve, MTT assay for viability, caspase-3/7 activity, migration and angiogenesis in vitro, and gene and protein expression level modification. Results: Immunofluorescence confirmed the endothelial phenotype of our primary GECs. A significant overexpression was observed for calpain-1/2/3 (CAPN) and calpain-small-subunits-1/2 (CAPNS1), whereas calpastatin gene, the calpain natural inhibitor, was reported to be downregulated. A significant negative correlation was observed between CAPN1/CAPNS1 and patient overall survival. GEC challenging revealed that the inhibition of calpain-1 exerts the strongest proapoptotic efficacy, so GEC mortality reached the 80%, confirmed by the increased activity of caspase-3/7. Functional assays revealed a strong affection of in vitro migration and angiogenesis. Gene and protein expression proved a downregulation of MAPK, VEGF/VEGFRs, and Bcl-2, and an upregulation of caspases and Bax-family mediators. Conclusion: Overall, the differential expression of calpains and their correlation with patient survival suggest a novel promising target pathway, whose blockade showed encouraging results toward precision medicine strategies. [ABSTRACT FROM AUTHOR]

Magnetic Resonance Imaging (MRI) is vital in diagnosing brain tumours, offering crucial insights into tumour morphology and precise localisation. Despite its pivotal role, accurately classifying brain tumours from MRI scans is inherently complex due to their heterogeneous characteristics. This study presents a novel integration of advanced segmentation methods with deep learning ensemble algorithms to enhance the classification accuracy of MRI-based brain tumour diagnosis. We conduct a thorough review of both traditional segmentation approaches and contemporary advancements in region-based and machine learning-driven segmentation techniques. This paper explores the utility of deep learning ensemble algorithms, capitalising on the diversity of model architectures to augment tumour classification accuracy and robustness. Through the synergistic amalgamation of sophisticated segmentation techniques and ensemble learning strategies, this research addresses the shortcomings of traditional methodologies, thereby facilitating more precise and efficient brain tumour classification. [ABSTRACT FROM AUTHOR]

Introduction: Glioblastoma, which affects a large number of patients every year and has an average overall lifespan of around 14.6 months following diagnosis stands out as the most lethal primary invasive brain tumor. Currently, surgery, radiation, and chemotherapy with temozolomide (TMZ) are the three major clinical treatment approaches. However, the ability to treat patients effectively is usually limited by TMZ resistance. Naringin, a bioflavonoid with anti-cancer, antioxidant, metal-chelating, and lipid-lowering effects, has emerged as a promising therapeutic option. Methods: To explore the targets and pathways of naringin and TMZ in glioblastoma network pharmacology, cell line-based ELISA, flow cytometry, immunocytochemistry, western blotting, and LC-HRMS based metabolomics study were used. Results: The findings through the network pharmacology suggested that the key targets of naringin in the chemosensitization of glioblastoma would be Poly [ADP-ribose] polymerase 1 (PARP-1), O-6-Methylguanine-DNA Methyltransferase (MGMT), and caspases. The functional enrichment analysis revealed that these targets were significantly enriched in important pathways such as p53 signaling, apoptosis, and DNA sensing. Further, the results of the in-vitro study in U87-MG and T98-G glioblastoma cells demonstrated that TMZ and naringin together significantly reduced the percentage of viability and inhibited the DNA repair enzymes PARP-1 and MGMT, and PI3K/AKT which led to chemosensitization and, in turn, induced apoptosis, which was indicated by increased p53, caspase-3 expression and decreased Bcl2 expression. Additionally, a metabolomics study in T98-G glioblastoma cells using liquid chromatography high-resolution mass spectrometry (LC-HRMS) revealed downregulation of C8-Carnitine (-2.79), L-Hexanoylcarnitine (-4.46), DLCarnitine (-2.46), Acetyl-L-carnitine (-3.12), Adenine (-1.3), Choline (-2.07), Propionylcarnitine (-1.69), Creatine (-1.33), Adenosine (-0.84), Spermine (-1.42), and upregulation of Palmitic Acid (+1.03) and Sphingosine (+0.89) in the naringin and TMZ treatment groups. Discussion: In conclusion, it can be said that naringin in combination with TMZ chemosensitized TMZ antiglioma response and induced apoptosis in tumor cells. [ABSTRACT FROM AUTHOR]

Glioblastoma (GBM) displays an infiltrative growth characteristic that recruits neighboring normal cells to facilitate tumor growth, maintenance, and invasion into the brain. While the blood-brain barrier serves as a critical natural defense mechanism for the central nervous system, GBM disrupts this barrier, resulting in the infiltration of macrophages from the peripheral bone marrow and the activation of resident microglia. Recent advancements in single-cell transcriptomics and spatial transcriptomics have refined the categorization of cells within the tumor microenvironment for precise identification. The intricate interactions and influences on cell growth within the tumor microenvironment under multi-omics conditions are succinctly outlined. The factors and mechanisms involving microglia, macrophages, endothelial cells, and T cells that impact the growth of GBM are individually examined. The collaborative mechanisms of tumor cell-immune cell interactions within the tumor microenvironment synergistically promote the growth, infiltration, and metastasis of gliomas, while also influencing the immune status and therapeutic response of the tumor microenvironment. As immunotherapy continues to progress, targeting the cells within the inter-tumor microenvironment emerges as a promising novel therapeutic approach for GBM. By comprehensively understanding and intervening in the intricate cellular interactions within the tumor microenvironment, novel therapeutic modalities may be developed to enhance treatment outcomes for patients with GBM. [ABSTRACT FROM AUTHOR]

Introduction: Primary central nervous system lymphoma (PCNSL) is a rare type of non-Hodgkin's lymphoma that affects brain parenchyma, eyes, cerebrospinal fluid, and spinal cord. Diagnosing PCNSL can be challenging because imaging studies often show similar patterns as other brain tumors, and stereotactic brain lesion biopsy conformation is invasive and not always possible. This study aimed to validate a previous proteomic profiling (PMID: 32610669) of cerebrospinal fluid (CSF) and develop a CSF-based proteomic panel for accurate PCNSL diagnosis and differentiation. Methods: CSF samples were collected from patients of 30 PCNSL, 30 other brain tumors, and 31 tumor-free/benign controls. Liquid chromatography tandemmass spectrometry targeted proteomics analysis was used to establish CSF-based proteomic panels. Results: Final proteomic panels were selected and optimized to diagnose PCNSL from tumor-free controls or other brain tumor lesions with an area under the curve (AUC) of 0.873 (95%CI: 0.723-0.948) and 0.937 (95%CI: 0.807- 0.985), respectively. Pathways analysis showed diagnosis panel features were significantly enriched in pathways related to extracellular matrices-receptor interaction, focal adhesion, and PI3K-Akt signaling, while prion disease, mineral absorption and HIF-1 signaling were significantly enriched with differentiation panel features. Discussion: This study suggests an accurate clinical test panel for PCNSL diagnosis and differentiation with CSF-based proteomic signatures, which may help overcome the challenges of current diagnostic methods and improve patient outcomes. [ABSTRACT FROM AUTHOR]

Glioblastoma (GB) is a lethal brain tumor that rapidly adapts to the dynamic changes of the tumor microenvironment (TME). Mesenchymal stem/stromal cells (MSCs) are one of the stromal components of the TME playing multiple roles in tumor progression. GB progression is prompted by the immunosuppressive microenvironment characterized by high concentrations of the nucleoside adenosine (ADO). ADO acts as a signaling molecule through adenosine receptors (ARs) but also as a genetic and metabolic regulator. Herein, the effects of high extracellular ADO concentrations were investigated in a human glioblastoma cellular model (U343MG) and MSCs. The modulation of the purinome machinery, i.e., the ADO production (CD39, CD73, and adenosine kinase [ADK]), transport (equilibrative nucleoside transporters 1 (ENT1) and 2 (ENT2)), and degradation (adenosine deaminase [ADA]) were investigated in both cell lines to evaluate if ADO could affect its cell management in a positive or negative feed‐back loop. Results evidenced a different behavior of GB and MSC cells upon exposure to high extracellular ADO levels: U343MG were less sensitive to the ADO concentration and only a slight increase in ADK and ENT1 was evidenced. Conversely, in MSCs, the high extracellular ADO levels reduced the ADK, ENT1, and ENT2 expression, which further sustained the increase of extracellular ADO. Of note, MSCs primed with the GB‐conditioned medium or co‐cultured with U343MG cells were not affected by the increase of extracellular ADO. These results evidenced how long exposure to ADO could produce different effects on cancer cells with respect to MSCs, revealing a negative feedback loop that can support the GB immunosuppressive microenvironment. These results improve the knowledge of the ADO role in the maintenance of TME, which should be considered in the development of therapeutic strategies targeting adenosine pathways as well as cell‐based strategies using MSCs. [ABSTRACT FROM AUTHOR]

Purpose: Brain metastases (BM) often leave residual tumors despite having visible margins, which increases the risk of local tumor recurrence and can impact overall patient survival rates. Fluorescence-guided surgery (FGS) utilizing sodium fluorescein (FL) has been reported as an effective technique in recent studies. This study aimed to evaluate the efficacy of FL FGS in improving the extent of resection of brain metastases and its impact on overall survival. Methods: We conducted a systematic search following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Our primary focus was on gross total resection (GTR). Additionally, we extracted survival data and evaluated the risk of bias using a modified version of the Joanna Briggs Institute critical appraisal tool. Results: The study comprised 970 patients with brain metastases through eight different studies. The study found that patients who underwent FL-guided resection had a significantly higher rate of GTR (OR: 2.02, 95% CI: 1.14–3.56, p = 0.0156, I2 = 41.5%). Additionally, the study concluded that FL-guided resection is associated with better overall survival rates (HR: 0.61, 95%CI: 0.47 0.80, p = 0.0003, I2 = 41.5%). Conclusion: Our research suggests that the use of FL is associated with a higher rate of GTR and improved overall patient survival. None of the studies we reviewed reported significant complications associated with the use of FL in patients. [ABSTRACT FROM AUTHOR]

Brainmetastatic cancer poses a significant clinical challenge, with limited treatment options and poor prognosis for patients. In recent years, immunotherapy has emerged as a promising strategy for addressing brain metastases, offering distinct advantages over conventional treatments. This review explores the evolving landscape of tumor immunotherapy in the context of brain metastatic cancer, focusing on the intricate interplay between the tumor microenvironment (TME) and immunotherapeutic approaches. By elucidating the complex interactions within the TME, including the role of immune cells, cytokines, and extracellular matrix components, this review highlights the potential of immunotherapy to reshape the treatment paradigm for brain metastases. Leveraging immune checkpoint inhibitors, cellular immunotherapies, and personalized treatment strategies, immunotherapy holds promise in overcoming the challenges posed by the blood-brain barrier and immunosuppressive microenvironment of brain metastases. Through a comprehensive analysis of current research findings and future directions, this review underscores the transformative impact of immunotherapy on the management of brain metastatic cancer, offering new insights and opportunities for personalized and precise therapeutic interventions. [ABSTRACT FROM AUTHOR]

Introduction: Brain diseases, particularly the classification of gliomas and brain metastases and the prediction of HT in strokes, pose significant challenges in healthcare. Existing methods, relying predominantly on clinical data or imaging-based techniques such as radiomics, often fall short in achieving satisfactory classification accuracy. These methods fail to adequately capture the nuanced features crucial for accurate diagnosis, often hindered by noise and the inability to integrate information across various scales. Methods: We propose a novel approach that mask attention mechanisms with multi-scale feature fusion for Multimodal brain disease classification tasks, termed M³, which aims to extract features highly relevant to the disease. The extracted features are then dimensionally reduced using Principal Component Analysis (PCA), followed by classification with a Support Vector Machine (SVM) to obtain the predictive results. Results: Our methodology underwent rigorous testing on multi-parametric MRI datasets for both brain tumors and strokes. The results demonstrate a significant improvement in addressing critical clinical challenges, including the classification of gliomas, brain metastases, and the prediction of hemorrhagic stroke transformations. Ablation studies further validate the effectiveness of our attention mechanism and feature fusion modules. Discussion: These findings underscore the potential of our approach to meet and exceed current clinical diagnostic demands, offering promising prospects for enhancing healthcare outcomes in the diagnosis and treatment of brain diseases. [ABSTRACT FROM AUTHOR]

The two types of craniopharyngioma, adamantinomatous (ACP) and papillary (PCP), are clinically relevant tumours in children and adults. Although the biology of primary craniopharyngioma is starting to be unravelled, little is known about the biology of recurrence. To fill this gap in knowledge, we have analysed through methylation array, RNA sequencing and pERK1/2 immunohistochemistry a cohort of paired primary and recurrent samples (32 samples from 14 cases of ACP and 4 cases of PCP). We show the presence of copy number alterations and clonal evolution across recurrence in 6 cases of ACP, and analysis of additional whole genome sequencing data from the Children's Brain Tumour Network confirms chromosomal arm copy number changes in at least 7/67 ACP cases. The activation of the MAPK/ERK pathway, a feature previously shown in primary ACP, is observed in all but one recurrent cases of ACP. The only ACP without MAPK activation is an aggressive case of recurrent malignant human craniopharyngioma harbouring a CTNNB1 mutation and loss of TP53. Providing support for a functional role of this TP53 mutation, we show that Trp53 loss in a murine model of ACP results in aggressive tumours and reduced mouse survival. Finally, we characterise the tumour immune infiltrate showing differences in the cellular composition and spatial distribution between ACP and PCP. Together, these analyses have revealed novel insights into recurrent craniopharyngioma and provided preclinical evidence supporting the evaluation of MAPK pathway inhibitors and immunomodulatory approaches in clinical trials in against recurrent ACP. [ABSTRACT FROM AUTHOR]

Cancer is a significant global health issue, with treatment challenges arising from intratumor heterogeneity. This heterogeneity stems mainly from somatic evolution, causing genetic diversity within the tumor, and phenotypic plasticity of tumor cells leading to reversible phenotypic changes. However, the interplay of both factors has not been rigorously investigated. Here, we examine the complex relationship between somatic evolution and phenotypic plasticity, explicitly focusing on the interplay between cell migration and proliferation. This type of phenotypic plasticity is essential in glioblastoma, the most aggressive form of brain tumor. We propose that somatic evolution alters the regulation of phenotypic plasticity in tumor cells, specifically the reaction to changes in the microenvironment. We study this hypothesis using a novel, spatially explicit model that tracks individual cells' phenotypic and genetic states. We assume cells change between migratory and proliferative states controlled by inherited and mutation-driven genotypes and the cells' microenvironment. We observe that cells at the tumor edge evolve to favor migration over proliferation and vice versa in the tumor bulk. Notably, different genetic configurations can result in this pattern of phenotypic heterogeneity. We analytically predict the outcome of the evolutionary process, showing that it depends on the tumor microenvironment. Synthetic tumors display varying levels of genetic and phenotypic heterogeneity, which we show are predictors of tumor recurrence time after treatment. Interestingly, higher phenotypic heterogeneity predicts poor treatment outcomes, unlike genetic heterogeneity. Our research offers a novel explanation for heterogeneous patterns of tumor recurrence in glioblastoma patients. Author summary: Intratumor heterogeneity presents a significant barrier to effective cancer therapy. This heterogeneity stems from the evolution of cancer cells and their capability for phenotypic plasticity. However, the interplay between these two factors still needs to be fully understood. This study examines the interaction between cancer cell evolution and phenotypic plasticity, focusing on the phenotypic switch between migration and proliferation. Such plasticity is particularly relevant to glioblastoma, the most aggressive form of brain tumor. By employing a novel model, we explore how tumor cell evolution, influenced by both genotype and microenvironment, contributes to tumor heterogeneity. We observe that cells at the tumor periphery tend to migrate, while those within the tumor are more inclined to proliferate. Interestingly, our analysis reveals that distinct genetic configurations of the tumor can lead to this observed pattern. Further, we delve into the implications for cancer treatment and discover that it is phenotypic, rather than genetic, heterogeneity that more accurately predicts tumor recurrence following therapy. Our findings offer insights into the significant variability observed in glioblastoma recurrence times post-treatment. [ABSTRACT FROM AUTHOR]

Background: Remifentanil, an ultra-short-acting µ-opioid receptor agonist, is commonly used for anesthetic management due to excellent adjustability. Remifentanil is known to cause sinus bradycardia, however, because it has a direct negative chronotropic effect on the cardiac conduction system and there is an indirect negative chronotropic effect via the parasympathetic nervous system. Case presentation: An 8-year-old Japanese boy was diagnosed with acute hydrocephalus due to a brain tumor in the fourth ventricle and underwent emergency surgery. Imaging examination showed brainstem compression. Endoscopic third ventriculostomy and ventriculoperitoneal shunt surgery were scheduled. Remifentanil was started during induction of general anesthesia, but electrocardiogram showed sinus bradycardia, then Wenckebach-type atrioventricular block, and then complete atrioventricular block. Remifentanil was immediately discontinued, and we administered atropine sulfate. Complete atrioventricular block was restored to sinus rhythm. When remifentanil was restarted, however, the electrocardiogram again showed sinus bradycardia, Wenckebach-type atrioventricular block, and then complete atrioventricular block. Remifentanil was again immediately discontinued, we administered adrenaline, and then complete atrioventricular block was restored to sinus rhythm. Fentanyl was used instead of remifentanil with continuous infusion of dopamine. There has since been no further occurrence of complete atrioventricular block. Conclusions: This is the first known case of complete atrioventricular block in a pediatric patient with increased intracranial pressure seemingly caused by administration of remifentanil. [ABSTRACT FROM AUTHOR]

Glioblastoma (GBM) is the most prevalent and aggressive malignant primary brain tumor. GBM proximal to the lateral ventricles (LVs) is more aggressive, potentially because of subventricular zone contact. Despite this, cross-talk between GBM and neural stem/progenitor cells (NSC/NPCs) is not well understood. Using cell-specific proteomics, we show that LV-proximal GBM prevents neuronal maturation of NSCs through induction of senescence. In addition, GBM brain tumor-initiating cells (BTICs) increase expression of cathepsin B (CTSB) upon interaction with NPCs. Lentiviral knockdown and recombinant protein experiments reveal that both cell-intrinsic and soluble CTSB promote malignancy-associated phenotypes in BTICs. Soluble CTSB stalls neuronal maturation in NPCs while promoting senescence, providing a link between LV-tumor proximity and neurogenesis disruption. Last, we show LV-proximal CTSB up-regulation in patients, showing the relevance of this cross-talk in human GBM biology. These results demonstrate the value of proteomic analysis in tumor microenvironment research and provide direction for new therapeutic strategies in GBM. [ABSTRACT FROM AUTHOR]

A fundamental computer vision task called semantic segmentation has significant uses in the understanding of medical pictures, including the segmentation of tumors in the brain. The G-Shaped Net architecture appears in this context as an innovative and promising design that combines components from many models to attain improved accuracy and efficiency. In order to improve efficiency, the G-Shaped Net architecture synergistically incorporates four fundamental components: the Self-Attention, Squeeze Excitation, Fusion, and Spatial Pyramid Pooling block structures. These factors work together to improve the precision and effectiveness of brain tumor segmentation. Self-Attention, a crucial component of G-Shaped architecture, gives the model the ability to concentrate on the image's most informative areas, enabling accurate localization of tumor boundaries. By adjusting channel-wise feature maps, Squeeze Excitation completes this by improving the model's capacity to capture fine-grained information in the medical pictures. Since the G-Shaped model's Spatial Pyramid Pooling component provides multi-scale contextual information, the model is capable of handling tumors of various sizes and complexity levels. Additionally, the Fusion block architectures combine characteristics from many sources, enabling a thorough comprehension of the image and improving the segmentation outcomes. The G-Shaped Net architecture is an asset for medical imaging and diagnostics and represents a substantial development in semantic segmentation, which is needed more and more for accurate brain tumor segmentation. [ABSTRACT FROM AUTHOR]

A study published in Acta Neuropathologica explores the relationship between chromosome 1p loss and the risk of recurrence in meningioma, a type of brain tumor. The researchers found that losses in chromosome 1p, particularly those exceeding 5%, were associated with an increased risk of recurrence. The study also suggests that even small losses in chromosome 1p may indicate chromosomal instability and increased tumor growth. The findings highlight the importance of considering 1p loss as a marker for increased risk in meningioma, with a proposed clinically relevant cut-off of 5%. [Extracted from the article]

Brain tumor is an extremely dangerous disease with a very high mortality rate worldwide. Detecting brain tumors accurately is crucial due to the varying appearance of tumor cells and the dimensional irregularities in their growth. This poses a significant challenge for detection algorithms. Currently, there are numerous algorithms utilized for this purpose, ranging from transform-based methods to those rooted in machine learning techniques. These algorithms aim to enhance the accuracy of detection despite the complexities involved in identifying brain tumor cells. The major limitation of these algorithms is the mapping of extracted features of a brain tumor in the classification algorithms. To employ a combination of transform methods to extract texture feature from brain tumor images. This paper employs a combination of transform methods based on sub band decomposition for texture feature extraction from MRI scans, hybrid feature optimization methods using firefly and glow-worm algorithms for selection of feature, employment of MKSVM algorithm and stacking ensemble classifier for classification and application of the feature of fusion of different feature extraction methods. The algorithm under consideration has been put into practice using MATLAB, utilizing datasets from BRATS (Brain Tumor Segmentation) for the years 2013, 2015, and 2018. These datasets serve as the foundation for testing and validating the algorithm’s performance across different time periods, providing a comprehensive assessment of its effectiveness in detecting brain tumors. The proposed algorithm achieves maximum detection accuracy, detection sensitivity and specificity up to 98%, 99% and 99.5% respectively. The experimental outcomes showcase the efficiency of the algorithm in detection of brain tumor. The proposed work mainly contributes in brain tumor detection in the following aspects: a) use of combination of transform methods for texture feature extraction from MRI scans b) hybrid feature selection methods using firefly and glow-worm optimization algorithms for selection of feature c) employment of MKSVM algorithm and stacking ensemble classifier for classification and application of the feature of fusion of different feature extraction methods. [ABSTRACT FROM AUTHOR]

Brain tumors are abnormal cell growths inside the skull that damage brain cells needed for brain function. The complex structure of the human brain makes it challenging to identify and categorize brain tumors. Nevertheless, segmenting brain tumors in MRI images is difficult due to the wide variation in tumor size, location, and intensity. Specifically, we propose a method with four modules: (i) preprocessing; (ii) decomposition; (iii) segmentation; and (iv) classification—that together overcome these difficulties. Here, we first remove the noise from the MRI brain image using a partial differential equation. Those pre-processed images are fed into the contourlet transform which works on the principle of multiscale decomposition of images. The contourlet transform employs a double filter bank structure comprised of the Laplacian pyramid and a directional filter bank to obtain a sparse representation of the smooth contour of an image. These extracted bands are segmented using a novel Possibilistic Fuzzy C-Means clustering algorithm. Brain tissue portions are finally classified into white matter, grey matter, cerebrospinal fluid, edema, and tumor tissues using an Optimized Support Vector Machine whose parameters are optimally chosen using an Opposition-based Grey Wolf Optimization algorithm. The BraTS2021 and Figshare datasets were used to evaluate the proposed method in terms of sensitivity, specificity, accuracy, PPV, NPV, FPR, and FNR. According to the experimental findings, the proposed methodology is superior to the conventional methods. Overall, the analysis demonstrates that the proposed method is more effective than the alternatives. [ABSTRACT FROM AUTHOR]