Years of potential life lost for brain and CNS tumors relative to other cancers in adults in the United States, 2010

MEOX2 promotes glioma growth and temozolomide chemoresistance

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The Power of a Belief System: A Systematic Qualitative Synthesis of Spiritual Care for Patients with Brain Tumors

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.

Metabolic Plasticity of Glioblastoma Cells in Response to DHODH Inhibitor BAY2402234 Treatment

Glioblastoma (IDH-wildtype) represents a formidable challenge in oncology, lacking effective chemotherapeutic or biological interventions. The metabolic reprogramming of cancer cells is a hallmark of tumor progression and drug resistance, yet the role of metabolic reprogramming in glioblastoma during drug treatment remains poorly understood. The dihydroorotate dehydrogenase (DHODH) inhibitor BAY2402234 is a blood-brain barrier penetrant drug showing efficiency in in vivo models of many brain cancers. In this study, we investigated the effect of BAY2402234 in regulating the metabolic phenotype of EGFRWT and EGFRvIII patient-derived glioblastoma cell lines. Our findings reveal the selective cytotoxicity of BAY2402234 toward EGFRWT glioblastoma subtypes with minimal effect on EGFRvIII patient cells. At sublethal doses, BAY2402234 induces triglyceride synthesis at the expense of membrane lipid synthesis and fatty acid oxidation in EGFRWT glioblastoma cells, while these effects are not observed in EGFRvIII glioblastoma cells. Furthermore, BAY2402234 reduced the abundance of signaling lipid species in EGFRWT glioblastoma. This study elucidates genetic mutation-specific metabolic plasticity and efficacy in glioblastoma cells in response to drug treatment, offering insights into therapeutic avenues for precision medicine approaches.

Conventional extraction of fucoidan from Irish brown seaweed Fucus vesiculosus followed by ultrasound-assisted depolymerization

Fucoidan has attracted considerable attention from scientists and pharmaceutical companies due to its antioxidant, anticoagulant, anti-inflammatory, anti-tumor, and health-enhancing properties. However, the extraction of fucoidan from seaweeds often involves the use of harsh chemicals, which necessitates the search for alternative solvents. Additionally, the high viscosity and low cell permeability of high molecular weight (Mw) fucoidan can limit its effectiveness in drug action, while lower Mw fractions exhibit increased biological activity and are also utilized as dietary supplements. The study aimed to (1) extract fucoidan from the seaweed Fucus vesiculosus (FV) using an environmentally friendly solvent and compare it with the most commonly used extraction solvent, hydrochloric acid, and (2) assess the impact of ultrasound-assisted depolymerization on reducing the molecular weight of the fucoidan extracts and examine the cytotoxic effect of different molecular weight fractions. The findings indicated that the green depolymerization solvent, in conjunction with a brief ultrasound treatment, effectively reduced the molecular weight. Moreover, a significant decrease in cell viability was observed in selected samples, indicating potential anticancer properties. As a result, ultrasound was determined to be an effective method for depolymerizing crude fucoidan from Fucus Vesiculosus seaweed.

Disparities in Neuro-Oncology

PURPOSEOF REVIEW

Health disparities are preventable differences in the diagnosis, treatment, and outcomes of many diseases, including central nervous system (CNS) tumors. This review will summarize and compile the existing literature on health disparities in neuro-oncology and provide directions for future research and interventions.

RECENT FINDINGS

Patients from historically marginalized groups are more likely to receive inadequate treatment, develop complications, and experience a shorter life expectancy. Financial toxicity can be particularly severe for patients with CNS tumors due to the high costs of treatment. Additionally, CNS clinical trials and research lack diverse representation.

Methods behind oncolytic virus-based DC vaccines in cancer: Toward a multiphase combined treatment strategy for Glioblastoma (GBM) patients

Glioblastoma (GBM) remains an orphan cancer disease with poor outcome. Novel treatment strategies are needed. Immunotherapy has several modes of action. The addition of active specific immunotherapy with dendritic cell vaccines resulted in improved overall survival of patients. Integration of DC vaccination within the first-line combined treatment became a challenge, and immunogenic cell death immunotherapy during chemotherapy was introduced. We used a retrospective analysis using real world data to evaluate the complex combined treatment, which included individualized multimodal immunotherapy during and after standard of care, and which required adaptations during treatment, and found a further improvement of overall survival. We also discuss the use of real world data as evidence. Novel strategies to move the field of individualized multimodal immunotherapy forward for GBM patients are reviewed.

Glioma patient-reported outcomes: patients and clinicians

INTRODUCTION

Routine assessment of patient-reported outcomes (PROs) in oncology has shown to improve the quality of the delivered care and to prolong survival. However, for successful implementation of routine assessment of PROs, more knowledge on their usability in clinical practice is needed.

OBJECTIVE

This study aimed to cross-sectionally assess the perspective of patients and clinicians on the practicality of routinely measuring PROs in clinical practice for glioma patients.

METHODS

Semistructured interviews were conducted evaluating the role of healthcare professionals (HCP) in discussing results of PRO measures (PROMs), and the preferred topics, methods and frequency of PRO assessment. Glioma patients, their proxies and HCPs involved in the treatment of glioma patients from eight centres in the Netherlands were included.

RESULTS

Twenty-four patients, 16 proxies and 35 HCPs were interviewed. The majority of patients, proxies and HCPs (92%, 81% and 80%, respectively) were willing to discuss PRO results during consultations. Although HCPs prefer that results are discussed with the nurse specialist, only one-third of patients/proxies agreed. Functioning of daily life was considered important in all three groups. Most participants indicated that discussion of PROM results should take place during standard follow-up visits, and completed at home about 1 week in advance. On group level, there was no preference for administration of questionnaires on paper or digitally. Lastly, all centres had staff available to send questionnaires on paper.

CONCLUSION

This study shows that routine assessment of PROs is desired by patients, proxies and HCP's in neuro-oncological care in Dutch hospitals.

Racial and socioeconomic disparities in glioblastoma outcomes: A single-center, retrospective cohort study

BACKGROUND

Glioblastoma (GBM) is the most common malignant primary brain tumor. Emerging reports have suggested that racial and socioeconomic disparities influence the outcomes of patients with GBM. No studies to date have investigated these disparities controlling for isocitrate dehydrogenase (IDH) mutation and O-6-methylguanine-DNA methyltransferase (MGMT) status.

METHODS

Adult patients with GBM were retrospectively reviewed at a single institution from 2008 to 2019. Univariable and multivariable complete survival analyses were performed. A Cox proportional hazards model was used to assess the effect of race and socioeconomic status controlling for a priori selected variables with known relevance to survival.

RESULTS

In total, 995 patients met inclusion criteria. Of these, 117 patients (11.7%) were African American (AA). The median overall survival for the entire cohort was 14.23 months. In the multivariable model, AA patients had better survival compared with White patients (hazard ratio [HR], 0.37; 95% confidence interval [CI], 0.2-0.69). The observed survival difference was significant in both a complete case analysis model and a multiple imputations model accounting for missing molecular data and controlling for treatment and socioeconomic status. AA patients with low income (HR, 2.17; 95% CI, 1.04-4.50), public insurance (HR, 2.25; 95% CI, 1.04-4.87), or no insurance (HR, 15.63; 95% CI, 2.72-89.67) had worse survival compared with White patients with low income, public insurance, or no insurance, respectively.

CONCLUSIONS

Significant racial and socioeconomic disparities were identified after controlling for treatment, GBM genetic profile, and other variables associated with survival. Overall, AA patients demonstrated better survival. These findings may suggest the possibility of a protective genetic advantage in AA patients.

PLAIN LANGUAGE SUMMARY

To best personalize treatment for and understand the causes of glioblastoma, racial and socioeconomic influences must be examined. The authors report their experience at the O'Neal Comprehensive Cancer Center in the deep south. In this report, contemporary molecular diagnostic data are included. The authors conclude that there are significant racial and socioeconomic disparities that influence glioblastoma outcome and that African American patients do better.

Acrolein produced by glioma cells under hypoxia inhibits neutrophil AKT activity and suppresses anti-tumoral activities

Acrolein, which is the most reactive aldehyde, is a byproduct of lipid peroxidation in a hypoxic environment. Acrolein has been shown to form acrolein-cysteine bonds, resulting in functional changes in proteins and immune effector cell suppression. Neutrophils are the most abundant immune effector cells in circulation in humans. In the tumor microenvironment, proinflammatory tumor-associated neutrophils (TANs), which are termed N1 neutrophils, exert antitumor effects via the secretion of cytokines, while anti-inflammatory neutrophils (N2 neutrophils) support tumor growth. Glioma is characterized by significant tissue hypoxia, immune cell infiltration, and a highly immunosuppressive microenvironment. In glioma, neutrophils exert antitumor effects early in tumor development but gradually shift to a tumor-supporting role as the tumor develops. However, the mechanism of this anti-to protumoral switch in TANs remains unclear. In this study, we found that the production of acrolein in glioma cells under hypoxic conditions inhibited neutrophil activation and induced an anti-inflammatory phenotype by directly reacting with Cys310 of AKT and inhibiting AKT activity. A higher percentage of cells expressing acrolein adducts in tumor tissue are associated with poorer prognosis in glioblastoma patients. Furthermore, high-grade glioma patients have increased serum acrolein levels and impaired neutrophil functions. These results suggest that acrolein suppresses neutrophil function and contributes to the switch in the neutrophil phenotype in glioma.

Integrated clustering signature of genomic heterogeneity, stemness and tumor microenvironment predicts glioma prognosis and immunotherapy response

BACKGROUND

Glioma is the most frequent primary tumor of the central nervous system. The high heterogeneity of glioma tumors enables them to adapt to challenging environments, leading to resistance to treatment. Therefore, to detect the driving factors and improve the prognosis of glioma, it is essential to have a comprehensive understanding of the genomic heterogeneity, stemness, and immune microenvironment of glioma.

METHODS

We classified gliomas into various subtypes based on stemness, genomic heterogeneity, and immune microenvironment consensus clustering analysis. We identified risk hub genes linked to heterogeneous characteristics using WGCNA, LASSO, and multivariate Cox regression analysis and utilized them to create an effective risk model.

RESULTS

We thoroughly investigated the genomic heterogeneity, stemness, and immune microenvironment of glioma and identified the risk hub genes RAB42, SH2D4A, and GDF15 based on the TCGA dataset. We developed a risk model utilizing these genes that can reliably predict the prognosis of glioma patients. The risk signature showed a positive correlation with T cell exhaustion and increased infiltration of immunosuppressive cells, and a negative correlation with the response to immunotherapy. Moreover, we discovered that SH2D4A, one of the risk hub genes, could stimulate the migration and proliferation of glioma cells.

CONCLUSIONS

This study identified risk hub genes and established a risk model by analyzing the genomic heterogeneity, stemness, and immune microenvironment of glioma. Our findings will facilitate the diagnosis and prediction of glioma prognosis and may lead to potential treatment strategies for glioma.

MR-guided LITT therapy in patients with primary irresectable glioblastoma: a prospective, controlled pilot study

PURPOSE

Laser interstitial thermal therapy (LITT) is increasingly being used in the treatment of brain tumors, whereas high-quality evidence of its effectiveness is lacking. This pilot examined the feasibility of conducting a randomized controlled trial (RCT) in patients with irresectable newly diagnosed glioblastoma (nGBM), and generated data on technical feasibility and safety.

METHODS

We included patients with irresectable nGBM with KPS ≥ 70 and feasible trajectories to ablate ≥ 70% of the tumor volume. Patients were initially randomized to receive either biopsy combined with LITT or biopsy alone, followed by chemoradiation (CRT). Randomization was stopped after 9 patients as the feasibility endpoint with respect to willingness to be randomized was met. Main endpoints were feasibility of performing an RCT, technical feasibility of LITT and safety. Follow-up was 3 months.

RESULTS

A total of 15 patients were included, of which 10 patients received a biopsy followed by LITT and 5 patients a biopsy. Most patients were able to complete the follow-up procedures (93% clinical, 86% questionnaires, 78% MRI). Patients were planned within 3 weeks after consultation (median 12 days, range 8-16) and no delay was observed in referring patients for CRT (median 37 days, range 28-61). Two CD ≥ 3 complications occurred in the LITT arm and none in the biopsy arm.

CONCLUSION

An RCT to study the effectiveness of LITT in patients with an irresectable nGBM seems feasible with acceptable initial safety data. The findings from this pilot study helped to further refine the design of a larger full-scale multicenter RCT in the Netherlands. Protocol and study identifier: The current study is registered at clinicaltrials.gov (EMITT pilot study, NTR: NCT04596930).

Uncertainty quantification and attention-aware fusion guided multi-modal MR brain tumor segmentation

Brain tumor is one of the most aggressive cancers in the world, accurate brain tumor segmentation plays a critical role in clinical diagnosis and treatment planning. Although deep learning models have presented remarkable success in medical segmentation, they can only obtain the segmentation map without capturing the segmentation uncertainty. To achieve accurate and safe clinical results, it is necessary to produce extra uncertainty maps to assist the subsequent segmentation revision. To this end, we propose to exploit the uncertainty quantification in the deep learning model and apply it to multi-modal brain tumor segmentation. In addition, we develop an effective attention-aware multi-modal fusion method to learn the complimentary feature information from the multiple MR modalities. First, a multi-encoder-based 3D U-Net is proposed to obtain the initial segmentation results. Then, an estimated Bayesian model is presented to measure the uncertainty of the initial segmentation results. Finally, the obtained uncertainty maps are integrated into a deep learning-based segmentation network, serving as an additional constraint information to further refine the segmentation results. The proposed network is evaluated on publicly available BraTS 2018 and BraTS 2019 datasets. The experimental results demonstrate that the proposed method outperforms the previous state-of-the-art methods on Dice score, Hausdorff distance and Sensitivity metrics. Furthermore, the proposed components could be easily applied to other network architectures and other computer vision fields.

Understanding the activity of antibody-drug conjugates in primary and secondary brain tumours

Antibody-drug conjugates (ADCs), a class of targeted cancer therapeutics combining monoclonal antibodies with a cytotoxic payload via a chemical linker, have already been approved for the treatment of several cancer types, with extensive clinical development of novel constructs ongoing. Primary and secondary brain tumours are associated with high mortality and morbidity, necessitating novel treatment approaches. Pharmacotherapy of brain tumours can be limited by restricted drug delivery across the blood-brain or blood-tumour barrier, although data from phase II studies of the HER2-targeted ADC trastuzumab deruxtecan indicate clinically relevant intracranial activity in patients with brain metastases from HER2⁺ breast cancer. However, depatuxizumab mafodotin, an ADC targeting wild-type EGFR and EGFR variant III, did not provide a definitive overall survival benefit in patients with newly diagnosed or recurrent EGFR-amplified glioblastoma in phase II and III trials, despite objective radiological responses in some patients. In this Review, we summarize the available data on the central nervous system activity of ADCs from trials involving patients with primary and secondary brain tumours and discuss their clinical implications. Furthermore, we explore pharmacological determinants of intracranial activity and discuss the optimal design of clinical trials to facilitate development of ADCs for the treatment of gliomas and brain metastases.

Brain tumor detection and segmentation: Interactive framework with a visual interface and feedback facility for dynamically improved accuracy and trust

Brain cancers caused by malignant brain tumors are one of the most fatal cancer types with a low survival rate mostly due to the difficulties in early detection. Medical professionals therefore use various invasive and non-invasive methods for detecting and treating brain tumors at the earlier stages thus enabling early treatment. The main non-invasive methods for brain tumor diagnosis and assessment are brain imaging like computed tomography (CT), positron emission tomography (PET) and magnetic resonance imaging (MRI) scans. In this paper, the focus is on detection and segmentation of brain tumors from 2D and 3D brain MRIs. For this purpose, a complete automated system with a web application user interface is described which detects and segments brain tumors with more than 90% accuracy and Dice scores. The user can upload brain MRIs or can access brain images from hospital databases to check presence or absence of brain tumor, to check the existence of brain tumor from brain MRI features and to extract the tumor region precisely from the brain MRI using deep neural networks like CNN, U-Net and U-Net++. The web application also provides an option for entering feedbacks on the results of the detection and segmentation to allow healthcare professionals to add more precise information on the results that can be used to train the model for better future predictions and segmentations.

Homotypic Membrane-Enhanced Blood-Brain Barrier Crossing and Glioblastoma Targeting for Precise Surgical Resection and Photothermal Therapy

The crossing of blood-brain barrier (BBB) is essential for glioblastoma (GBM) therapy, and homotypic targeting is an effective strategy to achieve BBB crossing. In this work, GBM patient-derived tumor cell membrane (GBM-PDTCM) is prepared to cloak gold nanorods (AuNRs). Relying on the high homology of the GBM-PDTCM to the brain cell membrane, GBM-PDTCM@AuNRs realize efficient BBB crossing and selective GBM targeting. Meanwhile, owing to the functionalization of Raman reporter and lipophilic fluorophore, GBM-PDTCM@AuNRs are able to generate fluorescence and Raman signals at GBM lesion, and almost all tumor can be precisely resected in 15 min by the guidance of dual signals, ameliorating the surgical treatment for advanced GBM. In addition, photothermal therapy for orthotopic xenograft mice is accomplished by intravenous injection of GBM-PDTCM@AuNRs, doubling the median survival time of the mice, which improves the nonsurgical treatment for early GBM. Therefore, benefiting from homotypic membrane-enhanced BBB crossing and GBM targeting, all-stage GBM can be treated with GBM-PDTCM@AuNRs in distinct ways, providing an alternative idea for the therapy of tumor in the brain.

A literature survey of MR-based brain tumor segmentation with missing modalities

Multimodal MR brain tumor segmentation is one of the hottest issues in the community of medical image processing. However, acquiring the complete set of MR modalities is not always possible in clinical practice, due to the acquisition protocols, image corruption, scanner availability, scanning cost or allergies to certain contrast materials. The missing information can cause some restraints to brain tumor diagnosis, monitoring, treatment planning and prognosis. Thus, it is highly desirable to develop brain tumor segmentation methods to address the missing modalities problem. Based on the recent advancements, in this review, we provide a detailed analysis of the missing modality issue in MR-based brain tumor segmentation. First, we briefly introduce the biomedical background concerning brain tumor, MR imaging techniques, and the current challenges in brain tumor segmentation. Then, we provide a taxonomy of the state-of-the-art methods with five categories, namely, image synthesis-based method, latent feature space-based model, multi-source correlation-based method, knowledge distillation-based method, and domain adaptation-based method. In addition, the principles, architectures, benefits and limitations are elaborated in each method. Following that, the corresponding datasets and widely used evaluation metrics are described. Finally, we analyze the current challenges and provide a prospect for future development trends. This review aims to provide readers with a thorough knowledge of the recent contributions in the field of brain tumor segmentation with missing modalities and suggest potential future directions.

Mathematical Assessment of Machine Learning Models Used for Brain Tumor Diagnosis

The brain is an intrinsic and complicated component of human anatomy. It is a collection of connective tissues and nerve cells that regulate the principal actions of the entire body. Brain tumor cancer is a serious mortality factor and a highly intractable disease. Even though brain tumors are not considered a fundamental cause of cancer deaths worldwide, about 40% of other cancer types are metastasized to the brain and transform into brain tumors. Computer-aided devices for diagnosis through magnetic resonance imaging (MRI) have remained the gold standard for the diagnosis of brain tumors, but this conventional method has been greatly challenged with inefficiencies and drawbacks related to the late detection of brain tumors, high risk in biopsy procedures, and low specificity. To circumvent these underlying hurdles, machine learning models have recently been developed to enhance computer-aided diagnosis tools for advanced, precise, and automatic early detection of brain tumors. This study takes a novel approach to evaluate machine learning models (support vector machine (SVM), random forest (RF), gradient-boosting model (GBM), convolutional neural network (CNN), K-nearest neighbor (KNN), AlexNet, GoogLeNet, CNN VGG19, and CapsNet) used for the early detection and classification of brain tumors by deploying the multicriteria decision-making method called fuzzy preference ranking organization method for enrichment evaluations (PROMETHEE), based on selected parameters, in this study: prediction accuracy, precision, specificity, recall, processing time, and sensitivity. To validate the results of our proposed approach, we performed a sensitivity analysis and cross-checking analysis with the PROMETHEE model. The CNN model, with an outranking net flow of 0.0251, is considered the most favorable model for the early detection of brain tumors. The KNN model, with a net flow of -0.0154, is the least appealing option. The findings of this study support the applicability of the proposed approach for making optimal choices regarding the selection of machine learning models. The decision maker is thus afforded the opportunity to expand the range of considerations which they must rely on in selecting the preferred models for early detection of brain tumors.

The Economic Burden of Malignant Brain Tumors

Malignant brain tumors consist of primary malignant tumors and metastatic brain tumors. The global incidence and prevalence of CNS cancers are increasing, their mortality and morbidity are relatively higher than other cancers (e.g., bladder cancer), and the management of disease utilizes sophisticated and expensive diagnostic and therapeutic technology. Therefore, malignant brain tumors, both primary and metastatic, impose a significant economic burden on patients, their families, and healthcare systems all around the world. To the best of our knowledge, there is no comprehensive and global systematic review for examining the costs of brain tumors, though sporadic reports highlight the importance of the problem. Besides, each study takes place in a setting with different methods (e.g., different treatment methods) and costs to manage brain tumors; therefore, we are unable to compare the costs between countries. Nevertheless, the general patterns seem to suggest that, among all, gliomas and glioblastomas are the most financially burdensome types of malignant brain cancer. Finally, most of the available studies have examined the economic burden of all gliomas or only glioblastoma. Hence, we are left with a substantial gap in knowledge to understand the actual economic burden of metastatic brain tumors, and there is a need for further accurate and internationally comparable studies on the subject, particularly with a focus on indirect and intangible costs.

Integration of a personalised mobile health (mHealth) application into the care of patients with brain tumours: proof-of-concept study (IDEAL stage 1)

Objectives

Brain tumours lead to significant morbidity including a neurocognitive, physical and psychological burden of disease. The extent to which they impact the multiple domains of health is difficult to capture leading to a significant degree of unmet needs. Mobile health tools such as Vinehealth have the potential to identify and address these needs through real-world data generation and delivery of personalised educational material and therapies. We aimed to establish the feasibility of Vinehealth integration into brain tumour care, its ability to collect real-world and (electronic) patient-recorded outcome (ePRO) data, and subjective improvement in care.

Design

A mixed-methodology IDEAL stage 1 study.

Setting

A single tertiary care centre.

Participants

Six patients consented and four downloaded and engaged with the mHealth application throughout the 12 weeks of the study.

Main outcome measures

Over a 12-week period, we collected real-world and ePRO data via Vinehealth. We assessed qualitative feedback from mixed-methodology surveys and semistructured interviews at recruitment and after 2 weeks.

Results

565 data points were captured including, but not limited to: symptoms, activity, well-being and medication. EORTC QLQ-BN20 and EQ-5D-5L completion rates (54% and 46%) were impacted by technical issues; 100% completion rates were seen when ePROs were received. More brain cancer tumour-specific content was requested. All participants recommended the application and felt it improved care.

Conclusions

Our findings indicate value in an application to holistically support patients living with brain cancer tumours and established the feasibility and safety of further studies to more rigorously assess this.

A novel prognostic signature of cuproptosis-related genes and the prognostic value of FDX1 in gliomas

Background: Gliomas are the most common malignant tumors of the central nervous system, with extremely bad prognoses. Cuproptosis is a novel form of regulated cell death. The impact of cuproptosis-related genes on glioma development has not been reported. Methods: The TCGA, GTEx, and CGGA databases were used to retrieve transcriptomic expression data. We employed Cox's regressions to determine the associations between clinical factors and cuproptosis-related gene expression. Overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) were evaluated using the Kaplan-Meier method. We also used the least absolute shrinkage and selection operator (LASSO) regression technique. Results: The expression levels of all 10 CRGs varied considerably between glioma tumors and healthy tissues. In glioma patients, the levels of CDKN2A, FDX1, DLD, DLAT, LIAS, LIPT1, and PDHA1 were significantly associated with the OS, disease-specific survival, and progression-free interval. We used LASSO Cox's regression to create a prognostic model; the risk score was (0.882340) *FDX1 expression + (0.141089) *DLD expression + (-0.333875) *LIAS expression + (0.356469) *LIPT1 expression + (-0.123851) *PDHA1 expression. A high-risk score/signature was associated with poor OS (hazard ratio = 3.50, 95% confidence interval 2, -4.55, log-rank p < 0.001). Cox's regression revealed that the FDX1 level independently predicted prognosis; FDX1 may control immune cell infiltration of the tumor microenvironment. Conclusion: The CRG signature may be prognostic in glioma patients, and the FDX1 level may independently predict glioma prognosis. These data may afford new insights into treatment.

MicroRNA-based therapy for glioblastoma: Opportunities and challenges

Glioblastoma (GBM) is the most common and aggressive primary malignant brain tumor and is characterized by high mortality and morbidity rates and unpredictable clinical behavior. The disappointing prognosis for patients with GBM even after surgery and postoperative radiation and chemotherapy has fueled the search for specific targets to provide new insights into the development of modern therapies. MicroRNAs (miRNAs/miRs) act as oncomirs and tumor suppressors to posttranscriptionally regulate the expression of various genes and silence many target genes involved in cell proliferation, the cell cycle, apoptosis, invasion, stem cell behavior, angiogenesis, the microenvironment and chemo- and radiotherapy resistance, which makes them attractive candidates as prognostic biomarkers and therapeutic targets or agents to advance GBM therapeutics. However, one of the major challenges of successful miRNA-based therapy is the need for an effective and safe system to deliver therapeutic compounds to specific tumor cells or tissues in vivo, particularly systems that can cross the blood-brain barrier (BBB). This challenge has shifted gradually as progress has been achieved in identifying novel tumor-related miRNAs and their targets, as well as the development of nanoparticles (NPs) as new carriers to deliver therapeutic compounds. Here, we provide an up-to-date summary (in recent 5 years) of the current knowledge of GBM-related oncomirs, tumor suppressors and microenvironmental miRNAs, with a focus on their potential applications as prognostic biomarkers and therapeutic targets, as well as recent advances in the development of carriers for nontoxic miRNA-based therapy delivery systems and how they can be adapted for therapy.

Protocol for the Tessa Jowell BRAIN MATRIX Platform Study

INTRODUCTION

Gliomas are the most common primary tumour of the central nervous system (CNS), with an estimated annual incidence of 6.6 per 100 000 individuals in the USA and around 14 deaths per day from brain tumours in the UK. The genomic and biological landscape of brain tumours has been increasingly defined and, since 2016, the WHO classification of tumours of the CNS incorporates molecular data, along with morphology, to define tumour subtypes more accurately. The Tessa Jowell BRAIN MATRIX Platform (TJBM) study aims to create a transformative clinical research infrastructure that leverages UK National Health Service resources to support research that is patient centric and attractive to both academic and commercial investors.

METHODS AND ANALYSIS

The TJBM study is a programme of work with the principal purpose to improve the knowledge of glioma and treatment for patients with glioma. The programme includes a platform study and subsequent interventional clinical trials (as separate protocols). The platform study described here is the backbone data-repository of disease, treatment and outcome data from clinical, imaging and pathology data being collected in patients with glioma from secondary care hospitals. The primary outcome measure of the platform is time from biopsy to integrated histological-molecular diagnosis using whole-genome sequencing and epigenomic classification. Secondary outcome measures include those that are process centred, patient centred and framework based. Target recruitment for the study is 1000 patients with interim analyses at 100 and 500 patients.

ETHICS AND DISSEMINATION

The study will be performed in accordance with the recommendations guiding physicians in biomedical research involving human subjects, adopted by the 18th World Medical Association General Assembly, Helsinki, Finland and stated in the respective participating countries' laws governing human research, and Good Clinical Practice. The protocol was initially approved on 18 February 2020 by West Midlands - Edgbaston Research Ethics Committee; the current protocol (v3.0) was approved on 15 June 2022. Participants will be required to provide written informed consent. A meeting will be held after the end of the study to allow discussion of the main results among the collaborators prior to publication. The results of this study will be disseminated through national and international presentations and peer-reviewed publications. Manuscripts will be prepared by the Study Management Group and authorship will be determined by mutual agreement.

TRIAL REGISTRATION NUMBER

NCT04274283, 18-Feb-2020; ISRCTN14218060, 03-Feb-2020.

Exosome-based strategies for diagnosis and therapy of glioma cancer

Glioblastoma belongs to the most aggressive type of cancer with a low survival rate that is characterized by the ability in forming a highly immunosuppressive tumor microenvironment. Intercellular communication are created via exosomes in the tumor microenvironment through the transport of various biomolecules. They are primarily involved in tumor growth, differentiation, metastasis, and chemotherapy or radiation resistance. Recently several studies have highlighted the critical role of tumor-derived exosomes against immune cells. According to the structural and functional properties, exosomes could be essential instruments to gain a better molecular mechanism for tumor understanding. Additionally, they are qualified as diagnostic/prognostic markers and therapeutic tools for specific targeting of invasive tumor cells such as glioblastomas. Due to the strong dependency of exosome features on the original cells and their developmental status, it is essential to review their critical modulating molecules, clinical relevance to glioma, and associated signaling pathways. This review is a non-clinical study, as the possible role of exosomes and exosomal microRNAs in glioma cancer are reported. In addition, their content to overcome cancer resistance and their potential as diagnostic biomarkers are analyzed.

Reconfiguration from emergency to urgent elective neurosurgery for glioblastoma patients improves length of stay, surgical adjunct use and extent of resective surgery

Background

Glioblastoma (GB) is the most common intrinsic brain cancer and is notorious for its aggressive nature. Despite widespread research and optimization of clinical management, the improvement in overall survival has been limited. The aim of this study was to characterize the impact of service reconfiguration on GB outcomes in a single centre.

Methods

Patients with a histopathological confirmation of a diagnosis of GB between 01/01/2014 and 31/12/2019 were retrospectively identified. Demographic and tumour characteristics, survival, treatment (surgical and oncological), admission status, use of surgical adjunct (5-aminolevulinic acid, intra-operative neuro-monitoring), the length of stay, extent of resection, and surgical complications were recorded from the hospital databases.

Results

From August 2018 the neurosurgical oncology service was reconfigured to manage high-grade tumours on an urgent outpatient basis by surgeons specializing in oncology. We demonstrate that these changes resulted in an increase in elective admissions, greater use of intra-operative adjuncts resulting in the improved extent of tumour resection, and a reduction in median length of stay and associated cost-savings.

Conclusions

Optimizing neuro-oncology patient management through service reconfiguration resulted in increased use of intra-operative adjuncts, improved surgical outcomes, and reduced hospital costs. These changes also have the potential to improve survival and disease-free progression for patients with GB.

Triple branched RGD modification on liposomes: A prospective strategy to enhance the glioma targeting efficiency

Glioma, as one of the most common primary intracranial tumors, is in an urgent need for specific targeting agents. Multi-branched RGD ligand is a promising alternative for liposome functionalization which combines the benefits of high affinity with α_vβ₃ receptors and proper branching structure in response to the receptor clustering. Herein, we designed and synthesized single branched, double branched and triple branched RGD ligand (1RGD-Chol, 2RGD-Chol and 3RGD-Chol) respectively, which were then modified on the liposomes to prepare six different kinds of liposomes (including 1RGD-Lip, 2RGD-Lip, 3RGD-Lip, 2 × 1RGD-Lip, 3 × 1RGD-Lip and unmodified Lip). Subsequently, a series of assays were conducted. The results exhibited that the liposome decorated with 3RGD-Chol ligand possessed superior cellular internalization ability in C6 cells and bEnd.3 cells, suggesting the strongest ability of 3RGD-Lip to target the blood-brain barrier (BBB) and glioma cells. Besides, both the cytotoxicity and pro-apoptotic assays revealed that PTX-3RGD-Lip had the strongest ability to inhibit the survival of C6 cells. Moreover, the enrichment of liposomes at tumor site was 3RGD-Lip > 3 × 1RGD-Lip ≈ 2RGD-Lip ≈ 2 × 1RGD-Lip > 1RGD-Lip > Lip according to the in vivo imaging of C6-bearing mice, which was consistent with the result of in vitro targeting experiments. To sum up, the targeting efficiency of liposomes can be strongly promoted by improving the amount of targeting molecules, whereas the branching structure and spatial distance of RGD residues also accounted for the affinity between liposomes and α_vβ₃ receptors. Collectively, PTX-3RGD-Lip would be a prospective strategy in glioma treatment.

An artificial intelligence framework and its bias for brain tumor segmentation: A narrative review

BACKGROUND

Artificial intelligence (AI) has become a prominent technique for medical diagnosis and represents an essential role in detecting brain tumors. Although AI-based models are widely used in brain lesion segmentation (BLS), understanding their effectiveness is challenging due to their complexity and diversity. Several reviews on brain tumor segmentation are available, but none of them describe a link between the threats due to risk-of-bias (RoB) in AI and its architectures. In our review, we focused on linking RoB and different AI-based architectural Cluster in popular DL framework. Further, due to variance in these designs and input data types in medical imaging, it is necessary to present a narrative review considering all facets of BLS.

APPROACH

The proposed study uses a PRISMA strategy based on 75 relevant studies found by searching PubMed, Scopus, and Google Scholar. Based on the architectural evolution, DL studies were subsequently categorized into four classes: convolutional neural network (CNN)-based, encoder-decoder (ED)-based, transfer learning (TL)-based, and hybrid DL (HDL)-based architectures. These studies were then analyzed considering 32 AI attributes, with clusters including AI architecture, imaging modalities, hyper-parameters, performance evaluation metrics, and clinical evaluation. Then, after these studies were scored for all attributes, a composite score was computed, normalized, and ranked. Thereafter, a bias cutoff (AP(ai)Bias 1.0, AtheroPoint, Roseville, CA, USA) was established to detect low-, moderate- and high-bias studies.

CONCLUSION

The four classes of architectures, from best-to worst-performing, are TL > ED > CNN > HDL. ED-based models had the lowest AI bias for BLS. This study presents a set of three primary and six secondary recommendations for lowering the RoB.

Nanomedicine for brain cancer

CNS tumors remain among the deadliest forms of cancer, resisting conventional and new treatment approaches, with mortality rates staying practically unchanged over the past 30 years. One of the primary hurdles for treating these cancers is delivering drugs to the brain tumor site in therapeutic concentration, evading the blood-brain (tumor) barrier (BBB/BBTB). Supramolecular nanomedicines (NMs) are increasingly demonstrating noteworthy prospects for addressing these challenges utilizing their unique characteristics, such as improving the bioavailability of the payloadsviacontrolled pharmacokinetics and pharmacodynamics, BBB/BBTB crossing functions, superior distribution in the brain tumor site, and tumor-specific drug activation profiles. Here, we review NM-based brain tumor targeting approaches to demonstrate their applicability and translation potential from different perspectives. To this end, we provide a general overview of brain tumor and their treatments, the incidence of the BBB and BBTB, and their role on NM targeting, as well as the potential of NMs for promoting superior therapeutic effects. Additionally, we discuss critical issues of NMs and their clinical trials, aiming to bolster the potential clinical applications of NMs in treating these life-threatening diseases.

Noninvasive differentiation of molecular subtypes of adult non-enhancing glioma using MRI perfusion and diffusion parameters

Background

Nonenhancing glioma typically have a favorable outcome, but approximately 19–44% have a highly aggressive course due to a glioblastoma genetic profile. The aim of this retrospective study is to use physiological MRI parameters of both perfusion and diffusion to distinguish the molecular profiles of glioma without enhancement at presentation.

Methods

Ninety-nine patients with nonenhancing glioma were included, in whom molecular status (including 1p/19q codeletion status and IDH mutation) and preoperative MRI (T2w/FLAIR, dynamic susceptibility-weighted, and diffusion-weighted imaging) were available. Tumors were segmented semiautomatically using ITK-SNAP to derive whole tumor histograms of relative Cerebral Blood Volume (rCBV) and Apparent Diffusion Coefficient (ADC). Tumors were divided into three clinically relevant molecular profiles: IDH mutation (IDHmt) with (n = 40) or without (n = 41) 1p/19q codeletion, and (n = 18) IDH-wildtype (IDHwt). ANOVA, Kruskal-Wallis, and Chi-Square analyses were performed using SPSS.

Results

rCBV (mean, median, 75^th and 85^th percentile) and ADC (mean, median, 15^th and 25^th percentile) showed significant differences across molecular profiles (P < .01). Posthoc analyses revealed that IDHwt and IDHmt 1p/19q codeleted tumors showed significantly higher rCBV compared to IDHmt 1p/19q intact tumors: mean rCBV (mean, SD) 1.46 (0.59) and 1.35 (0.39) versus 1.08 (0.31), P < .05. Also, IDHwt tumors showed significantly lower ADC compared to IDHmt 1p/19q codeleted and IDHmt 1p/19q intact tumors: mean ADC (mean, SD) 1.13 (0.23) versus 1.27 (0.15) and 1.45 (0.20), P < .001).

Conclusions

A combination of low ADC and high rCBV, reflecting high cellularity and high perfusion respectively, separates IDHwt from in particular IDHmt 1p/19q intact glioma.

The Digital Brain Tumour Atlas, an open histopathology resource

Currently, approximately 150 different brain tumour types are defined by the WHO. Recent endeavours to exploit machine learning and deep learning methods for supporting more precise diagnostics based on the histological tumour appearance have been hampered by the relative paucity of accessible digital histopathological datasets. While freely available datasets are relatively common in many medical specialties such as radiology and genomic medicine, there is still an unmet need regarding histopathological data. Thus, we digitized a significant portion of a large dedicated brain tumour bank based at the Division of Neuropathology and Neurochemistry of the Medical University of Vienna, covering brain tumour cases from 1995-2019. A total of 3,115 slides of 126 brain tumour types (including 47 control tissue slides) have been scanned. Additionally, complementary clinical annotations have been collected for each case. In the present manuscript, we thoroughly discuss this unique dataset and make it publicly available for potential use cases in machine learning and digital image analysis, teaching and as a reference for external validation.

Synergy between TMZ and individualized multimodal immunotherapy to improve overall survival of IDH1 wild-type MGMT promoter-unmethylated GBM patients

The prognosis of IDH1 wild-type MGMT promoter-unmethylated GBM patients remains poor. Addition of Temozolomide (TMZ) to first-line local treatment shifted the median overall survival (OS) from 11.8 to 12.6 months. We retrospectively analyzed the value of individualized multimodal immunotherapy (IMI) to improve OS in these patients. All adults meeting the criteria and treated 06/2015-06/2021 were selected. Thirty-two patients (12f, 20m) had a median age of 47 y (range 18-69) and a KPI of 70 (50-100). Extent of resection was complete (11), <complete (12) or not documented (9). Seven patients were treated with surgery/radio(chemo)therapy and subsequent IMI (Group-1); 25 patients were treated with radiochemotherapy followed by maintenance TMZ plus IMI during and after TMZ (Group-2). Age, KPI and extent of resection were not different amongst both groups. The median OS of group-1 patients was 11 m (2 y OS: 0%). Surprisingly the median OS of group-2 patients was 22 m with 2 y OS of 36% (CI95%: 16-57), which was significantly (Log-rank: p = 0.0001) different from group-1. The data suggest that addition of IMI after local therapy on its own has no relevant effect on OS in these GBM patients, similar to maintenance TMZ. However, the combination of both TMZ + IMI significantly improved OS.

Death anxiety in patients with primary brain tumor: Measurement, prevalence, and determinants

OBJECTIVE

This study investigated death anxiety in patients with primary brain tumor (PBT). We examined the psychometric properties of two validated death anxiety measures and determined the prevalence and possible determinants of death anxiety in this often-overlooked population.

METHODS

Two cross-sectional studies in neuro-oncology were conducted. In Study 1, 81 patients with PBT completed psychological questionnaires, including the Templer Death Anxiety Scale (DAS). In Study 2, 109 patients with PBT completed similar questionnaires, including the Death and Dying Distress Scale (DADDS). Medical and disease-specific variables were collected across participants in both studies. Psychometric properties, including construct validity, internal consistency, and concurrent validity, were investigated. Levels of distress were analyzed using frequencies, and determinants of death anxiety were identified using logistic regression.

RESULTS

The DADDS was more psychometrically sound than the DAS in patients with PBT. Overall, 66% of PBT patients endorsed at least one symptom of distress about death and dying, with 48% experiencing moderate-severe death anxiety. Generalized anxiety symptoms and the fear of recurrence significantly predicted death anxiety.

SIGNIFICANCE OF RESULTS

The DADDS is a more appropriate instrument than the DAS to assess death anxiety in neuro-oncology. The proportion of patients with PBT who experience death anxiety appears to be higher than in other advanced cancer populations. Death anxiety is a highly distressing symptom, especially when coupled with generalized anxiety and fears of disease progression, which appears to be the case in patients with PBT. Our findings call for routine monitoring and the treatment of death anxiety in neuro-oncology.

Valproic Acid Enhanced Temozolomide-Induced Anticancer Activity in Human Glioma Through the p53-PUMA Apoptosis Pathway

Glioblastoma (GBM), the most lethal type of brain tumor in adults, has considerable cellular heterogeneity. The standard adjuvant chemotherapeutic agent for GBM, temozolomide (TMZ), has a modest response rate due to the development of drug resistance. Multiple studies have shown that valproic acid (VPA) can enhance GBM tumor control and prolong survival when given in conjunction with TMZ. However, the beneficial effect is variable. In this study, we analyzed the impact of VPA on GBM patient survival and its possible correlation with TMZ treatment and p53 gene mutation. In addition, the molecular mechanisms of TMZ in combination with VPA were examined using both p53 wild-type and p53 mutant human GBM cell lines. Our analysis of clinical data indicates that the survival benefit of a combined TMZ and VPA treatment in GBM patients is dependent on their p53 gene status. In cellular experiments, our results show that VPA enhanced the antineoplastic effect of TMZ by enhancing p53 activation and promoting the expression of its downstream pro-apoptotic protein, PUMA. Our study indicates that GBM patients with wild-type p53 may benefit from a combined TMZ+VPA treatment.

Ischemic Stroke Risk Among Adult Brain Tumor Survivors: Evidence to Guide Practice

ABSTRACT

INTRODUCTION: Primary brain tumors are the leading cause of cancer mortality in the United States affecting approximately 90,000 Americans each year. A major complication for brain tumor survivors is acute ischemic stroke (AIS). Currently, there are limited research to provide guidelines for AIS prevention and management in adult brain tumor survivors. The purpose of this review is to discuss the most common risk factors for AIS in adult brain tumor survivors along with best evidence for assessment, screening, and strategies to prevent AIS in this population. METHODS: Relevant literature was identified by searching CINAHL and PubMed databases using the following keywords: "brain tumor survivors," "adults," "stroke," "risk factors," "guidelines," "prevention," and "management". Articles not pertaining to adult brain tumor survivors and AIS were excluded. RESULTS: The location of the tumor, dose, extent, and type of radiation contribute to the development of vascular injury and subsequent carotid stenosis among brain tumor survivors. Endothelial growth factor inhibitor and chemotherapy drugs induces vascular remodeling. Other symptoms such as neurological impairments and co-morbidities are also present among brain tumor survivors. Furthermore, AIS increases from the time of primary brain tumor diagnosis and incidence further increases among patients who were diagnosed with a brain tumor as a child. CONCLUSION: Nurses play a key role in the assessment, prevention, and identifying individuals who are at risk of AIS during brain tumor survivorship. Engaging patients and their caregivers on minimizing their risks of AIS is crucial in the outpatient setting. Annual surveillance visits that include intracranial artery imaging should be used to identify individuals considered most at risk for developing AIS symptoms.

New strategies for managing adult gliomas

Gliomas are hard to treat. Their prognosis has improved little over the past few decades. Fundamental therapeutic challenges such as treatment resistance, malignant progression, and tumour recurrence persist. New strategies are needed to advance the management and treatment of gliomas. Here, we focus on where those new strategies could emerge. We consider how recent advances in our understanding of the biology of adult gliomas are informing new approaches to their treatment.

Machine learning for real-time optical property recovery in interstitial photodynamic therapy: a stimulation-based study

With the continued development of non-toxic photosensitizer drugs, interstitial photodynamic therapy (iPDT) is showing more favorable outcomes in recent clinical trials. IPDT planning is crucial to further increase the treatment efficacy. However, it remains a major challenge to generate a high-quality, patient-specific plan due to uncertainty in tissue optical properties (OPs), µ a and µ s . These parameters govern how light propagates inside tissues, and any deviation from the planning-assumed values during treatment could significantly affect the treatment outcome. In this work, we increase the robustness of iPDT against OP variations by using machine learning models to recover the patient-specific OPs from light dosimetry measurements and then re-optimizing the diffusers' optical powers to adapt to these OPs in real time. Simulations on virtual brain tumor models show that reoptimizing the power allocation with the recovered OPs significantly reduces uncertainty in the predicted light dosimetry for all tissues involved.

Brain cancer incidence: a comparison of active-duty military and general populations

BACKGROUND

In the USA, brain cancer disproportionately affects young adults. The US military has a younger age structure than the general population and may have differential exposures related to brain cancer. This study aimed to compare the incidence rates of brain cancer in the active-duty military and general populations to provide clues for future etiologic research. The rates between military service branches were also compared.

METHODS

The data for this study were from the Department of Defense's Automated Central Tumor Registry (ACTUR) and the National Cancer Institute's Surveillance, Epidemiology, and End Results 9 (SEER-9) registries. Age- and sex-adjusted incidence rates of malignant neuroepithelial brain cancer among adults 20-54 years of age from 1990-2013 were calculated and compared between the two populations, given as incidence rate ratios (IRRs) with 95% confidence intervals (CIs).

RESULTS

The age and sex-adjusted incidence rate for malignant neuroepithelial brain cancer was significantly lower in the active-duty population than in the US general population (IRR = 0.62, 95% CI,  0.56-0.68). The reduced incidence rate in the active-duty population was observed in men, all races, individuals 20-44 of age, and for all histological subtypes and time periods assessed. There were no significant differences in rates between the military service branches.

CONCLUSION

The incidence rates of neuroepithelial brain cancer were lower in the active-duty military population than the US general population. This study highlights the need for more research to enhance our understanding of variations in brain cancer incidence between these two populations.

Starlike polymer brush-based ultrasmall nanoparticles with simultaneously improved NIR-II fluorescence and blood circulation for efficient orthotopic glioblastoma imaging

Fluorescence imaging (FI) in the second near-infrared region (NIR-II, 1000-1700 nm) has attracted great attention for brain tumor imaging due to its deep penetration and high resolution. However, traditional NIR-II organic fluorescent nanoparticles (NPs) are usually hindered by uncontrolled large size (~30-100 nm), marked aggregation-caused quenching (ACQ) effect, and limited blood circulation (~1-3 h), which have great impact on efficient NIR-II FI of deep brain tumors. Herein, starlike polymer brush-based ultrasmall TQFP-10 NPs, with bright NIR-II fluorescence, prolonged blood circulation, and enhanced tumor accumulation, are facilely prepared for efficient orthotopic glioblastoma (GBM) imaging. Compared with traditional method prepared NPs (physically coated TQF@NPs and PEG modified TQF-PEG_5K NPs), the ultrasmall (~8 nm) TQFP-10 NPs display a higher NIR-II fluorescence QY (1.9%), which is 2.1- and 3.8-fold higher than TQF@NPs (0.9%) and TQF-PEG_5K NPs (0.5%), respectively. In addition, TQFP-10 NPs present a 10.6-fold higher blood circulation half-life (t_1/2 = 8.5 h) than that of TQF-PEG_5K NPs. Consequently, TQFP-10 NPs exhibit 4.2- and 33-fold higher maximal tumor to normal tissue ratio in subcutaneous and in situ NIR-II FI of GBM, respectively, than TQF@NPs and TQF-PEG_5K NPs, attractively realizing GBM imaging. This work provides a general strategy for constructing ultrasmall NIR-II fluorescent NPs with simultaneously improved NIR-II fluorescence and blood circulation for efficient brain tumor imaging.

Receptor-Interacting Protein 140 Enhanced Temozolomide-Induced Cellular Apoptosis Through Regulation of E2F1 in Human Glioma Cell Lines

Glioblastoma (GBM), a grade IV glioma, is responsible for the highest years of potential life lost among cancers. The poor prognosis is attributable to its high recurrence rate, caused in part by the development of resistance to chemotherapy. Receptor-interacting protein 140 (RIP140) is a very versatile coregulator of nuclear receptors and transcription factors. Although many of the pathways regulated by RIP140 contribute significantly to cancer progression, the function of RIP140 in GBM remains to be determined. In this study, we found that higher RIP140 expression was associated with prolonged survival in patients with newly diagnosed GBM. Intracellular RIP140 levels were increased after E2F1 activation following temozolomide (TMZ) treatment, which in turn modulated the expression of E2F1-targeted apoptosis-related genes. Overexpression of RIP140 reduced glioma cell proliferation and migration, induced cellular apoptosis, and sensitized GBM cells to TMZ. Conversely, knockdown of RIP140 increased TMZ resistance. Taken together, our results suggest that RIP140 prolongs the survival of patients with GBM both by inhibiting tumor cell proliferation and migration and by increasing cellular sensitivity to chemotherapy. This study helps improve our understanding of glioma recurrence and may facilitate the development of more effective treatments.

Male-Female Disparities in Years of Potential Life Lost Attributable to COVID-19 in the United States: A State-by-State Analysis

Males are at higher risk relative to females of severe outcomes following COVID-19 infection. Focusing on COVID-19-attributable mortality in the United States (U.S.), we quantify and contrast years of potential life lost (YPLL) attributable to COVID-19 by sex based on data from the U.S. National Center for Health Statistics as of 31 March 2021, specifically by contrasting male and female percentages of total YPLL with their respective percent population shares and calculating age-adjusted male-to-female YPLL rate ratios both nationally and for each of the 50 states and the District of Columbia. Using YPLL before age 75 to anchor comparisons between males and females and a novel Monte Carlo simulation procedure to perform estimation and uncertainty quantification, our results reveal a near-universal pattern across states of higher COVID-19-attributable YPLL among males compared to females. Furthermore, the disproportionately high COVID-19 mortality burden among males is generally more pronounced when measuring mortality in terms of YPLL compared to age-irrespective death counts, reflecting dual phenomena of males dying from COVID-19 at higher rates and at systematically younger ages relative to females. The U.S. COVID-19 epidemic also offers lessons underscoring the importance of a public health environment that recognizes sex-specific needs as well as different patterns in risk factors, health behaviors, and responses to interventions between men and women. Public health strategies incorporating focused efforts to increase COVID-19 vaccinations among men are particularly urged.

Meta-Analyses of Splicing and Expression Quantitative Trait Loci Identified Susceptibility Genes of Glioma

Background

The functions of most glioma risk alleles are unknown. Very few studies had evaluated expression quantitative trait loci (eQTL), and insights of susceptibility genes were limited due to scarcity of available brain tissues. Moreover, no prior study had examined the effect of glioma risk alleles on alternative RNA splicing.

Objective

This study explored splicing quantitative trait loci (sQTL) as molecular QTL and improved the power of QTL mapping through meta-analyses of both cis eQTL and sQTL.

Methods

We first evaluated eQTLs and sQTLs of the CommonMind Consortium (CMC) and Genotype-Tissue Expression Project (GTEx) using genotyping, or whole-genome sequencing and RNA-seq data. Alternative splicing events were characterized using an annotation-free method that detected intron excision events. Then, we conducted meta-analyses by pooling the eQTL and sQTL results of CMC and GTEx using the inverse variance-weighted model. Afterward, we integrated QTL meta-analysis results (Q < 0.05) with the Glioma International Case Control Study (GICC) GWAS meta-analysis (case:12,496, control:18,190), using a summary statistics-based mendelian randomization (SMR) method.

Results

Between CMC and GTEx, we combined the QTL data of 354 unique individuals of European ancestry. SMR analyses revealed 15 eQTLs in 11 loci and 32 sQTLs in 9 loci relevant to glioma risk. Two loci only harbored sQTLs (1q44 and 16p13.3). In seven loci, both eQTL and sQTL coexisted (2q33.3, 7p11.2, 11q23.3 15q24.2, 16p12.1, 20q13.33, and 22q13.1), but the target genes were different for five of these seven loci. Three eQTL loci (9p21.3, 20q13.33, and 22q13.1) and 4 sQTL loci (11q23.3, 16p13.3, 16q12.1, and 20q13.33) harbored multiple target genes. Eight target genes of sQTLs (C2orf80, SEC61G, TMEM25, PHLDB1, RP11-161M6.2, HEATR3, RTEL1-TNFRSF6B, and LIME1) had multiple alternatively spliced transcripts.

Conclusion

Our study revealed that the regulation of transcriptome by glioma risk alleles is complex, with the potential for eQTL and sQTL jointly affecting gliomagenesis in risk loci. QTLs of many loci involved multiple target genes, some of which were specific to alternative splicing. Therefore, quantitative trait loci that evaluate only total gene expression will miss many important target genes.

The Management of Brain Metastases-Systematic Review of Neurosurgical Aspects

The multidisciplinary management of patients with brain metastases (BM) consists of surgical resection, different radiation treatment modalities, cytotoxic chemotherapy, and targeted molecular treatment. This review presents the current state of neurosurgical technology applied to achieve maximal resection with minimal morbidity as a treatment paradigm in patients with BM. In addition, we discuss the contribution of neurosurgical resection on functional outcome, advanced systemic treatment strategies, and enhanced understanding of the tumor biology.

The GAUGAA Motif Is Responsible for the Binding between circSMARCA5 and SRSF1 and Related Downstream Effects on Glioblastoma Multiforme Cell Migration and Angiogenic Potential

Circular RNAs (circRNAs) are a large class of RNAs with regulatory functions within cells. We recently showed that circSMARCA5 is a tumor suppressor in glioblastoma multiforme (GBM) and acts as a decoy for Serine and Arginine Rich Splicing Factor 1 (SRSF1) through six predicted binding sites (BSs). Here we characterized RNA motifs functionally involved in the interaction between circSMARCA5 and SRSF1. Three different circSMARCA5 molecules (Mut1, Mut2, Mut3), each mutated in two predicted SRSF1 BSs at once, were obtained through PCR-based replacement of wild-type (WT) BS sequences and cloned in three independent pcDNA3 vectors. Mut1 significantly decreased its capability to interact with SRSF1 as compared to WT, based on the RNA immunoprecipitation assay. In silico analysis through the “Find Individual Motif Occurrences” (FIMO) algorithm showed GAUGAA as an experimentally validated SRSF1 binding motif significantly overrepresented within both predicted SRSF1 BSs mutated in Mut1 (q-value = 0.0011). U87MG and CAS-1, transfected with Mut1, significantly increased their migration with respect to controls transfected with WT, as revealed by the cell exclusion zone assay. Immortalized human brain microvascular endothelial cells (IM-HBMEC) exposed to conditioned medium (CM) harvested from U87MG and CAS-1 transfected with Mut1 significantly sprouted more than those treated with CM harvested from U87MG and CAS-1 transfected with WT, as shown by the tube formation assay. qRT-PCR showed that the intracellular pro- to anti-angiogenic Vascular Endothelial Growth Factor A (VEGFA) mRNA isoform ratio and the amount of total VEGFA mRNA secreted in CM significantly increased in Mut1-transfected CAS-1 as compared to controls transfected with WT. Our data suggest that GAUGAA is the RNA motif responsible for the interaction between circSMARCA5 and SRSF1 as well as for the circSMARCA5-mediated control of GBM cell migration and angiogenic potential.

Multicellular "hotspots" harbor high-grade potential in lower-grade gliomas

BACKGROUND

Lower-grade gliomas may be indolent for many years before developing malignant behavior. The mechanisms underlying malignant progression remain unclear.

METHODS

We collected blocks of live human brain tissue donated by people undergoing glioma resection. The tissue blocks extended through the peritumoral cortex and into the glioma. The living human brain tissue was cut into ex vivo brain slices and bathed in 5-aminolevulinic acid (5-ALA). High-grade glioma cells avidly take up 5-ALA and accumulate high levels of the fluorescent metabolite, Protoporphyrin IX (PpIX). We exploited the PpIX fluorescence emitted by higher-grade glioma cells to investigate the earliest stages of malignant progression in lower-grade gliomas.

RESULTS

We found sparsely distributed "hot-spots" of PpIX-positive cells in living lower-grade glioma tissue. Glioma cells and endothelial cells formed part of the PpIX hotspots. Glioma cells in PpIX hotspots were IDH1 mutant and expressed nestin suggesting they had acquired stem-like properties. Spatial analysis with 5-ALA-conjugated quantum dots indicated that these glioma cells replicated adjacent to blood vessels. PpIX hotspots were formed in the absence of angiogenesis.

CONCLUSION

Our data show that PpIX hotspots represent microdomains of cells with high-grade potential within lower-grade gliomas and identify locations where malignant progression could start.

Immuno-informatics analysis and expression of a novel multi-domain antigen as a vaccine candidate against glioblastoma

Glioblastoma multiform is the most common of primary malignant brain tumors in adults. Currently, surgical resection of the tumor mass, followed by adjuvant radiotherapy and chemotherapy are standard treatments for glioblastoma multiform but so far are not effective treatments. Thus, the development of a vaccine, as a safe and efficient strategy for prophylactic or therapeutic purposes against glioblastoma multiform is very necessary. The present study aimed to design the multi-domain vaccine for glioblastoma multiform. An in silico approach was used to select the most potent domains of proteins to induce the host's B- and T-cell immune response against glioblastoma multiform. IL-13Rα-2 (amino acid positions 27-144), TNC (amino acid positions 1900-2100), and PTPRZ-1(amino acid positions 731-884) were found to have potent inducible immune responses. So, we considered them for fusing with a linker A(EAAAK)₃A to construct the multi-domain recombinant vaccine. The immuno-informatics analysis of the designed recombinant vaccine construct was performed to evaluate its efficacy. Although the designed recombinant vaccine construct did not show allergen property, its antigenicity was estimated at 0.78. The Physico-chemical properties of the recombinant vaccine construct were characterized and revealed the potency of the vaccine candidate. Then its secondary and tertiary structures, mRNA structure, molecular docking, and immune simulation were predicted using bioinformatics tools. Next, the designed recombinant vaccine construct was synthesized, and cloned into the pET28a vector and expressed in E. coli BL21. Besides, the circular dichroism spectroscopy was utilized for the investigation of the secondary structure changes of the recombinant vaccine construct. The results of the verification assessment of the recombinant vaccine construct expression indicated that in silico analysis was relatively accurate, and relatively change occurred on the protein secondary structure. In our future plan, the vaccine candidate that was confirmed by in silico tools should be validated by further in vitro and in vivo experimental studies.

Randomized Controlled Immunotherapy Clinical Trials for GBM Challenged

Simple Summary

Although multiple meta-analyses on active specific immunotherapy treatment for glioblastoma multiforme (GBM) have demonstrated a significant prolongation of overall survival, no single research group has succeeded in demonstrating the efficacy of this type of treatment in a prospective, double-blind, placebo-controlled, randomized clinical trial. In this paper, we explain how the complexity of the tumor biology and tumor–host interactions make proper stratification of a control group impossible. The individualized characteristics of advanced therapy medicinal products for immunotherapy contribute to heterogeneity within an experimental group. The dynamics of each tumor and in each patient aggravate comparative stable patient groups. Finally, combinations of immunotherapy strategies should be integrated with first-line treatment. We illustrate the complexity of a combined first-line treatment with individualized multimodal immunotherapy in a group of 70 adults with GBM and demonstrate that the integration of immunogenic cell death treatment within maintenance chemotherapy followed by dendritic cell vaccines and maintenance immunotherapy might provide a step towards improving the overall survival rate of GBM patients.

Abstract

Immunotherapies represent a promising strategy for glioblastoma multiforme (GBM) treatment. Different immunotherapies include the use of checkpoint inhibitors, adoptive cell therapies such as chimeric antigen receptor (CAR) T cells, and vaccines such as dendritic cell vaccines. Antibodies have also been used as toxin or radioactive particle delivery vehicles to eliminate target cells in the treatment of GBM. Oncolytic viral therapy and other immunogenic cell death-inducing treatments bridge the antitumor strategy with immunization and installation of immune control over the disease. These strategies should be included in the standard treatment protocol for GBM. Some immunotherapies are individualized in terms of the medicinal product, the immune target, and the immune tumor–host contact. Current individualized immunotherapy strategies focus on combinations of approaches. Standardization appears to be impossible in the face of complex controlled trial designs. To define appropriate control groups, stratification according to the Recursive Partitioning Analysis classification, MGMT promotor methylation, epigenetic GBM sub-typing, tumor microenvironment, systemic immune functioning before and after radiochemotherapy, and the need for/type of symptom-relieving drugs is required. Moreover, maintenance of a fixed treatment protocol for a dynamic, deadly cancer disease in a permanently changing tumor–host immune context might be inappropriate. This complexity is illustrated using our own data on individualized multimodal immunotherapies for GBM. Individualized medicines, including multimodal immunotherapies, are a rational and optimal yet also flexible approach to induce long-term tumor control. However, innovative methods are needed to assess the efficacy of complex individualized treatments and implement them more quickly into the general health system.

Importance and Evidence of Extent of Resection in Glioblastoma

Maximal safe resection is an essential part of the multidisciplinary care of patients with glioblastoma. A growing body of data shows that gross total resection is an independent prognostic factor associated with improved clinical outcome. The relationship between extent of glioblastoma (GB) resection and clinical benefit depends critically on the balance between cytoreduction and avoiding neurologic morbidity. The definition of the extent of tumor resection, how this is best measured pre- and postoperatively, and its relation to volume of residual tumor is still discussed. We review the literature supporting extent of resection in GB, highlighting the importance of a standardized definition and measurement of extent of resection to allow greater collaboration in research projects and trials. Recent developments in neurosurgical techniques and technologies focused on maximizing extent of resection and safety are discussed.

Endothelial-Tumor Cell Interaction in Brain and CNS Malignancies

Glioblastoma and other brain or CNS malignancies (like neuroblastoma and medulloblastoma) are difficult to treat and are characterized by excessive vascularization that favors further tumor growth. Since the mean overall survival of these types of diseases is low, the finding of new therapeutic approaches is imperative. In this review, we discuss the importance of the interaction between the endothelium and the tumor cells in brain and CNS malignancies. The different mechanisms of formation of new vessels that supply the tumor with nutrients are discussed. We also describe how the tumor cells (TC) alter the endothelial cell (EC) physiology in a way that favors tumorigenesis. In particular, mechanisms of EC-TC interaction are described such as (a) communication using secreted growth factors (i.e., VEGF, TGF-β), (b) intercellular communication through gap junctions (i.e., Cx43), and (c) indirect interaction via intermediate cell types (pericytes, astrocytes, neurons, and immune cells). At the signaling level, we outline the role of important mediators, like the gasotransmitter nitric oxide and different types of reactive oxygen species and the systems producing them. Finally, we briefly discuss the current antiangiogenic therapies used against brain and CNS tumors and the potential of new pharmacological interventions that target the EC-TC interaction.