Healthcare spending versus mortality in central nervous system cancer: Has anything changed?

Background: The financial implications of central nervous system (CNS) cancers are substantial, not only for the healthcare service and payers, but also for the patients who bear the brunt of direct, indirect, and intangible costs. This study sought to investigate the impact of healthcare spending on CNS cancer survival using recent US data. Methods: This study used public data from the Disease Expenditure Project 2016 and the Global Burden of Disease Study 2019. The primary outcome was the annual healthcare spending trend from 1996 and 2016 on CNS tumors adjusted for disease prevalence, alongside morbidity and mortality. Secondary outcomes included drivers of change in healthcare expenditures for CNS cancers. Subgroup analysis was performed stratified by age group, expenditure type, and care type provided. Results: There was a significant increase in total healthcare spending on CNS cancers from $2.72 billion (95% CI: $2.47B to $2.97B) in 1996 to $6.85 billion (95% CI: $5.98B to $7.57B) in 2016. Despite the spending increase, the mortality rate per 100 000 people increased, with 5.30 ±â€…0.47 in 1996 and 7.02 ±â€…0.47 in 2016, with an average of 5.78 ±â€…0.47 deaths per 100 000 over the period. The subgroups with the highest expenditure included patients aged 45 to 64, those with private insurance, and those receiving inpatient care. Conclusions: This study highlights a significant rise in healthcare costs for CNS cancers without corresponding improvements in mortality rate, indicating a mismatch of healthcare spending, contemporary advances, and patient outcomes as it relates to mortality.

Former Primary Caregivers of Patients With Glioblastoma Multiforme Evaluate the PATH (Preparedness Assessment for the Transition Home) Instrument.

AIM: To evaluate whether Preparedness Assessment for the Transition Home (PATH), a validated instrument assessing gaps in caregiver commitment and capacity to care for a patient with a disabling condition, would be helpful to identify gaps in preparing primary caregivers of patients with glioblastoma multiforme (GBM). DESIGN: A descriptive survey design with quantitative and qualitative data. METHODS: Former primary caregivers of patients with GBM were invited to complete a 17-question online survey during February and March 2023. Former caregivers, each having completed their caregiver journeys, are able to offer a unique perspective across the illness trajectory. Participants reviewed a copy of the PATH instrument and (a) responded to questions rating PATH helpfulness at each stage of the illness trajectory and (b) provided open-ended feedback on the instrument. RESULTS: One hundred seventeen of the 124 participants reported the PATH instrument would be helpful across all stages of the illness trajectory. While there were no statistically significant differences across the illness phases, response trends indicated using the PATH instrument earlier in the illness trajectory would have been more helpful to them as caregivers. Qualitative thematic analysis feedback indicated the most significant gap caregivers faced was education on the effects of the illness and treatment. CONCLUSION: It is vitally important to prepare and support caregivers. A validated instrument can identify unmet needs and inform care decisions. IMPLICATIONS FOR THE PROFESSION: Patient discharge plans should be guided by the needs and preferences of patients and caregivers. Identifying gaps in education and preparedness early in the illness trajectory may inform the care team of unmet needs, allowing them to tailor resources and support to improve outcomes for patients with GBM and their caregivers. IMPACT: Patient discharge plans should be guided by the needs and preferences of patients and caregivers. Identifying gaps in education and preparedness early in the illness trajectory may inform the care team of unmet needs, allowing them to tailor resources and support to improve outcomes for patients with GBM and their caregivers. PATH has the potential to inform healthcare professionals to develop customised care plans including education, resources and support for caregivers and patients with life-threatening illness. REPORTING METHOD: Study adheres to the STROBE reporting method. PATIENT OR PUBLIC CONTRIBUTION: Prior to deploying the survey to study participants, in addition to testing by study collaborators (authors), the survey was tested and feedback was received from graduate students and from administrators of the private Facebook group where the survey was promoted to study participants.

The effect of exposure to radiofrequency fields on cancer risk in the general and working population: A systematic review of human observational studies - Part I: Most researched outcomes.

BACKGROUND: The objective of this review was to assess the quality and strength of the evidence provided by human observational studies for a causal association between exposure to radiofrequency electromagnetic fields (RF-EMF) and risk of the most investigated neoplastic diseases. METHODS: Eligibility criteria: We included cohort and case-control studies of neoplasia risks in relation to three types of exposure to RF-EMF: near-field, head-localized, exposure from wireless phone use (SR-A); far-field, whole body, environmental exposure from fixed-site transmitters (SR-B); near/far-field occupational exposures from use of hand-held transceivers or RF-emitting equipment in the workplace (SR-C). While no restrictions on tumour type were applied, in the current paper we focus on incidence-based studies of selected "critical" neoplasms of the central nervous system (brain, meninges, pituitary gland, acoustic nerve) and salivary gland tumours (SR-A); brain tumours and leukaemias (SR-B, SR-C). We focussed on investigations of specific neoplasms in relation to specific exposure sources (i.e. E-O pairs), noting that a single article may address multiple E-O pairs. INFORMATION SOURCES: Eligible studies were identified by literature searches through Medline, Embase, and EMF-Portal. Risk-of-bias (RoB) assessment: We used a tailored version of the Office of Health Assessment and Translation (OHAT) RoB tool to evaluate each study's internal validity. At the summary RoB step, studies were classified into three tiers according to their overall potential for bias (low, moderate and high). DATA SYNTHESIS: We synthesized the study results using random effects restricted maximum likelihood (REML) models (overall and subgroup meta-analyses of dichotomous and categorical exposure variables), and weighted mixed effects models (dose-response meta-analyses of lifetime exposure intensity). Evidence assessment: Confidence in evidence was assessed using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach. RESULTS: We included 63 aetiological articles, published between 1994 and 2022, with participants from 22 countries, reporting on 119 different E-O pairs. RF-EMF exposure from mobile phones (ever or regular use vs no or non-regular use) was not associated with an increased risk of glioma [meta-estimate of the relative risk (mRR) = 1.01, 95 % CI = 0.89-1.13), meningioma (mRR = 0.92, 95 % CI = 0.82-1.02), acoustic neuroma (mRR = 1.03, 95 % CI = 0.85-1.24), pituitary tumours (mRR = 0.81, 95 % CI = 0.61-1.06), salivary gland tumours (mRR = 0.91, 95 % CI = 0.78-1.06), or paediatric (children, adolescents and young adults) brain tumours (mRR = 1.06, 95 % CI = 0.74-1.51), with variable degree of across-study heterogeneity (I2 = 0 %-62 %). There was no observable increase in mRRs for the most investigated neoplasms (glioma, meningioma, and acoustic neuroma) with increasing time since start (TSS) use of mobile phones, cumulative call time (CCT), or cumulative number of calls (CNC). Cordless phone use was not significantly associated with risks of glioma [mRR = 1.04, 95 % CI = 0.74-1.46; I2 = 74 %) meningioma, (mRR = 0.91, 95 % CI = 0.70-1.18; I2 = 59 %), or acoustic neuroma (mRR = 1.16; 95 % CI = 0.83-1.61; I2 = 63 %). Exposure from fixed-site transmitters (broadcasting antennas or base stations) was not associated with childhood leukaemia or paediatric brain tumour risks, independently of the level of the modelled RF exposure. Glioma risk was not significantly increased following occupational RF exposure (ever vs never), and no differences were detected between increasing categories of modelled cumulative exposure levels. DISCUSSION: In the sensitivity analyses of glioma, meningioma, and acoustic neuroma risks in relation to mobile phone use (ever use, TSS, CCT, and CNC) the presented results were robust and not affected by changes in study aggregation. In a leave-one-out meta-analyses of glioma risk in relation to mobile phone use we identified one influential study. In subsequent meta-analyses performed after excluding this study, we observed a substantial reduction in the mRR and the heterogeneity between studies, for both the contrast Ever vs Never (regular) use (mRR = 0.96, 95 % CI = 0.87-1.07, I2 = 47 %), and in the analysis by increasing categories of TSS ("<5 years": mRR = 0.97, 95 % CI = 0.83-1.14, I2 = 41 %; "5-9 years ": mRR = 0.96, 95 % CI = 0.83-1.11, I2 = 34 %; "10+ years": mRR = 0.97, 95 % CI = 0.87-1.08, I2 = 10 %). There was limited variation across studies in RoB for the priority domains (selection/attrition, exposure and outcome information), with the number of studies evenly classified as at low and moderate risk of bias (49 % tier-1 and 51 % tier-2), and no studies classified as at high risk of bias (tier-3). The impact of the biases on the study results (amount and direction) proved difficult to predict, and the RoB tool was inherently unable to account for the effect of competing biases. However, the sensitivity meta-analyses stratified on bias-tier, showed that the heterogeneity observed in our main meta-analyses across studies of glioma and acoustic neuroma in the upper TSS stratum (I2 = 77 % and 76 %), was explained by the summary RoB-tier. In the tier-1 study subgroup, the mRRs (95 % CI; I2) in long-term (10+ years) users were 0.95 (0.85-1.05; 5.5 %) for glioma, and 1.00 (0.78-1.29; 35 %) for acoustic neuroma. The time-trend simulation studies, evaluated as complementary evidence in line with a triangulation approach for external validity, were consistent in showing that the increased risks observed in some case-control studies were incompatible with the actual incidence rates of glioma/brain cancer observed in several countries and over long periods. Three of these simulation studies consistently reported that RR estimates > 1.5 with a 10+ years induction period were definitely implausible, and could be used to set a "credibility benchmark". In the sensitivity meta-analyses of glioma risk in the upper category of TSS excluding five studies reporting implausible effect sizes, we observed strong reductions in both the mRR [mRR of 0.95 (95 % CI = 0.86-1.05)], and the degree of heterogeneity across studies (I2 = 3.6 %). CONCLUSIONS: Consistently with the published protocol, our final conclusions were formulated separately for each exposure-outcome combination, and primarily based on the line of evidence with the highest confidence, taking into account the ranking of RF sources by exposure level as inferred from dosimetric studies, and the external coherence with findings from time-trend simulation studies (limited to glioma in relation to mobile phone use). For near field RF-EMF exposure to the head from mobile phone use, there was moderate certainty evidence that it likely does not increase the risk of glioma, meningioma, acoustic neuroma, pituitary tumours, and salivary gland tumours in adults, or of paediatric brain tumours. For near field RF-EMF exposure to the head from cordless phone use, there was low certainty evidence that it may not increase the risk of glioma, meningioma or acoustic neuroma. For whole-body far-field RF-EMF exposure from fixed-site transmitters (broadcasting antennas or base stations), there was moderate certainty evidence that it likely does not increase childhood leukaemia risk and low certainty evidence that it may not increase the risk of paediatric brain tumours. There were no studies eligible for inclusion investigating RF-EMF exposure from fixed-site transmitters and critical tumours in adults. For occupational RF-EMF exposure, there was low certainty evidence that it may not increase the risk of brain cancer/glioma, but there were no included studies of leukemias (the second critical outcome in SR-C). The evidence rating regarding paediatric brain tumours in relation to environmental RF exposure from fixed-site transmitters should be interpreted with caution, due to the small number of studies. Similar interpretative cautions apply to the evidence rating of the relation between glioma/brain cancer and occupational RF exposure, due to differences in exposure sources and metrics across the few included studies. OTHER: This project was commissioned and partially funded by the World Health Organization (WHO). Co-financing was provided by the New Zealand Ministry of Health; the Istituto Superiore di Sanità in its capacity as a WHO Collaborating Centre for Radiation and Health; and ARPANSA as a WHO Collaborating Centre for Radiation Protection. REGISTRATION: PROSPERO CRD42021236798. Published protocol: [(Lagorio et al., 2021) DOI https://doi.org/10.1016/j.envint.2021.106828].

AB035. Validation of EORTC brain cancer module (EORTC QLQ-BN20) for assessment of health-related quality of life in glioma patients in Singapore.

BACKGROUND: Existing international data has shown that glioma patients suffer from poorer health-related quality of life (HRQoL). The European Organization for Research and Treatment of Cancer (EORTC) brain cancer-specific Quality of Life Questionnaire (QLQ-BN20) was developed to be together with EORTC Core Quality of Life Questionnaire (QLQ-C30) for cancer patients, highlighting issues particularly relevant to brain tumor patients. It has since been translated and validated across numerous cohorts. However, its psychometric properties have yet to be examined in Singapore. This study aimed to validate the use of QLQ-BN20 in a nationally representative sample of glioma patients in Singapore. METHODS: Eighty-seven patients who had undergone neurosurgery for glioma from six hospitals in Singapore completed three self-reported measures of HRQoL (the EuroQol EQ-5D-5L, EORTC QLQ-C30, and EORTC QLQ-BN20). Descriptive statistics summarized their characteristics and scores on the questionnaires. Psychometric properties of QLQ-BN20 examined included convergent and discriminant validity, internal consistency (Cronbach's alpha), and construct validity (Spearman's correlation). Clinical validity of QLQ-BN20 was determined based on whether QLQ-BN20 scores could differentiate patients with good and poor functional status as measured by Karnofsky Performance Scale and Barthel's Index. RESULTS: The QLQ-BN20 was demonstrated to have good convergent validity (item-own scale correlation >0.70) and discriminant validity (item-own scale correlation higher than item-other scale correlation). There is high internal consistency, both overall (α=0.88) and within multi-item subscales (α=0.74-0.88). Conceptually similar subscales between different tools were more strongly correlated. For instance, the QLQ-C30 physical functioning subscale and the QLQ-BN20 motor dysfunction subscale (r=-0.65, P<0.001), and the QLQ-C30 cognitive functioning subscale and the QLQ-BN20 cognitive deficits subscale (r=-0.51, P<0.001). QLQ-BN20 was also able to distinguish between functional statuses of patients (P<0.05). CONCLUSIONS: This study supports the validity and reliability of the EORTC QLQ-BN20 among patients with glioma in Singapore. There is good convergent and discriminant validity, internal consistency, construct validity, and clinical validity. The QLQ-BN20 is a valuable supplement to the QLQ-C30. Hence, we recommend expanding its use for all glioma patients and possibly brain cancer patients in Singapore.

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

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

Spectral analysis comparison of pushbroom and snapshot hyperspectral cameras for in vivo brain tissues and chromophore identification.

Significance: Hyperspectral imaging sensors have rapidly advanced, aiding in tumor diagnostics for in vivo brain tumors. Linescan cameras effectively distinguish between pathological and healthy tissue, whereas snapshot cameras offer a potential alternative to reduce acquisition time. Aim: Our research compares linescan and snapshot hyperspectral cameras for in vivo brain tissues and chromophore identification. Approach: We compared a linescan pushbroom camera and a snapshot camera using images from 10 patients with various pathologies. Objective comparisons were made using unnormalized and normalized data for healthy and pathological tissues. We utilized the interquartile range (IQR) for the spectral angle mapping (SAM), the goodness-of-fit coefficient (GFC), and the root mean square error (RMSE) within the 659.95 to 951.42 nm range. In addition, we assessed the ability of both cameras to capture tissue chromophores by analyzing absorbance from reflectance information. Results: The SAM metric indicates reduced dispersion and high similarity between cameras for pathological samples, with a 9.68% IQR for normalized data compared with 2.38% for unnormalized data. This pattern is consistent across GFC and RMSE metrics, regardless of tissue type. Moreover, both cameras could identify absorption peaks of certain chromophores. For instance, using the absorbance measurements of the linescan camera, we obtained SAM values below 0.235 for four peaks, regardless of the tissue and type of data under inspection. These peaks are one for cytochrome b in its oxidized form at λ = 422 nm , two for HbO 2 at λ = 542 nm and λ = 576 nm , and one for water at λ = 976 nm . Conclusion: The spectral signatures of the cameras show more similarity with unnormalized data, likely due to snapshot sensor noise, resulting in noisier signatures post-normalization. Comparisons in this study suggest that snapshot cameras might be viable alternatives to linescan cameras for real-time brain tissue identification.

Psilocybin-Assisted Therapy for Brain Cancer Related Existential Distress: A Case-Report.

Introduction: Psilocybin-assisted therapy (PAT) has gained traction in palliative care as a treatment for existential distress in the last decade. Patients with brain cancer have been excluded from studies, yet they stand to benefit as much as other patients with cancer-related psychological distress. Case description: In this report, we discuss the case of a patient with end-of-life distress secondary to stage 4 astrocytoma that received PAT through Health Canada's Special Access Program. The patient had a positive response to PAT without adverse events. Discussion: Standard treatment for existential distress is often inefficacious and PAT is rarely available, especially for patients with brain cancer. We highlight the importance of making PAT more available as many patients with unresolved existential distress resort to medical assistance in dying without ever knowing of the existence of PAT. Conclusion: PAT was effective in partially alleviating the patient's existential distress. Access to PAT needs to be expanded urgently.

Methods in cancer research: Assessing therapy response of spheroid cultures by life cell imaging using a cost-effective live-dead staining protocol.

Spheroid cultures of cancer cell lines or primary cells represent a more clinically relevant model for predicting therapy response compared to two-dimensional cell culture. However, current live-dead staining protocols used for treatment response in spheroid cultures are often expensive, toxic to the cells, or limited in their ability to monitor therapy response over an extended period due to reduced stability. In our study, we have developed a cost-effective method utilizing calcein-AM and Helix NP™ Blue for live-dead staining, enabling the monitoring of therapy response of spheroid cultures for up to 10 days. Additionally, we used ICY BioImage Analysis and Z-stacks projection to calculate viability, which is a more accurate method for assessing treatment response compared to traditional methods on spheroid size. Using the example of glioblastoma cell lines and primary glioblastoma cells, we show that spheroid cultures typically exhibit a green outer layer of viable cells, a turquoise mantle of hypoxic quiescent cells, and a blue core of necrotic cells when visualized using confocal microscopy. Upon treatment of spheroids with the alkylating agent temozolomide, we observed a reduction in the viability of glioblastoma cells after an incubation period of 7 days. This method can also be adapted for monitoring therapy response in different cancer systems, offering a versatile and cost-effective approach for assessing therapy efficacy in three-dimensional culture models.

Three-dimensional dose prediction based on deep convolutional neural networks for brain cancer in CyberKnife: accurate beam modelling of homogeneous tissue.

Objectives: Accurate beam modelling is essential for dose calculation in stereotactic radiation therapy (SRT), such as CyberKnife treatment. However, the present deep learning methods only involve patient anatomical images and delineated masks for training. These studies generally focus on traditional intensity-modulated radiation therapy (RT) plans. Nevertheless, this paper aims to develop a deep CNN-based method for CyberKnife plan dose prediction about brain cancer patients. It utilized modelled beam information, target delineation, and patient anatomical information. Methods: This study proposes a method that adds beam information to predict the dose distribution of CyberKnife in brain cases. A retrospective dataset of 88 brain and abdominal cancer patients treated with the Ray-tracing algorithm was performed. The datasets include patients' anatomical information (planning CT), binary masks for organs at risk (OARs) and targets, and clinical plans (containing beam information). The datasets were randomly split into 68, 6, and 14 brain cases for training, validation, and testing, respectively. Results: Our proposed method performs well in SRT dose prediction. First, for the gamma passing rates in brain cancer cases, with the 2 mm/2% criteria, we got 96.7% ± 2.9% for the body, 98.3% ± 3.0% for the planning target volume, and 100.0% ± 0.0% for the OARs with small volumes referring to the clinical plan dose. Secondly, the model predictions matched the clinical plan's dose-volume histograms reasonably well for those cases. The differences in key metrics at the target area were generally below 1.0 Gy (approximately a 3% difference relative to the prescription dose). Conclusions: The preliminary results for selected 14 brain cancer cases suggest that accurate 3-dimensional dose prediction for brain cancer in CyberKnife can be accomplished based on accurate beam modelling for homogeneous tumour tissue. More patients and other cancer sites are needed in a further study to validate the proposed method fully. Advances in knowledge: With accurate beam modelling, the deep learning model can quickly generate the dose distribution for CyberKnife cases. This method accelerates the RT planning process, significantly improves its operational efficiency, and optimizes it.

Exosomal TNF-α mediates voltage-gated Na+ channel 1.6 overexpression and contributes to brain tumor-induced neuronal hyperexcitability.

Patients affected by glioma frequently experience epileptic discharges; however, the causes of brain tumor-related epilepsy (BTRE) are still not completely understood. We investigated the mechanisms underlying BTRE by analyzing the effects of exosomes released by U87 glioma cells and by patient-derived glioma cells. Rat hippocampal neurons incubated for 24 hours with these exosomes exhibited increased spontaneous firing, while their resting membrane potential shifted positively by 10-15 mV. Voltage clamp recordings demonstrated that the activation of the Na+ current shifted toward more hyperpolarized voltages by 10-15 mV. To understand the factors inducing hyperexcitability, we focused on exosomal cytokines. Western blot and ELISAs showed that TNF-α was present inside glioma-derived exosomes. Remarkably, incubation with TNF-α fully mimicked the phenotype induced by exosomes, with neurons firing continuously, while their resting membrane potential shifted positively. Real-time PCR revealed that both exosomes and TNF-α induced overexpression of the voltage-gated Na+ channel Nav1.6, a low-threshold Na+ channel responsible for hyperexcitability. When neurons were preincubated with infliximab, a specific TNF-α inhibitor, the hyperexcitability induced by exosomes and TNF-α was drastically reduced. We propose that infliximab, an FDA-approved drug to treat rheumatoid arthritis, could ameliorate the conditions of glioma patients with BTRE.

Pediatric glioma immune profiling identifies TIM3 as a therapeutic target in BRAF fusion pilocytic astrocytoma.

Despite being the leading cause of cancer-related childhood mortality, pediatric gliomas have been relatively understudied, and the repurposing of immunotherapies has not been successful. Whole-transcriptome sequencing, single-cell sequencing, and sequential multiplex immunofluorescence were used to identify an immunotherapeutic strategy that could be applied to multiple preclinical glioma models. MAPK-driven pediatric gliomas have a higher IFN signature relative to other molecular subgroups. Single-cell sequencing identified an activated and cytotoxic microglia (MG) population designated MG-Act in BRAF-fused, MAPK-activated pilocytic astrocytoma (PA), but not in high-grade gliomas or normal brain. T cell immunoglobulin and mucin domain 3 (TIM3) was expressed on MG-Act and on the myeloid cells lining the tumor vasculature but not normal brain vasculature. TIM3 expression became upregulated on immune cells in the PA microenvironment, and anti-TIM3 reprogrammed ex vivo immune cells from human PAs to a proinflammatory cytotoxic phenotype. In a genetically engineered murine model of MAPK-driven, low-grade gliomas, anti-TIM3 treatment increased median survival over IgG- and anti-PD-1-treated mice. Single-cell RNA-Seq data during the therapeutic window of anti-TIM3 revealed enrichment of the MG-Act population. The therapeutic activity of anti-TIM3 was abrogated in mice on the CX3CR1 MG-KO background. These data support the use of anti-TIM3 in clinical trials of pediatric low-grade, MAPK-driven gliomas.

Combination of locoregional radiotherapy with a TIM-3 aptamer improves survival in diffuse midline glioma models.

Pediatric diffuse midline gliomas (DMG) with altered H3-K27M are aggressive brain tumors that arise during childhood. Despite advances in genomic knowledge and the significant number of clinical trials testing new targeted therapies, patient outcomes are still poor. Immune checkpoint blockades with small molecules, such as aptamers, are opening new therapeutic options that represent hope for this orphan disease. Here, we demonstrated that a TIM-3 aptamer (TIM-3 Apt) as monotherapy increased the immune infiltration and elicited a strong specific immune response with a tendency to improve the overall survival of treated DMG-bearing mice. Importantly, combining TIM-3 Apt with radiotherapy increased the overall median survival and led to long-term survivor mice in 2 pediatric DMG orthotopic murine models. Interestingly, TIM-3 Apt administration increased the number of myeloid populations and the proinflammatory CD8-to-Tregs ratios in the tumor microenvironment as compared with nontreated groups after radiotherapy. Importantly, the depletion of T cells led to a major loss of the therapeutic effect achieved by the combination. This work uncovers TIM-3 targeting as an immunotherapy approach to improve the radiotherapy outcome in DMGs and offers a strong foundation for propelling a phase I clinical trial using radiotherapy and TIM-3 blockade combination as a treatment for these tumors.

Genomic, epigenomic and transcriptomic landscape of glioblastoma.

The mostly aggressive and extremely malignant type of central nervous system is Glioblastoma (GBM), which is characterized by an extremely short average survival time of lesser than 16 months. The primary cause of this phenomenon can be attributed to the extensively altered genome of GBM, which is characterized by the dysregulation of numerous critical signaling pathways and epigenetics regulations associated with proliferation, cellular growth, survival, and apoptosis. In light of this, different genetic alterations in critical signaling pathways and various epigenetics regulation mechanisms are associated with GBM and identified as distinguishing markers. Such GBM prognostic alterations are identified in PI3K/AKT, p53, RTK, RAS, RB, STAT3 and ZIP4 signaling pathways, metabolic pathway (IDH1/2), as well as alterations in epigenetic regulation genes (MGMT, CDKN2A-p16INK4aCDKN2B-p15INK4b). The exploration of innovative diagnostic and therapeutic approaches that specifically target these pathways is utmost importance to enhance the future medication for GBM. This study provides a comprehensive overview of dysregulated epigenetic mechanisms and signaling pathways due to mutations, methylation, and copy number alterations of in critical genes in GBM with prevalence and emphasizing their significance.

Soloxolone para-methylanilide effectively suppresses aggressive phenotype of glioblastoma cells including TGF-ß1-induced glial-mesenchymal transition in vitro and inhibits growth of U87 glioblastoma xenografts in mice.

Soloxolone amides are semisynthetic triterpenoids that can cross the blood-brain barrier and inhibit glioblastoma growth both in vitro and in vivo. Here we investigate the impact of these compounds on processes associated with glioblastoma invasiveness and therapy resistance. Screening of soloxolone amides against glioblastoma cells revealed the ability of compound 7 (soloxolone para-methylanilide) to inhibit transforming growth factor-beta 1 (TGF-ß1)-induced glial-mesenchymal transition Compound 7 inhibited morphological changes, wound healing, transwell migration, and expression of mesenchymal markers (N-cadherin, fibronectin, Slug) in TGF-ß1-induced U87 and U118 glioblastoma cells, while restoring their adhesiveness. Confocal microscopy and molecular docking showed that 7 reduced SMAD2/3 nuclear translocation probably by direct interaction with the TGF-ß type I and type II receptors (TßRI/II). In addition, 7 suppressed stemness of glioblastoma cells as evidenced by inhibition of colony forming ability, spheroid growth, and aldehyde dehydrogenase (ALDH) activity. Furthermore, 7 exhibited a synergistic effect with temozolomide (TMZ) on glioblastoma cell viability. Using N-acetyl-L-cysteine (NAC) and flow cytometry analysis of Annexin V-FITC-, propidium iodide-, and DCFDA-stained cells, 7 was found to synergize the cytotoxicity of TMZ by inducing ROS-dependent apoptosis. Further in vivo studies showed that 7, alone or in combination with TMZ, effectively suppressed the growth of U87 xenograft tumors in mice. Thus, 7 demonstrated promising potential as a component of combination therapy for glioblastoma, reducing its invasiveness and increasing its sensitivity to chemotherapy.

'I think both of us drew strength from it': qualitative reflections from next of kin following the death and post-mortem brain donation of a loved one with brain cancer.

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.

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.

A cross-shaped terahertz metamaterial absorber for brain cancer detection.

The article presents, for the first time, a terahertz metamaterial absorber (TMA) designed in the shape of a cross consisting of four orthogonally positioned horn-shaped patches in succession, to detect brain cancer cells. The design exhibits the property of mu-negative material, indicating magnetic resonance. The proposed TMA has achieved an impressive absorption rate of 99.43% at 2.334 THz and a high Q-factor of 47.15. The sensing capability has been investigated by altering the refractive index of the surrounding medium in the range of 1.3 to 1.48, resulting in a sensitivity of 0.502 THz/RIU. The proposed TMA exhibits complete polarization insensitivity, highlighting this as one of its advantageous features. The adequate sensing capability of the proposed TMA in differentiating normal and cancerous brain cells makes it a viable candidate for an early and efficient brain cancer detector. This research can be the foundation for future research on using THz radiation for brain cancer detection.

Deconvolution of the tumor-educated platelet transcriptome reveals activated platelet and inflammatory cell transcript signatures.

Tumor-educated platelets (TEPs) are a potential method of liquid biopsy for the diagnosis and monitoring of cancer. However, the mechanism underlying tumor education of platelets is not known, and transcripts associated with TEPs are often not tumor-associated transcripts. We demonstrated that direct tumor transfer of transcripts to circulating platelets is an unlikely source of the TEP signal. We used CDSeq, a latent Dirichlet allocation algorithm, to deconvolute the TEP signal in blood samples from patients with glioblastoma. We demonstrated that a substantial proportion of transcripts in the platelet transcriptome are derived from non-platelet cells, and the use of this algorithm allows the removal of contaminant transcripts. Furthermore, we used the results of this algorithm to demonstrate that TEPs represent a subset of more activated platelets, which also contain transcripts normally associated with non-platelet inflammatory cells, suggesting that these inflammatory cells, possibly in the tumor microenvironment, transfer transcripts to platelets that are then found in circulation. Our analysis suggests a useful and efficient method of processing TEP transcriptomic data to enable the isolation of a unique TEP signal associated with specific tumors.

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.

Multidisciplinary cancer disease classification using adaptive FL in healthcare industry 5.0.

Emerging Industry 5.0 designs promote artificial intelligence services and data-driven applications across multiple places with varying ownership that need special data protection and privacy considerations to prevent the disclosure of private information to outsiders. Due to this, federated learning offers a method for improving machine-learning models without accessing the train data at a single manufacturing facility. We provide a self-adaptive framework for federated machine learning of healthcare intelligent systems in this research. Our method takes into account the participating parties at various levels of healthcare ecosystem abstraction. Each hospital trains its local model internally in a self-adaptive style and transmits it to the centralized server for universal model optimization and communication cycle reduction. To represent a multi-task optimization issue, we split the dataset into as many subsets as devices. Each device selects the most advantageous subset for every local iteration of the model. On a training dataset, our initial study demonstrates the algorithm's ability to converge various hospital and device counts. By merging a federated machine-learning approach with advanced deep machine-learning models, we can simply and accurately predict multidisciplinary cancer diseases in the human body. Furthermore, in the smart healthcare industry 5.0, the results of federated machine learning approaches are used to validate multidisciplinary cancer disease prediction. The proposed adaptive federated machine learning methodology achieved 90.0%, while the conventional federated learning approach achieved 87.30%, both of which were higher than the previous state-of-the-art methodologies for cancer disease prediction in the smart healthcare industry 5.0.

Tools to study neural and glioma stem cell quiescence.

Quiescence is a prolonged but reversible state of cell-cycle arrest that is an adaptive feature of most adult stem cell populations. In the brain, quiescence helps to protect adult neural stem cells from stress and supports lifelong neurogenesis. Unfortunately however, entry into a quiescent or a slow-cycling state is also a malignant feature of brain cancer stem cells. In glioblastoma, where the process has been best characterised, quiescent glioma stem cells preferentially survive chemoradiation, and after therapy, reactivate to regrow the tumour and drive recurrence. In this Review, we discuss the in vitro and in vivo models that have been developed for studying neural stem cell quiescence and how these tools may be used to deepen biological understanding and to develop novel therapies targeting quiescent glioma stem cells.