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Three-dimensional visualization of cellular and subcellular-structures in histological-tissues is essential for understanding the complexities of biological-phenomena, especially with regards structural and spatial relationships and pathologlical-diagnosis. Recent advancements in tissue-clearing technology, such as Magnified Analysis of Proteome (MAP), have significantly improved our ability to study biological-structures in three-dimensional space; however, their wide applicability to a variety of tissues is limited by long incubation-times and a need for advanced imaging-systems that are not readily available in most-laboratories. Here, we present optimized MAP-based method for paper-thin samples, Paper-MAP, which allow for rapid clearing and subsequent imaging of three-dimensional sections derived from various tissues using conventional confocal-microscopy. Paper-MAP successfully clear tissues within 1-day, compared to the original-MAP, without significant differences in achieved optical-transparency. As a proof-of-concept, we investigated the vasculature and neuronal-networks of a variety of human and rodent tissues processed via Paper-MAP, in both healthy and diseased contexts, including Alzheimer's disease and glioma., (© 2021. The Author(s).)

Purpose: To develop a self-supervised learning method to retrospectively estimate T 1 and T 2 values from clinical weighted MRI., Methods: A self-supervised learning approach was constructed to estimate T 1 , T 2 , and proton density maps from conventional T 1 - and T 2 -weighted images. MR physics models were employed to regenerate the weighted images from the network outputs, and the network was optimized based on loss calculated between the synthesized and input weighted images, alongside additional constraints based on prior information. The method was evaluated on healthy volunteer data, with conventional mapping as references. The reproducibility was examined on two 3.0T scanners. Performance in tumor characterization was inspected by applying the method to a public glioblastoma dataset., Results: For T 1 and T 2 estimation from three weighted images (T 1 MPRAGE, T 1 gradient echo sequences, and T 2 turbo spin echo), the deep learning method achieved global voxel-wise error ≤9% in brain parenchyma and regional error ≤12.2% in six types of brain tissues. The regional measurements obtained from two scanners showed mean differences ≤2.4% and correlation coefficients >0.98, demonstrating excellent reproducibility. In the 50 glioblastoma patients, the retrospective quantification results were in line with literature reports from prospective methods, and the T 2 values were found to be higher in tumor regions, with sensitivity of 0.90 and specificity of 0.92 in a voxel-wise classification task between normal and abnormal regions., Conclusion: The self-supervised learning method is promising for retrospective T 1 and T 2 quantification from clinical MR images, with the potential to improve the availability of quantitative MRI and facilitate brain tumor characterization., (© 2024 International Society for Magnetic Resonance in Medicine.)

Adults diagnosed with Glioblastoma multiforme (GBM) are frequently faced with a 7% chance of surviving 2 years compared with pediatric patients with GBM who have a 26% survival rate. Our recent screen of possible glioma-associated antigen precursor protein (TAPP) profiles displayed from different types of pediatric brain tumors showed that pediatric patients contained a subset of the tumor antigens displayed by adult GBM patients. Adult GBM possess at least 27 tumor antigens that can potentially stimulate T cell immune responses, suggesting that these tumors are quite antigenic. In contrast, pediatric brain tumors only expressed nine tumor antigens with mRNA levels that were equivalent to those displayed by adult GBM. These tumor-associated antigens could be used as possible targets of therapeutic immunization for pediatric brain cancer patients. Children have developing immune systems that peak at puberty. An immune response mounted by these pediatric patients might account for their extended life spans, even though the pediatric brain tumors express far fewer total tumor-associated antigens. Here we present a hypothesis that pediatric brain tumor patients might be the best patients to show that immunotherapy can be used to successfully treat established cancers. We speculate that immunotherapy should include a panel of tumor antigens that might prevent the out-growth of more malignant tumor cells and thereby prevent the brain tumor relapse. Thus, pediatric brain tumor patients might provide an opportunity to prove the concept of immunoprevention.

Despite unprecedented survival in patients with glioblastoma (GB), the aggressive primary brain cancer remains largely incurable and its mechanisms of treatment resistance have gained particular attention. The cytokine interleukin 6 (IL-6) and its receptor weave through the hallmarks of malignant gliomas and may represent a key vulnerability to GB. Known for activating the STAT3 pathway in autocrine fashion, IL-6 is amplified in GB and has been recognized as a negative biomarker for GB prognosis, rendering it a putative target of novel GB therapies. While it has been recognized as a biologically active component of GB for three decades only with concurrent advances in understanding of complementary immunotherapy has the concept of targeting IL-6 for a human clinical trial gained scientific footing., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Boron neutron capture therapy (BNCT) is a binary radiotherapy based on the 10 B(n, α) 7 Li capture reaction. Nonradioactive isotope 10 B atoms which selectively concentrated in tumor cells will react with low energy neutrons (mainly thermal neutrons) to produce secondary particles with high linear energy transfer, thus depositing dose in tumor cells. In clinical practice, an appropriate treatment plan needs to be set on the basis of the treatment planning system (TPS). Existing BNCT TPSs usually use the Monte Carlo method to determine the three-dimensional (3D) therapeutic dose distribution, which often requires a lot of calculation time due to the complexity of simulating neutron transportation., Purpose: A neural network-based BNCT dose prediction method is proposed to achieve the rapid and accurate acquisition of BNCT 3D therapeutic dose distribution for patients with glioblastoma to solve the time-consuming problem of BNCT dose calculation in clinic., Methods: The clinical data of 122 patients with glioblastoma are collected. Eighteen patients are used as a test set, and the rest are used as a training set. The 3D-UNET is constructed through the design optimization of input and output data sets based on radiation field information and patient CT information to enable the prediction of 3D dose distribution of BNCT., Results: The average mean absolute error of the predicted and simulated equivalent doses of each organ are all less than 1 Gy. For the dose to 95% of the GTV volume (D 95 ), the relative deviation between predicted and simulated results are all less than 2%. The average 2 mm/2% gamma index is 89.67%, and the average 3 mm/3% gamma index is 96.78%. The calculation takes about 6 h to simulate the 3D therapeutic dose distribution of a patient with glioblastoma by Monte Carlo method using Intel Xeon E5-2699 v4, whereas the time required by the method proposed in this study is almost less than 1 s using a Titan-V graphics card., Conclusions: This study proposes a 3D dose prediction method based on 3D-UNET architecture in BNCT, and the feasibility of this method is demonstrated. Results indicate that the method can remarkably reduce the time required for calculation and ensure the accuracy of the predicted 3D therapeutic dose-effect. This work is expected to promote the clinical development of BNCT in the future., (© 2023 American Association of Physicists in Medicine.)

Background: Numerous patient-based studies have highlighted the protective role of immunoglobulin E-mediated allergic diseases on glioblastoma (GBM) susceptibility and prognosis. However, the mechanisms behind this observation remain elusive. Our objective was to establish a preclinical model able to recapitulate this phenomenon and investigate the role of immunity underlying such protection., Methods: An immunocompetent mouse model of allergic airway inflammation (AAI) was initiated before intracranial implantation of mouse GBM cells (GL261). RAG1-KO mice served to assess tumor growth in a model deficient for adaptive immunity. Tumor development was monitored by MRI. Microglia were isolated for functional analyses and RNA-sequencing. Peripheral as well as tumor-associated immune cells were characterized by flow cytometry. The impact of allergy-related microglial genes on patient survival was analyzed by Cox regression using publicly available datasets., Results: We found that allergy establishment in mice delayed tumor engraftment in the brain and reduced tumor growth resulting in increased mouse survival. AAI induced a transcriptional reprogramming of microglia towards a pro-inflammatory-like state, uncovering a microglia gene signature, which correlated with limited local immunosuppression in glioma patients. AAI increased effector memory T-cells in the circulation as well as tumor-infiltrating CD4 + T-cells. The survival benefit conferred by AAI was lost in mice devoid of adaptive immunity., Conclusion: Our results demonstrate that AAI limits both tumor take and progression in mice, providing a preclinical model to study the impact of allergy on GBM susceptibility and prognosis, respectively. We identify a potentiation of local and adaptive systemic immunity, suggesting a reciprocal crosstalk that orchestrates allergy-induced immune protection against GBM., (© 2022 The Authors. Allergy published by European Academy of Allergy and Clinical Immunology and John Wiley & Sons Ltd.)

Background: Biomarkers that reflect glioblastoma tumour activity and treatment response are urgently needed to help guide clinical management, particularly for recurrent disease. As the urinary system is a major clearance route of circulating extracellular vesicles (EVs; 30-1000 nm nanoparticles) we explored whether sampling urinary-EVs could serve as a simple and non-invasive liquid biopsy approach for measuring glioblastoma-associated biomarkers., Methods: Fifty urine specimens (15-60 ml) were collected from 24 catheterised glioblastoma patients immediately prior to primary (n = 17) and recurrence (n = 7) surgeries, following gross total resection (n = 9), and from age/gender-matched healthy participants (n = 14). EVs isolated by differential ultracentrifugation were characterised and extracted proteomes were analysed by high-resolution data-independent acquisition liquid chromatography tandem mass spectrometry (DIA-LC-MS/MS)., Results: Overall, 6857 proteins were confidently identified in urinary-EVs (q-value ≤ 0.01), including 94 EV marker proteins. Glioblastoma-specific proteomic signatures were determined, and putative urinary-EV biomarkers corresponding to tumour burden and recurrence were identified (FC ≥ | 2 | , adjust p-val≤0.05, AUC > 0.9)., Conclusion: In-depth DIA-LC-MS/MS characterisation of urinary-EVs substantiates urine as a viable source of glioblastoma biomarkers. The promising 'liquid gold' biomarker panels described here warrant further investigation., (© 2024. The Author(s).)

Glioblastoma multiforme (GBM) is the most common and aggressive form of brain cancer. Prognosis evaluation is of great significance in guiding individualized treatment and monitoring of GBM. By integrating different prognostic variables, nomograms simplify the statistical risk prediction model into numerical estimates for death or recurrence, and are hence widely applied in prognosis prediction. In the past two decades, the application of high-throughput profiling technology and the establishment of TCGA database and other public data deposits have provided opportunities to identify cancer-related molecules and prognostic biomarkers. As a result, both molecular features and clinical characteristics of cancer have been reported to be the key factors in nomogram model construction. This article comprehensively reviewed 35 studies of GBM nomograms, analyzed the present situation of GBM nomograms, and discussed the role and significance of nomograms in personalized risk assessment and clinical treatment decision-making. To facilitate the application of nomograms in the prognostic prediction of GBM patients, a website has been established for the online access of nomograms based on the studies of this review, which is called Consensus Nomogram Spectrum for Glioblastoma (CNSgbm) and is accessible through https://bioinfo.henu.edu.cn/nom/NomList.jsp., (© 2022 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Glioblastoma multiforme (GBM) is the most invasive form of primary brain astrocytoma, resulting in poor clinical outcomes. Herpes simplex virus thymidine kinase/ganciclovir (HSV-TK/GCV) gene therapy is considered a promising strategy for GBM treatment. Since Connexin43 (Cx43) expression is reduced in GBM cells, increasing Cx43 levels could enhance the effectiveness of gene therapy. The present study aims to examine the impact of fluoxetine on HSV-TK/GCV gene therapy in human GBM cells using human olfactory ensheathing cells (OECs) as vectors. The effect of fluoxetine on Cx43 levels was assessed using the western blot technique. GBM-derived astrocytes and OECs-TK were Cocultured, and the effect of fluoxetine on the Antitumor effect of OEC-TK/GCV gene therapy was evaluated using MTT assay and flow cytometry. Our results showed that fluoxetine increased Cx43 levels in OECs and GBM cells and augmented the killing effect of OECs-TK on GBM cells. Western blot data revealed that fluoxetine enhanced the Bax/Bcl2 ratio and the levels of cleaved caspase-3 in the coculture of OECs-TK and GBM cells. Moreover, flow cytometry data indicated that fluoxetine increased the percentage of apoptotic cells in the coculture system. This study suggests that fluoxetine, by upregulating Cx43 levels, could strengthen the Antitumor effect of OEC-TK/GCV gene therapy on GBM cells., (© 2023 Wiley Periodicals LLC.)

Lower-grade gliomas (LGG) can eventually progress to glioblastoma (GBM) and death. In the context of the transfer learning approach, we aimed to train and test an MRI-based radiomics model for predicting survival in GBM patients and validate it in LGG patients. From each patient's 704 MRI-based radiomics features, we chose seventeen optimal radiomics signatures in the GBM training set (n = 71) and used these features in both the GBM testing set (n = 31) and LGG validation set (n = 107) for further analysis. Each patient's risk score, calculated based on those optimal radiomics signatures, was chosen to represent the radiomics model. We compared the radiomics model with clinical, gene status models, and combined model integrating radiomics, clinical, and gene status in predicting survival. The average iAUCs of combined models in training, testing, and validation sets were respectively 0.804, 0.878, and 0.802, and those of radiomics models were 0.798, 0.867, and 0.717. The average iAUCs of gene status and clinical models ranged from 0.522 to 0.735 in all three sets. The radiomics model trained in GBM patients can effectively predict the overall survival of GBM and LGG patients, and the combined model improved this ability., (© 2023. International Federation for Medical and Biological Engineering.)

Numerous neurodegenerative conditions, such as Alzheimer's, Huntington's, Parkinson's, amyotrophic lateral sclerosis, and glioblastoma multiform are now becoming significant concerns of global health. Formulation-related issues, physiological and anatomical barriers, post-administration obstacles, physical challenges, regulatory limitations, environmental hurdles, and health and safety issues have all hindered successful delivery and effective outcomes despite a variety of treatment options. In the current review, we covered the intranasal route, an alternative strategic route targeting brain for improved delivery across the BBB. The trans-nasal pathway is non-invasive, directing therapeutics directly towards brain, circumventing the barrier and reducing peripheral exposure. The delivery of nanosized vesicles loaded with drugs was also covered in the review. Nanovesicle systems are organised in concentric bilayered lipid membranes separated with aqueous layers. These carriers surmount the disadvantages posed by intranasal delivery of rapid mucociliary clearance and enzymatic degradation, and enhance retention of drug to reach the site of target. In conclusion, the review covers in-depth conclusions on numerous aspects of formulation of drug-loaded vesicular system delivery across BBB, current marketed nasal devices, significant jeopardies, potential therapeutic aids, and current advancements followed by future perspectives., (© 2023. The Author(s), under exclusive licence to American Association of Pharmaceutical Scientists.)

Background: Glioblastoma (GBM) patients have poor survival outcomes despite treatment advances and most recurrences occur within the radiation field. Survival outcomes after dose escalation through hypofractionated accelerated RT(HART) were evaluated in this study. We previously reported the study's initial results showing similar survival outcomes with acceptable toxicities. Updated results after 5 years are being analysed to determine long-term survival trends., Patients and Methods: 89 patients of newly diagnosed GBM after surgery were randomized to conventional radiotherapy (CRT) or HART. CRT arm received adjuvant RT 60 Gy in 30 fractions over 6 weeks and the HART arm received 60 Gy in 20 fractions over 4 weeks, both with concurrent and adjuvant temozolomide., Results: 83 patients were eligible for analysis. After a median follow-up of 18.9 months, the median OS was 26.5 months and 22.4 months in the HART and CRT arms respectively. 5 year OS was 18.4% in the HART arm versus 3.8% in the CRT arm. This numerical difference in overall survival between the two arms was not statistically significant. The median PFS was not significantly different., Conclusion: The long-term results of the trial support HART as a promising treatment option with comparable survival outcomes to the current standard of care. Phase III trials are required for further validation of this regimen which has the potential to become the new standard of care in GBM., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Intra-tumoral heterogeneity and cell-state plasticity are key drivers for the therapeutic resistance of glioblastoma. Here, we investigate the association between spatial cellular organization and glioblastoma prognosis. Leveraging single-cell RNA-seq and spatial transcriptomics data, we develop a deep learning model to predict transcriptional subtypes of glioblastoma cells from histology images. Employing this model, we phenotypically analyze 40 million tissue spots from 410 patients and identify consistent associations between tumor architecture and prognosis across two independent cohorts. Patients with poor prognosis exhibit higher proportions of tumor cells expressing a hypoxia-induced transcriptional program. Furthermore, a clustering pattern of astrocyte-like tumor cells is associated with worse prognosis, while dispersion and connection of the astrocytes with other transcriptional subtypes correlate with decreased risk. To validate these results, we develop a separate deep learning model that utilizes histology images to predict prognosis. Applying this model to spatial transcriptomics data reveal survival-associated regional gene expression programs. Overall, our study presents a scalable approach to unravel the transcriptional heterogeneity of glioblastoma and establishes a critical connection between spatial cellular architecture and clinical outcomes., (© 2023. The Author(s).)

Purpose: To assess the repeatability of radiomic features in magnetic resonance (MR) imaging of glioblastoma (GBM) tumors with respect to test-retest, different image registration approaches and inhomogeneity bias field correction., Methods: We analyzed MR images of 17 GBM patients including T1- and T2-weighted images (performed within the same imaging unit on two consecutive days). For image segmentation, we used a comprehensive segmentation approach including entire tumor, active area of tumor, necrotic regions in T1-weighted images, and edema regions in T2-weighted images (test studies only; registration to retest studies is discussed next). Analysis included N3, N4 as well as no bias correction performed on raw MR images. We evaluated 20 image registration approaches, generated by cross-combination of four transformation and five cost function methods. In total, 714 images (17 patients × 2 images × ((4 transformations × 5 cost functions) + 1 test image) and 2856 segmentations (714 images × 4 segmentations) were prepared for feature extraction. Various radiomic features were extracted, including the use of preprocessing filters, specifically wavelet (WAV) and Laplacian of Gaussian (LOG), as well as discretization into fixed bin width and fixed bin count (16, 32, 64, 128, and 256), Exponential, Gradient, Logarithm, Square and Square Root scales. Intraclass correlation coefficients (ICC) were calculated to assess the repeatability of MRI radiomic features (high repeatability defined as ICC ≥ 95%)., Results: In our ICC results, we observed high repeatability (ICC ≥ 95%) with respect to image preprocessing, different image registration algorithms, and test-retest analysis, for example: RLNU and GLNU from GLRLM, GLNU and DNU from GLDM, Coarseness and Busyness from NGTDM, GLNU and ZP from GLSZM, and Energy and RMS from first order. Highest fraction (percent) of repeatable features was observed, among registration techniques, for the method Full Affine transformation with 12 degrees of freedom using Mutual Information cost function (mean 32.4%), and among image processing methods, for the method Laplacian of Gaussian (LOG) with Sigma (2.5-4.5 mm) (mean 78.9%). The trends were relatively consistent for N4, N3, or no bias correction., Conclusion: Our results showed varying performances in repeatability of MR radiomic features for GBM tumors due to test-retest and image registration. The findings have implications for appropriate usage in diagnostic and predictive models., (© 2020 American Association of Physicists in Medicine.)

Purpose: Pseudoprogression (PsP) occurs in 20-30% of patients with glioblastoma multiforme (GBM) after receiving the standard treatment. PsP exhibits similarities in shape and intensity to the true tumor progression (TTP) of GBM on the follow-up magnetic resonance imaging (MRI). These similarities pose challenges to the differentiation of these types of progression and hence the selection of the appropriate clinical treatment strategy., Methods: To address this challenge, we introduced a novel feature learning method based on deep convolutional generative adversarial network (DCGAN) and AlexNet, termed DC-AL GAN, to discriminate between PsP and TTP in MRI images. Due to the adversarial relationship between the generator and the discriminator of DCGAN, high-level discriminative features of PsP and TTP can be derived for the discriminator with AlexNet. We also constructed a multifeature selection module to concatenate features from different layers, contributing to more powerful features used for effectively discriminating between PsP and TTP. Finally, these discriminative features from the discriminator are used for classification by a support vector machine (SVM). Tenfold cross-validation (CV) and the area under the receiver operating characteristic (AUC) were applied to evaluate the performance of this developed algorithm., Results: The accuracy and AUC of DC-AL GAN for discriminating PsP and TTP after tenfold CV were 0.920 and 0.947. We also assessed the effects of different indicators (such as sensitivity and specificity) for features extracted from different layers to obtain a model with the best classification performance., Conclusions: The proposed model DC-AL GAN is capable of learning discriminative representations from GBM datasets, and it achieves desirable PsP and TTP classification performance superior to other state-of-the-art methods. Therefore, the developed model would be useful in the diagnosis of PsP and TTP for GBM., (© 2019 American Association of Physicists in Medicine.)

Glioblastoma is characterized by widespread genetic and transcriptional heterogeneity, yet little is known about the role of the epigenome in glioblastoma disease progression. Here, we present genome-scale maps of DNA methylation in matched primary and recurring glioblastoma tumors, using data from a highly annotated clinical cohort that was selected through a national patient registry. We demonstrate the feasibility of DNA methylation mapping in a large set of routinely collected FFPE samples, and we validate bisulfite sequencing as a multipurpose assay that allowed us to infer a range of different genetic, epigenetic, and transcriptional characteristics of the profiled tumor samples. On the basis of these data, we identified subtle differences between primary and recurring tumors, links between DNA methylation and the tumor microenvironment, and an association of epigenetic tumor heterogeneity with patient survival. In summary, this study establishes an open resource for dissecting DNA methylation heterogeneity in a genetically diverse and heterogeneous cancer, and it demonstrates the feasibility of integrating epigenomics, radiology, and digital pathology for a national cohort, thereby leveraging existing samples and data collected as part of routine clinical practice.

The burden of cancer continues to increase in society and negatively impacts the lives of numerous patients. Due to the high cost of current treatment strategies, there is a crucial unmet need to develop inexpensive preclinical platforms to accelerate the process of anti-cancer drug discovery to improve outcomes in cancer patients, most especially in female patients. Many current methods employ expensive animal models which not only present ethical concerns but also do not often accurately predict human physiology and the outcomes of anti-cancer drug responsiveness. Conventional treatment approaches for cancer generally include systemic therapy after a surgical procedure. Although this treatment technique is effective, the outcome is not always positive due to various complex factors such as intratumor heterogeneity and confounding factors within the tumor microenvironment (TME). Patients who develop metastatic disease still have poor prognosis. To that end, recent efforts have attempted to use 3D microengineered platforms to enhance the predictive power and efficacy of anti-cancer drug screening, ultimately to develop personalized therapies. Fascinating features of microengineered assays, such as microfluidics, have led to the advancement in the development of the tumor-on-chip technology platforms, which have shown tremendous potential for meaningful and physiologically relevant anti-cancer drug discovery and screening. Three dimensional microscale models provide unprecedented ability to unveil the biological complexities of cancer and shed light into the mechanism of anti-cancer drug resistance in a timely and resource efficient manner. In this review, we discuss recent advances in the development of microengineered tumor models for anti-cancer drug discovery and screening in female-related cancers. We specifically focus on female-related cancers to draw attention to the various approaches being taken to improve the survival rate of women diagnosed with cancers caused by sex disparities. We also briefly discuss other cancer types like colon adenocarcinomas and glioblastoma due to their high rate of occurrence in females, as well as the high likelihood of sex-biased mutations which complicate current treatment strategies for women. We highlight recent advances in the development of 3D microscale platforms including 3D tumor spheroids, microfluidic platforms as well as bioprinted models, and discuss how they have been utilized to address major challenges in the process of drug discovery, such as chemoresistance, intratumor heterogeneity, drug toxicity, etc. We also present the potential of these platform technologies for use in high-throughput drug screening approaches as a replacements of conventional assays. Within each section, we will provide our perspectives on advantages of the discussed platform technologies., (© 2021. Biomedical Engineering Society.)

Purpose: Immunohistochemical (IHC) testing for mismatch repair (MMR) deficiency (MMRD) is used as a screening tool to identify microsatellite instability in various cancers (especially colon). This not only identifies hereditary cancer syndromes like Lynch and constitutional mismatch repair deficiency (CMMRD) but also aids in prognostication and prediction of sensitivity to checkpoint inhibitor drugs. There are very few reported studies on MMRD status of pediatric high-grade gliomas (pHGG) and none from the Indian subcontinent. The aim of this study is to evaluate the frequency of MMRD in pHGG and to assess if there is a need for universal screening with immunohistochemistry., Methods: Paraffin blocks of consecutive cases of pHGG (< 18 years) were retrieved from 2 centres, and IHC with four MMR antibodies - MLH1, PMS2, MSH2 and MSH6 - was performed using tissue microarray-based technique., Results: Three out of nine cases (33%) studied showed loss of staining. One case had loss of MSH2 and MSH6 confirmed by gene sequencing. Eight of the cases were glioblastoma. One case of IDH1-mutated anaplastic astrocytoma showed loss of MLH1 and PMS2 staining. Isolated PMS2 loss was noted in 1 case, where the non-tumour cells also showed loss of staining, indicative CMMRD syndrome. This patient had prior colon cancer with isolated PMS2 loss and responded to check-point inhibitor therapy with nivolumab., Conclusion: Our study shows that the frequency of MMRD to be about one-third of pHGG. Universal IHC screening for MMRD in all pHGGs may benefit early diagnosis and play a role in therapeutic decisions. A larger multi-institutional study will help better assess the prevalence and treatment implications in MMRD tumours., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Objectives: Temporal muscle thickness (TMT) is a surrogate marker of sarcopenia, correlated with survival expectancy in patients suffering from brain metastases and recurrent or treated glioblastoma. We evaluated the prognostic relevance of TMT measured on brain MRIs acquired at diagnosis in patients affected by glioblastoma., Methods: We retrospectively enrolled 51 patients in our Institution affected by methylated MGMT promoter, IDH1-2 wild-type glioblastoma, who underwent complete surgical resection and subsequent radiotherapy with concomitant and maintenance temozolomide, from January 1, 2015, to April 30, 2017. The last clinical/radiological follow-up date was set to September 3, 2019. TMT was measured bilaterally on reformatted post-contrast 3D MPRAGE images, acquired on our 3-T scanner no more than 2 days before surgery. The median, 25th, and 75th percentile TMT values were identified and population was subdivided accordingly; afterwards, statistical analyses were performed to verify the association among overall survival (OS) and TMT, sex, age, and ECOG performance status., Results: In our cohort, the median OS was 20 months (range 3-51). Patients with a TMT ≥ 8.4 mm (median value) did not show a statistically significant increase in OS (Cox regression model: HR 1.34, 95% CI 0.68-2.63, p = 0.403). Similarly, patients with a TMT ≥ 9.85 mm (fourth quartile) did not differ in OS compared to those with TMT ≤ 7 mm (first quartile). The statistical analyses confirmed a significant association among TMT and sex (p = 0.0186), but none for age (p = 0.642) and performance status (p = 0.3982)., Conclusions: In our homogeneous cohort of patients with glioblastoma at diagnosis, TMT was not associated with prognosis, age, or ECOG performance status., Key Points: • Temporal muscle thickness (TMT) is a surrogate marker of sarcopenia and has been correlated with survival expectancy in patients suffering from brain metastases and recurrent or treated glioblastoma. • We appraised the correlation among TMT and survival, sex, age at surgery, and performance status, measured on brain MRIs of patients affected by glioblastoma at diagnosis. • TMT did not show any significant correlation with prognosis, age at surgery, or performance status, and its usefulness might be restricted only to patients with brain metastases and recurrent or treated glioblastoma.

Glioblastoma (GBM) is the most common, aggressive and malignant type of glioma, with poor prognosis, despite advances in medical knowledge and technology. It's known that some microRNAs (miRNAs) can be dysregulated and associated with tumors. We aim to investigate miRNAs that may have a role as potential biomarkers in human glioblastoma. A search was performed using PubMed, LILACS and SCIELO databases to find papers from 2015 to 2020, related to human in vitro and ex vivo data. From 99 articles, 10 were eligible and 13 dysregulated miRNAs were found with description of regulation, target(s), pathway(s) and mechanism(s). The miRNAs of interest were found and seem to be involved in development and progression of glioblastoma and used as target therapies. Understanding the mechanisms in which those miRNAs are involved and their role in epigenetic pathways that lead to cancer, as well as their potential in clinical application, may improve GBM clinical outcome (CRD42020182706, 07/10/2020, retrospectively registered).

Glioblastoma (GBM) is the most common primary brain tumor with a dismal prognosis. Current standard of treatment is safe maximal tumor resection followed by chemotherapy and radiation. Altered cerebral microcirculation and elevated blood-tumor barrier (BTB) permeability in tumor periphery due to glioma-induced vascular dysregulation allow T1 contrast-enhanced visualization of resectable tumor boundaries. Newer tracers that label the tumor and its vasculature are being increasingly used for intraoperative delineation of glioma boundaries for even more precise resection. Fluorescent 5-aminolevulinic acid (5-ALA) and indocyanine green (ICG) are examples of such intraoperative tracers. Recently, magnetic resonance imaging (MRI)-based MR thermometry is being employed for laser interstitial thermal therapy (LITT) for glioma debulking. However, aggressive, fatal recurrence always occurs. Postsurgical chemotherapy is hampered by the inability of most drugs to cross the blood-brain barrier (BBB). Understanding postsurgical changes in brain microcirculation and permeability is crucial to improve chemotherapy delivery. It is important to understand whether any microcirculatory indices can differentiate between true recurrence and radiation necrosis. LITT leads to peri-ablation BBB opening that persists for several weeks. Whether it can be a conduit for chemotherapy delivery is yet to be explored. This review will address the role of cerebral microcirculation in such emerging ideas in GBM diagnosis and therapy., (© 2021 John Wiley & Sons Ltd.)

Glioblastoma multiforme (GBM) is one of the most common and malignant form of adult brain tumor with a high mortality rate and dismal prognosis. The present standard treatment comprising surgical resection followed by radiation and chemotherapy using temozolomide can broaden patient's survival to some extent. However, the advantages are not palliative due to the development of resistance to the drug and tumor recurrence following the multimodal treatment approaches due to both intra- and intertumoral heterogeneity of GBM. One of the major contributors to temozolomide resistance is O 6 -methylguanine-DNA methyltransferase. Furthermore, deficiency of mismatch repair, base excision repair, and cytoprotective autophagy adds to temozolomide obstruction. Rising proof additionally showed that a small population of cells displaying certain stem cell markers, known as glioma stem cells, adds on to the resistance and tumor progression. Collectively, these findings necessitate the discovery of novel therapeutic avenues for treating glioblastoma. As of late, after understanding the pathophysiology and biology of GBM, some novel therapeutic discoveries, such as drug repurposing, targeted molecules, immunotherapies, antimitotic therapies, and microRNAs, have been developed as new potential treatments for glioblastoma. To help illustrate, "what are the mechanisms of resistance to temozolomide" and "what kind of alternative therapeutics can be suggested" with this fatal disease, a detailed history of these has been discussed in this review article, all with a hope to develop an effective treatment strategy for GBM., (© 2020 International Federation for Cell Biology.)

Introduction: Rehabilitation and exercise interventions are beneficial for the physical and psychological health of cancer survivors. Current clinic-based performance status measures do not accurately capture the survivor's functioning, or rehabilitation and exercise needs. Our primary objective was to explore the feasibility of performing a performance-based functional assessment with brain tumour survivors as a means to inform needs for rehabilitation and exercise., Methods: A feasibility study was conducted with survivors of brain and other neurological cancers attending new patient or follow-up clinics. Survivors were assessed using the Short Physical Performance Battery (SPPB), grip strength and Rosow-Breslau Physical Activity Self-Assessment (RSB)., Results: We approached 40 survivors with brain tumours, and 30 agreed to participate in the study. The SPPB was inversely correlated with Eastern Cooperative Oncology Group (ECOG) scores (r = -.73; p < .01), but scores on the SPPB for individuals classified as ECOG 1 ranged from 5 to 12 out of 12, indicating a large variability in functional scores within this ECOG grade., Conclusion: Implementation of objective functional testing is feasible in the neuro-oncology outpatient clinic. The SPPB appears to best inform the functional status of survivors with brain tumours, facilitating more individualised exercise and rehabilitation referrals., (© 2020 John Wiley & Sons Ltd.)

Background: Individuals with constitutional mismatch repair-deficiency syndrome (CMMR-D) are characterised by early occurrence of colon cancer, haematological malignancies, and brain tumors (malignant gliomas, high-grade gliomas) in childhood, adolescence, and early adulthood. High mutational tumor burden is typical of glioblastoma in CMMR-D patients and could be a reason why this type of glioblastoma responds well to immunotherapies, including those that employ checkpoint inhibitors., Observation: We describe a case of an adolescent with CMMR-D that had been genetically proven by whole exome sequencing (c.2T&gt;A/p.M1K and c.2521delT/p.W841fs PMS2 gene mutation). The patient presented successively with colon cancer and glioblastoma with a high mutational burden. The individualized glioblastoma therapy was based on the biological tumor profile and included immunotherapy with a combination of vaccination with autologous dendritic cells producing IL-12 and nivolumab, in addition to radiotherapy with metronomic temozolomide. The patient is still alive 21 months after the initial glioblastoma diagnosis and shows a complete therapeutic response documented by repeated magnetic resonance examinations., Conclusion: Individuals with CMMR-D should be regularly examined using established algorithms. Whole body magnetic resonance imaging can play a key role, because it enables the early diagnosis of malignancy during the asymptomatic period. Malignancies in CMMR-D patients usually exhibit a hypermutated genotype and respond to immunotherapy. Conventional glioblastoma therapy is only palliative. Patients can benefit from an individualized therapeutic plan based on the tumor biological profile. Extensive molecular analysis of the tumor tissue is necessary. Key words hereditary cancer predisposition syndromes - glioblastoma - whole exome sequencing - immunotherapy - vaccines - checkpoint inhibitors This study was supported by the research project of the Czech Ministry of Health AZV 16-33209A (Next generation sequencing and express profiling as diagnostic tools for personalized therapeutic plans in children with solid tumors). The authors declare they have no potential conflicts of interest concerning drugs, products, or services used in the study. The Editorial Board declares that the manuscript met the ICMJE recommendation for biomedical papers. Submitted: 26. 9. 2018 Accepted: 18. 11. 2018.

In the United States, an individual’s access to resources, insurance status, and wealth are critical social determinants that affect both the risk and outcomes of many diseases. One disease for which the correlation with socioeconomic status (SES) is less well-characterized is glioblastoma (GBM), a devastating brain malignancy. The aim of this study was to review the current literature characterizing the relationship between area-level SES and both GBM incidence and prognosis in the United States. A query of multiple databases was performed to identify the existing data on SES and GBM incidence or prognosis. Papers were filtered by relevant terms and topics. A narrative review was then constructed to summarize the current body of knowledge on this topic. We obtained a total of three papers that analyze SES and GBM incidence, which all report a positive correlation between area-level SES and GBM incidence. In addition, we found 14 papers that focus on SES and GBM prognosis, either overall survival or GBM-specific survival. Those studies that analyze data from greater than 1,530 patients report a positive correlation between area-level SES and individual prognosis, while those with smaller study populations report no significant relationship. Our report underlines the strong association between SES and GBM incidence and highlights the need for large study populations to assess SES and GBM prognosis to ideally guide interventions that improve outcomes. Further studies are needed to determine underlying socioeconomic stresses on GBM risk and outcomes to identify opportunities for intervention. [ABSTRACT FROM AUTHOR]

Glioblastoma multiforme (GBM), also known as grade IV astrocytoma, is the most common and deadly brain tumour. It has a poor prognosis and a low survival rate. GBM cells' immunological escape mechanism helps them resist advanced multimodal therapy. In physiological homeostasis, brain astrocytes and microglia suppress infections and clear the potential pathogen from the system. However, in severe pathological conditions like cancer, the immune response fails to eliminate mutated and rapidly over-proliferating GBM cells. The malignant cells' interactions with immune cells and the neoplasm's immunosuppressive environment enable the avoidance and their clearance. Immunotherapy efficiently addresses these difficulties, as shown by sufficient evidence. This review discusses how GBM cells inhibit and elude the immune system. These include MHC molecule expression alteration and PD-L1 and CTLA-4 immune checkpoint overexpression. Without co-stimulation, these changes induce effector T-cell tolerance and anergy. The review also covers how MDSCs, TAMs, Herpes Virus Entry Mediators, and Human cytomegalovirus protein decrease the effector immune response against glioblastoma. The latter part discusses various therapies that are available in the market or under clinical trials which revolves around combating resistance against the available multimodal therapies. The recent trends indicate that there are various monoclonal antibodies and peptide-based vaccines that can be utilized to overcome the immune evasion technique harbored by GBM cells. A strategic development of Immunotherapy considering these hallmarks of immune evasion may help in designing a therapy that may prove to be effective in killing the GBM cells thereby, improving the overall survival of GBM-affected patients., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Drug delivery routes play an essential role in determining the efficacy and safety of medications. This study focused on the development and optimization of 3D-printed reservoir type implants as a combinational therapy drug delivery system for Glioblastoma Multiforme (GBM) post-surgery, possessing also antibacterial properties. In this study, we used a multimodal agent, Acriflavine (ACF) as an alternative drug to treat GBM. To date, ACF is used only as an antiseptic agent, although it has been shown to possess strong anticancer activities. ACF and a low molecular weight PCL were loaded into 3D-printed reservoir-type implants for sustained drug delivery. The study demonstrated that ACF implants exhibited sustained drug release kinetics, with faster release during the initial 30 days, followed by a gradual decrease over 90 days. This controlled release profile enhances the effectiveness of ACF delivery to tumour targets while minimizing side effects associated with systemic administration. In vitro experiments confirmed the inhibitory activity of ACF against GBM cells compared to non-tumour cells. The study also highlighted the bacteriostatic effects of ACF, making the implants potentially useful for post-surgery infection management, particularly against S. aureus, a common bacterial infection associated with brain surgery. The long-term drug-release capabilities of the implants make them attractive candidates for both tumour inhibition and antibacterial treatment. The study suggests that the developed ACF delivery systems have the potential for future clinical studies. Their ability to provide increased drug efficacy without systemic toxicity makes them promising candidates for cancer therapy and post-surgery infection management., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Glioblastoma multiforme (GBM) is a highly aggressive form of primary brain tumor in adults, which unfortunately has an abysmal prognosis and poor survival rates. The reason behind the poor success rate of several FDA-approved drug is mainly attributed to insufficient drug distribution to the tumor site across the blood-brain barrier (BBB) and induction of resistance. In this study, we have developed a novel nanotherapeutic approach to achieve our goal. PLGA-based nanoencapsulation of both Temozolomide (TMZ) and EGFR inhibitor 3,3'-diindoyl methane (DIM) in a combinatorial approach enhances the delivery of them together. Their synergistic mode of actions, significantly enhances the cytotoxic effect of TMZ in vitro and in vivo. Moreover, the dual-loaded nanoformulation works more efficiently on DNA damage and apoptosis, resulting in a several-fold reduction in tumor burden in vivo, systemic drug toxicity, and increased survival. These findings suggest the preclinical potential of this new treatment strategy., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Glioblastoma (GBM), known as the most malignant and common primary brain tumor of the central nervous system, has finite therapeutic options and a poor prognosis. Studies have shown that host intestinal microorganisms play a role in the immune regulation of parenteral tumors in a number of different ways, either directly or indirectly. However, the potential impact of gut microbiota on tumor microenvironment, particularly glioma immunological milieu, has not been clarified exactly. In this study, by using an orthotopic GBM model, we found gut microbiota dysbiosis caused by antibiotic cocktail treatment boosted the tumor process in vivo. An obvious change that followed gut microbiota dysbiosis was the enhanced percentage of M2-like macrophages in the TME, in parallel with a decrease in the levels of gut microbial metabolite, short-chain fatty acids (SCFAs) in the blood and tumor tissues. Oral supplementation with SCFAs can increase the proportion of M1-like macrophages in the TME, which improves the outcomes of glioma. In terms of mechanism, SCFAs-activated glycolysis in the tumor-associated macrophages may be responsible for the elevated M1 polarization in the TME. This study will enable us to better comprehend the "gut-brain" axis and be meaningful for the development of TAM-targeting immunotherapeutic strategies for GBM patients., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Glioblastoma multiforme (GBM) represents one of the most prevailing and aggressive primary brain tumors among adults. Despite advances in therapeutic approaches, the complex microenvironment of GBM poses significant challenges in its optimal therapy, which are attributed to immune evasion, tumor repopulation by stem cells, and limited drug penetration across the blood-brain barrier (BBB). Nanotechnology has emerged as a promising avenue for GBM treatment, offering biosafety, sustained drug release, enhanced solubility, and improved BBB penetrability. In this review, a comprehensive overview of recent advancements in nanocarrier-based drug delivery systems for GBM therapy is emphasized. The conventional and novel treatment modalities for GBM and the potential of nanocarriers to overcome existing limitations are comprehensively covered. Furthermore, the updates in the clinical landscape of GBM therapeutics are presented in addition to the current status of drugs and patents in the same context. Through a critical evaluation of existing literature, the therapeutic prospect and limitations of nanocarrier-based drug delivery strategies are highlighted offering insights into future research directions and clinical translation., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 International Brain Research Organization (IBRO). Published by Elsevier Inc. All rights reserved.)

Glioblastoma (GBM) is a fatal adult brain tumor with an extremely poor prognosis. GBM poses significant challenges for targeted therapies due to its intra- and inter-tumoral heterogeneity, a highly immunosuppressive microenvironment, diffuse infiltration into normal brain parenchyma, protection by the blood-brain barrier and acquisition of therapeutic resistance. Recent studies have implicated epigenetic modifiers as key players driving tumorigenesis, resistance, and progression of GBM. While the vast majority of GBM research on epigenetic modifiers thus far has focused predominantly on elucidating the functional roles and targeting of DNA methyltransferases and histone deacetylases, emerging evidence indicates that histone acetyltransferases (HATs) also play a key role in mediating plasticity and therapeutic resistance in GBM. Here, we will provide an overview of HATs, their dual roles and functions in cancer as both tumor suppressors and oncogenes and focus specifically on their implications in GBM resistance. We also discuss the technical challenges in developing selective HAT inhibitors and highlight their promise as potential anti-cancer therapeutics for treating intractable cancers such as GBM., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Glioblastoma (GBM) poses a significant medical challenge due to its aggressive nature and poor prognosis. Mitochondrial unfolded protein response (UPRmt) and the heat shock factor 1 (HSF1) pathway play crucial roles in GBM pathogenesis. Post-translational modifications, such as SUMOylation, regulate the mechanism of action of HSF1 and may influence the progression of GBM. Understanding the interplay between SUMOylation-modified HSF1 and GBM pathophysiology is essential for developing targeted therapies., Methods: We conducted a comprehensive investigation using cellular, molecular, and in vivo techniques. Cell culture experiments involved establishing stable cell lines, protein extraction, Western blotting, co-immunoprecipitation, and immunofluorescence analysis. Mass spectrometry was utilized for protein interaction studies. Computational modeling techniques were employed for protein structure analysis. Plasmid construction and lentiviral transfection facilitated the manipulation of HSF1 SUMOylation. In vivo studies employed xenograft models for tumor growth assessment., Results: Our research findings indicate that HSF1 primarily undergoes SUMOylation at the lysine residue K298, enhancing its nuclear translocation, stability, and downstream heat shock protein expression, while having no effect on its trimer conformation. SUMOylated HSF1 promoted the UPRmt pathway, leading to increased GBM cell proliferation, migration, invasion, and reduced apoptosis. In vivo studies have confirmed that SUMOylation of HSF1 enhances its oncogenic effect in promoting tumor growth in GBM xenograft models., Conclusion: This study elucidates the significance of SUMOylation modification of HSF1 in driving GBM progression. Targeting SUMOylated HSF1 may offer a novel therapeutic approach for GBM treatment. Further investigation into the specific molecular mechanisms influenced by SUMOylated HSF1 is warranted for the development of effective targeted therapies to improve outcomes for GBM patients., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

Introduction: Inherent variations between inter-center data can undermine the robustness of segmentation models when applied at a specific center (dataset shift). We investigated whether specialized center-specific models are more effective compared to generalist models based on multi-center data, and how center-specific data could enhance the performance of generalist models within a particular center using a fine-tuning transfer learning approach. For this purpose, we studied the dataset shift at center level and conducted a comparative analysis to assess the impact of data source on glioblastoma segmentation models., Methods & Materials: The three key components of dataset shift were studied: prior probability shift-variations in tumor size or tissue distribution among centers; covariate shift-inter-center MRI alterations; and concept shift-different criteria for tumor segmentation. BraTS 2021 dataset was used, which includes 1251 cases from 23 centers. Thereafter, 155 deep-learning models were developed and compared, including 1) generalist models trained with multi-center data, 2) specialized models using only center-specific data, and 3) fine-tuned generalist models using center-specific data., Results: The three key components of dataset shift were characterized. The amount of covariate shift was substantial, indicating large variations in MR imaging between different centers. Glioblastoma segmentation models tend to perform best when using data from the application center. Generalist models, trained with over 700 samples, achieved a median Dice score of 88.98%. Specialized models surpassed this with 200 cases, while fine-tuned models outperformed with 50 cases., Conclusions: The influence of dataset shift on model performance is evident. Fine-tuned and specialized models, utilizing data from the evaluated center, outperform generalist models, which rely on data from other centers. These approaches could encourage medical centers to develop customized models for their local use, enhancing the accuracy and reliability of glioblastoma segmentation in a context where dataset shift is inevitable., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Introduction: Combination immunotherapy holds promise for improving survival in responsive glioblastoma (GBM) patients. Programmed death-ligand 1 (PD-L1) expression in immune microenvironment (IME) is the most important predictive biomarker for immunotherapy. Due to the heterogeneous distribution of PD-L1, post-operative histopathology fails to accurately capture its expression in residual tumors, making intra-operative diagnosis crucial for GBM treatment strategies. However, the current methods for evaluating the expression of PD-L1 are still time-consuming., Objective: To overcome the PD-L1 heterogeneity and enable rapid, accurate, and label-free imaging of PD-L1 expression level in GBM IME at the tissue level., Methods: We proposed a novel intra-operative diagnostic method, Machine Learning Cascade (MLC)-based Raman histopathology, which uses a coordinate localization system (CLS), hierarchical clustering analysis (HCA), support vector machine (SVM), and similarity analysis (SA). This method enables visualization of PD-L1 expression in glioma cells, CD8 + T cells, macrophages, and normal cells in addition to the tumor/normal boundary. The study quantified PD-L1 expression levels using the tumor proportion, combined positive, and cellular composition scores (TPS, CPS, and CCS, respectively) based on Raman data. Furthermore, the association between Raman spectral features and biomolecules was examined biochemically., Results: The entire process from signal collection to visualization could be completed within 30 min. In an orthotopic glioma mouse model, the MLC-based Raman histopathology demonstrated a high average accuracy (0.990) for identifying different cells and exhibited strong concordance with multiplex immunofluorescence (84.31 %) and traditional pathologists' scoring (R 2  ≥ 0.9). Moreover, the peak intensities at 837 and 874 cm -1 showed a positive linear correlation with PD-L1 expression level., Conclusions: This study introduced a new and extendable diagnostic method to achieve rapid and accurate visualization of PD-L1 expression in GBM IMB at the tissular level, leading to great potential in GBM intraoperative diagnosis for guiding surgery and post-operative immunotherapy., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Production and hosting by Elsevier B.V.)

Glyphosate, the world's most widely used herbicide, has a low toxicity rating despite substantial evidence of adverse health effects. Furthermore, glyphosate-based formulations (GBFs) contain several other chemicals, some of which are known to be harmful. Additionally, chronic, and acute exposure to GBFs among rural workers may lead to health impairments, such as neurodegenerative diseases and cancer. P53 is known as a tumor suppressor protein, acting as a key regulator of the cellular response to stress and DNA damage. Therefore, mutations in the TP53 gene, which encodes p53, are common genetic alterations found in various types of cancer. Therefore, this study aimed to evaluate the cytotoxicity and genotoxicity of GBF in two glioblastoma cell lines: U87MG (TP53-proficient) and U251MG (TP53-mutant). Additionally, the study aimed to identify the main proteins involved in the response to GBF exposure using Systems Biology in a network containing p53 and another network without p53. The MTT assay was used to study the toxicity of GBF in the cell lines, the clonogenic assay was used to investigate cell survival, and the Comet Assay was used for genotoxicity evaluation. For data analysis, bioinformatics tools such as String 12.0 and Stitch 5.0 were applied, serving as a basis for designing binary networks in the Cytoscape 3.10.1 program. From the in vitro test analyses, it was observed a decrease in cell viability at doses starting from 10 ppm. Comet Assay at concentrations of 10 ppm and 30 ppm for the U251MG and U87MG cell lines, respectively observed DNA damage. The network generated with systems biology showed that the presence of p53 is important for the regulation of biological processes involved in genetic stability and neurotoxicity, processes that did not appear in the TP53-mutant network., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Fernanda Rabaioli da Silva reports equipment, drugs, or supplies was provided by Conselho Nacional de Desenvolvimento Científico e Tecnológico - CNPq (Brazil). If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Sonodynamic therapy (SDT) has garnered significant attention in cancer treatment, however, the low-yield reactive oxygen species (ROS) generation from sonosensitizers remains a major challenge. In this study, titanium boride nanosheets (TiB 2 NSs) with photo-enhanced sonodynamic efficiency was fabricated for SDT of glioblastoma (GBM). Compared with commonly-used TiO 2 nanoparticles, the obtained TiB 2 NSs exhibited much higher ROS generation efficiency under ultrasound (US) irradiation due to their narrower band gap (2.50 eV). Importantly, TiB 2 NSs displayed strong localized surface plasmon resonance (LSPR) effect in the second near-infrared (NIR II) window, which facilitated charge transfer rate and improved the separation efficiency of US-triggered electron-hole pairs, leading to photo-enhanced ROS generation efficiency. Furthermore, TiB 2 NSs were encapsulated with macrophage cell membranes (CM) and then modified with RGD peptide to construct biomimetic nanoagents (TiB 2 @CM-RGD) for efficient blood-brain barrier (BBB) penetrating and GBM targeting. After intravenous injection into the tumor-bearing mouse, TiB 2 @CM-RGD can efficiently cross BBB and accumulate in the tumor sites. The tumor growth was significantly inhibited under simultaneous NIR II laser and US irradiation without causing appreciable long-term toxicity. Our work highlighted a new type of multifunctional titanium-based sonosensitizer with photo-enhanced sonodynamic efficiency for GBM treatment. STATEMENT OF SIGNIFICANCE: Titanium boride nanosheets (TiB 2 NSs) with photo-enhanced sonodynamic efficiency was fabricated for SDT of glioblastoma (GBM). The obtained TiB 2 NSs displayed strong localized surface plasmon resonance (LSPR) effect in the second near-infrared (NIR II) window, which facilitated charge transfer rate and improved the separation efficiency of US-triggered electron-hole pairs, leading to photo-enhanced ROS generation efficiency. Furthermore, TiB 2 NSs were encapsulated with macrophage cell membranes (CM) and then modified with RGD peptide to construct biomimetic nanoagents (TiB 2 @CM-RGD) for efficient blood-brain barrier (BBB) penetrating and GBM targeting. After intravenous injection into the tumor-bearing mouse, TiB 2 @CM-RGD can efficiently cross BBB and accumulate in the tumor sites. The tumor growth was significantly inhibited under simultaneous NIR II laser and US irradiation without causing appreciable long-term toxicity., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.)

In our continuing effort devoted at developing agents targeting the EphA2 receptor by means of protein-protein interaction (PPI) inhibitors, we report here the design and synthesis of a new class of l-β-homotryptophan conjugates of 3-β-hydroxy-Δ 5 -cholenic acid bearing a set of arylsulfonyl substituents at the indole nitrogen atom. An extensive structure-activity relationship (SAR) analysis indicates that the presence of a bulky lipophilic moiety at the indole nitrogen is fundamental for improving potency on the EphA2 receptor, while abrogating activity on the EphB1-EphB3 receptor subtypes. A rational exploration, guided by the combined application of an experimental design on σ p and π physicochemical descriptors and docking simulations, led to the discovery of UniPR1454, a 1-(4-(trifluoromethyl)phenyl)sulfonyl derivative acting as potent and competitive EphA2 antagonist able to inhibit ephrin-A1 dependent signals and to reduce proliferation of glioblastoma (U251) cell line at micromolar concentration., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Massimiliano Tognolini reports financial support was provided by Italian Association for Cancer Research. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Masson SAS.. All rights reserved.)

For diseases with high morbidity rates such as Glioblastoma Multiforme, the prognostic and treatment planning pipeline requires a comprehensive analysis of imaging, clinical, and molecular data. Many mutations have been shown to correlate strongly with the median survival rate and response to therapy of patients. Studies have demonstrated that these mutations manifest as specific visual biomarkers in tumor imaging modalities such as MRI. To minimize the number of invasive procedures on a patient and for the overall resource optimization for the prognostic and treatment planning process, the correlation of imaging and molecular features has garnered much interest. While the tumor mass is the most significant feature, the impacted tissue surrounding the tumor is also a significant biomarker contributing to the visual manifestation of mutations - which has not been studied as extensively. The pattern of tumor growth impacts the surrounding tissue accordingly, which is a reflection of tumor properties as well. Modeling how the tumor growth impacts the surrounding tissue can reveal important information about the patterns of tumor enhancement, which in turn has significant diagnostic and prognostic value. This paper presents the first work to automate the computational modeling of the impacted tissue surrounding the tumor using generative deep learning. The paper isolates and quantifies the impact of the Tumor Invasion (TI) on surrounding tissue based on change in mutation status, subsequently assessing its prognostic value. Furthermore, a TI Generative Adversarial Network (TI-GAN) is proposed to model the tumor invasion properties. Extensive qualitative and quantitative analyses, cross-dataset testing, and radiologist blind tests are carried out to demonstrate that TI-GAN can realistically model the tumor invasion under practical challenges of medical datasets such as limited data and high intra-class heterogeneity., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Glioblastoma (GBM) stands for the most common and aggressive type of brain tumour in adults. It is highly invasive, which explains its short rate of survival. Little is known about its risk factors, and current therapy is still ineffective. Hence, efforts are underway to develop novel and effective treatment approaches against this type of cancer. Exosomes are being explored as a promising strategy for conveying and delivering therapeutic cargo to GBM cells. They can fuse with the GBM cell membrane and, consequently, serve as delivery systems in this context. Due to their nanoscale size, exosomes can cross the blood-brain barrier (BBB), which constitutes a significant hurdle to most chemotherapeutic drugs used against GBM. They can subsequently inhibit oncogenes, activate tumour suppressor genes, induce immune responses, and control cell growth. However, despite representing a promising tool for the treatment of GBM, further research and clinical studies regarding exosome biology, engineering, and clinical applications still need to be completed. Here, we sought to review the application of exosomes in the treatment of GBM through an in-depth analysis of the scientific and clinical studies on the entire process, from the isolation and purification of exosomes to their design and transformation into anti-oncogenic drug delivery systems. Surface modification of exosomes to enhance BBB penetration and GBM-cell targeting is also a topic of discussion., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Curcumin (CUR) has received worldwide attention for its beneficial effects on human health. Research report possible cytotoxic activity against various cancers, including glioblastoma. So far, little attention has been given to the binding properties of CUR to lipid membranes, which influences their electrical characteristics and can provide insight into their membrane-permeation abilities. Biophysical interactions between the polyphenol and in vitro models (liposomes and LN-18 human glioblastoma cells) were investigated by monitoring zeta potential and the membrane's surface charge as a function of pH. We focused on practical measurements and undertook a theoretical analysis of interactions in the natural cell membrane. We used the MTT assay to evaluate the viability of CUR-treated cells. Measurements performed using the Electrophoretic Light Scattering method demonstrated the dose-dependent effect of CUR on both membrane surface charge and zeta potential analyzed in vitro models. We determined theoretical parameters characterizing the cell membrane based on a quantitative description of the adsorption equilibria formed due to the binding of solution ions to the membrane of glioblastoma cells. The interaction of CUR with liposomes and human cancer cells is pH-dependent., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Rapid proliferation is a hallmark of glioblastoma multiforme (GBM) and a major contributor to its recurrence. Aberrant ubiquitination has been implicated in various diseases, including cancer. In our preliminary studies, we identified Ubiquitin-conjugating enzyme E2S (UBE2S) as a potential glioma biomarker, exhibiting close associations with glioma grade and protein phosphatase 1, regulatory subunit 105 (Ki67) expression levels. However, the underlying molecular mechanisms remained elusive. NF-κB is an important signaling pathway that promotes GBM proliferation. Direct intervention targeting NF-κB has not yielded the expected results, prompting the exploration of new molecules for regulating NF-κB as a new direction., Methods: This study employed methods including yeast two-hybrid and immunoprecipitation to uncover the interaction between UBE2S and A kinase interacting protein 1 (AKIP1). Laser confocal microscopy was used to observe the localization of UBE2S and AKIP1. Dual luciferase reporter genes were utilized to observe the activation of NF-κB., Results: Our findings demonstrate that UBE2S deficiency significantly impedes GBM progression, both in vitro and in vivo. Mechanistically, UBE2S plays a crucial role in recruiting Ubiquitin Specific Peptidase 15 (USP15), facilitating the removal of K11-linked ubiquitination on AKIP1. This action enhances AKIP1 stability within the GBM context. The resulting increase in AKIP1 levels further augments nuclear factor kappa-B (NF-κB) transcriptional activity, leading to the upregulation of downstream genes regulated by the NF-κB pathway, thereby promoting GBM progression., Conclusions: In summary, our findings reveal the role of the UBE2S/AKIP1-NF-κB axis in regulating GBM progression and provide novel evidence supporting UBE2S as a potential drug target for GBM., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Glioblastoma (GBM) resection and medication treatment are limited, and local drug therapies are required. This study aims to create a hybrid system comprising liposome-like particles (LLP-DOX) encapsulated in chitosan/hyaluronic acid/polyethyleneimine (CHI/HA/PEI) hydrogels, enabling controlled local delivery of doxorubicin (DOX) into the resection cavity for treating GBM. CHI/HA/PEI hydrogels were characterized morphologically, physically, chemically, mechanically, and thermally. Findings revealed a high network and compact micro-network structure, along with enhanced physical and thermal stability compared to CHI/HA hydrogels. Simultaneously, drug release from CHI/HA/PEI/LLP-DOX hydrogels was assessed, revealing continuous and controlled release up to the 148th hour, with no significant burst release. Cell studies showed that CHI/HA/PEI hydrogels are biocompatible with low genotoxicity. Additionally, LLP-DOX-loaded CHI/HA/PEI hydrogels significantly decreased cell viability and gene expression levels compared to LLP-DOX alone. It was also observed that the viability of GBM spheroids decreased over time when interacting with CHI/HA/PEI/LLP-DOX hydrogels, accompanied by a reduction in total surface area and an increase in apoptotic tendencies. In this study, we hypothesized that creating a hybrid drug delivery system by encapsulating DOX-loaded LLPs within a CHI/HA/PEI hydrogel matrix could achieve sustained drug release, improve anticancer efficacy via localized treatment, and effectively mitigate GBM progression for 3D microtissues., Competing Interests: Declaration of competing interest The authors declare that no known financial interests or any personal that could have influence in the work of this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Mutations of the TP53 oncosuppressor gene are frequent events in patients with malignant tumors including IDH-wildtype GBM (GBM IDH wt). However, the effective impact of TP53 mutations on prognosis has been poorly evaluated., Methods: We performed a retrospective study investigating the impact of TP53 mutations on patients with GBM IDH wt. Only patients with PS=0-1, treated with temozolomide concurrent with and adjuvant to radiotherapy, and younger than 70 years assessed with NGS were included in the analysis., Results: 97 GBM IDH wt have been selected. The median follow-up was 34.5 months (95 %CI, 30.6 - NA). Overall, 20 patients (19.4 %) presented a TP53 mutation. There were no significant differences in terms of TERT mutation (75 % vs 79.2 %) between TP53 mutated and TP53 wild-type (wt) patients. We detected 6 TP53 mutations not previously described within GBM IDH wt patients. The overall survival (OS) did not significantly differ between TP53 mutated and wt patients (HR 0.69, 95 %CI 0.37-1.27, p = 0.24). Considering only patients with an OS longer than 36 months (n = 10), the presence of a TP53 mutation was significantly associated with prolonged survival (45.6 months vs Not Reached, p = 0.037)., Conclusion: The presence of a TP53 mutation does not appear to be correlated with overall survival in this patient cohort. While there is an association with survival for patients with an OS of 36 months or longer, the number of patients is low and there is no available evidence correlating TP53 mutations to long-term survivors., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier GmbH. All rights reserved.)

Background and Objective: Patients with glioblastoma have a five-year relative survival rate of less than 5 %. Thus, accurately predicting the overall survival (OS) of patients with glioblastoma is crucial for effective treatment planning., Methods: To fully leverage the imaging characteristics of glioblastomas, we propose a segmentation-guided regression method for predicting OS of patients with brain tumors using multimodal magnetic resonance imaging. Specifically, a brain tumor segmentation network was first pre-trained without leveraging survival information. Subsequently, the survival regression network was jointly trained with the guidance of brain tumor segmentation, focusing on tumor voxels and suppressing irrelevant backgrounds., Results: Our proposed framework, based on the well-known backbone of UNETR++, achieved a Dice score of 0.7910, Spearman correlation of 0.4112, and Harrell's concordance index of 0.6488. The model consistently showed promising results compared with baseline methods on two different datasets (BraTS and UCSF-PDGM). Furthermore, ablation studies on our training configurations demonstrated that both the pre-training segmentation network and contrastive loss significantly improved all metrics for OS prediction., Conclusions: In this study, we propose a joint learning framework based on a pre-trained segmentation backbone for OS prediction by leveraging a brain tumor segmentation map. By utilizing a spatial feature map, our model can operate using a sliding-window approach, which can be adopted by varying the matrix sizes and resolutions of the input images., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Glioblastoma multiforme (GBM) is an aggressive, incurable brain tumor with poor prognosis and limited treatment options. Temozolomide (TMZ) is the standard chemotherapeutic treatment for GBM, but its efficacy has drawn strong criticism from clinicians due to short survival gains and frequent relapses. One critical limitation of TMZ therapy is the hyperactivation of DNA repair pathways, which over time neutralizes the cytotoxic effects of TMZ, thus highlighting the urgent need for new treatment approaches. Addressing this, our study explores the therapeutic potential of in-house-designed phenothiazine-based Tousled-like kinase-1 (TLK1) inhibitors for GBM treatment. TLK1, overexpressed in GBM, plays a role in DNA repair. Phenothiazines are known to cross the blood-brain barrier (BBB). Among all molecules, J54 was identified as a potential lead molecule with improved cytotoxicity. In the context of O6-methylguanine-DNA methyltransferase (MGMT)-deficient GBM cells, the combined administration of phenothiazines and TMZ exhibited a collective reduction in clonogenic growth, coupled with anti-migratory and anti-invasion effects. Conversely, in MGMT-proficient cells, phenothiazine monotherapy alone showed reduced clonogenic growth, along with anti-migratory and anti-invasion effects. Notably, a synergistic increase in γH2AX levels and concurrent attenuation of DNA repair upon combinatorial exposure to TMZ and J54 were observed, implying increased cytotoxicity due to sustained DNA strand breaks. Overall, this study provides new insights into TLK1 inhibition for GBM therapy. Collectively, these findings indicate that TLK1 is one of the upregulated kinases in GBM and phenothiazine-based TLK1 inhibitors could be a promising treatment option for GBM patients., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

Glioblastoma multiforme (GBM) represents one of the most critical oncological diseases in neurological practice, being considered highly aggressive with a dismal prognosis. At a worldwide level, new therapeutic methods are continuously being researched. Magnetic hyperthermia (MHT) has been investigated for more than 30 years as a solution used as a single therapy or combined with others for glioma tumor assessment in preclinical and clinical studies. It is based on magnetic nanoparticles (MNPs) that are injected into the tumor, and, under the effect of an external alternating magnetic field, they produce heat with temperatures higher than 42 °C, which determines cancer cell death. It is well known that iron oxide nanoparticles have received FDA approval for anemia treatment and to be used as contrast substances in the medical imagining domain. Today, energetic, efficient MNPs are developed that are especially dedicated to MHT treatments. In this review, the subject's importance will be emphasized by specifying the number of patients with cancer worldwide, presenting the main features of GBM, and detailing the physical theory accompanying the MHT treatment. Then, synthesis routes for thermally efficient MNP manufacturing, strategies adopted in practice for increasing MHT heat performance, and significant in vitro and in vivo studies are presented. This review paper also includes combined cancer therapies, the main reasons for using these approaches with MHT, and important clinical studies on human subjects found in the literature. This review ends by describing the most critical challenges associated with MHT and future perspectives. It is concluded that MHT can be successfully and regularly applied as a treatment for GBM if specific improvements are made.

Glioblastoma multiforme is a highly aggressive form of brain cancer, with a median survival time for diagnosed patients of 15 months. Treatment of this cancer is typically a combination of radiation, chemotherapy and surgical removal of the tumour. However, the highly invasive and diffuse nature of glioblastoma makes surgical intrusions difficult, and the diffusive properties of glioblastoma are poorly understood. In this paper, we introduce a stochastic interacting particle system as a model of in vitro glioblastoma migration, along with a maximum likelihood-algorithm designed for inference using microscopy imaging data. The inference method is evaluated on in silico simulation of cancer cell migration, and then applied to a real data set. We find that the inference method performs with a high degree of accuracy on the in silico data, and achieve promising results given the in vitro data set., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.)