Sex-Specific Differences in Glioblastoma

Identification of new targets for glioblastoma therapy based on a DNA expression microarray

This study provides a comprehensive perspective on the deregulated pathways and impaired biological functions prevalent in human glioblastoma (GBM). In order to characterize differences in gene expression between individuals diagnosed with GBM and healthy brain tissue, we have designed and manufactured a specific, custom DNA microarray. The results obtained from differential gene expression analysis were validated by RT-qPCR. The datasets obtained from the analysis of common differential expressed genes in our cohort of patients were used to generate protein-protein interaction networks of functionally enriched genes and their biological functions. This network analysis, let us to identify 16 genes that exhibited either up-regulation (CDK4, MYC, FOXM1, FN1, E2F7, HDAC1, TNC, LAMC1, EIF4EBP1 and ITGB3) or down-regulation (PRKACB, MEF2C, CAMK2B, MAPK3, MAP2K1 and PENK) in all GBM patients. Further investigation of these genes and enriched pathways uncovered in this investigation promises to serve as a foundational step in advancing our comprehension of the molecular mechanisms underpinning GBM pathogenesis. Consequently, the present work emphasizes the critical role that the unveiled molecular pathways likely play in shaping innovative therapeutic approaches for GBM management. We finally proposed in this study a list of compounds that target hub of GBM-related genes, some of which are already in clinical use, underscoring the potential of those genes as targets for GBM treatment.

Glioma Tumor Grading Using Radiomics on Conventional MRI: A Comparative Study of WHO 2021 and WHO 2016 Classification of Central Nervous Tumors

BACKGROUND

Glioma grading transformed in World Health Organization (WHO) 2021 CNS tumor classification, integrating molecular markers. However, the impact of this change on radiomics-based machine learning (ML) classifiers remains unexplored.

PURPOSE

To assess the performance of ML in classifying glioma tumor grades based on various WHO criteria.

STUDY TYPE

Retrospective.

SUBJECTS

A neuropathologist regraded gliomas of 237 patients into WHO 2016 and 2021 from 2007 criteria.

FIELD STRENGTH/SEQUENCE

Multicentric 0.5 to 3 Tesla; pre- and post-contrast T1-weighted, T2-weighted, and fluid-attenuated inversion recovery.

ASSESSMENT

Radiomic features were selected using random forest-recursive feature elimination. The synthetic minority over-sampling technique (SMOTE) was implemented for data augmentation. Stratified 10-fold cross-validation with and without SMOTE was used to evaluate 11 classifiers for 3-grade (2, 3, and 4; WHO 2016 and 2021) and 2-grade (low and high grade; WHO 2007 and 2021) classification. Additionally, we developed the models on data randomly divided into training and test sets (mixed-data analysis), or data divided based on the centers (independent-data analysis).

STATISTICAL TESTS

We assessed ML classifiers using sensitivity, specificity, accuracy, and the area under the receiver operating characteristic curve (AUC). Top performances were compared with a t-test and categorical data with the chi-square test using a significance level of P < 0.05.

RESULTS

In the mixed-data analysis, Stacking Classifier without SMOTE achieved the highest accuracy (0.86) and AUC (0.92) in 3-grade WHO 2021 grouping. The results of WHO 2021 were significantly better than WHO 2016 (P-value<0.0001). In the 2-grade analysis, ML achieved 1.00 in all metrics. In the independent-data analysis, ML classifiers showed strong discrimination between grade 2 and 4, despite lower performance metrics than the mixed analysis.

DATA CONCLUSION

ML algorithms performed better in glioma tumor grading based on WHO 2021 criteria. Nonetheless, the clinical use of ML classifiers needs further investigation.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Navigating glioblastoma complexity: the interplay of neurotransmitters and chromatin

Glioblastoma is the most aggressive brain cancer with an unfavorable prognosis for patient survival. Glioma stem cells, a subpopulation of cancer cells, drive tumor initiation, self-renewal, and resistance to therapy and, together with the microenvironment, play a crucial role in glioblastoma maintenance and progression. Neurotransmitters such as noradrenaline, dopamine, and serotonin have contrasting effects on glioblastoma development, stimulating or inhibiting its progression depending on the cellular context and through their action on glioma stem cells, perhaps changing the epigenetic landscape. Recent studies have revealed that serotonin and dopamine induce chromatin modifications related to transcriptional plasticity in the mammalian brain and possibly in glioblastoma; however, this topic still needs to be explored because of its potential implications for glioblastoma treatment. Also, it is essential to consider that neurotransmitters' effects depend on the tumor's microenvironment since it can significantly influence the response and behavior of cancer cells. This review examines the possible role of neurotransmitters as regulators of glioblastoma development, focusing on their impact on the chromatin of glioma stem cells.

Unlocking novel therapeutic avenues in glioblastoma: Harnessing 4-amino cyanine and miRNA synergy for next-gen treatment convergence

Glioblastoma (GBM) poses a formidable challenge in oncology due to its aggressive nature and dismal prognosis, with average survival rates around 15 months despite conventional treatments. This review proposes a novel therapeutic strategy for GBM by integrating microRNA (miRNA) therapy with 4-amino cyanine molecules possessing near-infrared (NIR) properties. miRNA holds promise in regulating gene expression, particularly in GBM, making it an attractive therapeutic target. 4-amino cyanine molecules, especially those with NIR properties, have shown efficacy in targeted tumor cell degradation. The combined approach addresses gene expression regulation and precise tumor cell degradation, offering a breakthrough in GBM treatment. Additionally, the review explores noncoding RNAs classification and characteristics, highlighting their role in GBM pathogenesis. Advanced technologies such as antisense oligonucleotides (ASOs), locked nucleic acids (LNAs), and peptide nucleic acids (PNAs) show potential in targeting noncoding RNAs therapeutically, paving the way for precision medicine in GBM. This synergistic combination presents an innovative approach with the potential to advance cancer therapy in the challenging landscape of GBM.

Neuroradiological, genetic and clinical characteristics of histone H3 K27-mutant diffuse midline gliomas in the Kansai Molecular Diagnosis Network for CNS Tumors (Kansai Network): multicenter retrospective cohort

This study aims to elucidate the clinical and molecular characteristics, treatment outcomes and prognostic factors of patients with histone H3 K27-mutant diffuse midline glioma. We retrospectively analyzed 93 patients with diffuse midline glioma (47 thalamus, 24 brainstem, 12 spinal cord and 10 other midline locations) treated at 24 affiliated hospitals in the Kansai Molecular Diagnosis Network for CNS Tumors. Considering the term "midline" areas, which had been confused in previous reports, we classified four midline locations based on previous reports and anatomical findings. Clinical and molecular characteristics of the study cohort included: age 4-78 years, female sex (41%), lower-grade histology (56%), preoperative Karnofsky performance status (KPS) scores ≥ 80 (49%), resection (36%), adjuvant radiation plus chemotherapy (83%), temozolomide therapy (76%), bevacizumab therapy (42%), HIST1H3B p.K27M mutation (2%), TERT promoter mutation (3%), MGMT promoter methylation (9%), BRAF p.V600E mutation (1%), FGFR1 mutation (14%) and EGFR mutation (3%). Median progression-free and overall survival time was 9.9 ± 1.0 (7.9-11.9, 95% CI) and 16.6 ± 1.4 (13.9-19.3, 95% CI) months, respectively. Female sex, preoperative KPS score ≥ 80, adjuvant radiation + temozolomide and radiation ≥ 50 Gy were associated with favorable prognosis. Female sex and preoperative KPS score ≥ 80 were identified as independent good prognostic factors. This study demonstrated the current state of clinical practice for patients with diffuse midline glioma and molecular analyses of diffuse midline glioma in real-world settings. Further investigation in a larger population would contribute to better understanding of the pathology of diffuse midline glioma.

Unraveling the noncoding RNA landscape in glioblastoma: from pathogenesis to precision therapeutics

Glioblastoma (GBM) is an aggressive type IV brain tumor that originates from astrocytes and has a poor prognosis. Despite intensive research, survival rates have not significantly improved. Noncoding RNAs (ncRNAs) are emerging as critical regulators of carcinogenesis, progression, and increased treatment resistance in GBM cells. They influence angiogenesis, migration, epithelial-to-mesenchymal transition, and invasion in GBM cells. ncRNAs, such as long ncRNAs (lncRNAs), microRNAs (miRNAs), and circular RNAs (circRNAs), are commonly dysregulated in GBM. miRNAs, such as miR-21, miR-133a, and miR-27a-3p, are oncogenes that increase cell proliferation, metastasis, and migration by targeting TGFBR1 and BTG2. In contrast, lncRNAs, such as HOXD-AS2 and LINC00511, are oncogenes that increase the migration, invasion, and proliferation of cells. CircRNAs, such as circ0001730, circENTPD7, and circFOXO3, are oncogenes responsible for cell growth, angiogenesis, and viability. Developing novel therapeutic strategies targeting ncRNAs, cell migration, and angiogenesis is a promising approach for GBM. By targeting these dysregulated ncRNAs, we can potentially restore a healthy balance in gene expression and influence disease progression. ncRNAs abound within GBM, demonstrating significant roles in governing the growth and behavior of these tumors. They may also be useful as biomarkers or targets for therapy. The use of morpholino oligonucleotides (MOs) suppressing the oncogene expression of HOTAIR, BCYRN1, and cyrano, antisense oligonucleotides (ASOs) suppressing the expression of ncRNAs such as MALAT1 and miR-10b, locked nucleic acids (LNAs) suppressing miR-21, and peptide nucleic acids (PNAs) suppressing the expression of miR-155 inhibited the PI3K pathway, tumor growth, angiogenesis, proliferation, migration, and invasion. Targeting oncogenic ncRNAs with RNA-interfering strategies such as MOs, ASOs, LNAs, CRISPR-Cas9 gene editing, and PNA approaches may represent a promising therapeutic strategy for GBM. This review emphasizes the critical role of ncRNAs in GBM pathogenesis, as well as the potential for new therapeutic strategies targeting these pathways to improve the prognosis and quality of life for GBM patients.

Pharmacological treatment of depression in patients with brain tumors

Patients with brain tumors suffer from intense psychosocial distress. Although the prevalence of depressive symptoms in patients with brain tumors is high, the pharmacological antidepressant treatment of those patients is not well defined and results from clinical trials are largely missing. In this review, we describe the current standard of evidence and clinical guidelines for the pharmacological treatment of depression in brain tumor patients. We present specific side effects and interactions that should guide treatment decisions. Furthermore, we provide evidence for the diagnosis, screening and risk factors for depression in brain tumor patients and we elaborate on potential antineoplastic effects of antidepressant drugs and ongoing clinical trials. Antidepressant drugs should not be withheld from patients with brain tumors. Future clinical trials should explore the effectiveness and side effects of antidepressants in this specific patient population.

Revolutionizing Brain Tumor Care: Emerging Technologies and Strategies

Glioblastoma multiforme (GBM) is one of the most aggressive forms of brain tumor, characterized by a daunting prognosis with a life expectancy hovering around 12-16 months. Despite a century of relentless research, only a select few drugs have received approval for brain tumor treatment, largely due to the formidable barrier posed by the blood-brain barrier. The current standard of care involves a multifaceted approach combining surgery, irradiation, and chemotherapy. However, recurrence often occurs within months despite these interventions. The formidable challenges of drug delivery to the brain and overcoming therapeutic resistance have become focal points in the treatment of brain tumors and are deemed essential to overcoming tumor recurrence. In recent years, a promising wave of advanced treatments has emerged, offering a glimpse of hope to overcome the limitations of existing therapies. This review aims to highlight cutting-edge technologies in the current and ongoing stages of development, providing patients with valuable insights to guide their choices in brain tumor treatment.

Expression and prognostic significance of microsomal triglyceride transfer protein in brain tumors: a retrospective cohort study

Background

Glioblastoma (GBM) is the most common malignant brain tumor and has poor survival. An elevated cholesterol level is involved occurrence and progression of brain tumors. Microsomal triglyceride transfer protein (MTTP) is a target for lowering lipids, and its inhibition helps to improve hyperlipidemia. However, whether the altered expression of MTTP affects the development and prognosis of brain tumors is currently unidentified. The purpose of this study is to determine MTTP as a prognostic marker for brain tumors.

Methods

Data for patients with brain cancers and control brain tissue were acquired from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The datasets were analyzed using Mann-Whitney U-test or t-test to compare the expression of MTTP in normal and brain tumor tissues. To examine whether MTTP affected the prognosis of patients with brain tumors, log-rank test and multivariable Cox proportional hazard regression were conducted.

Results

The expression of MTTP was significantly upregulated in brain tumors and was correlated with age, tumor stage, and isocitrate dehydrogenase (IDH) mutation. Importantly, increased MTTP expression in brain tumors is associated with poor patient survival.

Conclusions

High MTTP expression is associated with brain tumor development, tumor stage, and prognosis. Therefore, MTTP is an independent prognostic indicator for brain tumors, which can serve as one of the possible targets for adjuvant treatment of GBM.

Altering biomolecular condensates as a potential mechanism that mediates cannabidiol effect on glioblastoma

Glioblastoma (GBM) is an extremely aggressive primary brain tumor with poor prognosis, short survival time post-diagnosis and high recurrence. Currently, no cure for GBM exists. The identification of an effective therapeutic modality for GBM remains a high priority amongst medical professionals and researches. In recent studies, inhalant cannabidiol (CBD) has demonstrated promise in effectively inhibiting GBM tumor growth. However, exactly how CBD treatment affects the physiology of these tumor cells remains unclear. Stress granules (SG) (a sub-class of biomolecular condensates (BMC)) are dynamic, membrane-less intracellular microstructures which contain proteins and nucleic acids. The formation and signaling of SGs and BMCs plays a significant role in regulating malignancies. This study investigates whether inhaled CBD may play an intervening role towards SGs in GBM tumor cells. Integrated bioinformatics approaches were preformed to gain further insights. This includes use of Immunohistochemistry and flow cytometry to measure SGs, as well as expression and phosphorylation of eukaryotic initiation factor-2α (eIF2α). The findings of this study reveal that CBD receptors (and co-regulated genes) have the potential to play an important biological role in the formation of BMCs within GBM. In this experiment, CBD treatment significantly increased the volume of TIAR-1. This increase directly correlated with elevation in both eIF2α expression and p-eIF2α in CBD treated tissues in comparison to the placebo group (p < 0.05). These results suggest that inhalant CBD significantly up-regulated SGs in GBM, and thus support a theory of targeting BMCs as a potential therapeutic substrate for treating GBM.

Ethnicity-Based Variations in Focal Adhesion Kinase Signaling in Glioblastoma Gene Expression: A Study of the Puerto Rican Hispanic Population

Glioblastoma (GBM), an aggressive form of brain cancer, has a higher incidence in non-Hispanics when compared to the US Hispanic population. Using data from RT-PCR analysis of 21 GBM tissue from Hispanic patients in Puerto Rico, we identified significant correlations in the gene expression of focal adhesion kinase and proline-rich tyrosine kinase (PTK2 and PTK2B) with NGFR (nerve growth factor receptor), PDGFRB (platelet-derived growth factor receptor B), EGFR (epithelial growth factor receptor), and CXCR1 (C-X-C motif chemokine receptor 1). This study further explores these correlations found in gene expression while accounting for sex and ethnicity. Statistically significant (p < 0.05) correlations with an r value > ±0.7 were subsequently contrasted with mRNA expression data acquired from cBioPortal for 323 GBM specimens. Significant correlations in Puerto Rican male patients were found between PTK2 and PTK2B, NGFR, PDGFRB, EGFR, and CXCR1, which did not arise in non-Hispanic male patient data. The data for Puerto Rican female patients showed correlations in PTK2 with PTK2B, NGFR, PDGFRB, and EGFR, all of which did not appear in the data for non-Hispanic female patients. The data acquired from cBioPortal for non-Puerto Rican Hispanic patients supported the correlations found in the Puerto Rican population for both sexes. Our findings reveal distinct correlations in gene expression patterns, particularly involving PTK2, PTK2B, NGFR, PDGFRB, and EGFR among Puerto Rican Hispanic patients when compared to non-Hispanic counterparts.

Artificial intelligence in neuro-oncology: advances and challenges in brain tumor diagnosis, prognosis, and precision treatment

This review delves into the most recent advancements in applying artificial intelligence (AI) within neuro-oncology, specifically emphasizing work on gliomas, a class of brain tumors that represent a significant global health issue. AI has brought transformative innovations to brain tumor management, utilizing imaging, histopathological, and genomic tools for efficient detection, categorization, outcome prediction, and treatment planning. Assessing its influence across all facets of malignant brain tumor management- diagnosis, prognosis, and therapy- AI models outperform human evaluations in terms of accuracy and specificity. Their ability to discern molecular aspects from imaging may reduce reliance on invasive diagnostics and may accelerate the time to molecular diagnoses. The review covers AI techniques, from classical machine learning to deep learning, highlighting current applications and challenges. Promising directions for future research include multimodal data integration, generative AI, large medical language models, precise tumor delineation and characterization, and addressing racial and gender disparities. Adaptive personalized treatment strategies are also emphasized for optimizing clinical outcomes. Ethical, legal, and social implications are discussed, advocating for transparency and fairness in AI integration for neuro-oncology and providing a holistic understanding of its transformative impact on patient care.

Integrative multi-omics characterization reveals sex differences in glioblastoma

BACKGROUND

Glioblastoma (GBM) is the most common and lethal primary brain tumor in adults, with limited treatment modalities and poor prognosis. Recent studies have highlighted the importance of considering sex differences in cancer incidence, prognosis, molecular disparities, and treatment outcomes across various tumor types, including colorectal adenocarcinoma, lung adenocarcinoma, and GBM.

METHODS

We performed comprehensive analyses of large-scale multi-omics data (genomic, transcriptomic, and proteomic data) from TCGA, GLASS, and CPTAC to investigate the genetic and molecular determinants that contribute to the unique clinical properties of male and female GBM patients.

RESULTS

Our results revealed several key differences, including enrichments of MGMT promoter methylation, which correlated with increased overall and post-recurrence survival and improved response to chemotherapy in female patients. Moreover, female GBM exhibited a higher degree of genomic instability, including aneuploidy and tumor mutational burden. Integrative proteomic and phosphor-proteomic characterization uncovered sex-specific protein abundance and phosphorylation activities, including EGFR activation in males and SPP1 hyperphosphorylation in female patients. Lastly, the identified sex-specific biomarkers demonstrated prognostic significance, suggesting their potential as therapeutic targets.

CONCLUSIONS

Collectively, our study provides unprecedented insights into the fundamental modulators of tumor progression and clinical outcomes between male and female GBM patients and facilitates sex-specific treatment interventions. Highlights Female GBM patients were characterized by increased MGMT promoter methylation and favorable clinical outcomes compared to male patients. Female GBMs exhibited higher levels of genomic instability, including aneuploidy and TMB. Each sex-specific GBM is characterized by unique pathway dysregulations and molecular subtypes. EGFR activation is prevalent in male patients, while female patients are marked by SPP1 hyperphosphorylation.

Glioblastoma Therapy: Past, Present and Future

Glioblastoma (GB) stands out as the most prevalent and lethal form of brain cancer. Although great efforts have been made by clinicians and researchers, no significant improvement in survival has been achieved since the Stupp protocol became the standard of care (SOC) in 2005. Despite multimodality treatments, recurrence is almost universal with survival rates under 2 years after diagnosis. Here, we discuss the recent progress in our understanding of GB pathophysiology, in particular, the importance of glioma stem cells (GSCs), the tumor microenvironment conditions, and epigenetic mechanisms involved in GB growth, aggressiveness and recurrence. The discussion on therapeutic strategies first covers the SOC treatment and targeted therapies that have been shown to interfere with different signaling pathways (pRB/CDK4/RB1/P16ink4, TP53/MDM2/P14arf, PI3k/Akt-PTEN, RAS/RAF/MEK, PARP) involved in GB tumorigenesis, pathophysiology, and treatment resistance acquisition. Below, we analyze several immunotherapeutic approaches (i.e., checkpoint inhibitors, vaccines, CAR-modified NK or T cells, oncolytic virotherapy) that have been used in an attempt to enhance the immune response against GB, and thereby avoid recidivism or increase survival of GB patients. Finally, we present treatment attempts made using nanotherapies (nanometric structures having active anti-GB agents such as antibodies, chemotherapeutic/anti-angiogenic drugs or sensitizers, radionuclides, and molecules that target GB cellular receptors or open the blood-brain barrier) and non-ionizing energies (laser interstitial thermal therapy, high/low intensity focused ultrasounds, photodynamic/sonodynamic therapies and electroporation). The aim of this review is to discuss the advances and limitations of the current therapies and to present novel approaches that are under development or following clinical trials.

Optimizing adjuvant treatment options for patients with glioblastoma

Background

This study focused on minimizing the costs and toxic effects associated with unnecessary chemotherapy. We sought to optimize the adjuvant therapy strategy, choosing between radiotherapy (RT) and chemoradiotherapy (CRT), for patients based on their specific characteristics. This selection process utilized an innovative deep learning method.

Methods

We trained six machine learning (ML) models to advise on the most suitable treatment for glioblastoma (GBM) patients. To assess the protective efficacy of these ML models, we employed various metrics: hazards ratio (HR), inverse probability treatment weighting (IPTW)-adjusted HR (HRa), the difference in restricted mean survival time (dRMST), and the number needed to treat (NNT).

Results

The Balanced Individual Treatment Effect for Survival data (BITES) model emerged as the most effective, demonstrating significant protective benefits (HR: 0.53, 95% CI, 0.48-0.60; IPTW-adjusted HR: 0.65, 95% CI, 0.55-0.78; dRMST: 7.92, 95% CI, 7.81-8.15; NNT: 1.67, 95% CI, 1.24-2.41). Patients whose treatment aligned with BITES recommendations exhibited notably better survival rates compared to those who received different treatments, both before and after IPTW adjustment. In the CRT-recommended group, a significant survival advantage was observed when choosing CRT over RT (p < 0.001). However, this was not the case in the RT-recommended group (p = 0.06). Males, older patients, and those whose tumor invasion is confined to the ventricular system were more frequently advised to undergo RT.

Conclusion

Our study suggests that BITES can effectively identify GBM patients likely to benefit from CRT. These ML models show promise in transforming the complex heterogeneity of real-world clinical practice into precise, personalized treatment recommendations.

Brain tumor classification from MRI scans: a framework of hybrid deep learning model with Bayesian optimization and quantum theory-based marine predator algorithm

Brain tumor classification is one of the most difficult tasks for clinical diagnosis and treatment in medical image analysis. Any errors that occur throughout the brain tumor diagnosis process may result in a shorter human life span. Nevertheless, most currently used techniques ignore certain features that have particular significance and relevance to the classification problem in favor of extracting and choosing deep significance features. One important area of research is the deep learning-based categorization of brain tumors using brain magnetic resonance imaging (MRI). This paper proposes an automated deep learning model and an optimal information fusion framework for classifying brain tumor from MRI images. The dataset used in this work was imbalanced, a key challenge for training selected networks. This imbalance in the training dataset impacts the performance of deep learning models because it causes the classifier performance to become biased in favor of the majority class. We designed a sparse autoencoder network to generate new images that resolve the problem of imbalance. After that, two pretrained neural networks were modified and the hyperparameters were initialized using Bayesian optimization, which was later utilized for the training process. After that, deep features were extracted from the global average pooling layer. The extracted features contain few irrelevant information; therefore, we proposed an improved Quantum Theory-based Marine Predator Optimization algorithm (QTbMPA). The proposed QTbMPA selects both networks' best features and finally fuses using a serial-based approach. The fused feature set is passed to neural network classifiers for the final classification. The proposed framework tested on an augmented Figshare dataset and an improved accuracy of 99.80%, a sensitivity rate of 99.83%, a false negative rate of 17%, and a precision rate of 99.83% is obtained. Comparison and ablation study show the improvement in the accuracy of this work.

Sex-specific molecular differences in glioblastoma: assessing the clinical significance of genetic variants

Introduction

Glioblastoma multiforme (GBM) is one of the most aggressive types of brain cancer, and despite rigorous research, patient prognosis remains poor. The characterization of sex-specific differences in incidence and overall survival (OS) of these patients has led to an investigation of the molecular mechanisms that may underlie this dimorphism.

Methods

We reviewed the published literature describing the gender specific differences in GBM Biology reported in the last ten years and summarized the available information that may point towards a patient-tailored GBM therapy.

Results

Radiomics analyses have revealed that imaging parameters predict OS and treatment response of GBM patients in a sex-specific manner. Moreover, gender-based analysis of the transcriptome GBM tumors has found differential expression of various genes, potentially impacting the OS survival of patients in a sex-dependent manner. In addition to gene expression differences, the timing (subclonal or clonal) of the acquisition of common GBM-driver mutations, metabolism requirements, and immune landscape of these tumors has also been shown to be sex-specific, leading to a differential therapeutic response by sex. In male patients, transformed astrocytes are more sensitive to glutaminase 1 (GLS1) inhibition due to increased requirements for glutamine uptake. In female patients, GBM is more sensitive to anti-IL1β due to an increased population of circulating granulocytic myeloid-derived suppressor cells (gMDSC).

Conclusion

Moving forward, continued elucidation of GBM sexual dimorphism will be critical in improving the OS of GBM patients by ensuring that treatment plans are structured to exploit these sex-specific, molecular vulnerabilities in GBM tumors.

The genomic alterations in glioblastoma influence the levels of CSF metabolites

Cerebrospinal fluid (CSF) analysis is underutilized in patients with glioblastoma (GBM), partly due to a lack of studies demonstrating the clinical utility of CSF biomarkers. While some studies show the utility of CSF cell-free DNA analysis, studies analyzing CSF metabolites in patients with glioblastoma are limited. Diffuse gliomas have altered cellular metabolism. For example, mutations in isocitrate dehydrogenase enzymes (e.g., IDH1 and IDH2) are common in diffuse gliomas and lead to increased levels of D-2-hydroxyglutarate in CSF. However, there is a poor understanding of changes CSF metabolites in GBM patients. In this study, we performed targeted metabolomic analysis of CSF from n = 31 patients with GBM and n = 13 individuals with non-neoplastic conditions (controls), by mass spectrometry. Hierarchical clustering and sparse partial least square-discriminant analysis (sPLS-DA) revealed differences in CSF metabolites between GBM and control CSF, including metabolites associated with fatty acid oxidation and the gut microbiome (i.e., carnitine, 2-methylbutyrylcarnitine, shikimate, aminobutanal, uridine, N-acetylputrescine, and farnesyl diphosphate). In addition, we identified differences in CSF metabolites in GBM patients based on the presence/absence of TP53 or PTEN mutations, consistent with the idea that different mutations have different effects on tumor metabolism. In summary, our results increase the understanding of CSF metabolites in patients with diffuse gliomas and highlight several metabolites that could be informative biomarkers in patients with GBM.

Harnessing the Stem Cell Niche in Regenerative Medicine: Innovative Avenue to Combat Neurodegenerative Diseases

Regenerative medicine harnesses the body's innate capacity for self-repair to restore malfunctioning tissues and organs. Stem cell therapies represent a key regenerative strategy, but to effectively harness their potential necessitates a nuanced understanding of the stem cell niche. This specialized microenvironment regulates critical stem cell behaviors including quiescence, activation, differentiation, and homing. Emerging research reveals that dysfunction within endogenous neural stem cell niches contributes to neurodegenerative pathologies and impedes regeneration. Strategies such as modifying signaling pathways, or epigenetic interventions to restore niche homeostasis and signaling, hold promise for revitalizing neurogenesis and neural repair in diseases like Alzheimer's and Parkinson's. Comparative studies of highly regenerative species provide evolutionary clues into niche-mediated renewal mechanisms. Leveraging endogenous bioelectric cues and crosstalk between gut, brain, and vascular niches further illuminates promising therapeutic opportunities. Emerging techniques like single-cell transcriptomics, organoids, microfluidics, artificial intelligence, in silico modeling, and transdifferentiation will continue to unravel niche complexity. By providing a comprehensive synthesis integrating diverse views on niche components, developmental transitions, and dynamics, this review unveils new layers of complexity integral to niche behavior and function, which unveil novel prospects to modulate niche function and provide revolutionary treatments for neurodegenerative diseases.

Highly cooperative chimeric super-SOX induces naive pluripotency across species

Our understanding of pluripotency remains limited: iPSC generation has only been established for a few model species, pluripotent stem cell lines exhibit inconsistent developmental potential, and germline transmission has only been demonstrated for mice and rats. By swapping structural elements between Sox2 and Sox17, we built a chimeric super-SOX factor, Sox2-17, that enhanced iPSC generation in five tested species: mouse, human, cynomolgus monkey, cow, and pig. A swap of alanine to valine at the interface between Sox2 and Oct4 delivered a gain of function by stabilizing Sox2/Oct4 dimerization on DNA, enabling generation of high-quality OSKM iPSCs capable of supporting the development of healthy all-iPSC mice. Sox2/Oct4 dimerization emerged as the core driver of naive pluripotency with its levels diminished upon priming. Transient overexpression of the SK cocktail (Sox+Klf4) restored the dimerization and boosted the developmental potential of pluripotent stem cells across species, providing a universal method for naive reset in mammals.

Risk factors for glioblastoma in adults in Japan: an exploratory cohort study based on the Shizuoka Kokuho Database, the Shizuoka study

PURPOSE

To elucidate the risk factors associated with the onset of glioblastoma (GBM) utilizing a comprehensive administrative claims database from a major governmental district in Japan.

METHODS

Using the Shizuoka Kokuho Database (SKDB) for the period from April 2012 to September 2021, we conducted a retrospective analysis of 1,465,353 participants, identifying GBM cases using specific Japanese disease codes in conjunction with associated treatments. Risk factors were assessed using both univariable and multivariable Cox proportional hazards models.

RESULTS

Within the cohort, 182 participants (0.012%) received a GBM diagnosis during the study period, resulting in an incidence rate of 2.1 per 100,000 person-years. The multivariable analysis revealed that older age, male sex, and peripheral vascular disease (PVD) significantly influenced the risk of GBM onset. No clear link was found between allergic conditions and GBM risk, in contrast to some previous research.

CONCLUSION

Employing a robust health insurance database, this study revealed significant associations between GBM and factors such as age, male sex, and PVD within the Japanese population. It provides key insights into GBM epidemiology and underscores the potential of health insurance databases for large-scale oncological research.

Clinical role of NDRG2-based methylation status on survival pattern of glioblastoma

OBJECTIVES

Gliobalstoma is the most common primary brain tumor in adults with an extensive genetic and transcriptional heterogeneity, still identification of the role of DNA methylation, as one of epigenetic alterations, is emerged. Authors aimed to study the clinical role of N-myc downstream-regulated gene 2 (NDRG2) -based methylation among GBM patients versus benign neurological diseases (BND), investigate its prognostic role and its relation with survival outcomes.

METHODS

A total of 78 FFPE specimens were recruited as follows: GBM (n = 58) and BND (n = 20) then analyzed for NDRG2 methylation using Methyl II quantitative PCR system. The sensitivity and specificity of methylation was detected using receiver operating characteristic (ROC) curve and the relation with clinicopathological criteria for GBM and response to treatment were studied. Survival patterns; progression free survival (PFS) and overall survival (OS) were analyzed using Kaplan-Meier analyses.

RESULTS

Mean methylation NDRG2 level was significantly increased in GBM patients as compared to BND and its sensitivity and specificity were 96.55% and 95%, respectively with area under curve (AUC) equals 0.973. Among the clinical characteristic factors, mean methylation level reported significant difference with ECOG and tumor site. Survival out comes revealed that NDRG2 methylation increased with worse PFS and OS at significant level (long rank test X2 = 13.3, p < .0001; and X2 = 7.1, p = .008, respectively).

CONCLUSION

Current findings highlight the importance of studying DNA methylation of NDRG2 as a key factor to understand the role of epigenetic alterations in GBM.

Targeting androgen receptor in glioblastoma

Glioblastomas are primary brain tumors that originate from glial stem cells or progenitor cells. There is a large difference in the incidence of glioblastoma between males and females. Studies revealed that the gender differences in the tumor may be attributable to the androgen receptor signaling axis. The incidence rate of glioblastoma in men is higher than that in women. Aberrant activation of the androgen receptor signaling pathway, or interactions between the androgen receptor signaling axis and other signaling axes promote the development of glioblastoma. Therefore, targeting the androgen receptor holds promise as a therapeutic approach for glioblastoma. This review investigates the dynamics of drug research into the treatment of glioblastoma by targeting the androgen receptor. The first finding in line with expectations is that androgen receptor antagonists, represented by enzalutamide, have been studied and shown to have anti-glioblastoma effects. In addition, it was found that the combination of 5-alpha reductase inhibitors and androgen receptor antagonists resulted in better therapeutic outcomes than each of them alone. Similar results were obtained with the combination of an epidermal growth factor receptor inhibitor and an androgen receptor antagonist. In addition, four small molecule compounds have been shown to exert significant anti-glioblastoma effects by directly or indirectly targeting the androgen receptor. Expectantly, one of these small molecules, seviteronel, progressed to the phase II clinical trial stage. These findings suggest that targeting the androgen receptor for glioblastoma may be a promising therapeutic option.

Sex-related incidence and survival differences in pediatric high-grade glioma subtypes: A population-based cohort study

Not much is known on sex differences in incidence, survival, and treatment characteristics for midline and hemispheric pHGGs. This population-based study confirms previously reported study results that found worse survival outcomes for malignant diffuse gliomas in girls in the age group 0-9 years. Additionally, in our study we pinpoint this difference to girls with midline pHGGs aged 0-4 years. We provide insight in the possible underlying mechanisms contributing to sex survival differences in pHGG patients. With first line treatment having no impact on the higher risk of dying for girls, but age and tumor characteristics having a neutralizing effect. The results of this population-based study serve as a basis for future pre-clinical and clinical studies to further unravel the underlying mechanisms responsible for the survival gap between sexes in midline pHGG.

γδ T cells as a potential therapeutic agent for glioblastoma

Although γδ T cells comprise a small population of T cells, they perform important roles in protecting against infection and suppressing tumors. With their distinct tissue-localizing properties, combined with their various target recognition mechanisms, γδ T cells have the potential to become an effective solution for tumors that do not respond to current therapeutic procedures. One such tumor, glioblastoma (GBM), is a malignant brain tumor with the highest World Health Organization grade and therefore the worst prognosis. The immune-suppressive tumor microenvironment (TME) and immune-evasive glioma stem cells are major factors in GBM immunotherapy failure. Currently, encouraged by the strong anti-tumoral function of γδ T cells revealed at the preclinical and clinical levels, several research groups have shown progression of γδ T cell-based GBM treatment. However, several limitations still exist that block effective GBM treatment using γδ T cells. Therefore, understanding the distinct roles of γδ T cells in anti-tumor immune responses and the suppression mechanism of the GBM TME are critical for successful γδ T cell-mediated GBM therapy. In this review, we summarize the effector functions of γδ T cells in tumor immunity and discuss current advances and limitations of γδ T cell-based GBM immunotherapy. Additionally, we suggest future directions to overcome the limitations of γδ T cell-based GBM immunotherapy to achieve successful treatment of GBM.

Identification of a RAD51B enhancer variant for susceptibility and progression to glioma

BACKGROUND

RAD51B plays a significant role in homologous recombination-mediated repair of DNA double-strand breaks. Many enhancer variants are involved in cancer development and progression. However, the significance of enhancer variants of RAD51B in glioma susceptibility and progression remains unclear.

METHODS

A case-control study consisting of 1056 individuals was conducted to evaluate the associations of enhancer variants of RAD51B with glioma susceptibility and progression. Sequenom MassARRAY technology was used for genotyping. The function of enhancer variants was explored by biochemical assays.

RESULTS

A significantly decreased risk of glioma was associated with rs6573816 GC genotype compared with rs6573816 GG genotype (OR = 0.66, 95% CI 0.45-0.97; P = 0.034). Multivariable Cox regression revealed that rs6573816 was significantly associated with glioma progression in a sex-dependent manner. Worse PFS was found in the male patients with high grade glioma carrying rs6573816 GC or CC genotype (HR = 2.28, 95% CI 1.14-4.57; P = 0.020). The rs6573816 C allele repressed enhancer activity by affecting transcription factor POU2F1 binding, which resulted in lower expression of RAD51B. Remarkably attenuated expression of RAD51B was observed following POU2F1 knockdown. Consistently, positive correlation between the expression of POU2F1 and RAD51B was found in lymphoblastic cells and glioma tissues.

CONCLUSIONS

These results indicate that an enhancer variant of RAD51B rs6573816 influences enhancer activity by changing a POU2F1 binding site and confers susceptibility and progression to glioma.

Testosterone upregulates glial cell line-derived neurotrophic factor (GDNF) and promotes neuroinflammation to enhance glioma cell survival and proliferation

BACKGROUND

Testosterone contributes to male organism development, such as bone density, muscle development, and fat repartition. Estrogen (derived from testosterone) also contributes to female reproductive system development. Here, we investigated the effect of testosterone on glioma cells and brain neuron inflammation essential for cancer development and progression.

METHODS

The human astrocyte and glioma cell lines were treated with 6 ng/ml exogenous testosterone in vitro. We performed cell counting kit-8, transwell, and wound healing assays to determine the effect of testosterone on glioma cell proliferation, migration, and invasion. The glioma cells were injected into the xenograft and treated with 5 µl concentrated testosterone. Transcriptional suppression of glial cell line-derived neurotrophic factor (GDNF) was performed to evaluate brain neuron inflammation and survival. The tumor tissues were assessed by hematoxylin-eosin staining and immunohistochemistry.

RESULTS

Testosterone upregulates GDNF to stimulate proliferation, migration, and invasion of glioma cells. Pathologically, the augmentation of GDNF and cyclophilin A contributed to neuroprotection when treated with testosterone. Our investigation showed that testosterone contributes to brain neuron and astrocyte inflammation through the upregulation of nuclear factor erythroid 2-related factor 2 (NRF2), glial fibrillary acid protein (GFAP), and sirtuin 5 (SIRT5), resulting in pro-inflammatory macrophages recruitments into the neural microenvironment. Mechanically, testosterone treatment regulates GDNF translocation from the glioma cells and astrocyte nuclei to the cytoplasm.

CONCLUSION

Testosterone upregulates GDNF in glioma cells and astrocytes essential for microglial proliferation, migration, and invasion. Testosterone contributes to brain tumor growth via GDNF and inflammation. The contribution of testosterone, macrophages, and astrocytes, in old neuron rescue, survival, and proliferation. During brain neuron inflammation, the organism activates and stimulates the neuron rescue through the enrichment of the old neuron microenvironment with growth factors such as GDNF, BDNF, SOX1/2, and MAPK secreted by the surrounding neurons and glial cells to maintain the damaged neuron by inflammation alive even if the axon is dead. The immune response also contributes to brain cell survival through the secretion of proinflammatory cytokines, resulting in inflammation maintenance. The rescued old neuron interaction with infiltrated macrophages contributes to angiogenesis to supplement the old neuron with more nutrients leading to metabolism activation and surrounding cell uncontrollable cell growth.

Extra-Neural Metastases of Glioblastoma: A Case Series

Glioblastoma (GBM) is the most common brain tumor and has a median survival of less than two years. The current standard of care consists of surgery followed by concomitant radio and chemotherapy with temozolomide. Although it is an aggressive tumor, distant metastases are extremely rare. The dissemination mechanisms are not fully understood and currently there is no standard of care for its treatment. In this study, the authors present a comprehensive analysis of all the existing cases of extra-neural metastases of GBM in a tertiary care center over the last five years, along with the procedures carried out in each case.

Age and sex disparities in Latin-American adults with gliomas: a systematic review and meta-analysis

OBJECTIVE

This study aimed to identify if there are ethnic differences in the age and sex distribution of gliomas in the Latino adult population.

METHODS

A systematic review and meta-analysis were conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 recommendations. Databases used were MEDLINE, LILACS, Web of Science, and Scopus. Studies were included if they reported the age and/or sex distribution of gliomas in Latin adults, published in English or Spanish from January 1st, 1985, to December 1st, 2022. The quality of the studies was assessed using the Newcastle-Ottawa Quality Assessment Scale and the NIH Quality Assessment Tool.

RESULTS

From 1096 articles, fifteen studies with information on 6,815 patients were selected for the systematic review, and thirteen were selected for the meta-analysis. The mean ages of diagnosis of glioma and glioblastoma were 50.9, 95\%\ CI [47.8-53.9] years and 53.33 years, 95 \% CI [51-55.6], respectively. The male-to-female incidence rate ratio of gliomas was 1.39.

CONCLUSION

Our study found mean ages of glioma and glioblastoma were 6 and 10 years lower than those reported in the CBTRUS. Our study suggests disparities in the age and sex distribution of gliomas in Latin America compared to other regions.

PROSPERO REGISTRATION NUMBER

CRD42021274423.

PDGFRA, KIT, and KDR Gene Amplification in Glioblastoma: Heterogeneity and Clinical Significance

Glioblastoma (GBM) is the most frequent tumor of the central nervous system, and its heterogeneity is a challenge in treatment. This study examined tumoral heterogeneity involving PDGFRA, KIT, and KDR gene amplification (GA) in 4q12 and its association with clinical parameters. Specimens from 22 GBM cases with GA for the 4q12 amplicon detected by FISH were investigated for homogeneous or heterogeneous coamplification patterns, diffuse or focal distribution of cells harboring GA throughout tumor sections, and pattern of clustering of fluorescence signals. Sixteen cases had homogenously amplification for all three genes (45.5%), for PDGFRA and KDR (22.7%), or only for PDGFRA (4.6%); six cases had heterogeneous GA patterns, with subpopulations including GA for all three genes and for two genes - PDGFRA and KDR (13.6%), or GA for all three and for only one gene - PDGFRA (9.1%) or KIT (4.6%). In 6 tumors (27.3%), GA was observed in focal tumor areas, while in the remaining 16 tumors (72.7%) it was diffusely distributed throughout the pathological specimen. Amplification was universally expressed as double minutes and homogenously stained regions. Coamplification of all three genes PDGFRA, KIT, and KDR, age ≥ 60 years, and total tumor resection were statistically associated with poor prognosis. FISH proved effective for detailed interpretation of molecular heterogeneity. The study uncovered an even more diverse range of amplification patterns involving the 4q12 oncogenes in GBM than previously described, thus highlighting a complex tumoral heterogeneity to be considered when devising more effective therapies.

Glioblastoma management in a lower middle-income country: Nationwide study of compliance with standard care protocols and survival outcomes in Ukraine

Background

The effective treatment of high-grade gliomas is a complex problem that requires ubiquitous implementation of sophisticated therapy protocols. The present study aimed to perform population-based analysis of glioblastoma management in lower-middle-income countries.

Methods

The National Cancer Registry of Ukraine was screened for the records of adult patients with primary glioblastomas diagnosed in 2015-2019. Survival analysis was performed using Kaplan-Meier method and a multivariable Cox model.

Results

A total of 2973 adult patients with histologically confirmed glioblastoma were included in the study. Mean age of patients was 55.6 ± 11.4 years, males slightly prevailed-1541 (51.8%) cases. The completed clinical protocol including surgery followed by chemoradiotherapy was applied only in 658 (19.0%) patients. The minority of patients 743 (25.0%) were treated at the academic medical centers, where patients were more likely to receive combined treatment 70.1% compared with 57.9% (P  = .0001) at the community hospitals. The overall median survival was 10.6 ± 0.2 months, and the 2-year survival rate was 17%. The number of utilized treatment modalities contributed to better survival rates and was associated with lower hazard ratio: Protocol with 2 modalities - 0.62 (P = .0001), 3 modalities - 0.48 (P = .0001).

Conclusions

The management of glioblastoma in lower-middle-income countries is characterized by insufficient availability of treatment in academic medical centers and low rates of advanced therapy application. Survival analysis showed similar prognostic risk factors and outcomes compared with high-income countries.

Plasma PD-L1 as a biomarker in the clinical management of glioblastoma multiforme-a retrospective cohort study

Background and objectives

Glioblastoma multiforme (GBM) is the most aggressive, malignant, and therapy-resistant tumor of the brain. Blockade therapy targeting the programmed cell death protein 1 (PD-1)/programmed death ligand (PD-L1) axis is currently under investigation for the clinical management of the GBM. This study has quantified the plasma levels of PD-L1 as a biomarker for the clinical management of GBM.

Methods

A cohort (n = 128) of Pakistani adult glioblastoma patients together with age- and sex-matched healthy controls was used for quantification of pre-surgery levels of plasma PD-L1. PD-L1 protein and mRNA were measured by PD-L1 platinum enzyme-linked immunosorbent assay and quantitative real-time PCR, respectively. Receiver operating characteristic (ROC) curve analysis was used to compute area under the curve (AUC) for specificity and sensitivity analyses. The Kaplan-Meier survival analysis was employed to compute overall survival.

Results

PD-L1 protein and mRNA were significantly higher in GBM compared to the healthy controls (p < 0.0001). Mean PD-L1 concentration for the GBM was found to be 48.98 ± 2.290 pg/ml compared to 27.63 ± 1.281 pg/ml for controls. Gene expression analysis showed statistically significant upregulation (p < 0.0001) of PD-L1 in blood of GBM compared to healthy controls. Plasma PD-L1 showed an AUC of 0.840 (p < 0.0001; 95% CI = 0.7716 to 0.9090) where a cutoff value higher than 46 pg/ml demonstrated 100% specificity and 57.81% sensitivity. Higher pre-surgery levels of PD-L1 were found to be associated with overall poor survival [p < 0.0001; HR (log-rank) = 0.08; 95% CI = 0.04 to 0.15]. Age, gender, and ethnic background were not found to be associated with plasma PD-L1 levels.

Conclusion

The study concludes that blood-based measurements of PD-L1 in GBM can be a promising prognostic marker and therapeutic target besides a rapid and relatively non-invasive screening tool for routine clinical management. Future work extending the analysis to larger cohorts through multi-center collaborations involving pre-treatment and post-treatment groups is required to fully explore the usefulness of circulating PD-L1 for effective clinical applications.

MDM2 Inhibition in the Treatment of Glioblastoma: From Concept to Clinical Investigation

Inhibition of the interaction between MDM2 and p53 has emerged as a promising strategy for combating cancer, including the treatment of glioblastoma (GBM). Numerous MDM2 inhibitors have been developed and are currently undergoing rigorous testing for their potential in GBM therapy. Encouraging results from studies conducted in cell culture and animal models suggest that MDM2 inhibitors could effectively treat a specific subset of GBM patients with wild-type TP53 or functional p53. Combination therapy with clinically established treatment modalities such as radiation and chemotherapy offers the potential to achieve a more profound therapeutic response. Furthermore, an increasing array of other molecularly targeted therapies are being explored in combination with MDM2 inhibitors to increase the effects of individual treatments. While some MDM2 inhibitors have progressed to early phase clinical trials in GBM, their efficacy, alone and in combination, is yet to be confirmed. In this article, we present an overview of MDM2 inhibitors currently under preclinical and clinical investigation, with a specific focus on the drugs being assessed in ongoing clinical trials for GBM patients.

Evaluation of RANO Criteria for the Assessment of Tumor Progression for Lower-Grade Gliomas

PURPOSE

The Response Assessment in Neuro-Oncology (RANO) criteria for lower-grade gliomas (LGGs) define tumor progression as ≥25% change in the T2/FLAIR signal area based on an operator's discretion of the perpendicular diameter of the largest tumor cross-section. Potential sources of error include acquisition inconsistency of 2D slices, operator selection variabilities in both representative tumor cross-section and measurement line locations, and the inability to quantify infiltrative tumor margins and satellite lesions. Our goal was to assess the accuracy and reproducibility of RANO in LG.

MATERIALS AND METHODS

A total of 651 FLAIR MRIs from 63 participants with LGGs were retrospectively analyzed by three blinded attending physicians and three blinded resident trainees using RANO criteria, 2D visual assessment, and computer-assisted 3D volumetric assessment.

RESULTS

RANO product measurements had poor-to-moderate inter-operator reproducibility (r² = 0.28-0.82; coefficient of variance (CV) = 44-110%; mean percent difference (diff) = 0.4-46.8%) and moderate-to-excellent intra-operator reproducibility (r² = 0.71-0.88; CV = 31-58%; diff = 0.3-23.9%). When compared to 2D visual ground truth, the accuracy of RANO compared to previous and baseline scans was 66.7% and 65.1%, with an area under the ROC curve (AUC) of 0.67 and 0.66, respectively. When comparing to volumetric ground truth, the accuracy of RANO compared to previous and baseline scans was 21.0% and 56.5%, with an AUC of 0.39 and 0.55, respectively. The median time delay at diagnosis was greater for false negative cases than for false positive cases for the RANO assessment compared to previous (2.05 > 0.50 years, p = 0.003) and baseline scans (1.08 > 0.50 years, p = 0.02).

CONCLUSION

RANO-based assessment of LGGs has moderate reproducibility and poor accuracy when compared to either visual or volumetric ground truths.

Algorithmic fairness in artificial intelligence for medicine and healthcare

In healthcare, the development and deployment of insufficiently fair systems of artificial intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models stratified across subpopulations have revealed inequalities in how patients are diagnosed, treated and billed. In this Perspective, we outline fairness in machine learning through the lens of healthcare, and discuss how algorithmic biases (in data acquisition, genetic variation and intra-observer labelling variability, in particular) arise in clinical workflows and the resulting healthcare disparities. We also review emerging technology for mitigating biases via disentanglement, federated learning and model explainability, and their role in the development of AI-based software as a medical device.

An online survival predictor in glioma patients using machine learning based on WHO CNS5 data

Background

The World Health Organization (WHO) CNS5 classification system highlights the significance of molecular biomarkers in providing meaningful prognostic and therapeutic information for gliomas. However, predicting individual patient survival remains challenging due to the lack of integrated quantitative assessment tools. In this study, we aimed to design a WHO CNS5-related risk signature to predict the overall survival (OS) rate of glioma patients using machine learning algorithms.

Methods

We extracted data from patients who underwent an operation for histopathologically confirmed glioma from our hospital database (2011-2022) and split them into a training and hold-out test set in a 7/3 ratio. We used biological markers related to WHO CNS5, clinical data (age, sex, and WHO grade), and prognosis follow-up information to identify prognostic factors and construct a predictive dynamic nomograph to predict the survival rate of glioma patients using 4 kinds machine learning algorithms (RF, SVM, XGB, and GLM).

Results

A total of 198 patients with complete WHO5 molecular data and follow-up information were included in the study. The median OS time of all patients was 29.77 [95% confidence interval (CI): 21.19-38.34] months. Age, FGFR2, IDH1, CDK4, CDK6, KIT, and CDKN2A were considered vital indicators related to the prognosis and OS time of glioma. To better predict the prognosis of glioma patients, we constructed a WHO5-related risk signature and nomogram. The AUC values of the ROC curves of the nomogram for predicting the 1, 3, and 5-year OS were 0.849, 0.835, and 0.821 in training set, and, 0.844, 0.943, and 0.959 in validation set. The calibration plot confirmed the reliability of the nomogram, and the c-index was 0.742 in training set and 0.775 in validation set. Additionally, our nomogram showed a superior net benefit across a broader scale of threshold probabilities in decision curve analysis. Therefore, we selected it as the backend for the online survival prediction tool (Glioma Survival Calculator, https://who5pumch.shinyapps.io/DynNomapp/), which can calculate the survival probability for a specific time of the patients.

Conclusion

An online prognosis predictor based on WHO5-related biomarkers was constructed. This therapeutically promising tool may increase the precision of forecast therapy outcomes and assess prognosis.

Update for astrocytomas: medical and surgical management considerations

Astrocytomas include a wide range of tumors with unique mutations and varying grades of malignancy. These tumors all originate from the astrocyte, a star-shaped glial cell that plays a major role in supporting functions of the central nervous system (CNS), including blood-brain barrier (BBB) development and maintenance, water and ion regulation, influencing neuronal synaptogenesis, and stimulating the immunological response. In terms of epidemiology, glioblastoma (GB), the most common and malignant astrocytoma, generally occur with higher rates in Australia, Western Europe, and Canada, with the lowest rates in Southeast Asia. Additionally, significantly higher rates of GB are observed in males and non-Hispanic whites. It has been suggested that higher levels of testosterone observed in biological males may account for the increased rates of GB. Hereditary syndromes such as Cowden, Lynch, Turcot, Li-Fraumeni, and neurofibromatosis type 1 have been linked to increased rates of astrocytoma development. While there are a number of specific gene mutations that may influence malignancy or be targeted in astrocytoma treatment, O 6-methylguanine-DNA methyltransferase (MGMT) gene function is an important predictor of astrocytoma response to chemotherapeutic agent temozolomide (TMZ). TMZ for primary and bevacizumab in the setting of recurrent tumor formation are two of the main chemotherapeutic agents currently approved in the treatment of astrocytomas. While stereotactic radiosurgery (SRS) has debatable implications for increased survival in comparison to whole-brain radiotherapy (WBRT), SRS demonstrates increased precision with reduced radiation toxicity. When considering surgical resection of astrocytoma, the extent of resection (EoR) is taken into consideration. Subtotal resection (STR) spares the margins of the T1 enhanced magnetic resonance imaging (MRI) region, gross total resection (GTR) includes the margins, and supramaximal resection (SMR) extends beyond the margin of the T1 and into the T2 region. Surgical resection, radiation, and chemotherapy are integral components of astrocytoma treatment.

Antitumor Potential of Antiepileptic Drugs in Human Glioblastoma: Pharmacological Targets and Clinical Benefits

Glioblastoma (GBM) is characterized by fast-growing cells, genetic and phenotypic heterogeneity, and radio-chemo-therapy resistance, contributing to its dismal prognosis. Various medical comorbidities are associated with the natural history of GBM. The most disabling and greatly affecting patients' quality of life are neurodegeneration, cognitive impairment, and GBM-related epilepsy (GRE). Hallmarks of GBM include molecular intrinsic mediators and pathways, but emerging evidence supports the key role of non-malignant cells within the tumor microenvironment in GBM aggressive behavior. In this context, hyper-excitability of neurons, mediated by glutamatergic and GABAergic imbalance, contributing to GBM growth strengthens the cancer-nervous system crosstalk. Pathogenic mechanisms, clinical features, and pharmacological management of GRE with antiepileptic drugs (AEDs) and their interactions are poorly explored, yet it is a potentially promising field of research in cancer neuroscience. The present review summarizes emerging cooperative mechanisms in oncogenesis and epileptogenesis, focusing on the neuron-to-glioma interface. The main effects and efficacy of selected AEDs used in the management of GRE are discussed in this paper, as well as their potential beneficial activity as antitumor treatment. Overall, although still many unclear processes overlapping in GBM growth and seizure onset need to be elucidated, this review focuses on the intriguing targeting of GBM-neuron mutual interactions to improve the outcome of the so challenging to treat GBM.

Patient-derived glioblastoma organoids reflect tumor heterogeneity and treatment sensitivity

Background

Treatment resistance and tumor relapse are the primary causes of mortality in glioblastoma (GBM), with intratumoral heterogeneity playing a significant role. Patient-derived cancer organoids have emerged as a promising model capable of recapitulating tumor heterogeneity. Our objective was to develop patient-derived GBM organoids (PGO) to investigate treatment response and resistance.

Methods

GBM samples were used to generate PGOs and analyzed using whole-exome sequencing (WES) and single-cell karyotype sequencing. PGOs were subjected to temozolomide (TMZ) to assess viability. Bulk RNA sequencing was performed before and after TMZ.

Results

WES analysis on individual PGOs cultured for 3 time points (1-3 months) showed a high inter-organoid correlation and retention of genetic variants (range 92.3%-97.7%). Most variants were retained in the PGO compared to the tumor (range 58%-90%) and exhibited similar copy number variations. Single-cell karyotype sequencing demonstrated preservation of genetic heterogeneity. Single-cell multiplex immunofluorescence showed maintenance of cellular states. TMZ treatment of PGOs showed a differential response, which largely corresponded with MGMT promoter methylation. Differentially expressed genes before and after TMZ revealed an upregulation of the JNK kinase pathway. Notably, the combination treatment of a JNK kinase inhibitor and TMZ demonstrated a synergistic effect.

Conclusions

Overall, these findings demonstrate the robustness of PGOs in retaining the genetic and phenotypic heterogeneity in culture and the application of measuring clinically relevant drug responses. These data show that PGOs have the potential to be further developed into avatars for personalized adaptive treatment selection and actionable drug target discovery and as a platform to study GBM biology.

Integrated regulatory and metabolic networks of the tumor microenvironment for therapeutic target prioritization

Translation of genomic discovery, such as single-cell sequencing data, to clinical decisions remains a longstanding bottleneck in the field. Meanwhile, computational systems biological models, such as cellular metabolism models and cell signaling pathways, have emerged as powerful approaches to provide efficient predictions in metabolites and gene expression levels, respectively. However, there has been limited research on the integration between these two models. This work develops a methodology for integrating computational models of probabilistic gene regulatory networks with a constraint-based metabolism model. By using probabilistic reasoning with Bayesian Networks, we aim to predict cell-specific changes under different interventions, which are embedded into the constraint-based models of metabolism. Applications to single-cell sequencing data of glioblastoma brain tumors generate predictions about the effects of pharmaceutical interventions on the regulatory network and downstream metabolisms in different cell types from the tumor microenvironment. The model presents possible insights into treatments that could potentially suppress anaerobic metabolism in malignant cells with minimal impact on other cell types' metabolism. The proposed integrated model can guide therapeutic target prioritization, the formulation of combination therapies, and future drug discovery. This model integration framework is also generalizable to other applications, such as different cell types, organisms, and diseases.

Targeting interleukin-13 receptor α2 (IL-13Rα2) for glioblastoma therapy with surface functionalized nanocarriers

Despite surgical and therapeutic advances, glioblastoma multiforme (GBM) is among the most fatal primary brain tumor that is aggressive in nature. Patients with GBM have a median lifespan of just 15 months when treated with the current standard of therapy, which includes surgical resection and concomitant chemo-radiotherapy. In recent years, nanotechnology has shown considerable promise in treating a variety of illnesses, and certain nanomaterials have been proven to pass the blood-brain barrier (BBB) and stay in glioblastoma tissues. Recent preclinical research suggests that the diagnosis and treatment of brain tumor is significantly explored through the intervention of nanomaterials that has showed enhanced effect. In order to elicit an antitumor response, it is necessary to retain the therapeutic candidates within glioblastoma tissues and this job is effectively carried out by nanocarrier particularly functionalized nanocarriers. In the arena of neoplastic diseases including GBM have achieved great attention in recent decades. Furthermore, interleukin-13 receptor α chain variant 2 (IL13Rα2) is a highly expressed and studied target in GBM that is lacked by the surrounding environment. The absence of IL13Rα2 in surrounding normal tissues has made it a suitable target in glioblastoma therapy. In this review article, we highlighted the role of IL13Rα2 as a potential target in GBM along with design and fabrication of efficient targeting strategies for IL13Rα2 through surface functionalized nanocarriers.

Prognostic Factors for Survival of Patients with Glioblastoma in the Southern Region of Morocco

Background: Glioblastoma is the most common brain cancer in adults. It is caused by the abnormal proliferation of central nervous system cells called astrocytes, with an incidence rate of 4.32 per 100,000 in the United States. The median survival for glioblastoma is about 1 to 2 years. In Morocco, the survival of patients with glioblastoma is relatively little explored. Objectives: This research aims to study overall survival and these prognostic factors in patients with glioblastoma. Methods: This is a retrospective study; the data were extracted from the files of patients with glioblastoma in the public reference oncology center in the southern region of Morocco; it is a prognostic study including all patients with glioblastoma cancer between 2014 and October 2021. Results: The present study ultimately focused on 71 files of cases diagnosed with glioblastoma. The median age at diagnosis was 57, with a sex ratio of 1.44. The median survival time for all glioblastoma patients in this study was 11 months (95% CI: 9.96 to 12.03 months). Univariate analysis revealed that age, sex, geographical origin, type of treatment, and type of surgery were significant at P = 0.20 and then included in the multivariate model. After adjusting for all factors, the results revealed that only gender, age, and geographical origin were statistically significant predictors of overall survival. Conclusions: The survival rate in patients with glioblastoma is improved with surgery, followed by concomitant radio-chemotherapy. We also confirmed that age and sex are important prognostic factors for the survival of patients with glioblastoma. Moreover, the data suggest the effect of the geographical origin of the patients on the overall survival of the patients as the only modifiable prognostic factor.

The complex, dynamic SpliceOme of the small GTPase transcripts altered by technique, sex, genetics, tissue specificity, and RNA base editing

The small GTPase family is well-studied in cancer and cellular physiology. With 162 annotated human genes, the family has a broad expression throughout cells of the body. Members of the family have multiple exons that require splicing. Yet, the role of splicing within the family has been underexplored. We have studied the splicing dynamics of small GTPases throughout 41,671 samples by integrating Nanopore and Illumina sequencing techniques. Within this work, we have made several discoveries. 1). Using the GTEx long read data of 92 samples, each small GTPase gene averages two transcripts, with 83 genes (51%) expressing two or more isoforms. 2). Cross-tissue analysis of GTEx from 17,382 samples shows 41 genes (25%) expressing two or more protein-coding isoforms. These include protein-changing transcripts in genes such as RHOA, RAB37, RAB40C, RAB4B, RAB5C, RHOC, RAB1A, RAN, RHEB, RAC1, and KRAS. 3). The isolation and library technique of the RNAseq influences the abundance of non-sense-mediated decay and retained intron transcripts of small GTPases, which are observed more often in genes than appreciated. 4). Analysis of 16,243 samples of "Blood PAXgene" identified seven genes (3.7%; RHOA, RAB40C, RAB4B, RAB37, RAB5B, RAB5C, RHOC) with two or more transcripts expressed as the major isoform (75% of the total gene), suggesting a role of genetics in altering splicing. 5). Rare (ARL6, RAB23, ARL13B, HRAS, NRAS) and common variants (GEM, RHOC, MRAS, RAB5B, RERG, ARL16) can influence splicing and have an impact on phenotypes and diseases. 6). Multiple genes (RAB9A, RAP2C, ARL4A, RAB3A, RAB26, RAB3C, RASL10A, RAB40B, and HRAS) have sex differences in transcript expression. 7). Several exons are included or excluded for small GTPase genes (RASEF, KRAS, RAC1, RHEB, ARL4A, RHOA, RAB30, RHOBTB1, ARL16, RAP1A) in one or more forms of cancer. 8). Ten transcripts are altered in hypoxia (SAR1B, IFT27, ARL14, RAB11A, RAB10, RAB38, RAN, RIT1, RAB9A) with RHOA identified to have a transient 3'UTR RNA base editing at a conserved site found in all of its transcripts. Overall, we show a remarkable and dynamic role of splicing within the small GTPase family that requires future explorations.

Targeting the CTLA-4/B7 axes in glioblastoma: preclinical evidence and clinical interventions

INTRODUCTION

Glioblastoma Multiforme (GBM) is one of the fatal cancers of the Central Nervous System (CNS). A variety of reasons exist for why previous immunotherapy strategies, especially Immune Checkpoint Blockers (ICBs), did not work in treating GBM patients. The cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) is a key immune checkpoint receptor. Its overexpression in cancer and immune cells causes tumor cell progression. CTLA-4 suppresses anti-tumor responses inside the GBM tumor-immune microenvironment.

AREAS COVERED

It has been attempted to explain the immunobiology of CTLA-4 as well as its interaction with different immune cells and cancer cells that lead to GBM progression. Additionally, CTLA-4 targeting studies have been reviewed and CTLA-4 combination therapy, as a promising therapeutic target and strategy for GBM immunotherapy, is recommended.

EXPERT OPINION

CTLA-4 could be a possible supplement for future cancer immunotherapies of GBM. However, many challenges remain such as the high toxicity of CTLA-4 blockers, and the unresponsiveness of most patients to immunotherapy. For the future clinical success of CTLA-4 blocker therapy, combination approaches with other targeted treatments would be a potentially effective strategy. Going forward, predictive biomarkers can be used to reduce trial timelines and increase the chance of success.

Androgen Receptor Expression in the Various Regions of Resected Glioblastoma Multiforme Tumors and in an In Vitro Model

Glioblastoma multiforme (GBM) is a malignant glioma, difficult to detect and with the lowest survival rates among gliomas. Its greater incidence among men and its higher survival rate among premenopausal women suggest that it may be associated with the levels of androgens. As androgens stimulate the androgen receptor (AR), which acts as a transcription factor, the aim of this study was the investigate the role of AR in the progression of GBM. The study was conducted on tissues collected from three regions of GBM tumors (tumor core, enhancing tumor region, and peritumoral area). In addition, an in vitro experiment was conducted on U-87 cells under various culture conditions (necrotic, hypoxic, and nutrient-deficient), mimicking the conditions in a tumor. In both of the models, androgen receptor expression was determined at the gene and protein levels, and the results were confirmed by confocal microscopy and immunohistochemistry. AR mRNA expression was higher under nutrient-deficient conditions and lower under hypoxic conditions in vitro. However, there were no differences in AR protein expression. No differences in AR mRNA expression were observed between the tested tumor structures taken from patients. No differences in AR mRNA expression were observed between the men and women. However, AR protein expression in tumors resected from patients was higher in the enhancing tumor region and in the peritumoral area than in the tumor core. In women, higher AR expression was observed in the peritumoral area than in the tumor core. AR expression in GBM tumors did not differ significantly between men and women, which suggests that the higher incidence of GBM in men is not associated with AR expression. In the group consisting of men and women, AR expression varied between the regions of the tumor: AR expression was higher in the enhancing tumor region and in the peritumoral area than in the tumor core, showing a dependence on tumor conditions (hypoxia and insufficient nutrient supply).

Enzalutamide Induces Apoptotic Insults to Human Drug-Resistant and -Sensitive Glioblastoma Cells via an Intrinsic Bax-Mitochondrion-Cytochrome C Caspase Cascade Activation Pathway

Glioblastoma multiforme (GBM) is the most common and malignant brain tumor. Temozolomide (TMZ) is the first-line chemotherapeutic drug for treating GBM. However, drug resistance is still a challenging issue in GBM therapy. Our preliminary results showed upregulation of androgen receptor (AR) gene expression in human GBM tissues. This study was designed to evaluate the effects of enzalutamide, a specific inhibitor of the AR, on killing drug-resistant and -sensitive glioblastoma cells and the possible mechanisms. Data mining from The Cancer Genome Atlas (TCGA) database revealed upregulation of AR messenger (m)RNA and protein expressions in human GBM tissues, especially in male patients, compared to normal human brains. In addition, expressions of AR mRNA and protein in human TMZ-sensitive U87 MG and -resistant U87 MG-R glioblastoma cells were elevated compared to normal human astrocytes. Exposure of human U87 MG and U87 MG-R cells to enzalutamide concentration- and time-dependently decreased cell viability. As to the mechanism, enzalutamide killed these two types of glioblastoma cells via an apoptotic mechanism. Specifically, exposure to enzalutamide augmented enzyme activities of caspase-9 rather than those of caspase-8. Moreover, enzalutamide successively triggered an elevation in levels of the proapoptotic Bax protein, a reduction in the mitochondrial membrane potential, release of cytochrome c, cascade activation of caspases-3 and -6, DNA fragmentation, and cell apoptosis in human TMZ-sensitive and -resistant glioblastoma cells. Pretreatment with Z-VEID-FMK, an inhibitor of caspase-6, caused significant attenuations in enzalutamide-induced morphological shrinkage, DNA damage, and apoptotic death. Taken together, this study showed that enzalutamide could significantly induce apoptotic insults to human drug-resistant and -sensitive glioblastoma cells via an intrinsic Bax-mitochondrion-cytochrome c-caspase cascade activation pathway. Enzalutamide has the potential to be a drug candidate for treating GBM by targeting the AR signaling axis.

The Next Frontier in Health Disparities—A Closer Look at Exploring Sex Differences in Glioma Data and Omics Analysis, from Bench to Bedside and Back

Sex differences are increasingly being explored and reported in oncology, and glioma is no exception. As potentially meaningful sex differences are uncovered, existing gender-derived disparities mirror data generated in retrospective and prospective trials, real-world large-scale data sets, and bench work involving animals and cell lines. The resulting disparities at the data level are wide-ranging, potentially resulting in both adverse outcomes and failure to identify and exploit therapeutic benefits. We set out to analyze the literature on women’s data disparities in glioma by exploring the origins of data in this area to understand the representation of women in study samples and omics analyses. Given the current emphasis on inclusive study design and research, we wanted to explore if sex bias continues to exist in present-day data sets and how sex differences in data may impact conclusions derived from large-scale data sets, omics, biospecimen analysis, novel interventions, and standard of care management.