A contemporary update on glioblastoma: molecular biology, current management, and a vision towards bio-adaptable personalized care

Glut-3 Gene Knockdown as a Potential Strategy to Overcome Glioblastoma Radioresistance

The hypoxic pattern of glioblastoma (GBM) is known to be a primary cause of radioresistance. Our study explored the possibility of using gene knockdown of key factors involved in the molecular response to hypoxia, to overcome GBM radioresistance. We used the U87 cell line subjected to chemical hypoxia generated by CoCl2 and exposed to 2 Gy of X-rays, as single or combined treatments, and evaluated gene expression changes of biomarkers involved in the Warburg effect, cell cycle control, and survival to identify the best molecular targets to be knocked-down, among those directly activated by the HIF-1α transcription factor. By this approach, glut-3 and pdk-1 genes were chosen, and the effects of their morpholino-induced gene silencing were evaluated by exploring the proliferative rates and the molecular modifications of the above-mentioned biomarkers. We found that, after combined treatments, glut-3 gene knockdown induced a greater decrease in cell proliferation, compared to pdk-1 gene knockdown and strong upregulation of glut-1 and ldha, as a sign of cell response to restore the anaerobic glycolysis pathway. Overall, glut-3 gene knockdown offered a better chance of controlling the anaerobic use of pyruvate and a better proliferation rate reduction, suggesting it is a suitable silencing target to overcome radioresistance.

CXCR2-Blocking Has Context-Sensitive Effects on Rat Glioblastoma Cell Line Outgrowth (S635) in an Organotypic Rat Brain Slice Culture Depending on Microglia-Depletion (PLX5622) and Dexamethasone Treatment

In glioblastoma (GBM), the interplay of different immune cell subtypes, cytokines, and/or drugs shows high context-dependencies. Interrelations between the routinely applied dexamethasone (Dex) and microglia remain elusive. Here, we exploited rat organotypic brain slice co-cultures (OBSC) to examine the effects on a rat GBM cell line (S635) outgrowth resulting from the presence of Dex and pretreatment with the colony-stimulating factor receptor 1 (CSF1-R) inhibitor PLX5622: in native OBSC (without PLX5622-pretreatment), a diminished S635 spheroid outgrowth was observable, whereas Dex-treatment enhanced outgrowth in this condition compared to PLX5622-pretreated OBSC. Screening the supernatants of our model with a proteome profiler, we found that CXCL2 was differentially secreted in a Dex- and PLX5622-dependent fashion. To analyze causal interrelations, we interrupted the CXCL2/CXCR2-axis: in the native OBSC condition, CXCR2-blocking resulted in increased outgrowth, in combination with Dex, we found potentiated outgrowth. No effect was found in the PLX5622-pretreated. Our method allowed us to study the influence of three different factors-dexamethasone, PLX5622, and CXCL2-in a well-controlled, simplified, and straight-forward mechanistic manner, and at the same time in a more realistic ex vivo scenario compared to in vitro studies. In our model, we showed a GBM outgrowth enhancing synergism between CXCR2-blocking and Dex-treatment in the native condition, which was levelled by PLX5622-pretreatment.

Personalized Treatment of Glioblastoma: Current State and Future Perspective

Glioblastoma (GBM) is the most aggressive glial tumor of the central nervous system. Despite intense scientific efforts, patients diagnosed with GBM and treated with the current standard of care have a median survival of only 15 months. Patients are initially treated by a neurosurgeon with the goal of maximal safe resection of the tumor. Obtaining tissue samples during surgery is indispensable for the diagnosis of GBM. Technological improvements, such as navigation systems and intraoperative monitoring, significantly advanced the possibility of safe gross tumor resection. Usually within six weeks after the surgery, concomitant radiotherapy and chemotherapy with temozolomide are initiated. However, current radiotherapy regimens are based on population-level studies and could also be improved. Implementing artificial intelligence in radiotherapy planning might be used to individualize treatment plans. Furthermore, detailed genetic and molecular markers of the tumor could provide patient-tailored immunochemotherapy. In this article, we review current standard of care and possibilities of personalizing these treatments. Additionally, we discuss novel individualized therapeutic options with encouraging results. Due to inherent heterogeneity of GBM, applying patient-tailored treatment could significantly prolong survival of these patients.

Effects of Dendrimer-microRNA Nanoformulations against Glioblastoma Stem Cells

Glioblastoma is a rapidly progressing tumor quite resistant to conventional treatment. These features are currently assigned to a self-sustaining population of glioblastoma stem cells. Anti-tumor stem cell therapy calls for a new means of treatment. In particular, microRNA-based treatment is a solution, which in turn requires specific carriers for intracellular delivery of functional oligonucleotides. Herein, we report a preclinical in vitro validation of antitumor activity of nanoformulations containing antitumor microRNA miR-34a and microRNA-21 synthetic inhibitor and polycationic phosphorus and carbosilane dendrimers. The testing was carried out in a panel of glioblastoma and glioma cell lines, glioblastoma stem-like cells and induced pluripotent stem cells. We have shown dendrimer-microRNA nanoformulations to induce cell death in a controllable manner, with cytotoxic effects being more pronounced in tumor cells than in non-tumor stem cells. Furthermore, nanoformulations affected the expression of proteins responsible for interactions between the tumor and its immune microenvironment: surface markers (PD-L1, TIM3, CD47) and IL-10. Our findings evidence the potential of dendrimer-based therapeutic constructions for the anti-tumor stem cell therapy worth further investigation.

Nanotechnology-Based Combinatorial Anti-Glioblastoma Therapies: Moving from Terminal to Treatable

Aggressive glioblastoma (GBM) has no known treatment as a primary brain tumor. Since the cancer is so heterogeneous, an immunosuppressive tumor microenvironment (TME) exists, and the blood–brain barrier (BBB) prevents chemotherapeutic chemicals from reaching the central nervous system (CNS), therapeutic success for GBM has been restricted. Drug delivery based on nanocarriers and nanotechnology has the potential to be a handy tool in the continuing effort to combat the challenges of treating GBM. There are various new therapies being tested to extend survival time. Maximizing therapeutic effectiveness necessitates using many treatment modalities at once. In the fight against GBM, combination treatments outperform individual ones. Combination therapies may be enhanced by using nanotechnology-based delivery techniques. Nano-chemotherapy, nano-chemotherapy–radiation, nano-chemotherapy–phototherapy, and nano-chemotherapy–immunotherapy for GBM are the focus of the current review to shed light on the current status of innovative designs.

Expression Profiles of HOXC6 Predict the Survival of Glioblastoma Patients and Correlate with Cell Cycle

The goal of this study was to investigate the homeobox (HOX) gene expression status and its prognostic value in glioblastoma multiforme (GBM) and to uncover the biological processes related to its expression. The prognostic value of HOX genes in GBM was systematically investigated by a genome-wide analysis of HOX gene expression profiles in GBM patient samples in The Cancer Genome Atlas (TCGA) project (microarray dataset) and validation datasets. Using the differentially expressed gene (DEG) analysis and a Cox regression model, we discovered that the HOXC6 could stratify patients into significantly different survival (p = 0.0012, log-rank test) groups in the training cohort. TCGA RNA-seq and GSE16011 datasets were used for validation. Multivariate Cox and stratification analysis indicated that HOXC6 was an independent prognostic factor after adjusting for other clinical covariates. Bioinformatic analysis suggested that the HOXC6 might be involved in the cell cycle-related biological processes and pathways that are well established in the context of glioblastoma tumorigenesis. We further explored the bioinformatic implications by gene set enrichment analysis (GSEA). Tumor cell biology experiments verified the role of HOXC6 in proliferation and cell cycle progression. In conclusion, HOXC6 might be a candidate biomarker gene for individual treatment optimization of glioblastoma. HOXC6 expression has a significant prognostic value and is related to the cell cycle process in glioblastoma.

Novel Concepts of Glioblastoma Therapy Concerning Its Heterogeneity

Although treatment outcomes of glioblastoma, the most malignant central nervous system (CNS) tumor, has improved in the past decades, it is still incurable, and survival has only slightly improved. Advances in molecular biology and genetics have completely transformed our understanding of glioblastoma. Multiple classifications and different diagnostic methods were made according to novel molecular markers. Discovering tumor heterogeneity only partially explains the ineffectiveness of current anti-proliferative therapies. Dynamic heterogeneity secures resistance to combined oncotherapy. As tumor growth proceeds, new therapy-resistant sub clones emerge. Liquid biopsy is a new and promising diagnostic tool that can step up with the dynamic genetic change. Getting a 'real-time' picture of a specific tumor, anti-invasion and multi-target treatment can be designed. During invasion to the peri-tumoral brain tissue, glioma cells interact with the extracellular matrix components. The expressional levels of these matrix molecules give a characteristic pattern, the invasion spectrum, which possess vast diagnostical, predictive and prognostic information. It is a huge leap forward combating tumor heterogeneity and searching for novel therapies. Using the invasion spectrum of a tumor sample is a novel tool to distinguish between histological subtypes, specifying the tumor grades or different prognostic groups. Moreover, new therapeutic methods and their combinations are under trial. These are crucial steps towards personalized oncotherapy.

The Evolving Role of Induced Pluripotent Stem Cells and Cerebral Organoids in Treating and Modeling Neurosurgical Diseases

Over the past decade, the use of induced pluripotent stem cells (IPSCs), as both direct therapeutics and building blocks for 3D in vitro models, has exhibited exciting potential in both helping to elucidate pathogenic mechanisms and treating diseases relevant to neurosurgery. Transplantation of IPSCs is being studied in neurological injuries and diseases, such as spinal cord injury and Parkinson's disease, whose clinical manifestations stem from underlying neuronal and/or axonal degeneration. Both animal models and clinical trials have shown that IPSCs have the ability to regenerate damaged neural tissue. Such evidence makes IPSCs a potentially promising therapeutic modality for patients who suffer from these neurological injuries/diseases. In addition, the cerebral organoid, a 3D assembly of IPSC aggregates that develops heterogeneous brain regions, has become the first in vitro model to closely recapitulate the complexity of the brain extracellular matrix, a 3-dimensional network of molecules that structurally and biochemically support neighboring cells. Cerebral organoids have become an exciting prospect for modeling and testing drug susceptibility of brain tumors, such as glioblastoma and metastatic brain cancer. As patient-derived organoid models are becoming more faithful to the brain, they are becoming an increasingly accurate substitute for patient clinical trials; such patient-less trials would protect the patient from potentially ineffective drugs, and speed up trial results and optimize cost. In this review, we aim to describe the role of IPSCs and cerebral organoids in treating and modeling diseases that are relevant to neurosurgery.

Genomic Analysis of Glioblastoma Multiforme Reveals a Key Transcription Factor Signature Relevant to Prognosis and the Immune Processes

Introduction

Glioblastoma multiforme (GBM) develops through the accumulation of both genetic and expression alterations. Although many gene signatures have been developed as prognostic and predictive biomarkers, their robustness and functional aspects are less well characterized. The expression of most genes is regulated by transcription factors (TFs); therefore, we aimed to investigate a TF signature relevant to GBM prognosis.

Methods

We used bioinformatic methods and data from public databases to establish four clusters of key TF genes, among which cluster 1, comprising 24 TFs, showed significant prognostic value. Further in silico functional analyses were applied to investigate the utility of the TF signature.

Results

Different mutation and copy number variation patterns were observed between different risk score groups (based on the TF signature). In silico analyses suggested that the cases with relative high risk scores were involved in immune and inflammatory processes or pathways.

Conclusion

The TF signature has significant prognostic value in different cohorts or subgroups of patients with GBM and could lead to the development immunotherapy for GBM.