Glioblastoma multiforme (GBM) is the most common and fatal primary brain tumor, is highly resistant to conventional radiation and chemotherapy, and is not amenable to effective surgical resection. The present review summarizes recent advances in our understanding of the molecular mechanisms of therapeutic resistance of GBM to already known drugs, the molecular characteristics of glioblastoma cells, and the barriers in the brain that underlie drug resistance. We also discuss the progress that has been made in the development of new targeted drugs for glioblastoma, as well as advances in drug delivery across the blood-brain barrier (BBB) and blood-brain tumor barrier (BBTB).

Molecular Mechanisms of Drug Resistance in Glioblastoma.

Simple Summary Glioblastoma stem cells are a unique population of tumor cells that contribute to tumor growth, invasion, and resistance to chemotherapy and radiation therapy. These stem cells are capable of self-renewal and proliferation. Traditional treatment strategies that target glioblastoma often fail to eradicate these stem cells, contributing to tumor recurrence. Dysregulation of several critical signaling pathways drive the oncogenic nature of glioblastoma stem cells and represent attractive therapeutic targets. Additionally, these stem cells possess a high mutation rate and feature epigenomic changes that alter the landscape of their genomic expression. Here, we review the phenotypic characteristics of glioblastoma stem cells, their interactions with the tumor microenvironment, critical signaling pathways, and epigenomic landscape of glioblastoma stem cells. Therapeutic targets are discussed in the context of these pathways and mutations. A multi-pronged therapeutic approach will likely be needed to simultaneously target multiple pathways and molecules to overcome tumor resistance mechanisms. Abstract Glioblastoma (GBM) is an aggressive tumor of the central nervous system categorized by the World Health Organization as a Grade 4 astrocytoma. Despite treatment with surgical resection, adjuvant chemotherapy, and radiation therapy, outcomes remain poor, with a median survival of only 14-16 months. Although tumor regression is often observed initially after treatment, long-term recurrence or progression invariably occurs. Tumor growth, invasion, and recurrence is mediated by a unique population of glioblastoma stem cells (GSCs). Their high mutation rate and dysregulated transcriptional landscape augment their resistance to conventional chemotherapy and radiation therapy, explaining the poor outcomes observed in patients. Consequently, GSCs have emerged as targets of interest in new treatment paradigms. Here, we review the unique properties of GSCs, including their interactions with the hypoxic microenvironment that drives their proliferation. We discuss vital signaling pathways in GSCs that mediate stemness, self-renewal, proliferation, and invasion, including the Notch, epidermal growth factor receptor, phosphatidylinositol 3-kinase/Akt, sonic hedgehog, transforming growth factor beta, Wnt, signal transducer and activator of transcription 3, and inhibitors of differentiation pathways. We also review epigenomic changes in GSCs that influence their transcriptional state, including DNA methylation, histone methylation and acetylation, and miRNA expression. The constituent molecular components of the signaling pathways and epigenomic regulators represent potential sites for targeted therapy, and representative examples of inhibitory molecules and pharmaceuticals are discussed. Continued investigation into the molecular pathways of GSCs and candidate therapeutics is needed to discover new effective treatments for GBM and improve survival.

https://www.mdpi.com/2072-6694/14/15/3743/pdf?version=1659587166

Molecular Pathways and Genomic Landscape of Glioblastoma Stem Cells: Opportunities for Targeted Therapy

In our recent transcriptomic meta-analysis, we used random forest machine learning to accurately predict age in human blood, bone, brain, heart, and retina tissues given gene inputs. Although each ...

Pan-tissue aging clock genes that have intimate connections with the immune system and age-related disease

To predict chromosome 7 gain and chromosome 10 loss (+7/-10) in IDH wild-type (IDH-wt) histologically low-grade gliomas (LGG) by machine learning models based on MRI radiomics and semantic features.A total of 122 patients diagnosed as IDH-wt histologically LGG were retrospectively included in this study. The patients were randomly divided into a training group and a test group in a ratio of 7:3. The radiomics features were extracted from axial T1WI, T2WI, FLAIR and CET1 sequences, respectively. The distance correlation (DC) and least absolute shrinkage and selection operator (LASSO) were used to select the radiomics signatures. Three machine learning algorithms including neural network (NN), support vector machine (SVM), and linear discriminant analysis (LDA) were used to construct radiomics models. In addition, a nomogram was developed by combining the optimal radiomics signature with clinical risk factors, and the potential clinical utility of the nomogram was evaluated using decision curve analysis.The LDA+DC model was identified as the optimal classifier among the six radiomics models. Necrosis was determined as a risk factor for +7/-10 in IDH-wt histologically LGG. The nomogram achieved the best performance, with an AUC of 0.854 and an accuracy of 0.778 in the independent test group. The decision curve of the nomogram confirmed its clinical usefulness in a wide range of thresholds.The nomogram combining radiomics and semantic features can predict the +7/-10 status effectively, which may contribute to the risk stratification and individualized treatment planning of patients with IDH-wt histologically LGG.

Development of a nomogram based on radiomics and semantic features for predicting chromosome 7 gain/chromosome 10 loss in IDH wild-type histologically low-grade gliomas

Glioblastomas (GB) are aggressive brain tumors characterized for remarkably resistance to conventional therapies, resulting in low patient survival rates. Despite all the efforts to improve the therapeutic approaches, the truth is that GB heterogeneity and the existence of a Blood-Brain Barrier (BBB) have been associated with most treatments’ failure. This chapter focuses on the new therapeutical avenues to overcome these main treatment limitations. We discuss the use of single-cell analysis and how it could be one of the alternatives to unravel GB heterogeneity by helping to identify new molecular targets. Additionally, we highlight the recent advances in the synthetic nanoparticles field to overcome the BBB challenge by acting as a drug-delivery system to the brain and targeting the GB. We culminate, bringing to light the most relevant clinical trials in the course using the described technology and methodology along this chapter to cure this tumor. Herein, an overview of GB research’s recent advances and challenges is provided to set the stage for future directions. 

Glioblastoma heterogeneity and resistance: A glance in biology and therapeutic approach

Glioblastoma is a common, malignant brain tumor whose disease incidence increases with age. Glioblastoma stem-like cells (GSCs) are thought to contribute to cancer therapy resistance and to be responsible for tumor initiation, maintenance, and recurrence. This study utilizes both SNP array and gene expression profiling to better understand GSCs and their relation to malignant disease. Peripheral blood and primary glioblastoma tumor tissue were obtained from patients, the latter of which was used to generate GSCs as well as a CD133pos./CD15pos. subpopulation. The stem cell features of GSCs were confirmed via the immunofluorescent expression of Nestin, SOX2, and CD133. Both tumor tissue and the isolated primary cells shared unique abnormal genomic characteristics, including a gain of chromosome 7 as well as either a partial or complete loss of chromosome 10. Individual genomic differences were also observed, including the loss of chromosome 4 and segmental uniparental disomy of 9p24.3→p21.3 in GSCs. Gene expression profiling revealed 418 genes upregulated in tumor tissue vs. CD133pos./CD15pos. cells and 44 genes upregulated in CD133pos./CD15pos. cells vs. tumor tissue. Pathway analyses demonstrated that upregulated genes in CD133pos./CD15pos. cells are relevant to cell cycle processes and cancerogenesis. In summary, we detected previously undescribed genomic and gene expression differences when comparing tumor tissue and isolated stem-like subpopulations.

/pdf/molecular-analyses-of-glioblastoma-stem-like-cells-and-zlxk2l4838.pdf

Molecular analyses of glioblastoma stem-like cells and glioblastoma tissue

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Molecular analyses of glioblastoma stem-like cells and glioblastoma tissue