Molecular analyses of glioblastoma stem-like cells and glioblastoma tissue

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

Purpose

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.

Methods

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.

Results

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.

Conclusion

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.

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

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.

A Combined Effect of G-Quadruplex and Neuro-Inducers as an Alternative Approach to Human Glioblastoma Therapy

Cancer cell reprogramming based on treatment with G-quadruplex, having antiproliferative power, along with small molecules able to develop iPSCs into neurons, could create a novel approach to diminish the chance of glioblastoma recurrence and circumvent tumor resistance to conventional therapy. In this research, we have tested several combinations of factors to affect both total cell cultures, derived from tumor tissue of patients after surgical resection and two subfractions of this cell culture after dividing them into CD133-enriched and CD133-depleted populations (assuming CD133 to be a marker of glioblastoma stem-like cells). CD133⁺ and CD133⁻ cells exhibit different responses to the same combinations of factors; CD133⁺ cells have stem-like properties and are more resistant. Therefore, the ability to affect CD133⁺ cells provides a possibility to circumvent resistance to conventional therapy and to build a promising strategy for translation to improve the treatment of patients with glioblastoma.

Pan-Tissue Aging Clock Genes That Have Intimate Connections with the Immune System and Age-Related Disease

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 tissue-specific model utilized a unique number of genes for age prediction, we found that the following six genes were prioritized in all five tissues: CHI3L2, CIDEC, FCGR3A, RPS4Y1, SLC11A1, and VTCN1. Since being selected for age prediction in multiple tissues is unique, we decided to explore these pan-tissue clock genes in greater detail. In the present study, we began by performing over-representation and network topology-based enrichment analyses in the Gene Ontology Biological Process database. These analyses revealed that the immunological terms "response to protozoan," "immune response," and "positive regulation of immune system process" were significantly enriched by these clock inputs. Expression analyses in mouse and human tissues identified that these inputs are frequently upregulated or downregulated with age. A detailed literature search showed that all six genes had noteworthy connections to age-related disease. For example, mice deficient in Cidec are protected against various metabolic defects, while suppressing VTCN1 inhibits age-related cancers in mouse models. Using a large multitissue transcriptomic dataset, we additionally generate a novel, minimalistic aging clock that can predict human age using just these six genes as inputs. Taken all together, these six genes are connected to diverse aspects of aging.

Molecular Mechanisms of Drug Resistance in Glioblastoma

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).