Surgical Management and Advances in the Treatment of Glioma

MiR-326: Role and significance in brain cancers

MicroRNAs (miRNAs) are small non-coding RNAs that act as critical regulators of gene expression by repressing mRNA translation. The role of miRNAs in cell physiology spans from cell cycle control to cell proliferation and differentiation, both during development and in adult tissues. Accordingly, dysregulated expression of miRNAs has been reported in several diseases, including cancer, where miRNAs can act as oncogenes or oncosuppressors. Of note, miRNA signatures are also under investigation for classification, diagnosis, and prognosis of cancer patients. Brain tumours are primarily associated with poor prognosis and high mortality, highlighting an urgent need for novel diagnostic, prognostic, and therapeutic tools. Among miRNAs investigated in brain tumours, miR-326 has been shown to act as a tumour suppressor in adult and paediatric brain cancers. In this review, we describe the role of miR-326 in malignant as well as benign cancers originating from brain tissue. In addition, since miR-326 expression can be regulated by other non-coding RNA species, adding a further layer of regulation in the cancer-promoting axis, we discuss this miRNA's role in targeted therapy for brain cancers.

Biopsy location and tumor-associated macrophages in predicting malignant glioma recurrence using an in-silico model

Predicting the biological behavior and time to recurrence (TTR) of high-grade diffuse gliomas (HGG) after maximum safe neurosurgical resection and combined radiation and chemotherapy plays a pivotal role in planning clinical follow-up, selecting potentially necessary second-line treatment and improving the quality of life for patients diagnosed with a malignant brain tumor. The current standard-of-care (SoC) for HGG includes follow-up neuroradiological imaging to detect recurrence as early as possible and relies on several clinical, neuropathological, and radiological prognostic factors, which have limited accuracy in predicting TTR. In this study, using an in-silico analysis, we aim to improve predictive power for TTR by considering the role of (i) prognostically relevant information available through diagnostics used in the current SoC, (ii) advanced image-based information not currently part of the standard diagnostic workup, such as tumor-normal tissue interface (edge) features and quantitative data specific to biopsy positions within the tumor, and (iii) information on tumor-associated macrophages. In particular, we introduced a state-of-the-art spatio-temporal model of tumor-immune interactions, emphasizing the interplay between macrophages and glioma cells. This model serves as a synthetic reality for assessing the predictive value of various features. We generated a cohort of virtual patients based on our mathematical model. Each patient's dataset includes simulated T1Gd and Fluid-attenuated inversion recovery (FLAIR) MRI volumes. T1-weighted imaging highlights anatomical structures with high contrast, providing clear detail on brain morphology, whereas FLAIR suppresses fluid signals, improving the visualization of lesions near fluid-filled spaces, which is particularly helpful for identifying peritumoral edema. Additionally, we simulated results on macrophage density and proliferative activity, either in a specified part of the tumor, namely the tumor core or edge ("localized"), or unspecified ("non-localized"). To enhance the realism of our synthetic data, we imposed different levels of noise. Our findings reveal that macrophage density at the tumor edge contributed to a high predictive value of feature importance for the selected regression model. Moreover, there are lower MSE values for the "localized" biopsy in prediction accuracy toward recurrence post-resection compared with "non-localized" specimens in the noisy data. In conclusion, the results show that localized biopsies provided more information about tumor behavior, especially at the interface of tumor and normal tissue (Edge).

Enhanced Antiglioma Effect by a Vitamin D3-Inserted Lipid Hybrid Neutrophil Membrane Biomimetic Multimodal Nanoplatform

Glioblastoma, the most prevalent malignant brain tumor, is a lethal threat to human health, with aggressive and infiltrative growth characteristics that compromise the clinical treatment. Herein, we developed a vitamin D3-inserted lipid hybrid neutrophil membrane biomimetic multimodal nanoplatform (designated as NED@MnO2-DOX) through doxorubicin (DOX)-loaded manganese dioxide nanoparticles (MnO2) which were coated with a vitamin D3-inserted lipid hybrid neutrophil membrane. It was demonstrated that in addition to chemotherapy and chemo-dynamic therapy efficacy, NED@MnO2-DOX exhibited great power to activate and amplify immune responses related to the cGAS STING pathway, bolstering the secretion of type I interferon-β and proinflammatory cytokines, promoting the maturation of DC cells and infiltration of CD8+T cells into the glioma tissue, thereby reversing the immunosuppressive microenvironment of glioma from a "cold" tumor to a "hot" tumor. The biomimetic multimodal nanoplatform has potential as a multimodal strategy for glioma-targeted treatment, especially holding considerable promise for the development of innate immune therapy for glioma.

Gene Expression of CSF3R/CD114 Is Associated with Poorer Patient Survival in Glioma

Gliomas comprise most cases of central nervous system (CNS) tumors. Gliomas afflict both adults and children, and glioblastoma (GBM) in adults represents the clinically most important type of malignant brain cancer, with a very poor prognosis. The cell surface glycoprotein CD114, which is encoded by the CSF3R gene, acts as the receptor for the granulocyte colony stimulating factor (GCSF), and is thus also called GCSFR or CSFR. CD114 is a marker of cancer stem cells (CSCs), and its expression has been reported in several cancer types. In addition, CD114 may represent one among various cases where brain tumors hijack molecular mechanisms involved in neuronal survival and synaptic plasticity. Here, we describe CSF3R mRNA expression in human gliomas and their association with patient prognosis as assessed by overall survival (OS). We found that the levels of CSF3R/CD114 transcripts are higher in a few different types of gliomas, namely astrocytoma, pilocytic astrocytoma, and GBM, in comparison to non-tumoral neural tissue. We also observed that higher expression of CSF3R/CD114 in gliomas is associated with poorer outcome as measured by a shorter OS. Our findings provide early evidence suggesting that CSF3R/CD114 shows a potential role as a prognosis marker of OS in patients with GBM.