Glioblastoma (GBM) may arise from astrocytes through a multistep process involving a progressive accumulation of mutations. We explored whether GBM-derived extracellular vesicles (EVs) may facilitate neoplastic transformation and malignant growth of astrocytes. We utilized conditioned media (CM) of cultured glioma cells, its sequential filtration, diverse cell-based assays, RNA sequencing, and metabolic assays to compare the effects of EV-containing and EV-depleted CM. GBM EVs facilitated the neoplastic growth of pre-transformed astrocytes but not normal human or mouse astrocytes. They induced proliferation, self-renewal, and colony formation of pre-transformed astrocytes and enhanced astrocytoma growth in a mouse allograft model. GBM EVs appear to reprogram astrocyte metabolism by inducing a shift in gene expression that may be partly associated with EV-mediated transfer of full-length mRNAs encoding ribosomal proteins, oxidative phosphorylation, and glycolytic factors. Our study suggests an EV/extracellular RNA (exRNA)-mediated mechanism that contributes to astrocyte transformation via metabolic reprograming and implicates horizontal mRNA transfer.

Background and objective: Cognitive impairments have been reported in patients with hyperprolactinemia; however, there is a lack of knowledge of brain structure alterations relevant to hyperprolactinemia in prolactinomas. Thus, we aimed to identify changes in brain structure in prolactinomas and to determine whether these changes are related to cognitive performance and clinical characteristics. Methods: Participants were 32 female patients with prolactinomas and 26 healthy controls (HC) matched for age, sex, education, and handedness. All participants underwent magnetic resonance imaging brain scans, neuropsychological assessments, and clinical evaluations. Voxel-based morphometry analysis was used to identify changes in gray matter volume (GMV). Partial correlation analysis and multiple linear regression were performed to determine the relationship between GMV, cognition, and clinical characteristics. Results: Compared to HC, patients with prolactinomas demonstrated a decrease in GMV in the left hippocampus, left orbitofrontal cortex, right middle frontal cortex (MFC), and right inferior frontal cortex (IFC). In addition, patients performed worse than controls on tests for verbal memory and executive function, and this was significantly related to the GMV of the left hippocampus and right MFC, respectively. Moreover, in the patients, we found a negative relationship between serum prolactin levels and the GMV of the left hippocampus and right IFC, whereas a positive relationship was found between the GMV of the left hippocampus and serum levels of estradiol and luteinizing hormone. Conclusion: In patients with prolactinomas, specific brain structure abnormalities have been identified and are associated with cognitive impairments and dysfunctional hormones. This study enhances our understanding of brain structure changes that may occur with prolactinomas and provides novel and fundamental evidence for previous behavioral findings relevant to hyperprolactinemia.

Neurosurgery has been at the forefront of a paradigm shift from a localizationist perspective to a network-based approach to brain mapping. Over the last 2 decades, we have seen dramatic improvements in the way we can image the human brain and noninvasively estimate the location of critical functional networks. In certain patients with brain tumors and epilepsy, intraoperative electrical stimulation has revealed direct links between these networks and their function. The focus of these techniques has rightfully been identification and preservation of so-called “eloquent” brain functions (i.e., motor and language), but there is building momentum for more extensive mapping of cognitive and emotional networks. In addition, there is growing interest in mapping these functions in patients with a broad range of neurosurgical diseases. Resting-state functional MRI (rs-fMRI) is a noninvasive imaging modality that is able to measure spontaneous low-frequency blood oxygen level–dependent signal fluctuations at rest to infer neuronal activity. Rs-fMRI may be able to map cognitive and emotional networks for individual patients. In this review, the authors give an overview of the rs-fMRI technique and associated cognitive and emotional resting-state networks, discuss the potential applications of rs-fMRI, and propose future directions for the mapping of cognition and emotion in neurosurgical patients.

Recombinant adeno-associated viruses (rAAVs) have emerged as an attractive tool for gene delivery, and demonstrated tremendous promise in gene therapy and gene editing—therapeutic modalities with potential “one-and-done” treatment benefits compared to conventional drugs. Given their tropisms for the central nervous system (CNS) across various species including humans, rAAVs have been extensively investigated in both pre-clinical and clinical studies targeting neurodegenerative disease. However, major challenges remain in the application of rAAVs for CNS gene therapy, such as suboptimal vector design, low CNS transduction efficiency and specificity, and therapy-induced immunotoxicity. Therefore, continuing efforts are being made to optimize the rAAV vectors from their “core” genetic payloads to their “coat” or capsid structure. In this review, we describe current approaches for rAAV vector design tailored for transgene expression in the CNS, summarize the development of CNS-targeting AAV serotypes, and highlight recent advancements in AAV capsid engineering, aimed at generating a new generation of rAAVs with improved CNS tropism. Additionally, we discuss various administration routes for delivering rAAVs to the CNS and provide an overview of AAV-mediated gene therapies currently under investigation in clinical trials for the treatment of neurodegenerative diseases.