Meningiomas are mostly benign, slow-growing tumors of the CNS that originate from arachnoidal cap cells. While monosomy 22 is the most frequent genetic abnormality found in meningiomas, a multitude of other aberrant chromosomal alterations, signaling pathways, and growth factors have been implicated in its pathogenesis. Losses on 22q12.2, a region encoding the tumor suppressor gene merlin, represent the most common genetic alterations in early meningioma formation. Malignant meningioma progression, however, is associated with more complex karyotypes and greater genetic instability. Cytogenetic studies of atypical and anaplastic meningiomas revealed gains and losses on chromosomes 9, 10, 14, and 18, with amplifications on chromosome 17. However, the specific gene targets in a majority of these chromosomal abnormalities remain elusive. Studies have also implicated a myriad of aberrant signaling pathways involved with meningioma tumorigenesis, including those involved with proliferation, angiogenesis, and autocrine loops. Understanding these disrupted pathways will aid in deciphering the relationship between various genetic changes and their downstream effects on meningioma pathogenesis. Despite advancements in our understanding of meningioma pathogenesis, the conventional treatments, including surgery, radiotherapy, and stereotactic radiosurgery, have remained largely stagnant. Surgery and radiation therapy are curative in the majority of lesions, yet treatment remains challenging for meningiomas that are recurrent, aggressive, or refractory to conventional treatments. Future therapies will include combinations of targeted molecular agents as a result of continued progress in the understanding of genetic and biological changes associated with meningiomas.

T he scientific, academic, medical and data science communities have come together in the face of the COVID-19 pandemic crisis to rapidly assess novel paradigms in artificial intelligence (AI) that are rapid and secure, and potentially incentivize data sharing and model training and testing without the usual privacy and data ownership hurdles of conventional collaborations 1,2 . Healthcare providers, researchers and industry have pivoted their focus to address unmet and critical clinical needs created by the crisis, with remarkable results [3][4][5][6][7][8][9] . Clinical trial recruitment has been expedited and facilitated by national regulatory bodies and an international cooperative spirit 10-12 . The data analytics and AI disciplines have always fostered open

Our results demonstrate CSF-derived EVs contain RNA signatures reflective of the underlying molecular genetic status of GBMs in terms of wtEGFR expression and EGFRvIII status. The high specificity of the CSF-derived EV diagnostic test gives us an accurate determination of positive EGFRvIII tumor status and is essentially a less invasive "liquid biopsy" that might direct mutation-specific therapies for GBMs.

Introduction Analysis of extracellular vesicles (EVs) derived from plasma or cerebrospinal fluid (CSF) has emerged as a promising biomarker platform for therapeutic monitoring in glioblastoma patients. However, the contents of the various subpopulations of EVs in these clinical specimens remain poorly defined. Here we characterize the relative abundance of miRNA species in EVs derived from the serum and cerebrospinal fluid of glioblastoma patients. Methods EVs were isolated from glioblastoma cell lines as well as the plasma and CSF of glioblastoma patients. The microvesicle subpopulation was isolated by pelleting at 10,000×g for 30 min after cellular debris was cleared by a 2,000×g (20 min) spin. The exosome subpopulation was isolated by pelleting the microvesicle supernatant at 120,000×g (120 min). qRT-PCR was performed to examine the distribution of miR-21, miR-103, miR-24, and miR-125. Global miRNA profiling was performed in select glioblastoma CSF samples. Results In plasma and cell line derived EVs, the relative abundance of miRNAs in exosome and microvesicles were highly variable. In some specimens, the majority of the miRNA species were found in exosomes while in other, they were found in microvesicles. In contrast, CSF exosomes were enriched for miRNAs relative to CSF microvesicles. In CSF, there is an average of one molecule of miRNA per 150-25,000 EVs. Conclusion Most EVs derived from clinical biofluids are devoid of miRNA content. The relative distribution of miRNA species in plasma exosomes or microvesicles is unpredictable. In contrast, CSF exosomes are the major EV compartment that harbor miRNAs.

Central neurocytoma (CN) is a rare, benign brain tumor often located in the lateral ventricles. CN may cause obstructive hydrocephalus and manifest as signs of increased intracranial pressure. The goal of treatment for CN is a gross total resection (GTR), which often yields excellent prognosis with a very high rate of tumor control and survival. Adjuvant radiosurgery and radiotherapy may be considered to improve tumor control when GTR cannot be achieved. Chemotherapy is also not considered a primary treatment, but has been used as a salvage therapy. The radiological features of CN are indistinguishable from those of other brain tumors; therefore, many histological markers, such as synaptophysin, can be very useful for diagnosing CNs. Furthermore, the MIB-1 Labeling Index seems to be correlated with the prognosis of CN. We also discuss oncogenes associated with these elusive tumors. Further studies may improve our ability to accurately diagnose CNs and to design the optimal treatment regimens for patients with CNs.

Interferon-alpha and IFN-gamma can significantly upregulate the MHC Class I molecules that are expressed on the cell surface of human GBM cells as well as the potentially immunogenic peptides bound to the MHC. These results may help explain the molecular basis for increased immunogenicity with IFN treatment of human GBMs and might provide added insight into the design of future antitumor vaccines for human brain tumors.

Head computed tomography (CT) is instrumental for managing patients of all ages. However, its low dose radiation may pose a low but non-zero risk of tumor induction in pediatric patients. Here, we present a systematic literature review on the estimated incidence of brain tumor induction from head CT exams performed on children and adolescents. MEDLINE was searched using an electronic protocol and bibliographic searches to identify articles related to CT, cancer, and epidemiology or risk assessment. Sixteen studies that predicted or measured head CT-related neoplasm incidence or mortality were identified and reviewed. Epidemiological studies consistently cited increased tumor incidence in pediatric patients (ages 0–18) exposed to head CTs. Excess relative risk of new brain tumor averaged 1.29 (95% confidence interval, 0.66–1.93) for pediatric patients exposed to one or more head CTs. Tumor incidence increased with number of pediatric head CTs in a dose-dependent manner, with measurable excess incidence even after a single scan. Converging evidence from epidemiological studies supported a small excess risk of brain tumor incidence after even a single CT exam in pediatric patients. However, refined epidemiological methods are needed to control for confounding variables that may contribute to reverse causation, such as patients with pre-existing cancer or cancer susceptibility. CT remains an invaluable technology that should be utilized so long as there is clinical indication for the study and the radiation dose is as small as reasonably achievable.

Central neurocytoma (CN) typically presents as an intraventricular mass causing obstructive hydrocephalus. The first line of treatment is surgical resection with adjuvant conventional radiotherapy. Stereotactic radiosurgery (SRS) was proposed as an alternative therapy for CN because of its lower risk profile. The objective of this systematic analysis is to assess the efficacy of SRS for CN. A systematic analysis for CN treated with SRS was conducted in PubMed. Baseline patient characteristics and outcomes data were extracted. Heterogeneity and publication bias were also assessed. Univariate and multivariate linear regressions were used to test for correlations to the primary outcome: local control (LC). The estimated cumulative rate of LC was 92.2% (95% confidence interval: 86.5-95.7%, p<0.001). Mean follow-up time was 62.4 months (range 3-149 months). Heterogeneity and publication bias were insignificant. The univariate linear regression models for both mean tumor volume and mean dose were significantly correlated with improved LC (p<0.001). Our data suggests that SRS may be an effective and safe therapy for CN. However, the rarity of CN still limits the efficacy of a quantitative analysis. Future multi-institutional, randomized trials of CN patients should be considered to further elucidate this therapy.