The 2021 WHO Classification of Tumors of the Central Nervous System includes several tumor types and subtypes for which the diagnosis is at least partially reliant on utilization of whole genome methylation profiling. The current approach to array DNA methylation profiling utilizes a reference library of tumor DNA methylation data, and a machine learning-based tumor classifier. This approach was pioneered and popularized by the German Cancer Research Network (DKFZ) and University Hospital Heidelberg. This research group has kindly made their classifier for central nervous system tumors freely available as a research tool via a web-based portal. However, their classifier is not maintained in a clinical testing environment. Therefore, the Northwestern Medicine (NM) classifier was developed and validated. The NM classifier was validated using the same training and validation data sets as the DKFZ group. Using the DKFZ validation data set, the NM classifier's performance showed high concordance (92%) and comparable accuracy (specificity 94.0% versus 84.9% for DKFZ, sensitivity 88.6% versus 94.7% for DKFZ). Receiver-operator characteristic curves showed areas under the curve of 0.964 versus 0.966 for NM and DKFZ classifiers, respectively. In addition, in-house validation was performed and performance was compared using both classifiers. The NM classifier performed comparably well and is currently offered for clinical testing.

The blood–tumor barrier (BTB) limits the entry of effective chemotherapeutic agents into the brain for treatment of malignant tumors like glioblastoma. Poor drug entry across the BTB allows infiltrative glioma stem cells to evade therapy and develop treatment resistance. Regadenoson, an FDA-approved adenosine A2A receptor (A2AR) agonist, has been shown to increase drug delivery across the blood–brain barrier in non–tumor-bearing rodents without a defined mechanism of enhancing BTB permeability. Here, we characterize the time-dependent impact of regadenoson on brain endothelial cell interactions and paracellular transport, using mouse and rat brain endothelial cells and tumor models. In vitro, A2AR activation leads to disorganization of cytoskeletal actin filaments by 30 minutes, downregulation of junctional protein expression by 4 hours, and reestablishment of endothelial cell integrity by 8 hours. In rats bearing intracranial gliomas, regadenoson treatment results in increase of intratumoral temozolomide concentrations, yet no increased survival noted with combined temozolomide therapy. These findings demonstrate regadenoson's ability to induce brain endothelial structural changes among glioma to increase BTB permeability. The use of vasoactive mediators, like regadenoson, which transiently influences paracellular transport, should further be explored to evaluate their potential to enhance central nervous system treatment delivery to aggressive brain tumors. Implications: This study provides insight on the use of a vasoactive agent to increase exposure of the BTB to chemotherapy with intention to improve glioma treatment efficacy.

Adult-type diffusely infiltrating gliomas, of which glioblastoma is the most common and aggressive, almost always recur after treatment and are fatal. Improved understanding of therapy-driven tumor evolution and acquired therapy resistance in gliomas is essential for improving patient outcomes, yet the majority of the models currently used in preclinical research are of therapy-naïve tumors. Here, we describe the development of therapy-resistant IDH-wildtype glioblastoma patient-derived xenografts (PDX) through orthotopic engraftment of therapy naïve PDX in athymic nude mice, and repeated in vivo exposure to the therapeutic modalities most often used in treating glioblastoma patients: radiotherapy and temozolomide chemotherapy. Post-temozolomide PDX became enriched for C>T transition mutations, acquired inactivating mutations in DNA mismatch repair genes (especially MSH6), and developed hypermutation. Such post-temozolomide PDX were resistant to additional temozolomide (median survival decrease from 80 days in parental PDX to 42 days in a temozolomide-resistant derivative). However, temozolomide-resistant PDX were sensitive to lomustine (also known as CCNU), a nitrosourea which induces tumor cell apoptosis by a different mechanism than temozolomide. These PDX models mimic changes observed in recurrent GBM in patients, including critical features of therapy-driven tumor evolution. These models can therefore serve as valuable tools for improving our understanding and treatment of recurrent glioma.

Purpose: Evidence suggests that MAPK pathway activation, as measured by ERK1/2 phosphorylation (p-ERK), predicts overall survival (OS) in patients with recurrent glioblastoma receiving anti-PD-1 therapy. We aimed to validate these findings in independent cohorts. Experimental Design: In a 24-patient clinical trial on recurrent glioblastoma and high-grade gliomas, we examined the link between p-ERK levels and OS. Patients received intravenous nivolumab, followed by maximal safe resection and an intracerebral injection of either ipilimumab alone or combined with nivolumab. Biweekly adjuvant nivolumab was then administered up to five times (NCT03233152). Using REporting recommendations for tumor MARKER prognostic studies (REMARK) criteria, we conducted independent analyses for p-ERK quantification and statistical evaluations. Additional comparative analysis included prior cohorts, totaling 65 patients. Cox proportional hazards models and meta-analysis were employed to assess p-ERK as a predictive biomarker after immunotherapy. Results: Lower median p-ERK+ cell density was observed compared with prior studies, likely due to variable tissue processing across cohorts. Nonetheless, high p-ERK was associated with prolonged OS, particularly in isocitrate dehydrogenase wild-type glioblastomas (P = 0.036). Median OS for high and low p-ERK patients were 55.6 and 30 weeks, respectively. Multivariable analysis reinforced p-ERK's significance in survival prediction (P = 0.011). Upon p-ERK normalization across cohorts (n = 65), meta-analysis supported the survival benefit of elevated tumor p-ERK levels (P = 0.0424). Conclusions: This study strengthens the role of p-ERK as a predictive biomarker for OS in patients with glioblastoma on immune checkpoint blockade. Future research should focus on further validation in prospective trials and the standardization of preanalytical variables influencing p-ERK quantification.

Utilizing a Scoping Review strategy in the domain of immune biology to identify immune therapeutic targets, knowledge gaps for implementing immune therapeutic strategies for pediatric brain tumors was assessed. The analysis demonstrated limited efforts to date to characterize and understand the immunological aspects of tumor biology with an over-reliance on observations from the adult glioma population. Foundational knowledge regarding the frequency and ubiquity of immune therapeutic targets is an area of unmet need along with the development of immune-competent pediatric tumor models to test therapeutics and especially combinatorial treatment. Opportunities arise in the evolution of pediatric tumor classification from histological to molecular with targeted immune therapeutics.

The classification, grading, and risk stratification of central nervous system (CNS) tumors have rapidly evolved with the advent of integrative advanced molecular testing. Here, we review the advances and challenges associated with DNA methylation-based classification of central nervous system (CNS) tumors. Specifically, we will review the brief background information about the role of epigenetic signatures, including DNA methylation status of CpG islands, in identifying the cell of origin, bioinformatic methods, and products of DNA methylation profiling, namely t-distributed stochastic neighbor embedding (t-SNE) plot vs. uniform manifold approximation and projection (UMAP), CNS tumor classifications, methylguanine methyltransferase (MGMT), and chromosomal copy number variations. We will follow with the diagnostic utility, accuracy, and impact on clinical outcomes. We will conclude the chapter by highlighting the limitations of DNA methylation, bioethical issues, and the future directions for this diagnostic tool.