Pediatric glioma of the subclass MYCN are highly aggressive tumors with a median age at diagnosis of 8 years and a median survival of only 14 months. Molecularly, they frequently carry MYCN amplifications, TP53 mutations or both of these alterations. Due to their rarity, such tumors have only recently been identified as a distinct entity, and both biological as well as clinical details have not been fully addressed. In order to further investigate the biology and treatment options of these tumors, preclinical models are urgently needed. Therefore, we generated a genetically engineered model by breeding hGFAP-cre::Trp53Fl/Fl::lsl-MYCN mice, which carry a loss of Trp53 and show aberrant MYCN expression in neural precursors of the central nervous system. All such mice developed aggressive forebrain tumors early in lifetime that mimic their human counterparts regarding histology, DNA methylation, and gene expression. Single cell RNA sequencing revealed a high intratumoral heterogeneity with neuronal and oligodendroglial lineage signatures. To find new treatment options, we performed in vitro high-throughput drug screening on both, mouse and human tumor cells. Among 640 investigated anticancer compounds, Doxorubicin, Irinotecan, and Etoposide effectively suppressed the growth of tumor cells. As FDA-approved chemotherapeutics, these compounds are used for the treatment of other pediatric brain tumors. Repurposing them for the treatment of MYCN-driven high grade glioma could achieve a rapid transition to glioma treatment. We believe that our model will pave the way to improved treatment strategies for patients with these highly aggressive tumors.

Medulloblastomas (MBs) are malignant pediatric brain tumors that are molecularly and clinically very heterogenous. To unravel phenotypically relevant MB subtypes, we compiled a harmonized proteome dataset of 167 MBs and integrated findings with DNA methylation and N-glycome data. Six proteome MB subtypes emerged, that could be assigned to two main molecular programs: transcription/translation (pSHHt, pWNT and pGroup3-Myc), and synapses/immunological processes (pSHHs, pGroup3 and pGroup4). Multiomic analysis revealed different conservation levels of proteome features across MB subtypes at the DNA-methylation level. Aggressive pGroup3-Myc MBs and favorable pWNT MBs were most similar in cluster hierarchies concerning overall proteome patterns but showed different protein abundances of the vincristine resistance associated multiprotein complex TriC/CCT and of N-glycan turnover associated factors. The N-glycome reflected proteome subtypes and complex-bisecting N-glycans characterized pGroup3-Myc tumors. Our results shed light on new targetable alterations in MB and set a foundation for potential immunotherapies targeting glycan structures.

Investigating the proteome can add a significant layer of information to manifold existing methylation, mutation, and transcriptome data on brain tumors as proteins represent the pharmacologically addressable phenotype of a disease. Small cohorts limit the usability and validity of statistical methods, and variable technical setups and high numbers of missing values make data integration from public sources challenging. Using a newly developed framework being able to reduce batch effects without the need for data reduction or missing value imputation, we show –based on in-house and publicly available datasets- successful integration of proteomic data across different tissue types, quantification platforms, and technical setups. Exemplarily, data of a Sonic hedgehog (Shh) medulloblastoma mouse model were analyzed, showing efficient data integration independent of tissue preservation strategy or batch. We further integrated batches of publicly available data of human brain tumors, confirming proposed proteomic cancer subtypes correlating with clinical features. We show that, missing value tolerant reduction of technical variances may be helpful to identify biomarkers, proteomic signatures, and altered pathways characteristic for molecular brain cancer subtypes.

Multiple recent publications have described a highly aggressive subgroup of pediatric glioblastoma, which is clearly separable from other pediatric and adult glioblastoma based on its DNA methylation profile (GBM MYCN). These tumors almost exclusively occur in children and have a median overall survival of only 14 months. Many tumors in this group are driven by MYCN amplifications and harbor TP53 mutations. Otherwise, information about these tumors are still sparse and treatment is ineffective and causes severe side effects in many cases. In order to further investigate the biology and treatment options of these tumors, preclinical models are urgently needed. Here, we describe the generation of hGFAP-cre::TP53Fl/Fl::lsl-MYCN mice, which carry a loss of TP53 and show aberrant MYCN expression in neural precursors of the central nervous system. These animals develop large forebrain tumors within the first 80 days of life with 100 % penetrance. These tumors resemble human GBM MYCN tumors by histology, global gene expression, and DNA methylation. In order to understand the developmental biology and intratumoral heterogeneity, we employed single cell RNA sequencing (scRNAseq) to the murine tumors with first results indicating a resemblance of tumor cells to committed oligodendrocyte precursors. We further show that both murine and human tumor cells are sensitive to AURKA inhibition in vitro, suggesting a potential new therapeutic option for improved patient care. We believe that further characterization and utilization of the model will pave the way to improved treatment strategies for patients with these highly aggressive tumors.