We report genomic analysis of 300 meningiomas, the most common primary brain tumors, leading to the discovery of mutations in TRAF7, a proapoptotic E3 ubiquitin ligase, in nearly one-fourth of all meningiomas. Mutations in TRAF7commonly occurred with a recurrent mutation (K409Q) in KLF4, a transcription factor known for its role in inducing pluripotency, or with AKT1E17K, a mutation known to activate the PI3K pathway. SMO mutations, which activate Hedgehog signaling, were identified in ~5% of non-NF2 mutant meningiomas. These non-NF2 meningiomas were clinically distinctive—nearly always benign, with chromosomal stability, and originating from the medial skull base. In contrast, meningiomas with mutant NF2 and/or chromosome 22 loss were more likely to be atypical, showing genomic instability, and localizing to the cerebral and cerebellar hemispheres. Collectively, these findings identify distinct meningioma subtypes, suggesting avenues for targeted therapeutics.

Gliomas represent approximately 30% of all central nervous system tumors and 80% of malignant brain tumors1. To understand the molecular mechanisms underlying the malignant progression of low-grade gliomas with mutations in IDH1 (encoding isocitrate dehydrogenase 1), we studied paired tumor samples from 41 patients, comparing higher-grade, progressed samples to their lower-grade counterparts. Integrated genomic analyses, including whole-exome sequencing and copy number, gene expression and DNA methylation profiling, demonstrated nonlinear clonal expansion of the original tumors and identified oncogenic pathways driving progression. These include activation of the MYC and RTK-RAS-PI3K pathways and upregulation of the FOXM1- and E2F2-mediated cell cycle transitions, as well as epigenetic silencing of developmental transcription factor genes bound by Polycomb repressive complex 2 in human embryonic stem cells. Our results not only provide mechanistic insight into the genetic and epigenetic mechanisms driving glioma progression but also identify inhibition of the bromodomain and extraterminal (BET) family as a potential therapeutic approach.

Twenty years of oncolytic virus (OV) development have created a field that is driven by the potential promise of lasting impact on our cancer treatment repertoire. With the field constantly expanding – over 20 viruses have been recognized as potential OVs – new virus candidates continue to emerge even as established viruses reach clinical trials. They all share the defining commonalities of selective replication in tumors, subsequent tumor cell lysis, and dispersion within the tumor. Members from diverse virus classes with distinctly different biologies and host species have been identified. Of these viruses, 15 have been tested on human glioblastoma multiforme (GBM). So far, 20 clinical trials have been conducted or initiated using attenuated strains of 7 different oncolytic viruses against GBM. In this review, we present an overview of viruses that have been developed or considered for GBM treatment. We outline the principles of tumor targeting and selective viral replication, which include mechanisms of tumor-selective binding, and molecular elements usurping cellular biosynthetic machinery in transformed cells. Results from clinical trials have clearly established the proof of concept and have confirmed the general safety of OV application in the brain. The moderate clinical efficacy has not yet matched the promising preclinical lab results; next-generation OVs that are either “armed” with therapeutic genes or that are embedded in a multimodality treatment regimen should enhance the clinical results.

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OBJECTIVERecent large-cohort sequencing studies have investigated the genomic landscape of meningiomas, identifying somatic coding alterations in NF2, SMARCB1, SMARCE1, TRAF7, KLF4, POLR2A, BAP1, and members of the PI3K and Hedgehog signaling pathways. Initial associations between clinical features and genomic subgroups have been described, including location, grade, and histology. However, further investigation using an expanded collection of samples is needed to confirm previous findings, as well as elucidate relationships not evident in smaller discovery cohorts.METHODSTargeted sequencing of established meningioma driver genes was performed on a multiinstitution cohort of 3016 meningiomas for classification into mutually exclusive subgroups. Relevant clinical information was collected for all available cases and correlated with genomic subgroup. Nominal variables were analyzed using Fisher’s exact tests, while ordinal and continuous variables were assessed using Kruskal-Wallis and 1-way ANOVA tests, respectively. Machine-learning approaches were used to predict genomic subgroup based on noninvasive clinical features.RESULTSGenomic subgroups were strongly associated with tumor locations, including correlation of HH tumors with midline location, and non-NF2 tumors in anterior skull base regions. NF2 meningiomas were significantly enriched in male patients, while KLF4 and POLR2A mutations were associated with female sex. Among histologies, the results confirmed previously identified relationships, and observed enrichment of microcystic features among “mutation unknown” samples. Additionally, KLF4-mutant meningiomas were associated with larger peritumoral brain edema, while SMARCB1 cases exhibited elevated Ki-67 index. Machine-learning methods revealed that observable, noninvasive patient features were largely predictive of each tumor’s underlying driver mutation.CONCLUSIONSUsing a rigorous and comprehensive approach, this study expands previously described correlations between genomic drivers and clinical features, enhancing our understanding of meningioma pathogenesis, and laying further groundwork for the use of targeted therapies. Importantly, the authors found that noninvasive patient variables exhibited a moderate predictive value of underlying genomic subgroup, which could improve with additional training data. With continued development, this framework may enable selection of appropriate precision medications without the need for invasive sampling procedures.

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We identified a genomically, histologically, and clinically distinct subgroup of HGGs that harbored somatic POLE mutations and carried an improved prognosis. Identification of distinctive molecular and pathological HGG phenotypes has implications not only for improved classification but also for potential targeted treatments.