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Murat Günel and colleagues identify recurrent mutations in POLR2A , which encodes the catalytic subunit of RNA polymerase II, in a subset of meningiomas. They find that POLR2A -mutant tumors can be distinguished on the basis of their super-enhancer and gene expression profiles, which show dysregulation of key meningeal identity genes. RNA polymerase II mediates the transcription of all protein-coding genes in eukaryotic cells, a process that is fundamental to life. Genomic mutations altering this enzyme have not previously been linked to any pathology in humans, which is a testament to its indispensable role in cell biology. On the basis of a combination of next-generation genomic analyses of 775 meningiomas, we report that recurrent somatic p.Gln403Lys or p.Leu438_His439del mutations in POLR2A , which encodes the catalytic subunit of RNA polymerase II (ref. 1 ), hijack this essential enzyme and drive neoplasia. POLR2A mutant tumors show dysregulation of key meningeal identity genes 2 , 3 , including WNT6 and ZIC1 / ZIC4 . In addition to mutations in POLR2A , NF2 , SMARCB1, TRAF7 , KLF4 , AKT1 , PIK3CA , and SMO 4 , 5 , 6 , 7 , 8 , we also report somatic mutations in AKT3 , PIK3R1 , PRKAR1A , and SUFU in meningiomas. Our results identify a role for essential transcriptional machinery in driving tumorigenesis and define mutually exclusive meningioma subgroups with distinct clinical and pathological features.

Murat Günel and colleagues use an integrated genomic approach to analyze the malignant progression of IDH1 -mutant gliomas. They observe nonlinear clonal expansion of the original tumors and identify oncogenic pathways driving progression, including activation of MYC and RTK-RAS-PI3K pathways and epigenetic silencing of developmental transcription factors. Gliomas represent approximately 30% of all central nervous system tumors and 80% of malignant brain tumors 1 . 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.

Meningiomas are mostly benign brain tumours, with a potential for becoming atypical or malignant. On the basis of comprehensive genomic, transcriptomic and epigenomic analyses, we compared benign meningiomas to atypical ones. Here, we show that the majority of primary ( de novo ) atypical meningiomas display loss of NF2 , which co-occurs either with genomic instability or recurrent SMARCB1 mutations. These tumours harbour increased H3K27me3 signal and a hypermethylated phenotype, mainly occupying the polycomb repressive complex 2 (PRC2) binding sites in human embryonic stem cells, thereby phenocopying a more primitive cellular state. Consistent with this observation, atypical meningiomas exhibit upregulation of EZH2, the catalytic subunit of the PRC2 complex, as well as the E2F2 and FOXM1 transcriptional networks. Importantly, these primary atypical meningiomas do not harbour TERT promoter mutations, which have been reported in atypical tumours that progressed from benign ones. Our results establish the genomic landscape of primary atypical meningiomas and potential therapeutic targets. Meningiomas are mostly benign brain tumours with the potential for becoming atypical or malignant. Here, the authors show that primary atypical meningiomas are epigenetically and genetically distinct from benign and progressed tumours, highlighting possible therapeutic targets such as PRC2.

ObjectivesTo establish a quantitative MR model that uses clinically relevant features of tumor location and tumor volume to differentiate lower grade glioma (LRGG, grades II and III) and glioblastoma (GBM, grade IV).MethodsWe extracted tumor location and tumor volume (enhancing tumor, non-enhancing tumor, peritumor edema) features from 229 The Cancer Genome Atlas (TCGA)-LGG and TCGA-GBM cases. Through two sampling strategies, i.e., institution-based sampling and repeat random sampling (10 times, 70% training set vs 30% validation set), LASSO (least absolute shrinkage and selection operator) regression and nine–machine learning method–based models were established and evaluated.ResultsPrincipal component analysis of 229 TCGA-LGG and TCGA-GBM cases suggested that the LRGG and GBM cases could be differentiated by extracted features. For nine machine learning methods, stack modeling and support vector machine achieved the highest performance (institution-based sampling validation set, AUC > 0.900, classifier accuracy > 0.790; repeat random sampling, average validation set AUC > 0.930, classifier accuracy > 0.850). For the LASSO method, regression model based on tumor frontal lobe percentage and enhancing and non-enhancing tumor volume achieved the highest performance (institution-based sampling validation set, AUC 0.909, classifier accuracy 0.830). The formula for the best performance of the LASSO model was established.ConclusionsComputer-generated, clinically meaningful MRI features of tumor location and component volumes resulted in models with high performance (validation set AUC > 0.900, classifier accuracy > 0.790) to differentiate lower grade glioma and glioblastoma.Key Points• Lower grade glioma and glioblastoma have significant different location and component volume distributions.• We built machine learning prediction models that could help accurately differentiate lower grade gliomas and GBM cases. We introduced a fast evaluation model for possible clinical differentiation and further analysis.

Introduction Meningiomas are generally considered “benign,” however, these tumors can demonstrate variability in behavior and a surprising aggressiveness with elevated rates of recurrence. The advancement of next-generation molecular technologies have led to the understanding of the genomic and epigenomic landscape of meningiomas and more recent correlations with clinical characteristics and behavior. Methods Based on a thorough review of recent peer-reviewed publications (PubMed) and edited texts, we provide a molecular overview of meningiomas with a focus on relevant clinical implications. Results The identification of specific somatic driver mutations has led to the classification of several major genomic subgroups, which account for more than 80% of sporadic meningiomas, and can be distinguished using noninvasive clinical variables to help guide management decisions. Other somatic genomic modifications, including non-coding alterations and copy number variations, have also been correlated with tumor characteristics. Furthermore, epigenomic modifications in meningiomas have recently been described, with DNA methylation being the most widely studied and potentially most clinically relevant. Based on these molecular insights, several clinical trials are currently underway in an effort to establish effective medical therapeutic options for meningioma. Conclusion As we enhance our multiomic understanding of meningiomas, our ability to care for patients with these tumors will continue to improve. Further biological insights will lead to additional progress in precision medicine for meningiomas.

Meningiomas are the most common primary tumors of the central nervous system and are typically treated with surgery or radiation, as targeted therapies remain limited. Despite extensive study, seventeen percent of meningiomas lack known genetic drivers. Our analysis of meningiomas without driver mutations or major chromosomal alterations identifies a subset with recurrent genomic rearrangements involving the FOS and FOSB genes. These tumors exhibit elevated FOS/FOSB protein levels and retain meningothelial lineage. Here we show that FOS / FOSB fusion-positive meningiomas represent a distinct molecular subgroup, defined by unique gene expression patterns, including activation of AP-1 target genes and signatures resembling preadipocyte-like and mast cell–associated profiles. Clinically, these tumors display low-grade behavior and DNA methylation profiles consistent with benign subtypes. Our findings identify a meningioma subgroup with distinct genetic, transcriptomic, and clinical features, expanding the molecular classification of meningiomas and opening new avenues for targeted treatment strategies. Approximately 17% of meningiomas remain genomically uncharacterized. Here, the authors analyze 105 meningiomas without known driver mutations or significant copy number alterations and identify a subgroup of meningiomas, defined by FOS/FOSB gene fusions with distinctive transcriptomic and histopathological features.

Background Pilomyxoid astrocytomas are an aggressive subtype of astrocytoma, not graded by WHO, frequently located in hypothalamic/chiasmatic region, affecting diencephalic structures, and characterized by shorter survival and high recurrence rates. Pilomyxoid astrocytoma management remains controversial, with pathologic tissue diagnosis and relief of mass effect being the main goals of surgery while avoiding treatment‐related morbidity, including vision loss, panhypopituitarism, and hypothalamic dysfunction. Chemotherapy (typically vincristine and carboplatin) in all pediatric patients and radiation therapy in pediatric patients over 5 years of age are used for treatment. Methods We report clinical presentation, surgical management, and whole exome sequencing results in a pediatric patient with the subtotally resected pilomyxoid astrocytoma. Results We identified two somatic activating missense mutations affecting FGFR1, including FGFR1 p.K656E and FGFR1 p.V561M. While the former is a known hotspot mutation that is both activating and transforming, the latter has been described as a gatekeeper mutation imparting resistance to FGFR inhibitors. Interestingly, both mutations were present with similar variant allele frequency within the tumor. Conclusion Similar variant allele frequencies of FGFR1 p.K656E and FGFR1 p.V561M mutations in our patient's tumor suggest that these mutations may have occurred at similar time points. Use of FGFR inhibitors in addition to STAT3 or PI3K/mTOR inhibition may prove a useful strategy in targeting our patient's pilomyxoid astrocytoma. Pilomyxoid astrocytomas are an aggressive subtype of astrocytoma, not graded by WHO, frequently located in hypothalamic/chiasmatic regions, affecting diencephalic structures, and characterized by shorter survival and high recurrence rates; their management remains controversial. We describe a pediatric patient with a pilomyxoid astrocytoma. We identified a known hotspot mutation FGFR1 p.K656E that is both activating and transforming, and a gatekeeper mutation FGFR1 p.V561M imparting resistance to FGFR inhibitors. Use of FGFR inhibitors in addition to STAT3 or PI3K/mTOR inhibition may prove a useful strategy in targeting our patient's pilomyxoid astrocytoma.

Gliomas with CDKN2A mutations are known to have worse prognosis but imaging features of these gliomas are unknown. Our goal is to identify CDKN2A specific qualitative imaging biomarkers in glioblastomas using a new informatics workflow that enables rapid analysis of qualitative imaging features with Visually AcceSAble Rembrandtr Images (VASARI) for large datasets in PACS. Sixty nine patients undergoing GBM resection with CDKN2A status determined by whole-exome sequencing were included. GBMs on magnetic resonance images were automatically 3D segmented using deep learning algorithms incorporated within PACS. VASARI features were assessed using FHIR forms integrated within PACS. GBMs without CDKN2A alterations were significantly larger (64 vs. 30%, p  = 0.007) compared to tumors with homozygous deletion (HOMDEL) and heterozygous loss (HETLOSS). Lesions larger than 8 cm were four times more likely to have no CDKN2A alteration (OR: 4.3; 95% CI 1.5–12.1; p  < 0.001). We developed a novel integrated PACS informatics platform for the assessment of GBM molecular subtypes and show that tumors with HOMDEL are more likely to have radiographic evidence of pial invasion and less likely to have deep white matter invasion or subependymal invasion. These imaging features may allow noninvasive identification of CDKN2A allele status.

Gliosarcoma is a variant of glioblastoma with equally poor prognosis and characterized by mixed glial and mesenchymal pathology. Metastasis is not uncommon but the involvement of the spinal cord is rare, and comprehensive genetic characterization of spinal gliosarcoma is lacking. We describe a patient initially diagnosed with a low-grade brain glioma via biopsy, followed by adjuvant radiation and temozolomide treatment. Nearly 2 years after diagnosis, she developed neurological deficits from an intradural, extramedullary tumor anterior to the spinal cord at T4, which was resected and diagnosed as gliosarcoma. Whole-exome sequencing (WES) of this tumor revealed a hypermutated phenotype, characterized by somatic mutations in key DNA mismatch repair (MMR) pathway genes, an abundance of C>T transitions within the identified somatic single nucleotide variations, and microsatellite stability, together consistent with temozolomide-mediated hypermutagenesis. This is the first report of a hypermutator phenotype in gliosarcoma, which may represent a novel genomic mechanism of progression from lower grade glioma.

The original version of this article, published on 05 February 2020, unfortunately contained a mistake.