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The history of human responses to epidemics carries various lessons for our current situation. Two of the more disheartening ones are that stigmatization follows closely on the heels of pathogens and that outbreaks too often claim the lives of health care providers. The article is accompanied by a slide show.

Pilocytic astrocytomas (PAs) were recognized as a discrete clinical entity over 70 years ago. They are relatively benign (WHO grade I) and have, as a group, a 10-year survival of over 90 %. Many require merely surgical removal and only very infrequently do they progress to more malignant gliomas. While most show classical morphology, they may present a spectrum of morphological patterns, and there are difficult cases that show similarities to other gliomas, some of which are malignant and require aggressive treatment. Until recently, almost nothing was known about the molecular mechanisms involved in their development. The use of high-throughput sequencing techniques interrogating the whole genome has shown that single abnormalities of the mitogen-activating protein kinase (MAPK) pathway are exclusively found in almost all cases, indicating that PA represents a one-pathway disease. The most common mechanism is a tandem duplication of a ≈2 Mb-fragment of #7q, giving rise to a fusion between two genes, resulting in a transforming fusion protein, consisting of the N-terminus of KIAA1549 and the kinase domain of BRAF. Additional infrequent fusion partners have been identified, along with other abnormalities of the MAP-K pathway, affecting tyrosine kinase growth factor receptors at the cell surface (e.g., FGFR1) as well as BRAF V600E, KRAS, and NF1 mutations among others. However, while the KIAA1549-BRAF fusion occurs in all areas, the incidence of the various other mutations identified differs in PAs that develop in different regions of the brain. Unfortunately, from a diagnostic standpoint, almost all mutations found have been reported in other brain tumor types, although some retain considerable utility. These molecular abnormalities will be reviewed, and the difficulties in their potential use in supporting a diagnosis of PA, when the histopathological findings are equivocal or in the choice of individualized therapy, will be discussed.

Diffuse gliomas are represented in the 2007 WHO classification as astrocytomas, oligoastrocytomas and oligodendrogliomas of grades II and III and glioblastomas WHO grade IV. Molecular data on these tumors have a major impact on prognosis and therapy of the patients. Consequently, the inclusion of molecular parameters in the WHO definition of brain tumors is being planned and has been forwarded as the “ISN-Haarlem” consensus. We, here, analyze markers of special interest including ATRX, IDH and 1p/19q codeletion in a series of 405 adult patients. Among the WHO 2007 classified tumors were 152 astrocytomas, 61 oligodendrogliomas, 63 oligoastrocytomas and 129 glioblastomas. Following the concepts of the “ISN-Haarlem”, we rediagnosed the series to obtain “integrated” diagnoses with 155 tumors being astrocytomas, 100 oligodendrogliomas and 150 glioblastomas. In a subset of 100 diffuse gliomas from the NOA-04 trial with long-term follow-up data available, the “integrated” diagnosis had a significantly greater prognostic power for overall and progression-free survival compared to WHO 2007. Based on the “integrated” diagnoses, loss of ATRX expression was close to being mutually exclusive to 1p/19q codeletion, with only 2 of 167 ATRX-negative tumors exhibiting 1p/19q codeletion. All but 4 of 141 patients with loss of ATRX expression and diffuse glioma carried either IDH1 or IDH2 mutations. Interestingly, the majority of glioblastoma patients with loss of ATRX expression but no IDH mutations exhibited an H3F3A mutation. Further, all patients with 1p/19 codeletion carried a mutation in IDH1 or IDH2 . We present an algorithm based on stepwise analysis with initial immunohistochemistry for ATRX and IDH1-R132H followed by 1p/19q analysis followed by IDH sequencing which reduces the number of molecular analyses and which has a far better association with patient outcome than WHO 2007.

Epileptogenic tumors affecting children and young adults are a morphologically diverse collection of neuroepithelial neoplasms that, as a group, exhibit varying levels of glial and/or neuronal differentiation. Recent advances in molecular profiling technology, including comprehensive DNA sequencing and methylation analysis, have enabled the application of more precise and biologically relevant classification schemes to these tumors. In this report, we describe a morphologically and molecularly distinct epileptogenic neoplasm, the polymorphous low-grade neuroepithelial tumor of the young (PLNTY), which likely accounts for a sizable portion of oligodendroglioma-like tumors affecting the pediatric population. Characteristic microscopic findings most notably include infiltrative growth, the invariable presence of oligodendroglioma-like cellular components, and intense immunolabeling for cluster of differentiation 34 (CD34). Moreover, integrative molecular profiling reveals a distinct DNA methylation signature for PLNTYs, along with frequent genetic abnormalities involving either B-Raf proto-oncogene ( BRAF ) or fibroblast growth factor receptors 2 and 3 ( FGFR2 , FGFR3 ). These findings suggest that PLNTY represents a distinct biological entity within the larger spectrum of pediatric, low-grade neuroepithelial tumors.

Machine learning is a branch of artificial intelligence (AI) involving computer programs that are able to improve their own performance through experience (training). The diverse applications of new ‘deep learning’ approaches with neural networks are now expanding into the field of biology. But these applications to biological data require more scrutiny and caution to increase the standards of publishing and allow the AI revolution in biology to take off.

In contrast to the relative morphological uniformity of histone H3 K27-mutant high-grade gliomas, H3 G34-mutant tumors present as a histopathologically heterogeneous group of neoplasms, with microscopic characteristics typical of either glioblastoma (GBM) or central nervous system primitive neuroectodermal tumors (CNS-PNET). In the current study, we performed an integrative clinical, histopathological and molecular analysis of 81 G34-mutant CNS tumors. Routinely prepared tumor tissues were investigated for genomic and epigenomic alterations. Despite their divergent histopathological appearance, CNS tumors with H3.3 G34 mutations displayed uniform epigenetic signatures, suggesting a single biological origin. Comparative cytogenetic analysis with other GBM subtypes disclosed a high frequency and high specificity of 3q and 4q loss across G34-mutant tumors. PDGFRA amplification was more common in cases with GBM than with PNET morphology (36 vs. 5 %, respectively), while CCND2 amplifications showed the opposite trend (5 vs. 27 %). Survival analysis revealed the presence of amplified oncogene(s) and MGMT methylation as independent prognostic markers for poor and favorable outcomes, respectively. No difference in outcome was found between morphological variants (GBM vs. PNET). Thus, different histological variants of G34-mutant CNS tumors likely comprise a single biological entity (high-grade glioma with H3 G34 mutation, HGG_G34), which should be outlined in future diagnostic and therapeutic classifications. Screening for H3.3 G34 mutation should therefore be recommended as a routine diagnostic marker for supratentorial CNS tumors across a broad histological spectrum.

Meningioma is the most common primary brain tumor and carries a substantial risk of local recurrence. Methylation profiles of meningioma and their clinical implications are not well understood. We hypothesized that aggressive meningiomas have unique DNA methylation patterns that could be used to better stratify patient management. Samples ( n  = 140) were profiled using the Illumina HumanMethylation450BeadChip. Unsupervised modeling on a training set ( n  = 89) identified 2 molecular methylation subgroups of meningioma (MM) with significantly different recurrence-free survival (RFS) times between the groups: a prognostically unfavorable subgroup (MM-UNFAV) and a prognostically favorable subgroup (MM-FAV). This finding was validated in the remaining 51 samples and led to a baseline meningioma methylation classifier (bMMC) defined by 283 CpG loci (283-bMMC). To further optimize a recurrence predictor, probes subsumed within the baseline classifier were subject to additional modeling using a similar training/validation approach, leading to a 64-CpG loci meningioma methylation predictor (64-MMP). After adjustment for relevant clinical variables [WHO grade, mitotic index, Simpson grade, sex, location, and copy number aberrations (CNAs)] multivariable analyses for RFS showed that the baseline methylation classifier was not significant ( p  = 0.0793). The methylation predictor, however, was significantly associated with tumor recurrence ( p  < 0.0001). CNAs were extracted from the 450k intensity profiles. Tumor samples in the MM-UNFAV subgroup showed an overall higher proportion of CNAs compared to the MM-FAV subgroup tumors and the CNAs were complex in nature. CNAs in the MM-UNFAV subgroup included recurrent losses of 1p, 6q, 14q and 18q, and gain of 1q, all of which were previously identified as indicators of poor outcome. In conclusion, our analyses demonstrate robust DNA methylation signatures in meningioma that correlate with CNAs and stratify patients by recurrence risk.

With the number of prognostic and predictive genetic markers in neuro-oncology steadily growing, the need for comprehensive molecular analysis of neuropathology samples has vastly increased. We therefore developed a customized enrichment/hybrid-capture-based next-generation sequencing (NGS) gene panel comprising the entire coding and selected intronic and promoter regions of 130 genes recurrently altered in brain tumors, allowing for the detection of single nucleotide variations, fusions, and copy number aberrations. Optimization of probe design, library generation and sequencing conditions on 150 samples resulted in a 5-workday routine workflow from the formalin-fixed paraffin-embedded sample to neuropathological report. This protocol was applied to 79 retrospective cases with established molecular aberrations for validation and 71 prospective cases for discovery of potential therapeutic targets. Concordance of NGS compared to established, single biomarker methods was 98.0 %, with discrepancies resulting from one case where a TERT promoter mutation was not called by NGS and three ATRX mutations not being detected by Sanger sequencing. Importantly, in samples with low tumor cell content, NGS was able to identify mutant alleles that were not detectable by traditional methods. Information derived from NGS data identified potential targets for experimental therapy in 37/47 (79 %) glioblastomas, 9/10 (90 %) pilocytic astrocytomas, and 5/14 (36 %) medulloblastomas in the prospective target discovery cohort. In conclusion, we present the settings for high-throughput, adaptive next-generation sequencing in routine neuropathology diagnostics. Such an approach will likely become highly valuable in the near future for treatment decision making, as more therapeutic targets emerge and genetic information enters the classification of brain tumors.

Recent sequencing efforts have described the mutational landscape of the pediatric brain tumor medulloblastoma. Although MLL2 is among the most frequent somatic single nucleotide variants (SNV), the clinical and biological significance of these mutations remains uncharacterized. Through targeted re-sequencing, we identified mutations of MLL2 in 8 % (14/175) of MBs, the majority of which were loss of function. Notably, we also report mutations affecting the MLL2-binding partner KDM6A , in 4 % (7/175) of tumors. While MLL2 mutations were independent of age, gender, histological subtype, M-stage or molecular subgroup, KDM6A mutations were most commonly identified in Group 4 MBs, and were mutually exclusive with MLL2 mutations. Immunohistochemical staining for H3K4me3 and H3K27me3, the chromatin effectors of MLL2 and KDM6A activity, respectively, demonstrated alterations of the histone code in 24 % (53/220) of MBs across all subgroups. Correlating these MLL2- and KDM6A-driven histone marks with prognosis, we identified populations of MB with improved (K4+/K27−) and dismal (K4−/K27−) outcomes, observed primarily within Group 3 and 4 MBs. Group 3 and 4 MBs demonstrate somatic copy number aberrations, and transcriptional profiles that converge on modifiers of H3K27-methylation ( EZH2 , KDM6A , KDM6B ), leading to silencing of PRC2-target genes. As PRC2-mediated aberrant methylation of H3K27 has recently been targeted for therapy in other diseases, it represents an actionable target for a substantial percentage of medulloblastoma patients with aggressive forms of the disease.

Key Points Glioblastoma is the most frequent and most aggressive malignant primary brain tumour and remains almost universally incurable in both children and adults. Comprehensive molecular profiling studies have greatly broadened our knowledge of the underlying genomic and epigenomic aberrations that are associated with glioblastoma initiation and progression. Genetic lesions result in disrupted epigenetic control mechanisms by altering histone modifications, DNA methylation and gene expression patterns in a large proportion of glioblastomas. Based on recurrent combinations of genomic and/or epigenomic features with distinct patient characteristics, glioblastomas across all ages are being divided into meaningful biological subgroups, which are likely to guide the design of future clinical trials. The complex interplay between the glioblastoma genome and epigenome opens the way for the development of novel innovative therapeutic strategies that are urgently needed to tackle this deadly brain tumour. The latest large-scale genomic and epigenomic profiling studies have yielded an unprecedented abundance of novel data and provided deeper insights into gliomagenesis across all age groups. These studies have highlighted key distinctions, but also some commonalities, which are discussed in this Review. We have extended our understanding of the molecular biology that underlies adult glioblastoma over many years. By contrast, high-grade gliomas in children and adolescents have remained a relatively under-investigated disease. The latest large-scale genomic and epigenomic profiling studies have yielded an unprecedented abundance of novel data and provided deeper insights into gliomagenesis across all age groups, which has highlighted key distinctions but also some commonalities. As we are on the verge of dissecting glioblastomas into meaningful biological subgroups, this Review summarizes the hallmark genetic alterations that are associated with distinct epigenetic features and patient characteristics in both paediatric and adult disease, and examines the complex interplay between the glioblastoma genome and epigenome.