Since the update of the 4th edition of the WHO Classification of Central Nervous System (CNS) Tumors published in 2016, particular molecular characteristics are part of the definition of a subset of these neoplasms. This combined ‘histo-molecular’ approach allows for a much more precise diagnosis of especially diffuse gliomas and embryonal CNS tumors. This review provides an update of the most important diagnostic and prognostic markers for state-of-the-art diagnosis of primary CNS tumors. Defining molecular markers for diffuse gliomas are IDH1/IDH2 mutations, 1p/19q codeletion and mutations in histone H3 genes. Medulloblastomas, the most frequent embryonal CNS tumors, are divided into four molecularly defined groups according to the WHO 2016 Classification: wingless/integrated (WNT) signaling pathway activated, sonic hedgehog (SHH) signaling pathway activated and tumor protein p53 gene ( TP53 ) - mutant, SHH-activated and TP53- wildtype, and non-WNT/non-SHH-activated. Molecular characteristics are also important for the diagnosis of several other CNS tumors, such as RELA fusion-positive subtype of ependymoma, atypical teratoid rhabdoid tumor (AT/RT), embryonal tumor with multilayered rosettes, and solitary fibrous tumor/hemangiopericytoma. Immunohistochemistry is a helpful alternative for further molecular characterization of several of these tumors. Additionally, genome-wide methylation profiling is a very promising new tool in CNS tumor diagnostics. Much progress has thus been made by translating the most relevant molecular knowledge into a more precise clinical diagnosis of CNS tumors. Hopefully, this will enable more specific and more effective therapeutic approaches for the patients suffering from these tumors.

Rosette-forming glioneuronal tumor (RGNT) is a rare brain neoplasm that primarily affects young adults. Although alterations affecting the mitogen-activated protein kinase (MAPK) and phosphoinositide 3-kinase (PI3K) signaling pathway have been associated with this lowgrade glioneuronal entity, comprehensive molecular investigations of RGNT in larger series have not been performed to date, and an integrated view of their genetic and epigenetic profiles is still lacking. Here we describe a genome-wide DNA methylation and targeted sequencing-based characterization of a molecularly distinct class of tumors (n = 30), initially identified through genome-wide DNA methylation screening amongst a cohort of > 30,000 tumors, of which most were diagnosed histologically as RGNT. FGFR1 hotspot mutations were observed in all tumors analyzed, with co-occurrence of PIK3CA mutations in about two thirds of the cases (63%). Additional loss-of-function mutations in the tumor suppressor gene NF1 were detected in a subset of cases (33%). Notably, in contrast to most other low-grade gliomas, these tumors often displayed co-occurrence of two or even all three of these mutations. Our data highlight that molecularly defined RGNTs are characterized by combined genetic alterations affecting both MAPK and PI3K signaling pathways. Thus, these two pathways appear to synergistically interact in the formation of RGNT, and offer potential therapeutic targets for this disease.

Aims Methylation profiling (MP) is increasingly incorporated in the diagnostic process of central nervous system (CNS) tumours at our centres in The Netherlands and Scandinavia. We aimed to identify the benefits and challenges of MP as a support tool for CNS tumour diagnostics. Methods About 502 CNS tumour samples were analysed using (850 k) MP. Profiles were matched with the DKFZ/Heidelberg CNS Tumour Classifier. For each case, the final pathological diagnosis was compared to the diagnosis before MP. Results In 54.4% (273/502) of all analysed cases, the suggested methylation class (calibrated score ≥0.9) corresponded with the initial pathological diagnosis. The diagnosis of 24.5% of these cases (67/273) was more refined after incorporation of the MP result. In 9.8% of cases (49/502), the MP result led to a new diagnosis, resulting in an altered WHO grade in 71.4% of these cases (35/49). In 1% of cases (5/502), the suggested class based on MP was initially disregarded/interpreted as misleading, but in retrospect, the MP result predicted the right diagnosis for three of these cases. In six cases, the suggested class was interpreted as ‘discrepant but noncontributory’. The remaining 33.7% of cases (169/502) had a calibrated score <0.9, including 7.8% (39/502) for which no class indication was given at all (calibrated score <0.3). Conclusions MP is a powerful tool to confirm and fine‐tune the pathological diagnosis of CNS tumours, and to avoid misdiagnoses. However, it is crucial to interpret the results in the context of clinical, radiological, histopathological and other molecular information.