Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging-with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology.

Two recurrent mutations, K27M and G34R/V, within histone variant H3.3 were recently identified in ∼50% of pHGGs. Both mutations define clinically and biologically distinct subgroups of pHGGs. Here, we provide further insight about the dominant-negative effect of K27M mutant H3.3, leading to a global reduction of the repressive histone mark H3K27me3. We demonstrate that this is caused by aberrant recruitment of the PRC2 complex to K27M mutant H3.3 and enzymatic inhibition of the H3K27me3-establishing methyltransferase EZH2. By performing chromatin immunoprecipitation followed by next-generation sequencing and whole-genome bisulfite sequencing in primary pHGGs, we show that reduced H3K27me3 levels and DNA hypomethylation act in concert to activate gene expression in K27M mutant pHGGs.

Based on extensive pre-clinical studies, the oncolytic parvovirus H-1 (H-1PV) is currently applied to patients with recurrent glioblastoma in a phase I/IIa clinical trial (ParvOryx01, NCT01301430). Cure rates of about 40% in pediatric high-risk medulloblastoma (MB) patients also indicate the need of new therapeutic approaches. In order to prepare a future application of oncolytic parvovirotherapy to MB, the present study preclinically evaluates the cytotoxic efficacy of H-1PV on MB cells in vitro and characterizes cellular target genes involved in this effect. Six MB cell lines were analyzed by whole genome oligonucleotide microarrays after treatment and the results were matched to known molecular and cytogenetic risk factors. In contrast to non-transformed infant astrocytes and neurons, in five out of six MB cell lines lytic H-1PV infection and efficient viral replication could be demonstrated. The cytotoxic effects induced by H-1PV were observed at LD50s below 0.05 p. f. u. per cell indicating high susceptibility. Gene expression patterns in the responsive MB cell lines allowed the identification of candidate target genes mediating the cytotoxic effects of H-1PV. H-1PV induced down-regulation of key regulators of early neurogenesis shown to confer poor prognosis in MB such as ZIC1, FOXG1B, MYC, and NFIA. In MB cell lines with genomic amplification of MYC, expression of MYC was the single gene most significantly repressed after H-1PV infection. H-1PV virotherapy may be a promising treatment approach for MB since it targets genes of functional relevance and induces cell death at very low titers of input virus.

Pilocytic astrocytoma (PA) is the most frequent pediatric brain tumor. Activation of the MAPK pathway is well established as the oncogenic driver of the disease. It is most frequently caused by KIAA1549:BRAF fusions, and leads to oncogene induced senescence (OIS). OIS is thought to be a major reason for growth arrest of PA cells in vitro and in vivo, preventing establishment of PA cultures. Hence, valid preclinical models are currently very limited, but preclinical testing of new compounds is urgently needed. We transduced the PA short-term culture DKFZ-BT66 derived from the PA of a 2-year old patient with a doxycycline-inducible system coding for Simian Vacuolating Virus 40 Large T Antigen (SV40-TAg). SV40-TAg inhibits TP53/CDKN1A and CDKN2A/RB1, two pathways critical for OIS induction and maintenance. DNA methylation array and KIAA1549:BRAF fusion analysis confirmed pilocytic astrocytoma identity of DKFZ-BT66 cells after establishment. Readouts were analyzed in proliferating as well as senescent states, including cell counts, viability, cell cycle analysis, expression of SV40-Tag, CDKN2A (p16), CDKN1A (p21), and TP53 (p53) protein, and gene-expression profiling. Selected MAPK inhibitors (MAPKi) including clinically available MEK inhibitors (MEKi) were tested in vitro. Expression of SV40-TAg enabled the cells to bypass OIS and to resume proliferation with a mean doubling time of 45h allowing for propagation and long-term culture. Withdrawal of doxycycline led to an immediate decrease of SV40-TAg expression, appearance of senescent morphology, upregulation of CDKI proteins and a subsequent G1 growth arrest in line with the re-induction of senescence. DKFZ-BT66 cells still underwent replicative senescence that was overcome by TERT expression. Testing of a set of MAPKi revealed differential responses in DKFZ-BT66. MEKi efficiently inhibited MAPK signaling at clinically achievable concentrations, while BRAF V600E- and RAF Type II inhibitors showed paradoxical activation. Taken together, we have established the first patient-derived long term expandable PA cell line expressing the KIAA1549:BRAF-fusion suitable for preclinical drug testing.

A hallmark of pediatric low-grade glioma (pLGG) is aberrant signaling of the mitogen activated protein kinase (MAPK) pathway. Hence, inhibition of MAPK signaling using small molecule inhibitors such as MEK inhibitors (MEKi) may be a promising strategy.

Molecular groups of medulloblastoma (MB) are well established. Novel risk stratification parameters include Group 3/4 (non-WNT/non-SHH) methylation subgroups I-VIII or whole-chromosomal aberration (WCA) phenotypes. This study investigates the integration of clinical and molecular parameters to improve risk stratification of non-WNT/non-SHH MB. Non-WNT/non-SHH MB from the HIT2000 study and the HIT-MED registries were selected based on availability of DNA-methylation profiling data. MYC or MYCN amplification and WCA of chromosomes 7, 8, and 11 were inferred from methylation array-based copy number profiles. In total, 403 non-WNT/non-SHH MB were identified, 346/403 (86%) had a methylation class family Group 3/4 methylation score (classifier v11b6) ≥ 0.9, and 294/346 (73%) were included in the risk stratification modeling based on Group 3 or 4 score (v11b6) ≥ 0.8 and subgroup I-VIII score (mb_g34) ≥ 0.8. Group 3 MB (5y-PFS, survival estimation ± standard deviation: 41.4 ± 4.6%; 5y-OS: 48.8 ± 5.0%) showed poorer survival compared to Group 4 (5y-PFS: 68.2 ± 3.7%; 5y-OS: 84.8 ± 2.8%). Subgroups II (5y-PFS: 27.6 ± 8.2%) and III (5y-PFS: 37.5 ± 7.9%) showed the poorest and subgroup VI (5y-PFS: 76.6 ± 7.9%), VII (5y-PFS: 75.9 ± 7.2%), and VIII (5y-PFS: 66.6 ± 5.8%) the best survival. Multivariate analysis revealed subgroup in combination with WCA phenotype to best predict risk of progression and death. The integration of clinical (age, M and R status) and molecular (MYC/N, subgroup, WCA phenotype) variables identified a low-risk stratum with a 5y-PFS of 94 ± 5.7 and a very high-risk stratum with a 5y-PFS of 29 ± 6.1%. Validation in an international MB cohort confirmed the combined stratification scheme with 82.1 ± 6.0% 5y-PFS in the low and 47.5 ± 4.1% in very high-risk groups, and outperformed the clinical model. These newly identified clinico-molecular low-risk and very high-risk strata, accounting for 6%, and 21% of non-WNT/non-SHH MB patients, respectively, may improve future treatment stratification.

Sarcomas are malignant soft tissue and bone tumours affecting adults, adolescents and children. They represent a morphologically heterogeneous class of tumours and some entities lack defining histopathological features. Therefore, the diagnosis of sarcomas is burdened with a high inter-observer variability and misclassification rate. Here, we demonstrate classification of soft tissue and bone tumours using a machine learning classifier algorithm based on array-generated DNA methylation data. This sarcoma classifier is trained using a dataset of 1077 methylation profiles from comprehensively pre-characterized cases comprising 62 tumour methylation classes constituting a broad range of soft tissue and bone sarcoma subtypes across the entire age spectrum. The performance is validated in a cohort of 428 sarcomatous tumours, of which 322 cases were classified by the sarcoma classifier. Our results demonstrate the potential of the DNA methylation-based sarcoma classification for research and future diagnostic applications.

Long-term complications such as radiation-induced second malignancies occur in a subset of patients following radiation-therapy, particularly relevant in pediatric patients due to the long follow-up period in case of survival. Radiation-induced gliomas (RIGs) have been reported in patients after treatment with cranial irradiation for various primary malignancies such as acute lymphoblastic leukemia (ALL) and medulloblastoma (MB). We perform comprehensive (epi-) genetic and expression profiling of RIGs arising after cranial irradiation for MB (n = 23) and ALL (n = 9). Our study reveals a unifying molecular signature for the majority of RIGs, with recurrent PDGFRA amplification and loss of CDKN2A/B and an absence of somatic hotspot mutations in genes encoding histone 3 variants or IDH1/2, uncovering diagnostic markers and potentially actionable targets.

Ependymomas encompass a heterogeneous group of central nervous system (CNS) neoplasms that occur along the entire neuroaxis. In recent years, extensive (epi-)genomic profiling efforts have identified several molecular groups of ependymoma that are characterized by distinct molecular alterations and/or patterns. Based on unsupervised visualization of a large cohort of genome-wide DNA methylation data, we identified a highly distinct group of pediatric-type tumors (n = 40) forming a cluster separate from all established CNS tumor types, of which a high proportion were histopathologically diagnosed as ependymoma. RNA sequencing revealed recurrent fusions involving the pleomorphic adenoma gene-like 1 (PLAGL1) gene in 19 of 20 of the samples analyzed, with the most common fusion being EWSR1:PLAGL1 (n = 13). Five tumors showed a PLAGL1:FOXO1 fusion and one a PLAGL1:EP300 fusion. High transcript levels of PLAGL1 were noted in these tumors, with concurrent overexpression of the imprinted genes H19 and IGF2, which are regulated by PLAGL1. Histopathological review of cases with sufficient material (n = 16) demonstrated a broad morphological spectrum of tumors with predominant ependymoma-like features. Immunohistochemically, tumors were GFAP positive and OLIG2- and SOX10 negative. In 3/16 of the cases, a dot-like positivity for EMA was detected. All tumors in our series were located in the supratentorial compartment. Median age of the patients at the time of diagnosis was 6.2 years. Median progression-free survival was 35 months (for 11 patients with data available). In summary, our findings suggest the existence of a novel group of supratentorial neuroepithelial tumors that are characterized by recurrent PLAGL1 fusions and enriched for pediatric patients.

Large-scale molecular profiling studies in recent years have shown that central nervous system (CNS) tumors display a much greater heterogeneity in terms of molecularly distinct entities, cellular origins and genetic drivers than anticipated from histological assessment. DNA methylation profiling has emerged as a useful tool for robust tumor classification, providing new insights into these heterogeneous molecular classes. This is particularly true for rare CNS tumors with a broad morphological spectrum, which are not possible to assign as separate entities based on histological similarity alone. Here, we describe a molecularly distinct subset of predominantly pediatric CNS neoplasms (n = 60) that harbor PATZ1 fusions. The original histological diagnoses of these tumors covered a wide spectrum of tumor types and malignancy grades. While the single most common diagnosis was glioblastoma (GBM), clinical data of the PATZ1-fused tumors showed a better prognosis than typical GBM, despite frequent relapses. RNA sequencing revealed recurrent MN1:PATZ1 or EWSR1:PATZ1 fusions related to (often extensive) copy number variations on chromosome 22, where PATZ1 and the two fusion partners are located. These fusions have individually been reported in a number of glial/glioneuronal tumors, as well as extracranial sarcomas. We show here that they are more common than previously acknowledged, and together define a biologically distinct CNS tumor type with high expression of neural development markers such as PAX2, GATA2 and IGF2. Drug screening performed on the MN1:PATZ1 fusion-bearing KS-1 brain tumor cell line revealed preliminary candidates for further study. In summary, PATZ1 fusions define a molecular class of histologically polyphenotypic neuroepithelial tumors, which show an intermediate prognosis under current treatment regimens.

MYC-driven Group 3 medulloblastoma (MB) (subtype II) is a highly aggressive childhood brain tumor. Sensitivity of MYC-driven MB to class I histone deacetylase inhibitors (HDACi) has been previously demonstrated in vitro and in vivo. In this study we characterize the transcriptional effects of class I HDACi in MYC-driven MB and explore beneficial drug combinations.

The large diversity of central nervous system (CNS) tumor types in children and adolescents results in disparate patient outcomes and renders accurate diagnosis challenging. In this study, we prospectively integrated DNA methylation profiling and targeted gene panel sequencing with blinded neuropathological reference diagnostics for a population-based cohort of more than 1,200 newly diagnosed pediatric patients with CNS tumors, to assess their utility in routine neuropathology. We show that the multi-omic integration increased diagnostic accuracy in a substantial proportion of patients through annotation to a refining DNA methylation class (50%), detection of diagnostic or therapeutically relevant genetic alterations (47%) or identification of cancer predisposition syndromes (10%). Discrepant results by neuropathological WHO-based and DNA methylation-based classification (30%) were enriched in histological high-grade gliomas, implicating relevance for current clinical patient management in 5% of all patients. Follow-up (median 2.5 years) suggests improved survival for patients with histological high-grade gliomas displaying lower-grade molecular profiles. These results provide preliminary evidence of the utility of integrating multi-omics in neuropathology for pediatric neuro-oncology.

Copy-number variations (CNVs) are common genetic alterations in cancer and their detection may impact tumor classification and therapeutic decisions. However, detection of clinically relevant large and focal CNVs remains challenging when sample material or resources are limited. This has motivated us to create a software tool to infer CNVs from DNA methylation arrays which are often generated as part of clinical routines and in research settings.

Patients with MYC-amplified Group 3 medulloblastoma (MB) (subtype II) show poor progression-free survival rates. Class I histone deacetylase inhibitors (HDACi) are highly effective for the treatment of MYC-amplified MB in vitro and in vivo. Drug combination regimens including class I HDACi may represent an urgently needed novel treatment approach for this high risk disease.

Recurrent mutations affecting the histone H3.3 residues Lys27 or indirectly Lys36 are frequent drivers of pediatric high-grade gliomas (over 30% of HGGs). To identify additional driver mutations in HGGs, we investigated a cohort of 60 pediatric HGGs using whole-exome sequencing (WES) and compared them to 543 exomes from non-cancer control samples. We identified mutations in SETD2, a H3K36 trimethyltransferase, in 15% of pediatric HGGs, a result that was genome-wide significant (FDR = 0.029). Most SETD2 alterations were truncating mutations. Sequencing the gene in this cohort and another validation cohort (123 gliomas from all ages and grades) showed SETD2 mutations to be specific to high-grade tumors affecting 15% of pediatric HGGs (11/73) and 8% of adult HGGs (5/65) while no SETD2 mutations were identified in low-grade diffuse gliomas (0/45). Furthermore, SETD2 mutations were mutually exclusive with H3F3A mutations in HGGs (P = 0.0492) while they partly overlapped with IDH1 mutations (4/14), and SETD2-mutant tumors were found exclusively in the cerebral hemispheres (P = 0.0055). SETD2 is the only H3K36 trimethyltransferase in humans, and SETD2-mutant tumors showed a substantial decrease in H3K36me3 levels (P < 0.001), indicating that the mutations are loss-of-function. These data suggest that loss-of-function SETD2 mutations occur in older children and young adults and are specific to HGG of the cerebral cortex, similar to the H3.3 G34R/V and IDH mutations. Taken together, our results suggest that mutations disrupting the histone code at H3K36, including H3.3 G34R/V, IDH1 and/or SETD2 mutations, are central to the genesis of hemispheric HGGs in older children and young adults.

Pilocytic astrocytoma is the most common childhood brain tumor, characterized by constitutive MAPK activation. MAPK signaling induces oncogene-induced senescence (OIS), which may cause unpredictable growth behavior of pilocytic astrocytomas. The senescence-associated secretory phenotype (SASP) has been shown to regulate OIS, but its role in pilocytic astrocytoma remains unknown.Experimental Design: The patient-derived pilocytic astrocytoma cell culture model, DKFZ-BT66, was used to demonstrate presence of the SASP and analyze its impact on OIS in pilocytic astrocytoma. The model allows for doxycycline-inducible switching between proliferation and OIS. Both states were studied using gene expression profiling (GEP), Western blot, ELISA, and cell viability testing. Primary pilocytic astrocytoma tumors were analyzed by GEP and multiplex assay.

Pleomorphic xanthoastrocytoma (PXA) in its classic manifestation exhibits distinct morphological features and is assigned to CNS WHO grade 2 or grade 3. Distinction from glioblastoma variants and lower grade glial and glioneuronal tumors is a common diagnostic challenge. We compared a morphologically defined set of PXA (histPXA) with an independent set, defined by DNA methylation analysis (mcPXA). HistPXA encompassed 144 tumors all subjected to DNA methylation array analysis. Sixty-two histPXA matched to the methylation class mcPXA. These were combined with the cases that showed the mcPXA signature but had received a histopathological diagnosis other than PXA. This cohort constituted a set of 220 mcPXA. Molecular and clinical parameters were analyzed in these groups. Morphological parameters were analyzed in a subset of tumors with FFPE tissue available. HistPXA revealed considerable heterogeneity in regard to methylation classes, with methylation classes glioblastoma and ganglioglioma being the most frequent mismatches. Similarly, the mcPXA cohort contained tumors of diverse histological diagnoses, with glioblastoma constituting the most frequent mismatch. Subsequent analyses demonstrated the presence of canonical pTERT mutations to be associated with unfavorable prognosis among mcPXA. Based on these data, we consider the tumor type PXA to be histologically more varied than previously assumed. Histological approach to diagnosis will predominantly identify cases with the established archetypical morphology. DNA methylation analysis includes additional tumors in the tumor class PXA that share similar DNA methylation profile but lack the typical morphology of a PXA. DNA methylation analysis also assist in separating other tumor types with morphologic overlap to PXA. Our data suggest the presence of canonical pTERT mutations as a robust indicator for poor prognosis in methylation class PXA.

Glioneuronal tumors are a heterogenous group of CNS neoplasms that can be challenging to accurately diagnose. Molecular methods are highly useful in classifying these tumors-distinguishing precise classes from their histological mimics and identifying previously unrecognized types of tumors. Using an unsupervised visualization approach of DNA methylation data, we identified a novel group of tumors (n = 20) that formed a cluster separate from all established CNS tumor types. Molecular analyses revealed ATRX alterations (in 16/16 cases by DNA sequencing and/or immunohistochemistry) as well as potentially targetable gene fusions involving receptor tyrosine-kinases (RTK; mostly NTRK1-3) in all of these tumors (16/16; 100%). In addition, copy number profiling showed homozygous deletions of CDKN2A/B in 55% of cases. Histological and immunohistochemical investigations revealed glioneuronal tumors with isomorphic, round and often condensed nuclei, perinuclear clearing, high mitotic activity and microvascular proliferation. Tumors were mainly located supratentorially (84%) and occurred in patients with a median age of 19 years. Survival data were limited (n = 18) but point towards a more aggressive biology as compared to other glioneuronal tumors (median progression-free survival 12.5 months). Given their molecular characteristics in addition to anaplastic features, we suggest the term glioneuronal tumor with ATRX alteration, kinase fusion and anaplastic features (GTAKA) to describe these tumors. In summary, our findings highlight a novel type of glioneuronal tumor driven by different RTK fusions accompanied by recurrent alterations in ATRX and homozygous deletions of CDKN2A/B. Targeted approaches such as NTRK inhibition might represent a therapeutic option for patients suffering from these tumors.

Pediatric low-grade gliomas (pLGG) show heterogeneous responses to MAPK inhibitors (MAPKi) in clinical trials. Thus, more complex stratification biomarkers are needed to identify patients likely to benefit from MAPKi therapy. Here, we identify MAPK-related genes enriched in MAPKi-sensitive cell lines using the GDSC dataset and apply them to calculate class-specific MAPKi sensitivity scores (MSSs) via single-sample gene set enrichment analysis. The MSSs discriminate MAPKi-sensitive and non-sensitive cells in the GDSC dataset and significantly correlate with response to MAPKi in an independent PDX dataset. The MSSs discern gliomas with varying MAPK alterations and are higher in pLGG compared to other pediatric CNS tumors. Heterogenous MSSs within pLGGs with the same MAPK alteration identify proportions of potentially sensitive patients. The MEKi MSS predicts treatment response in a small set of pLGG patients treated with trametinib. High MSSs correlate with a higher immune cell infiltration, with high expression in the microglia compartment in single-cell RNA sequencing data, while low MSSs correlate with low immune infiltration and increased neuronal score. The MSSs represent predictive tools for the stratification of pLGG patients and should be prospectively validated in clinical trials. Our data supports a role for microglia in the response to MAPKi.

Biallelic inactivation of SMARCB1, encoding a member of the SWI/SNF chromatin remodeling complex, is the hallmark genetic aberration of atypical teratoid rhabdoid tumors (ATRT). Here, we report how loss of SMARCB1 affects the epigenome in these tumors. Using chromatin immunoprecipitation sequencing (ChIP-seq) on primary tumors for a series of active and repressive histone marks, we identified the chromatin states differentially represented in ATRTs compared with other brain tumors and non-neoplastic brain. Re-expression of SMARCB1 in ATRT cell lines enabled confirmation of our genome-wide findings for the chromatin states. Additional generation of ChIP-seq data for SWI/SNF and Polycomb group proteins and the transcriptional repressor protein REST determined differential dependencies of SWI/SNF and Polycomb complexes in regulation of diverse gene sets in ATRTs.