New Brain Tumor Entities Emerge from Molecular Classification of CNS-PNETs.

Primitive neuroectodermal tumors of the central nervous system (CNS-PNETs) are highly aggressive, poorly differentiated embryonal tumors occurring predominantly in young children but also affecting adolescents and adults. Herein, we demonstrate that a significant proportion of institutionally diagnosed CNS-PNETs display molecular profiles indistinguishable from those of various other well-defined CNS tumor entities, facilitating diagnosis and appropriate therapy for patients with these tumors. From the remaining fraction of CNS-PNETs, we identify four new CNS tumor entities, each associated with a recurrent genetic alteration and distinct histopathological and clinical features. These new molecular entities, designated "CNS neuroblastoma with FOXR2 activation (CNS NB-FOXR2)," "CNS Ewing sarcoma family tumor with CIC alteration (CNS EFT-CIC)," "CNS high-grade neuroepithelial tumor with MN1 alteration (CNS HGNET-MN1)," and "CNS high-grade neuroepithelial tumor with BCOR alteration (CNS HGNET-BCOR)," will enable meaningful clinical trials and the development of therapeutic strategies for patients affected by poorly differentiated CNS tumors.

Conumee 2.0: enhanced copy-number variation analysis from DNA methylation arrays for humans and mice.

MOTIVATION: 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. RESULTS: We present our R package, conumee 2.0, that combines tangent normalization, an adjustable genomic binning heuristic, and weighted circular binary segmentation to utilize DNA methylation arrays for CNV analysis and mitigate technical biases and batch effects. Segmentation results were validated in a lung squamous cell carcinoma dataset from TCGA (n = 367 samples) by comparison to segmentations derived from genotyping arrays (Pearson's correlation coefficient of 0.91). We further introduce a segmented block bootstrapping approach to detect focal alternations that achieved 60.9% sensitivity and 98.6% specificity for deletions affecting CDKN2A/B (60.0% and 96.9% for RB1, respectively) in a low-grade glioma cohort from TCGA (n = 239 samples). Finally, our tool provides functionality to detect and summarize CNVs across large sample cohorts. AVAILABILITY AND IMPLEMENTATION: Conumee 2.0 is available under open-source license at: https://github.com/hovestadtlab/conumee2.

The molecular landscape of ETMR at diagnosis and relapse.

Embryonal tumours with multilayered rosettes (ETMRs) are aggressive paediatric embryonal brain tumours with a universally poor prognosis1. Here we collected 193 primary ETMRs and 23 matched relapse samples to investigate the genomic landscape of this distinct tumour type. We found that patients with tumours in which the proposed driver C19MC2-4 was not amplified frequently had germline mutations in DICER1 or other microRNA-related aberrations such as somatic amplification of miR-17-92 (also known as MIR17HG). Whole-genome sequencing revealed that tumours had an overall low recurrence of single-nucleotide variants (SNVs), but showed prevalent genomic instability caused by widespread occurrence of R-loop structures. We show that R-loop-associated chromosomal instability can be induced by the loss of DICER1 function. Comparison of primary tumours and matched relapse samples showed a strong conservation of structural variants, but low conservation of SNVs. Moreover, many newly acquired SNVs are associated with a mutational signature related to cisplatin treatment. Finally, we show that targeting R-loops with topoisomerase and PARP inhibitors might be an effective treatment strategy for this deadly disease.

DNA methylation-based classification of central nervous system tumours.

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.

Molecular characterisation defines clinically-actionable heterogeneity within Group 4 medulloblastoma and improves disease risk-stratification.

Group 4 tumours (MBGrp4) represent the majority of non-WNT/non-SHH medulloblastomas. Their clinical course is poorly predicted by current risk-factors. MBGrp4 molecular substructures have been identified (e.g. subgroups/cytogenetics/mutations), however their inter-relationships and potential to improve clinical sub-classification and risk-stratification remain undefined. We comprehensively characterised the paediatric MBGrp4 molecular landscape and determined its utility to improve clinical management. A clinically-annotated discovery cohort (n = 362 MBGrp4) was assembled from UK-CCLG institutions and SIOP-UKCCSG-PNET3, HIT-SIOP-PNET4 and PNET HR + 5 clinical trials. Molecular profiling was undertaken, integrating driver mutations, second-generation non-WNT/non-SHH subgroups (1-8) and whole-chromosome aberrations (WCAs). Survival models were derived for patients ≥ 3 years of age who received contemporary multi-modal therapies (n = 323). We first independently derived and validated a favourable-risk WCA group (WCA-FR) characterised by ≥ 2 features from chromosome 7 gain, 8 loss, and 11 loss. Remaining patients were high-risk (WCA-HR). Subgroups 6 and 7 were enriched for WCA-FR (p < 0·0001) and aneuploidy. Subgroup 8 was defined by predominantly balanced genomes with isolated isochromosome 17q (p < 0·0001). While no mutations were associated with outcome and overall mutational burden was low, WCA-HR harboured recurrent chromatin remodelling mutations (p = 0·007). Integration of methylation and WCA groups improved risk-stratification models and outperformed established prognostication schemes. Our MBGrp4 risk-stratification scheme defines: favourable-risk (non-metastatic disease and (i) subgroup 7 or (ii) WCA-FR (21% of patients, 5-year PFS 97%)), very-high-risk (metastatic disease with WCA-HR (36%, 5-year PFS 49%)) and high-risk (remaining patients; 43%, 5-year PFS 67%). These findings validated in an independent MBGrp4 cohort (n = 668). Importantly, our findings demonstrate that previously established disease-wide risk-features (i.e. LCA histology and MYC(N) amplification) have little prognostic relevance in MBGrp4 disease. Novel validated survival models, integrating clinical features, methylation and WCA groups, improve outcome prediction and re-define risk-status for ~ 80% of MBGrp4. Our MBGrp4 favourable-risk group has MBWNT-like excellent outcomes, thereby doubling the proportion of medulloblastoma patients who could benefit from therapy de-escalation approaches, aimed at reducing treatment induced late-effects while sustaining survival outcomes. Novel approaches are urgently required for the very-high-risk patients.

Identification of low and very high-risk patients with non-WNT/non-SHH medulloblastoma by improved clinico-molecular stratification of the HIT2000 and I-HIT-MED cohorts.

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.

Amplification of the PLAG-family genes-PLAGL1 and PLAGL2-is a key feature of the novel tumor type CNS embryonal tumor with PLAGL amplification.

Pediatric central nervous system (CNS) tumors represent the most common cause of cancer-related death in children aged 0-14 years. They differ from their adult counterparts, showing extensive clinical and molecular heterogeneity as well as a challenging histopathological spectrum that often impairs accurate diagnosis. Here, we use DNA methylation-based CNS tumor classification in combination with copy number, RNA-seq, and ChIP-seq analysis to characterize a newly identified CNS tumor type. In addition, we report histology, patient characteristics, and survival data in this tumor type. We describe a biologically distinct pediatric CNS tumor type (n = 31 cases) that is characterized by focal high-level amplification and resultant overexpression of either PLAGL1 or PLAGL2, and an absence of recurrent genetic alterations characteristic of other pediatric CNS tumor types. Both genes act as transcription factors for a regulatory subset of imprinted genes (IGs), components of the Wnt/ß-Catenin pathway, and the potential drug targets RET and CYP2W1, which are also specifically overexpressed in this tumor type. A derived PLAGL-specific gene expression signature indicates dysregulation of imprinting control and differentiation/development. These tumors occurred throughout the neuroaxis including the cerebral hemispheres, cerebellum, and brainstem, and were predominantly composed of primitive embryonal-like cells lacking robust expression of markers of glial or neuronal differentiation (e.g., GFAP, OLIG2, and synaptophysin). Tumors with PLAGL1 amplification were typically diagnosed during adolescence (median age 10.5 years), whereas those with PLAGL2 amplification were diagnosed during early childhood (median age 2 years). The 10-year overall survival was 66% for PLAGL1-amplified tumors, 25% for PLAGL2-amplified tumors, 18% for male patients, and 82% for female patients. In summary, we describe a new type of biologically distinct CNS tumor characterized by PLAGL1/2 amplification that occurs predominantly in infants and toddlers (PLAGL2) or adolescents (PLAGL1) which we consider best classified as a CNS embryonal tumor and which is associated with intermediate survival. The cell of origin and optimal treatment strategies remain to be defined.

Glioneuronal tumor with ATRX alteration, kinase fusion and anaplastic features (GTAKA): a molecularly distinct brain tumor type with recurrent NTRK gene fusions.

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.

A synergistic interaction between HDAC- and PARP inhibitors in childhood tumors with chromothripsis.

Chromothripsis is a form of genomic instability characterized by the occurrence of tens to hundreds of clustered DNA double-strand breaks in a one-off catastrophic event. Rearrangements associated with chromothripsis are detectable in numerous tumor entities and linked with poor prognosis in some of these, such as Sonic Hedgehog medulloblastoma, neuroblastoma and osteosarcoma. Hence, there is a need for therapeutic strategies eliminating tumor cells with chromothripsis. Defects in DNA double-strand break repair, and in particular homologous recombination repair, have been linked with chromothripsis. Targeting DNA repair deficiencies by synthetic lethality approaches, we performed a synergy screen using drug libraries (n = 375 compounds, 15 models) combined with either a PARP inhibitor or cisplatin. This revealed a synergistic interaction between the HDAC inhibitor romidepsin and PARP inhibition. Functional assays, transcriptome analyses and in vivo validation in patient-derived xenograft mouse models confirmed the efficacy of the combinatorial treatment.

Molecular tumor classification using DNA methylome analysis.

Tumor classifiers based on molecular patterns promise to define and reliably classify tumor entities. The high tissue- and cell type-specificity of DNA methylation, as well as its high stability, makes DNA methylation an ideal choice for the development of tumor classifiers. Herein, we review existing tumor classifiers using DNA methylome analysis and will provide an overview on their emerging impact on cancer classification, the detection of novel cancer subentities and patient stratification with a focus on brain tumors, sarcomas and hematopoietic malignancies. Furthermore, we provide an outlook on the enormous potential of DNA methylome analysis to complement classical histopathological and genetic diagnostics, including the emerging field of epigenomic analysis in liquid biopsies.

Anaplastic ganglioglioma-A diagnosis comprising several distinct tumour types.

AIMS: Anaplastic ganglioglioma is a rare tumour, and diagnosis has been based on histological criteria. The 5th edition of the World Health Organization Classification of Tumours of the Central Nervous System (CNS WHO) does not list anaplastic ganglioglioma as a distinct diagnosis due to lack of molecular data in previous publications. We retrospectively compiled a cohort of 54 histologically diagnosed anaplastic gangliogliomas to explore whether the molecular profiles of these tumours represent a separate type or resolve into other entities. METHODS: Samples were subjected to histological review, desoxyribonucleic acid (DNA) methylation profiling and next-generation sequencing. Morphological and molecular data were summarised to an integrated diagnosis. RESULTS: The majority of tumours designated as anaplastic gangliogliomas resolved into other CNS WHO diagnoses, most commonly pleomorphic xanthoastrocytoma (16/54), glioblastoma, isocitrate dehydrogenase protein (IDH) wild type and diffuse paediatric-type high-grade glioma, H3 wild type and IDH wild type (11 and 2/54), followed by low-grade glial or glioneuronal tumours including pilocytic astrocytoma, dysembryoplastic neuroepithelial tumour and diffuse leptomeningeal glioneuronal tumour (5/54), IDH mutant astrocytoma (4/54) and others (6/54). A subset of tumours (10/54) was not assignable to a CNS WHO diagnosis, and common molecular profiles pointing to a separate entity were not evident. CONCLUSIONS: In summary, we show that tumours histologically diagnosed as anaplastic ganglioglioma comprise a wide spectrum of CNS WHO tumour types with different prognostic and therapeutic implications. We therefore suggest assigning this designation with caution and recommend comprehensive molecular workup.

Accurate calling of KIAA1549-BRAF fusions from DNA of human brain tumours using methylation array-based copy number and gene panel sequencing data.

AIMS: KIAA1549-BRAF fusions occur in certain brain tumours and provide druggable targets due to a constitutive activation of the MAP-kinase pathway. We introduce workflows for calling the KIAA1549-BRAF fusion from DNA methylation array-derived copy number as well as DNA panel sequencing data. METHODS: Copy number profiles were analysed by automated screening and visual verification of a tandem duplication on chromosome 7q34, indicative of the KIAA1549-BRAF fusion. Pilocytic astrocytomas of the ICGC cohort with known fusion status were used for validation. KIAA1549-BRAF fusions were called from DNA panel sequencing data using the fusion callers Manta, Arriba with modified filtering criteria and deFuse. We screened DNA methylation and panel sequencing data of 7790 specimens from brain tumour and sarcoma entities. RESULTS: We identified the fusion in 337 brain tumours with both DNA methylation and panel sequencing data. Among these, we detected the fusion from copy number data in 84% and from DNA panel sequencing data in more than 90% using Arriba with modified filters. While in 74% the KIAA1549-BRAF fusion was detected from both methylation array-derived copy number and panel sequencing data, in 9% it was detected from copy number data only and in 16% from panel data only. The fusion was almost exclusively found in pilocytic astrocytomas, diffuse leptomeningeal glioneuronal tumours and high-grade astrocytomas with piloid features. CONCLUSIONS: The KIAA1549-BRAF fusion can be reliably detected from either DNA methylation array or DNA panel data. The use of both methods is recommended for the most sensitive detection of this diagnostically and therapeutically important marker.

Clear cell meningiomas are defined by a highly distinct DNA methylation profile and mutations in SMARCE1.

Clear cell meningioma represents an uncommon variant of meningioma that typically affects children and young adults. Although an enrichment of loss-of-function mutations in the SMARCE1 gene has been reported for this subtype, comprehensive molecular investigations are lacking. Here we describe a molecularly distinct subset of tumors (n = 31), initially identified through genome-wide DNA methylation screening among a cohort of 3093 meningiomas, of which most were diagnosed histologically as clear cell meningioma. This cohort was further supplemented by an additional 11 histologically diagnosed clear cell meningiomas for analysis (n = 42). Targeted DNA sequencing revealed SMARCE1 mutations in 33/34 analyzed samples, accompanied by a nuclear loss of expression determined via immunohistochemistry and a decreased SMARCE1 transcript expression in the tumor cells. Analysis of time to progression or recurrence of patients within the clear cell meningioma group (n = 14) in comparison to those with meningioma WHO grade 2 (n = 220) revealed a similar outcome and support the assignment of WHO grade 2 to these tumors. Our findings indicate the existence of a highly distinct epigenetic signature of clear cell meningiomas, separate from all other variants of meningiomas, with recurrent mutations in the SMARCE1 gene. This suggests that these tumors may arise from a different precursor cell population than the broad spectrum of the other meningioma subtypes.

Recurrent fusions in PLAGL1 define a distinct subset of pediatric-type supratentorial neuroepithelial tumors.

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.

PATZ1 fusions define a novel molecularly distinct neuroepithelial tumor entity with a broad histological spectrum.

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.

Glioblastomas with primitive neuronal component harbor a distinct methylation and copy-number profile with inactivation of TP53, PTEN, and RB1.

Glioblastoma IDH-wildtype presents with a wide histological spectrum. Some features are so distinctive that they are considered as separate histological variants or patterns for the purpose of classification. However, these usually lack defined (epi-)genetic alterations or profiles correlating with this histology. Here, we describe a molecular subtype with overlap to the unique histological pattern of glioblastoma with primitive neuronal component. Our cohort consists of 63 IDH-wildtype glioblastomas that harbor a characteristic DNA methylation profile. Median age at diagnosis was 59.5 years. Copy-number variations and genetic sequencing revealed frequent alterations in TP53, RB1 and PTEN, with fewer gains of chromosome 7 and homozygous CDKN2A/B deletions than usually described for IDH-wildtype glioblastoma. Gains of chromosome 1 were detected in more than half of the cases. A poorly differentiated phenotype with frequent absence of GFAP expression, high proliferation index and strong staining for p53 and TTF1 often caused misleading histological classification as carcinoma metastasis or primitive neuroectodermal tumor. Clinically, many patients presented with leptomeningeal dissemination and spinal metastasis. Outcome was poor with a median overall survival of only 12 months. Overall, we describe a new molecular subtype of IDH-wildtype glioblastoma with a distinct histological appearance and genetic signature.

Drivers underpinning the malignant transformation of giant cell tumour of bone.

The rare benign giant cell tumour of bone (GCTB) is defined by an almost unique mutation in the H3.3 family of histone genes H3-3A or H3-3B; however, the same mutation is occasionally found in primary malignant bone tumours which share many features with the benign variant. Moreover, lung metastases can occur despite the absence of malignant histological features in either the primary or metastatic lesions. Herein we investigated the genetic events of 17 GCTBs including benign and malignant variants and the methylation profiles of 122 bone tumour samples including GCTBs. Benign GCTBs possessed few somatic alterations and no other known drivers besides the H3.3 mutation, whereas all malignant tumours harboured at least one additional driver mutation and exhibited genomic features resembling osteosarcomas, including high mutational burden, additional driver event(s), and a high degree of aneuploidy. The H3.3 mutation was found to predate the development of aneuploidy. In contrast to osteosarcomas, malignant H3.3-mutated tumours were enriched for a variety of alterations involving TERT, other than amplification, suggesting telomere dysfunction in the transformation of benign to malignant GCTB. DNA sequencing of the benign metastasising GCTB revealed no additional driver alterations; polyclonal seeding in the lung was identified, implying that the metastatic lesions represent an embolic event. Unsupervised clustering of DNA methylation profiles revealed that malignant H3.3-mutated tumours are distinct from their benign counterpart, and other bone tumours. Differential methylation analysis identified CCND1, encoding cyclin D1, as a plausible cancer driver gene in these tumours because hypermethylation of the CCND1 promoter was specific for GCTBs. We report here the genomic and methylation patterns underlying the rare clinical phenomena of benign metastasising and malignant transformation of GCTB and show how the combination of genomic and epigenomic findings could potentially distinguish benign from malignant GCTBs, thereby predicting aggressive behaviour in challenging diagnostic cases. © 2020 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

Molecular subgrouping of primary pineal parenchymal tumors reveals distinct subtypes correlated with clinical parameters and genetic alterations.

Tumors of the pineal region comprise several different entities with distinct clinical and histopathological features. Whereas some entities predominantly affect adults, pineoblastoma (PB) constitutes a highly aggressive malignancy of childhood with a poor outcome. PBs mainly arise sporadically, but may also occur in the context of cancer predisposition syndromes including DICER1 and RB1 germline mutation. With this study, we investigate clinico-pathological subgroups of pineal tumors and further characterize their biological features. We performed genome-wide DNA methylation analysis in 195 tumors of the pineal region and 20 normal pineal gland controls. Copy-number profiles were obtained from DNA methylation data; gene panel sequencing was added for 93 tumors and analysis was further complemented by miRNA sequencing for 22 tumor samples. Unsupervised clustering based on DNA methylation profiling separated known subgroups, like pineocytoma, pineal parenchymal tumor of intermediate differentiation, papillary tumor of the pineal region and PB, and further distinct subtypes within these groups, including three subtypes within the core PB subgroup. The novel molecular subgroup Pin-RB includes cases of trilateral retinoblastoma as well as sporadic pineal tumors with RB1 alterations, and displays similarities with retinoblastoma. Distinct clinical associations discriminate the second novel molecular subgroup PB-MYC from other PB cases. Alterations within the miRNA processing pathway (affecting DROSHA, DGCR8 or DICER1) are found in about two thirds of cases in the three core PB subtypes. Methylation profiling revealed biologically distinct groups of pineal tumors with specific clinical and molecular features. Our findings provide a foundation for further clinical as well as molecular and functional characterization of PB and other pineal tumors, including the role of miRNA processing defects in oncogenesis.

Desmoplastic myxoid tumor, SMARCB1-mutant: clinical, histopathological and molecular characterization of a pineal region tumor encountered in adolescents and adults.

Atypical teratoid/rhabdoid tumor (ATRT) is a highly malignant brain tumor predominantly occurring in infants. Mutations of the SMARCB1 gene are the characteristic genetic lesion. SMARCB1-mutant tumors in adolescents and adults are rare and may show uncommon histopathological and clinical features. Here we report seven SMARCB1-deficient intracranial tumors sharing distinct clinical, histopathological and molecular features. Median age of the four females and three males was 40 years (range 15-61 years). All tumors were located in the pineal region. Histopathologically, these tumors displayed spindled and epithelioid cells embedded in a desmoplastic stroma alternating with a variable extent of a loose myxoid matrix. All cases showed loss of nuclear SMARCB1/INI1 protein expression, expression of EMA and CD34 was frequent and the Ki67/MIB1 proliferation index was low in the majority of cases (median 3%). Three cases displayed heterozygous SMARCB1 deletions and two cases a homozygous SMARCB1 deletion. On sequencing, one tumor showed a 2 bp deletion in exon 4 (c.369_370del) and one a short duplication in exon 3 (c.237_276dup) both resulting in frameshift mutations. Most DNA methylation profiles were not classifiable using the Heidelberg Brain Tumor Classifier (version v11b4). By unsupervised t-SNE analysis and hierarchical clustering analysis, however, all tumors grouped closely together and showed similarities with ATRT-MYC. After a median observation period of 48 months, three patients were alive with stable disease, whereas one patient experienced tumor progression and three patients had succumbed to disease. In conclusion, our series represents an entity with distinct clinical, histopathological and molecular features showing epigenetic similarities with ATRT-MYC. We propose the designation desmoplastic myxoid tumor (DMT), SMARCB1-mutant, for these tumors.

RF_Purify: a novel tool for comprehensive analysis of tumor-purity in methylation array data based on random forest regression.

BACKGROUND: With the advent of array-based techniques to measure methylation levels in primary tumor samples, systematic investigations of methylomes have widely been performed on a large number of tumor entities. Most of these approaches are not based on measuring individual cell methylation but rather the bulk tumor sample DNA, which contains a mixture of tumor cells, infiltrating immune cells and other stromal components. This raises questions about the purity of a certain tumor sample, given the varying degrees of stromal infiltration in different entities. Previous methods to infer tumor purity require or are based on the use of matching control samples which are rarely available. Here we present a novel, reference free method to quantify tumor purity, based on two Random Forest classifiers, which were trained on ABSOLUTE as well as ESTIMATE purity values from TCGA tumor samples. We subsequently apply this method to a previously published, large dataset of brain tumors, proving that these models perform well in datasets that have not been characterized with respect to tumor purity . RESULTS: Using two gold standard methods to infer purity - the ABSOLUTE score based on whole genome sequencing data and the ESTIMATE score based on gene expression data- we have optimized Random Forest classifiers to predict tumor purity in entities that were contained in the TCGA project. We validated these classifiers using an independent test data set and cross-compared it to other methods which have been applied to the TCGA datasets (such as ESTIMATE and LUMP). Using Illumina methylation array data of brain tumor entities (as published in Capper et al. (Nature 555:469-474,2018)) we applied this model to estimate tumor purity and find that subgroups of brain tumors display substantial differences in tumor purity. CONCLUSIONS: Random forest- based tumor purity prediction is a well suited tool to extrapolate gold standard measures of purity to novel methylation array datasets. In contrast to other available methylation based tumor purity estimation methods, our classifiers do not need a priori knowledge about the tumor entity or matching control tissue to predict tumor purity.