Cellular development and evolution of the mammalian cerebellum.

The expansion of the neocortex, a hallmark of mammalian evolution1,2, was accompanied by an increase in cerebellar neuron numbers3. However, little is known about the evolution of the cellular programmes underlying the development of the cerebellum in mammals. In this study we generated single-nucleus RNA-sequencing data for around 400,000 cells to trace the development of the cerebellum from early neurogenesis to adulthood in human, mouse and the marsupial opossum. We established a consensus classification of the cellular diversity in the developing mammalian cerebellum and validated it by spatial mapping in the fetal human cerebellum. Our cross-species analyses revealed largely conserved developmental dynamics of cell-type generation, except for Purkinje cells, for which we observed an expansion of early-born subtypes in the human lineage. Global transcriptome profiles, conserved cell-state markers and gene-expression trajectories across neuronal differentiation show that cerebellar cell-type-defining programmes have been overall preserved for at least 160 million years. However, we also identified many orthologous genes that gained or lost expression in cerebellar neural cell types in one of the species or evolved new expression trajectories during neuronal differentiation, indicating widespread gene repurposing at the cell-type level. In sum, our study unveils shared and lineage-specific gene-expression programmes governing the development of cerebellar cells and expands our understanding of mammalian brain evolution.

Functional loss of a noncanonical BCOR-PRC1.1 complex accelerates SHH-driven medulloblastoma formation.

Medulloblastoma is a malignant childhood brain tumor arising from the developing cerebellum. In Sonic Hedgehog (SHH) subgroup medulloblastoma, aberrant activation of SHH signaling causes increased proliferation of granule neuron progenitors (GNPs), and predisposes these cells to tumorigenesis. A second, cooperating genetic hit is often required to push these hyperplastic cells to malignancy and confer mutation-specific characteristics associated with oncogenic signaling. Somatic loss-of-function mutations of the transcriptional corepressor BCOR are recurrent and enriched in SHH medulloblastoma. To investigate BCOR as a putative tumor suppressor, we used a genetically engineered mouse model to delete exons 9/10 of Bcor (BcorΔE9-10 ) in GNPs during development. This mutation leads to reduced expression of C-terminally truncated BCOR (BCORΔE9-10). While BcorΔE9-10 alone did not promote tumorigenesis or affect GNP differentiation, BcorΔE9-10 combined with loss of the SHH receptor gene Ptch1 resulted in fully penetrant medulloblastomas. In Ptch1+/- ;BcorΔE9-10 tumors, the growth factor gene Igf2 was aberrantly up-regulated, and ectopic Igf2 overexpression was sufficient to drive tumorigenesis in Ptch1+/- GNPs. BCOR directly regulates Igf2, likely through the PRC1.1 complex; the repressive histone mark H2AK119Ub is decreased at the Igf2 promoter in Ptch1+/- ;BcorΔE9-10 tumors. Overall, our data suggests that BCOR-PRC1.1 disruption leads to Igf2 overexpression, which transforms preneoplastic cells to malignant tumors.

Clinically unfavorable transcriptome subtypes of non-WNT/non-SHH medulloblastomas are associated with a predominance in proliferating and progenitor-like cell subpopulations.

The non-WNT/non-SHH (Grp3/Grp4) medulloblastomas (MBs) include eight second-generation subgroups (SGS; I-VIII) each with distinct molecular and clinical characteristics. Recently, we also identified two prognostically relevant transcriptome subtypes within each SGS MB, which are associated with unique gene expression signatures and signaling pathways. These prognostic subsets may be in connection to the intra-tumoral cell landscape that underlies SGS MB clinical-molecular diversity. Here, we performed a deconvolution analysis of the Grp3/Grp4 MB bulk RNA profiles using the previously identified single-cell RNA-seq reference dataset and focusing on variability in the cellular composition of SGS MB. RNA deconvolution analysis of the Grp3/Grp4 MB disclosed the subgroup-specific neoplastic cell subpopulations. Neuronally differentiated axodendritic GP3-C1 and glutamatergic GP4-C1 subpopulations were distributed within Grp3- and Grp4-associated SGS MB, respectively. Progenitor GP3-B2 subpopulation was prominent in aggressive SGS II MB, whereas photoreceptor/visual perception GP3/4-C2 cell content was typical for SGS III/IV MB. The current study also revealed significant variability in the proportions of cell subpopulations between clinically relevant SGS MB transcriptome subtypes, where unfavorable cohorts were enriched with cell cycle and progenitor-like cell subpopulations and, vice versa, favorable subtypes were composed of neuronally differentiated cell fractions predominantly. A higher than median proportion of proliferating and progenitor cell subpopulations conferred the shortest survival of the Grp3 and Grp 4 MB, and similar survival associations were identified for all SGS MB except SGS IV MB. In summary, the recently identified clinically relevant Grp3/Grp4 MB transcriptome subtypes are composed of different cell populations. Future studies should aim to validate the prognostic and therapeutic role of the identified Grp3/Grp4 MB inter-tumoral cellular heterogeneity. The application of the single-cell techniques on each SGS MB separately could help to clarify the clinical significance of subgroup-specific variability in tumor cell content and its relation with prognostic transcriptome signatures identified before.

Therapeutic targeting of ependymoma as informed by oncogenic enhancer profiling.

Genomic sequencing has driven precision-based oncology therapy; however, the genetic drivers of many malignancies remain unknown or non-targetable, so alternative approaches to the identification of therapeutic leads are necessary. Ependymomas are chemotherapy-resistant brain tumours, which, despite genomic sequencing, lack effective molecular targets. Intracranial ependymomas are segregated on the basis of anatomical location (supratentorial region or posterior fossa) and further divided into distinct molecular subgroups that reflect differences in the age of onset, gender predominance and response to therapy. The most common and aggressive subgroup, posterior fossa ependymoma group A (PF-EPN-A), occurs in young children and appears to lack recurrent somatic mutations. Conversely, posterior fossa ependymoma group B (PF-EPN-B) tumours display frequent large-scale copy number gains and losses but have favourable clinical outcomes. More than 70% of supratentorial ependymomas are defined by highly recurrent gene fusions in the NF-κB subunit gene RELA (ST-EPN-RELA), and a smaller number involve fusion of the gene encoding the transcriptional activator YAP1 (ST-EPN-YAP1). Subependymomas, a distinct histologic variant, can also be found within the supratetorial and posterior fossa compartments, and account for the majority of tumours in the molecular subgroups ST-EPN-SE and PF-EPN-SE. Here we describe mapping of active chromatin landscapes in 42 primary ependymomas in two non-overlapping primary ependymoma cohorts, with the goal of identifying essential super-enhancer-associated genes on which tumour cells depend. Enhancer regions revealed putative oncogenes, molecular targets and pathways; inhibition of these targets with small molecule inhibitors or short hairpin RNA diminished the proliferation of patient-derived neurospheres and increased survival in mouse models of ependymomas. Through profiling of transcriptional enhancers, our study provides a framework for target and drug discovery in other cancers that lack known genetic drivers and are therefore difficult to treat.

Transcriptome analysis stratifies second-generation non-WNT/non-SHH medulloblastoma subgroups into clinically tractable subtypes.

Medulloblastoma (MB), one of the most common malignant pediatric brain tumor, is a heterogenous disease comprised of four distinct molecular groups (WNT, SHH, Group 3, Group 4). Each of these groups can be further subdivided into second-generation MB (SGS MB) molecular subgroups, each with distinct genetic and clinical characteristics. For instance, non-WNT/non-SHH MB (Group 3/4) can be subdivided molecularly into eight distinct and clinically relevant tumor subgroups. A further molecular stratification/summarization of these SGS MB would allow for the assignment of patients to risk-associated treatment protocols. Here, we performed DNA- and RNA-based analysis of 574 non-WNT/non-SHH MB and analyzed the clinical significance of various molecular patterns within the entire cohort and the eight SGS MB, with the aim to develop an optimal risk stratification of these tumors. Multigene analysis disclosed several survival-associated genes highly specific for each molecular subgroup within this non-WNT/non-SHH MB cohort with minimal inter-subgroup overlap. These subgroup-specific and prognostically relevant genes were associated with pathways that could underlie SGS MB clinical-molecular diversity and tumor-driving mechanisms. By combining survival-associated genes within each SGS MB, distinct metagene sets being appropriate for their optimal risk stratification were identified. Defined subgroup-specific metagene sets were independent variables in the multivariate models generated for each SGS MB and their prognostic value was confirmed in a completely non-overlapping validation cohort of non-WNT/non-SHH MB (n = 377). In summary, the current results indicate that the integration of transcriptome data in risk stratification models may improve outcome prediction for each non-WNT/non-SHH SGS MB. Identified subgroup-specific gene expression signatures could be relevant for clinical implementation and survival-associated metagene sets could be adopted for further SGS MB risk stratification. Future studies should aim at validating the prognostic role of these transcriptome-based SGS MB subtypes in prospective clinical trials.

Gene expression profiling of Group 3 medulloblastomas defines a clinically tractable stratification based on KIRREL2 expression.

Medulloblastomas (MB) molecularly designated as Group 3 (Grp 3) MB represent a more clinically aggressive tumor variant which, as a group, displays heterogeneous molecular characteristics and disease outcomes. Reliable risk stratification of Grp 3 MB would allow for appropriate assignment of patients to aggressive treatment protocols and, vice versa, for sparing adverse effects of high-dose radio-chemotherapy in patients with standard or low-risk tumors. Here we performed RNA-based analysis on an international cohort of 179 molecularly designated Grp 3 MB treated with HIT protocols. We analyzed the clinical significance of differentially expressed genes, thereby developing optimal prognostic subdivision of this MB molecular group. We compared the transcriptome profiles of two Grp 3 MB subsets with various outcomes (76 died within the first 60 months vs. 103 survived this period) and identified 224 differentially expressed genes (DEG) between these two clinical groups (Limma R algorithm, adjusted p-value < 0.05). We selected the top six DEG overexpressed in the unfavorable cohort for further survival analysis and found that expression of all six genes strongly correlated with poor outcomes. However, only high expression of KIRREL2 was identified as an independent molecular prognostic indicator of poor patients' survival. Based on clinical and molecular patterns, four risk categories were outlined for Grp 3 MB patients: i. low-risk: M0-1/MYC non-amplified/KIRREL2 low (n = 48; 5-year OS-95%); ii. standard-risk: M0-1/MYC non-amplified/KIRREL2 high or M2-3/MYC non-amplified/KIRREL2 low (n = 65; 5-year OS-70%); iii. high-risk: M2-3/MYC non-amplified/KIRREL2 high (n = 36; 5-year OS-30%); iv. very high risk-all MYC amplified tumors (n = 30; 5-year OS-0%). Cross-validated survival models incorporating KIRREL2 expression with clinical features allowed for the reclassification of up to 50% of Grp 3 MB patients into a more appropriate risk category. Finally, KIRREL2 immunopositivity was also identified as a predictive indicator of Grp 3 MB poor survival, thus suggesting its application as a possible prognostic marker in routine clinical settings. Our results indicate that integration of KIRREL2 expression in risk stratification models may improve Grp 3 MB outcome prediction. Therefore, simple gene and/or protein expression analyses for this molecular marker could be easily adopted for Grp 3 MB prognostication and may help in assigning patients to optimal therapeutic approaches in prospective clinical trials.

Targeting fibroblast growth factor receptors to combat aggressive ependymoma.

Ependymomas (EPN) are central nervous system tumors comprising both aggressive and more benign molecular subtypes. However, therapy of the high-risk subtypes posterior fossa group A (PF-A) and supratentorial RELA-fusion positive (ST-RELA) is limited to gross total resection and radiotherapy, as effective systemic treatment concepts are still lacking. We have recently described fibroblast growth factor receptors 1 and 3 (FGFR1/FGFR3) as oncogenic drivers of EPN. However, the underlying molecular mechanisms and their potential as therapeutic targets have not yet been investigated in detail. Making use of transcriptomic data across 467 EPN tissues, we found that FGFR1 and FGFR3 were both widely expressed across all molecular groups. FGFR3 mRNA levels were enriched in ST-RELA showing the highest expression among EPN as well as other brain tumors. We further identified high expression levels of fibroblast growth factor 1 and 2 (FGF1, FGF2) across all EPN subtypes while FGF9 was elevated in ST-EPN. Interrogation of our EPN single-cell RNA-sequencing data revealed that FGFR3 was further enriched in cycling and progenitor-like cell populations. Corroboratively, we found FGFR3 to be predominantly expressed in radial glia cells in both mouse embryonal and human brain datasets. Moreover, we detected alternative splicing of the FGFR1/3-IIIc variant, which is known to enhance ligand affinity and FGFR signaling. Dominant-negative interruption of FGFR1/3 activation in PF-A and ST-RELA cell models demonstrated inhibition of key oncogenic pathways leading to reduced cell growth and stem cell characteristics. To explore the feasibility of therapeutically targeting FGFR, we tested a panel of FGFR inhibitors in 12 patient-derived EPN cell models revealing sensitivity in the low-micromolar to nano-molar range. Finally, we gain the first clinical evidence for the activity of the FGFR inhibitor nintedanib in the treatment of a patient with recurrent ST-RELA. Together, these preclinical and clinical data suggest FGFR inhibition as a novel and feasible approach to combat aggressive EPN.

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.

Subgroup and subtype-specific outcomes in adult medulloblastoma.

Medulloblastoma, a common pediatric malignant central nervous system tumour, represent a small proportion of brain tumours in adults. Previously it has been shown that in adults, Sonic Hedgehog (SHH)-activated tumours predominate, with Wingless-type (WNT) and Group 4 being less common, but molecular risk stratification remains a challenge. We performed an integrated analysis consisting of genome-wide methylation profiling, copy number profiling, somatic nucleotide variants and correlation of clinical variables across a cohort of 191 adult medulloblastoma cases identified through the Medulloblastoma Advanced Genomics International Consortium. We identified 30 WNT, 112 SHH, 6 Group 3, and 41 Group 4 tumours. Patients with SHH tumours were significantly older at diagnosis compared to other subgroups (p < 0.0001). Five-year progression-free survival (PFS) for WNT, SHH, Group 3, and Group 4 tumours was 64.4 (48.0-86.5), 61.9% (51.6-74.2), 80.0% (95% CI 51.6-100.0), and 44.9% (95% CI 28.6-70.7), respectively (p = 0.06). None of the clinical variables (age, sex, metastatic status, extent of resection, chemotherapy, radiotherapy) were associated with subgroup-specific PFS. Survival among patients with SHH tumours was significantly worse for cases with chromosome 3p loss (HR 2.9, 95% CI 1.1-7.6; p = 0.02), chromosome 10q loss (HR 4.6, 95% CI 2.3-9.4; p < 0.0001), chromosome 17p loss (HR 2.3, 95% CI 1.1-4.8; p = 0.02), and PTCH1 mutations (HR 2.6, 95% CI 1.1-6.2; p = 0.04). The prognostic significance of 3p loss and 10q loss persisted in multivariable regression models. For Group 4 tumours, chromosome 8 loss was strongly associated with improved survival, which was validated in a non-overlapping cohort (combined cohort HR 0.2, 95% CI 0.1-0.7; p = 0.007). Unlike in pediatric medulloblastoma, whole chromosome 11 loss in Group 4 and chromosome 14q loss in SHH was not associated with improved survival, where MYCN, GLI2 and MYC amplification were rare. In sum, we report unique subgroup-specific cytogenetic features of adult medulloblastoma, which are distinct from those in younger patients, and correlate with survival disparities. Our findings suggest that clinical trials that incorporate new strategies tailored to high-risk adult medulloblastoma patients are urgently needed.

Transcriptional profiling of medulloblastoma with extensive nodularity (MBEN) reveals two clinically relevant tumor subsets with VSNL1 as potent prognostic marker.

Medulloblastoma with extensive nodularity (MBEN) is one of the few central nervous system (CNS) tumor entities occurring in infants which is traditionally associated with good to excellent prognosis. Some MBEN, however, have been reported with an unfavorable clinical course. We performed an integrated DNA/RNA-based molecular analysis of a multi-institutional MBEN cohort (n = 41) to identify molecular events which might be responsible for variability in patients' clinical outcomes. RNA sequencing analysis of this MBEN cohort disclosed two clear transcriptome clusters (TCL) of these CNS tumors: "TCL1 MBEN" and "TCL2 MBEN" which were associated with various gene expression signatures, mutational landscapes and, importantly, prognosis. Thus, the clinically unfavorable "TCL1 MBEN" subset revealed transcriptome signatures composed of cancer-associated signaling pathways and disclosed a high frequency of clinically relevant germline PTCH1/SUFU alterations. In contrast, gene expression profiles of tumors from the clinically favorable "TCL2 MBEN" subgroup were associated with activation of various neurometabolic and neurotransmission signaling pathways, and germline SHH-pathway gene mutations were extremely rare in this transcriptome cluster. "TCL2 MBEN" also revealed strong and ubiquitous expression of VSNL1 (visinin-like protein 1) both at the mRNA and protein level, which was correlated with a favorable clinical course. Thus, combining mutational and epigenetic profiling with transcriptome analysis including VSNL1 immunohistochemistry, MBEN patients could be stratified into clinical risk groups of potential value for subsequent treatment planning.

InTAD: chromosome conformation guided analysis of enhancer target genes.

BACKGROUND: High-throughput technologies for analyzing chromosome conformation at a genome scale have revealed that chromatin is organized in topologically associated domains (TADs). While TADs are relatively stable across cell types, intra-TAD activities are cell type specific. Epigenetic profiling of different tissues and cell-types has identified a large number of non-coding epigenetic regulatory elements ('enhancers') that can be located far away from coding genes. Linear proximity is a commonly chosen criterion for associating enhancers with their potential target genes. While enhancers frequently regulate the closest gene, unambiguous identification of enhancer regulated genes remains to be a challenge in the absence of sample matched chromosome conformation data. RESULTS: To associate enhancers with their target genes, we have previously developed and applied a method that tests for significant correlations between enhancer and gene expressions across a cohort of samples. To limit the number of tests, we constrain this analysis to gene-enhancer pairs embedded in the same TAD, where information on TAD boundaries is borrowed from publicly available chromosome conformation capturing ('Hi-C') data. We have now implemented this method as an R Bioconductor package 'InTAD' and verified the software package by reanalyzing available enhancer and gene expression data derived from ependymoma brain tumors. CONCLUSION: The open-source package InTAD is an easy-to-use software tool for identifying proximal and distal enhancer target genes by leveraging information on correlated expression of enhancers and genes that are located in the same TAD. InTAD can be applied to any heterogeneous cohort of samples analyzed by a combination of gene expression and epigenetic profiling techniques and integrates either public or custom information of TAD boundaries.

Desmoplastic/nodular medulloblastomas (DNMB) and medulloblastomas with extensive nodularity (MBEN) disclose similar epigenetic signatures but different transcriptional profiles.

Desmoplastic/nodular medulloblastomas (DNMB) and medulloblastomas with extensive nodularity (MBEN) were outlined in the current WHO classification of tumors of the nervous system as two distinct histological MB variants. However, they are often considered as cognate SHH MB entities, and it is a reason why some clinical MB trials do not separate the patients with DNMB or MBEN histology. In the current study, we performed an integrated DNA/RNA-based molecular analysis of 83 DNMB and 36 MBEN to assess the etiopathogenetic relationship between these SHH MB variants. Methylation profiling revealed "infant" and "children" SHH MB clusters but neither DNMB nor MBEN composed separate epigenetic cohorts, and their profiles were intermixed within the "infant" cluster. In contrast, RNA-based transcriptional profiling disclosed that expression signatures of all MBEN were clustered separately from most of DNMB and a set of differentially expressed genes was identified. MBEN transcriptomes were enriched with genes associated with synaptic transmission, neuronal differentiation and metabolism, whereas DNMB profiling signatures included sets of genes involved in phototransduction and NOTCH signaling pathways. Thus, DNMB and MBEN are distinct tumor entities within the SHH MB family whose biology is determined by different transcriptional programs. Therefore, we recommend a transcriptome analysis as an optimal molecular tool to discriminate between DNMB and MBEN, which may be of benefit for patients' risk stratification in clinical trials. Molecular events identified in DNMB by RNA sequencing could be considered in the future as potent molecular targets for novel therapeutic interventions in treatment-resistant cases.

MYCN amplification drives an aggressive form of spinal ependymoma.

Spinal ependymal tumors form a histologically and molecularly heterogeneous group of tumors with generally good prognosis. However, their treatment can be challenging if infiltration of the spinal cord or dissemination throughout the central nervous system (CNS) occurs and, in these cases, clinical outcome remains poor. Here, we describe a new and relatively rare subgroup of spinal ependymal tumors identified using DNA methylation profiling that is distinct from other molecular subgroups of ependymoma. Copy number variation plots derived from DNA methylation arrays showed MYCN amplification as a characteristic genetic alteration in all cases of our cohort (n = 13), which was subsequently validated using fluorescence in situ hybridization. The histological diagnosis was anaplastic ependymoma (WHO Grade III) in ten cases and classic ependymoma (WHO Grade II) in three cases. Histological re-evaluation in five primary tumors and seven relapses showed characteristic histological features of ependymoma, namely pseudorosettes, GFAP- and EMA positivity. Electron microscopy revealed cilia, complex intercellular junctions and intermediate filaments in a representative sample. Taking these findings into account, we suggest to designate this molecular subgroup spinal ependymoma with MYCN amplification, SP-EPN-MYCN. SP-EPN-MYCN tumors showed distinct growth patterns with intradural, extramedullary localization mostly within the thoracic and cervical spine, diffuse leptomeningeal spread throughout the whole CNS and infiltrative invasion of the spinal cord. Dissemination was observed in 100% of cases. Despite high-intensity treatment, SP-EPN-MYCN showed significantly worse median progression free survival (PFS) (17 months) and median overall survival (OS) (87 months) than all other previously described molecular spinal ependymoma subgroups. OS and PFS were similar to supratentorial ependymoma with RELA-fusion (ST-EPN-RELA) and posterior fossa ependymoma A (PF-EPN-A), further highlighting the aggressiveness of this distinct new subgroup. We, therefore, propose to establish SP-EPN-MYCN as a new molecular subgroup in ependymoma and advocate for testing newly diagnosed spinal ependymal tumors for MYCN amplification.

DNA methylation-based classification and grading system for meningioma: a multicentre, retrospective analysis.

BACKGROUND: The WHO classification of brain tumours describes 15 subtypes of meningioma. Nine of these subtypes are allotted to WHO grade I, and three each to grade II and grade III. Grading is based solely on histology, with an absence of molecular markers. Although the existing classification and grading approach is of prognostic value, it harbours shortcomings such as ill-defined parameters for subtypes and grading criteria prone to arbitrary judgment. In this study, we aimed for a comprehensive characterisation of the entire molecular genetic landscape of meningioma to identify biologically and clinically relevant subgroups. METHODS: In this multicentre, retrospective analysis, we investigated genome-wide DNA methylation patterns of meningiomas from ten European academic neuro-oncology centres to identify distinct methylation classes of meningiomas. The methylation classes were further characterised by DNA copy number analysis, mutational profiling, and RNA sequencing. Methylation classes were analysed for progression-free survival outcomes by the Kaplan-Meier method. The DNA methylation-based and WHO classification schema were compared using the Brier prediction score, analysed in an independent cohort with WHO grading, progression-free survival, and disease-specific survival data available, collected at the Medical University Vienna (Vienna, Austria), assessing methylation patterns with an alternative methylation chip. FINDINGS: We retrospectively collected 497 meningiomas along with 309 samples of other extra-axial skull tumours that might histologically mimic meningioma variants. Unsupervised clustering of DNA methylation data clearly segregated all meningiomas from other skull tumours. We generated genome-wide DNA methylation profiles from all 497 meningioma samples. DNA methylation profiling distinguished six distinct clinically relevant methylation classes associated with typical mutational, cytogenetic, and gene expression patterns. Compared with WHO grading, classification by individual and combined methylation classes more accurately identifies patients at high risk of disease progression in tumours with WHO grade I histology, and patients at lower risk of recurrence among WHO grade II tumours (p=0·0096) from the Brier prediction test). We validated this finding in our independent cohort of 140 patients with meningioma. INTERPRETATION: DNA methylation-based meningioma classification captures clinically more homogenous groups and has a higher power for predicting tumour recurrence and prognosis than the WHO classification. The approach presented here is potentially very useful for stratifying meningioma patients to observation-only or adjuvant treatment groups. We consider methylation-based tumour classification highly relevant for the future diagnosis and treatment of meningioma. FUNDING: German Cancer Aid, Else Kröner-Fresenius Foundation, and DKFZ/Heidelberg Institute of Personalized Oncology/Precision Oncology Program.

Qualimap 2: advanced multi-sample quality control for high-throughput sequencing data.

MOTIVATION: Detection of random errors and systematic biases is a crucial step of a robust pipeline for processing high-throughput sequencing (HTS) data. Bioinformatics software tools capable of performing this task are available, either for general analysis of HTS data or targeted to a specific sequencing technology. However, most of the existing QC instruments only allow processing of one sample at a time. RESULTS: Qualimap 2 represents a next step in the QC analysis of HTS data. Along with comprehensive single-sample analysis of alignment data, it includes new modes that allow simultaneous processing and comparison of multiple samples. As with the first version, the new features are available via both graphical and command line interface. Additionally, it includes a large number of improvements proposed by the user community. AVAILABILITY AND IMPLEMENTATION: The implementation of the software along with documentation is freely available at http://www.qualimap.org. CONTACT: meyer@mpiib-berlin.mpg.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Cancer-specific epigenome identifies oncogenic hijacking by nuclear factor I family proteins for medulloblastoma progression.

Normal cells coordinate proliferation and differentiation by precise tuning of gene expression based on the dynamic shifts of the epigenome throughout the developmental timeline. Although non-mutational epigenetic reprogramming is an emerging hallmark of cancer, the epigenomic shifts that occur during the transition from normal to malignant cells remain elusive. Here, we capture the epigenomic changes that occur during tumorigenesis in a prototypic embryonal brain tumor, medulloblastoma. By comparing the epigenomes of the different stages of transforming cells in mice, we identify nuclear factor I family of transcription factors, known to be cell fate determinants in development, as oncogenic regulators in the epigenomes of precancerous and cancerous cells. Furthermore, genetic and pharmacological inhibition of NFIB validated a crucial role of this transcription factor by disrupting the cancer epigenome in medulloblastoma. Thus, this study exemplifies how epigenomic changes contribute to tumorigenesis via non-mutational mechanisms involving developmental transcription factors.

Compartments in medulloblastoma with extensive nodularity are connected through differentiation along the granular precursor lineage.

Medulloblastomas with extensive nodularity are cerebellar tumors characterized by two distinct compartments and variable disease progression. The mechanisms governing the balance between proliferation and differentiation in MBEN remain poorly understood. Here, we employ a multi-modal single cell transcriptome analysis to dissect this process. In the internodular compartment, we identify proliferating cerebellar granular neuronal precursor-like malignant cells, along with stromal, vascular, and immune cells. In contrast, the nodular compartment comprises postmitotic, neuronally differentiated malignant cells. Both compartments are connected through an intermediate cell stage resembling actively migrating CGNPs. Notably, we also discover astrocytic-like malignant cells, found in proximity to migrating and differentiated cells at the transition zone between the two compartments. Our study sheds light on the spatial tissue organization and its link to the developmental trajectory, resulting in a more benign tumor phenotype. This integrative approach holds promise to explore intercompartmental interactions in other cancers with varying histology.

Unipro UGENE: a unified bioinformatics toolkit.

UNLABELLED: Unipro UGENE is a multiplatform open-source software with the main goal of assisting molecular biologists without much expertise in bioinformatics to manage, analyze and visualize their data. UGENE integrates widely used bioinformatics tools within a common user interface. The toolkit supports multiple biological data formats and allows the retrieval of data from remote data sources. It provides visualization modules for biological objects such as annotated genome sequences, Next Generation Sequencing (NGS) assembly data, multiple sequence alignments, phylogenetic trees and 3D structures. Most of the integrated algorithms are tuned for maximum performance by the usage of multithreading and special processor instructions. UGENE includes a visual environment for creating reusable workflows that can be launched on local resources or in a High Performance Computing (HPC) environment. UGENE is written in C++ using the Qt framework. The built-in plugin system and structured UGENE API make it possible to extend the toolkit with new functionality. AVAILABILITY AND IMPLEMENTATION: UGENE binaries are freely available for MS Windows, Linux and Mac OS X at http://ugene.unipro.ru/download.html. UGENE code is licensed under the GPLv2; the information about the code licensing and copyright of integrated tools can be found in the LICENSE.3rd_party file provided with the source bundle.

Qualimap: evaluating next-generation sequencing alignment data.

MOTIVATION: The sequence alignment/map (SAM) and the binary alignment/map (BAM) formats have become the standard method of representation of nucleotide sequence alignments for next-generation sequencing data. SAM/BAM files usually contain information from tens to hundreds of millions of reads. Often, the sequencing technology, protocol and/or the selected mapping algorithm introduce some unwanted biases in these data. The systematic detection of such biases is a non-trivial task that is crucial to drive appropriate downstream analyses. RESULTS: We have developed Qualimap, a Java application that supports user-friendly quality control of mapping data, by considering sequence features and their genomic properties. Qualimap takes sequence alignment data and provides graphical and statistical analyses for the evaluation of data. Such quality-control data are vital for highlighting problems in the sequencing and/or mapping processes, which must be addressed prior to further analyses. AVAILABILITY: Qualimap is freely available from http://www.qualimap.org.