Gliomas are the most common CNS tumors in children and adolescents, and they show an extremely broad range of clinical behavior. The majority of pediatric gliomas present as benign, slow-growing ...lesions classified as grade I or II by the WHO classification of CNS tumors. These pediatric low-grade gliomas (LGGs) are fundamentally different from IDH-mutant LGGs occurring in adults, because they rarely undergo malignant transformation and show excellent overall survival under current treatment strategies. However, a significant fraction of gliomas develop over a short period of time and progress rapidly and are therefore classified as WHO grade III or IV high-grade gliomas (HGGs). Despite all therapeutic efforts, they remain largely incurable, with the most aggressive forms being lethal within months. Thus, the intentions of neurosurgeons, pediatric oncologists, and radiotherapists to improve care for pediatric patients with glioma range from increasing quality of life and preventing long-term sequelae in what is often a chronic, but rarely life-threatening disease (LGG), to uncovering effective treatment options to prolong patient survival in an almost universally fatal setting (HGG). The last decade has seen unprecedented progress in understanding the molecular biology underlying pediatric gliomas, fueling hopes to achieve both goals. Large-scale collaborative studies around the globe have cataloged genomic and epigenomic alterations in gliomas across ages, grades, and histologies. These studies have revealed biologic subgroups characterized by distinct molecular, pathologic, and clinical features, with clear relevance for patient management. In this review, we summarize hallmark discoveries that have expanded our knowledge in pediatric LGGs and HGGs, explain their role in tumor biology, and convey our current concepts on how these findings may be translated into novel therapeutic approaches.
Abstract
The fifth edition of the WHO Classification of Tumors of the Central Nervous System (CNS), published in 2021, is the sixth version of the international standard for the classification of ...brain and spinal cord tumors. Building on the 2016 updated fourth edition and the work of the Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy, the 2021 fifth edition introduces major changes that advance the role of molecular diagnostics in CNS tumor classification. At the same time, it remains wedded to other established approaches to tumor diagnosis such as histology and immunohistochemistry. In doing so, the fifth edition establishes some different approaches to both CNS tumor nomenclature and grading and it emphasizes the importance of integrated diagnoses and layered reports. New tumor types and subtypes are introduced, some based on novel diagnostic technologies such as DNA methylome profiling. The present review summarizes the major general changes in the 2021 fifth edition classification and the specific changes in each taxonomic category. It is hoped that this summary provides an overview to facilitate more in-depth exploration of the entire fifth edition of the WHO Classification of Tumors of the Central Nervous System.
Medulloblastoma, a malignant brain tumour primarily diagnosed during childhood, has recently been the focus of intensive molecular profiling efforts, profoundly advancing our understanding of ...biologically and clinically heterogeneous disease subgroups. Genomic, epigenomic, transcriptomic and proteomic landscapes have now been mapped for an unprecedented number of bulk samples from patients with medulloblastoma and, more recently, for single medulloblastoma cells. These efforts have provided pivotal new insights into the diverse molecular mechanisms presumed to drive tumour initiation, maintenance and recurrence across individual subgroups and subtypes. Translational opportunities stemming from this knowledge are continuing to evolve, providing a framework for improved diagnostic and therapeutic interventions. In this Review, we summarize recent advances derived from this continued molecular characterization of medulloblastoma and contextualize this progress towards the deployment of more effective, molecularly informed treatments for affected patients.
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FZAB, GEOZS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Ependymal tumors are rare CNS tumors and may occur at any age, but their proportion among primary brain tumors is highest in children and young adults. Thus, the level of evidence of diagnostic and ...therapeutic interventions is higher in the pediatric compared with the adult patient population.The diagnosis and disease staging is performed by craniospinal MRI. Tumor classification is achieved by histological and molecular diagnostic assessment of tissue specimens according to the World Health Organization (WHO) classification 2016. Surgery is the crucial initial treatment in both children and adults. In pediatric patients with intracranial ependymomas of WHO grades II or III, surgery is followed by local radiotherapy regardless of residual tumor volume. In adults, radiotherapy is employed in patients with anaplastic ependymoma WHO grade III, and in case of incomplete resection of WHO grade II ependymoma. Chemotherapy alone is reserved for young children <12 months and for adults with recurrent disease when further surgery and irradiation are no longer feasible. A gross total resection is the mainstay of treatment in spinal ependymomas, and radiotherapy is reserved for incompletely resected tumors. Nine subgroups of ependymal tumors across different anatomical compartments (supratentorial, posterior fossa, spinal) and patient ages have been identified with distinct genetic and epigenetic alterations, and with distinct outcomes. These findings may lead to more precise diagnostic and prognostic assessments, molecular subgroup-adapted therapies, and eventually new recommendations pending validation in prospective studies.
Recently, we described a machine learning approach for classification of central nervous system tumors based on the analysis of genome-wide DNA methylation patterns
6
. Here, we report on DNA ...methylation-based central nervous system (CNS) tumor diagnostics conducted in our institution between the years 2015 and 2018. In this period, more than 1000 tumors from the neurosurgical departments in Heidelberg and Mannheim and more than 1000 tumors referred from external institutions were subjected to DNA methylation analysis for diagnostic purposes. We describe our current approach to the integrated diagnosis of CNS tumors with a focus on constellations with conflicts between morphological and molecular genetic findings. We further describe the benefit of integrating DNA copy-number alterations into diagnostic considerations and provide a catalog of copy-number changes for individual DNA methylation classes. We also point to several pitfalls accompanying the diagnostic implementation of DNA methylation profiling and give practical suggestions for recurring diagnostic scenarios.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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 .
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.
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.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Historical risk stratification criteria for medulloblastoma rely primarily on clinicopathological variables pertaining to age, presence of metastases, extent of resection, histological subtypes and ...in some instances individual genetic aberrations such as
MYC
and
MYCN
amplification. In 2010, an international panel of experts established consensus defining four main subgroups of medulloblastoma (WNT, SHH, Group 3 and Group 4) delineated by transcriptional profiling. This has led to the current generation of biomarker-driven clinical trials assigning WNT tumors to a favorable prognosis group in addition to clinicopathological criteria including
MYC
and
MYCN
gene amplifications. However, outcome prediction of non-WNT subgroups is a challenge due to inconsistent survival reports. In 2015, a consensus conference was convened in Heidelberg with the objective to further refine the risk stratification in the context of subgroups and agree on a definition of risk groups of non-infant, childhood medulloblastoma (ages 3–17). Published and unpublished data over the past 5 years were reviewed, and a consensus was reached regarding the level of evidence for currently available biomarkers. The following risk groups were defined based on current survival rates: low risk (>90 % survival), average (standard) risk (75–90 % survival), high risk (50–75 % survival) and very high risk (<50 % survival) disease. The WNT subgroup and non-metastatic Group 4 tumors with whole chromosome 11 loss or whole chromosome 17 gain were recognized as low-risk tumors that may qualify for reduced therapy. High-risk strata were defined as patients with metastatic SHH or Group 4 tumors, or
MYCN
-amplified SHH medulloblastomas. Very high-risk patients are Group 3 with metastases or SHH with
TP53
mutation. In addition, a number of consensus points were reached that should be standardized across future clinical trials. Although we anticipate new data will emerge from currently ongoing and recently completed clinical trials, this consensus can serve as an outline for prioritization of certain molecular subsets of tumors to define and validate risk groups as a basis for future clinical trials.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Extensive prior research focused on somatic copy-number alterations (SCNAs) affecting cancer genes, yet the extent to which recurrent SCNAs exert their influence through rearrangement of ...cis-regulatory elements (CREs) remains unclear. Here we present a framework for inferring cancer-related gene overexpression resulting from CRE reorganization (e.g., enhancer hijacking) by integrating SCNAs, gene expression data and information on topologically associating domains (TADs). Analysis of 7,416 cancer genomes uncovered several pan-cancer candidate genes, including IRS4, SMARCA1 and TERT. We demonstrate that IRS4 overexpression in lung cancer is associated with recurrent deletions in cis, and we present evidence supporting a tumor-promoting role. We additionally pursued cancer-type-specific analyses and uncovered IGF2 as a target for enhancer hijacking in colorectal cancer. Recurrent tandem duplications intersecting with a TAD boundary mediate de novo formation of a 3D contact domain comprising IGF2 and a lineage-specific super-enhancer, resulting in high-level gene activation. Our framework enables systematic inference of CRE rearrangements mediating dysregulation in cancer.
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IJS, NUK, SBMB, UL, UM, UPUK
In 2012, an international consensus paper reported that medulloblastoma comprises four molecular subgroups (WNT, SHH, Group 3, and Group 4), each associated with distinct genomic features and ...clinical behavior. Independently, multiple recent reports have defined further intra-subgroup heterogeneity in the form of biologically and clinically relevant subtypes. However, owing to differences in patient cohorts and analytical methods, estimates of subtype number and definition have been inconsistent, especially within Group 3 and Group 4. Herein, we aimed to reconcile the definition of Group 3/Group 4 MB subtypes through the analysis of a series of 1501 medulloblastomas with DNA-methylation profiling data, including 852 with matched transcriptome data. Using multiple complementary bioinformatic approaches, we compared the concordance of subtype calls between published cohorts and analytical methods, including assessments of class-definition confidence and reproducibility. While the lowest complexity solutions continued to support the original consensus subgroups of Group 3 and Group 4, our analysis most strongly supported a definition comprising eight robust Group 3/Group 4 subtypes (types I–VIII). Subtype II was consistently identified across all component studies, while all others were supported by multiple class-definition methods. Regardless of analytical technique, increasing cohort size did not further increase the number of identified Group 3/Group 4 subtypes. Summarizing the molecular and clinico-pathological features of these eight subtypes indicated enrichment of specific driver gene alterations and cytogenetic events amongst subtypes, and identified highly disparate survival outcomes, further supporting their biological and clinical relevance. Collectively, this study provides continued support for consensus Groups 3 and 4 while enabling robust derivation of, and categorical accounting for, the extensive intertumoral heterogeneity within Groups 3 and 4, revealed by recent high-resolution subclassification approaches. Furthermore, these findings provide a basis for application of emerging methods (e.g., proteomics/single-cell approaches) which may additionally inform medulloblastoma subclassification. Outputs from this study will help shape definition of the next generation of medulloblastoma clinical protocols and facilitate the application of enhanced molecularly guided risk stratification to improve outcomes and quality of life for patients and their families.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Organ development is orchestrated by cell- and time-specific gene regulatory networks. In this study, we investigated the regulatory basis of mouse cerebellum development from early neurogenesis to ...adulthood. By acquiring snATAC-seq (single-nucleus assay for transposase accessible chromatin using sequencing) profiles for ~90,000 cells spanning 11 stages, we mapped cerebellar cell types and identified candidate cis
regulatory elements (CREs). We detected extensive spatiotemporal heterogeneity among progenitor cells and a gradual divergence in the regulatory programs of cerebellar neurons during differentiation. Comparisons to vertebrate genomes and snATAC-seq profiles for ∼20,000 cerebellar cells from the marsupial opossum revealed a shared decrease in CRE conservation during development and differentiation as well as differences in constraint between cell types. Our work delineates the developmental and evolutionary dynamics of gene regulation in cerebellar cells and provides insights into mammalian organ development.
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