Dataset Information

Intracranial ependymomas: molecular insights and translation to treatment.

ABSTRACT: Ependymomas are primary central nervous system tumors (CNS), arising within the posterior fossa and supratentorial regions of the brain, and in the spine. Over the last decade, research has resulted in substantial insights into the molecular characteristics of ependymomas, and significant advances have been made in the establishment of a molecular classification system. Ependymomas both within and between the three CNS regions in which they arise, have been shown to contain distinct genetic, epigenetic and cytogenic aberrations, with at least three molecularly distinct subgroups identified within each region. However, these advances in molecular characterization have yet to be translated into clinical practice, with the standard treatment for ependymoma patients largely unchanged. This review summarizes the advances made in the molecular characterization of intracranial ependymomas, outlines the progress made in establishing preclinical models and proposes strategies for moving toward subgroup-specific preclinical investigations and treatment.

SUBMITTER: Lester A

PROVIDER: S-EPMC8018002 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Intracranial ependymomas: molecular insights and translation to treatment.

Lester Ashleigh A McDonald Kerrie L KL

Brain pathology (Zurich, Switzerland) 20190912 1

Ependymomas are primary central nervous system tumors (CNS), arising within the posterior fossa and supratentorial regions of the brain, and in the spine. Over the last decade, research has resulted in substantial insights into the molecular characteristics of ependymomas, and significant advances have been made in the establishment of a molecular classification system. Ependymomas both within and between the three CNS regions in which they arise, have been shown to contain distinct genetic, epi ...[more]

PMID: 31433520

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Project description:Extensive molecular analyses of ependymal tumors have revealed that supratentorial and posterior fossa ependymomas have distinct molecular profiles and are likely to be different diseases. The presence of C11orf95-RELA fusion genes in a subset of supratentorial ependymomas (ST-EPN) indicated the existence of molecular subgroups. However, the pathogenesis of RELA fusion-negative ependymomas remains elusive. To investigate the molecular pathogenesis of these tumors and validate the molecular classification of ependymal tumors, we conducted thorough molecular analyses of 113 locally diagnosed ependymal tumors from 107 patients in the Japan Pediatric Molecular Neuro-Oncology Group. All tumors were histopathologically reviewed and 12 tumors were re-classified as non-ependymomas. A combination of RT-PCR, FISH, and RNA sequencing identified RELA fusion in 19 of 29 histologically verified ST-EPN cases, whereas another case was diagnosed as ependymoma RELA fusion-positive via the methylation classifier (68.9%). Among the 9 RELA fusion-negative ST-EPN cases, either the YAP1 fusion, BCOR tandem duplication, EP300-BCORL1 fusion, or FOXO1-STK24 fusion was detected in single cases. Methylation classification did not identify a consistent molecular class within this group. Genome-wide methylation profiling successfully sub-classified posterior fossa ependymoma (PF-EPN) into PF-EPN-A (PFA) and PF-EPN-B (PFB). A multivariate analysis using Cox regression confirmed that PFA was the sole molecular marker which was independently associated with patient survival. A clinically applicable pyrosequencing assay was developed to determine the PFB subgroup with 100% specificity using the methylation status of 3 genes, CRIP1, DRD4 and LBX2. Our results emphasized the significance of molecular classification in the diagnosis of ependymomas. RELA fusion-negative ST-EPN appear to be a heterogeneous group of tumors that do not fall into any of the existing molecular subgroups and are unlikely to form a single category.

Project description:Based on DNA-methylation, ependymomas growing in the spinal cord comprise two major molecular types termed spinal (SP-EPN) and myxopapillary ependymomas (MPE(-A/B)), which differ with respect to their clinical features and prognosis. Due to the existing discrepancy between histomorphogical diagnoses and classification using methylation data, we asked whether deep neural networks can predict the DNA methylation class of spinal cord ependymomas from hematoxylin and eosin stained whole-slide images. Using explainable AI, we further aimed to prospectively improve the consistency of histology-based diagnoses with DNA methylation profiling by identifying and quantifying distinct morphological patterns of these molecular ependymoma types. We assembled a case series of 139 molecularly characterized spinal cord ependymomas (nMPE = 84, nSP-EPN = 55). Self-supervised and weakly-supervised neural networks were used for classification. We employed attention analysis and supervised machine-learning methods for the discovery and quantification of morphological features and their correlation to the diagnoses of experienced neuropathologists. Our best performing model predicted the DNA methylation class with 98% test accuracy and used self-supervised learning to outperform pretrained encoder-networks (86% test accuracy). In contrast, the diagnoses of neuropathologists matched the DNA methylation class in only 83% of cases. Domain-adaptation techniques improved model generalization to an external validation cohort by up to 22%. Statistically significant morphological features were identified per molecular type and quantitatively correlated to human diagnoses. The approach was extended to recently defined subtypes of myxopapillary ependymomas (MPE-(A/B), 80% test accuracy). In summary, we demonstrated the accurate prediction of the DNA methylation class of spinal cord ependymomas (SP-EPN, MPE(-A/B)) using hematoxylin and eosin stained whole-slide images. Our approach may prospectively serve as a supplementary resource for integrated diagnostics and may even help to establish a standardized, high-quality level of histology-based diagnostics across institutions-in particular in low-income countries, where expensive DNA-methylation analyses may not be readily available.

Dataset Information

Intracranial ependymomas: molecular insights and translation to treatment.

Publications

Intracranial ependymomas: molecular insights and translation to treatment.

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