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High level MYCN amplification and distinct methylation signature define an aggressive subtype of spinal cord ependymoma.

ABSTRACT: We report a novel group of clinically aggressive spinal cord ependymomas characterized by Grade III histology, MYCN amplification, an absence of NF2 alterations or other recurrent pathogenic mutations, and a unique methylation classifier profile. Seven cases were found to have MYCN amplification in the course of routine mutational profiling of 552 patients with central nervous system tumors between December 2016 and July of 2019 and an eighth patient was identified from an unrelated set of cases. Methylation array analysis revealed that none of the 8 cases clustered with any of the nine previously described ependymoma methylation subgroups, and 7 of 8 formed their own tight unique cluster. Histologically all cases showed grade III features, and all demonstrated aggressive clinical behavior. These findings are presented in the context of data from three other studies describing similar cases. Therefore, a combined total of 27 MYCN amplified spinal cord ependymoma cases have now been reported in the literature, warranting their consideration as a distinctive subtype of spinal cord ependymoma (SP-EPN-MYCN) with their unique molecular characteristics and aggressive clinical behavior.

SUBMITTER: Raffeld M

PROVIDER: S-EPMC7346356 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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High level MYCN amplification and distinct methylation signature define an aggressive subtype of spinal cord ependymoma.

Raffeld Mark M Abdullaev Zied Z Pack Svetlana D SD Xi Liqiang L Nagaraj Sushma S Briceno Nicole N Vera Elizabeth E Pittaluga Stefania S Lopes Abath Neto Osorio O Quezado Martha M Aldape Kenneth K Armstrong Terri S TS Gilbert Mark R MR

Acta neuropathologica communications 20200708 1

We report a novel group of clinically aggressive spinal cord ependymomas characterized by Grade III histology, MYCN amplification, an absence of NF2 alterations or other recurrent pathogenic mutations, and a unique methylation classifier profile. Seven cases were found to have MYCN amplification in the course of routine mutational profiling of 552 patients with central nervous system tumors between December 2016 and July of 2019 and an eighth patient was identified from an unrelated set of cases ...[more]

PMID: 32641156

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Project description: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.

Project description:Molecular subtypes of serous ovarian cancer have been recently described. Using data from independent datasets including over 900 primary tumour samples, we show that deregulation of the Let-7 pathway is specifically associated with the C5 molecular subtype of serous ovarian cancer. DNA copy number and gene expression of HMGA2, alleles of Let-7, LIN28, LIN28B, MYC, MYCN, DICER1, and RNASEN were measured using microarray and quantitative reverse transcriptase PCR. Immunohistochemistry was performed on 127 samples using tissue microarrays and anti-HMGA2 antibodies. Fluorescence in situ hybridisation of bacterial artificial chromosomes hybridized to 239 ovarian tumours was used to measure translocation at the LIN28B locus. Short interfering RNA knockdown in ovarian cell lines was used to test the functionality of associations observed. Four molecular subtypes (C1, C2, C4, C5) of high-grade serous ovarian cancers were robustly represented in each dataset and showed similar pattern of patient survival. We found highly specific activation of a pathway involving MYCN, LIN28B, Let-7 and HMGA2 in the C5 molecular subtype defined by MYCN amplification and over-expression, over-expression of MYCN targets including the Let-7 repressor LIN28B, loss of Let-7 expression and HMGA2 amplification and over-expression. DICER1, a known Let-7 target, and RNASEN were over-expressed in C5 tumours. We saw no evidence of translocation at the LIN28B locus in C5 tumours. The reported interaction between LIN28B and Let-7 was recapitulated by siRNA knockdown in ovarian cancer cell lines. Our results associate deregulation of MYCN and downstream targets, including Let-7 and oncofetal genes, with serous ovarian cancer. We define for the first time how elements of an oncogenic pathway, involving multiple genes that contribute to stem cell renewal, is specifically altered in a molecular subtype of serous ovarian cancer. By defining the drivers of a molecular subtype of serous ovarian cancers we provide a novel strategy for targeted therapeutic intervention.

Project description:PurposeMYCN amplification plays a critical role in defining high-risk subgroup of patients with neuroblastoma. We aimed to develop and validate the CT-based machine learning models for predicting MYCN amplification in pediatric abdominal neuroblastoma.MethodsA total of 172 patients with MYCN amplified (n = 47) and non-amplified (n = 125) were enrolled. The cohort was randomly stratified sampling into training and testing groups. Clinicopathological parameters and radiographic features were selected to construct the clinical predictive model. The regions of interest (ROIs) were segmented on three-phrase CT images to extract first-, second- and higher-order radiomics features. The ICCs, mRMR and LASSO methods were used for dimensionality reduction. The selected features from the training group were used to establish radiomics models using Logistic regression, Support Vector Machine (SVM), Bayes and Random Forest methods. The performance of four different radiomics models was evaluated according to the area under the receiver operator characteristic (ROC) curve (AUC), and then compared by Delong test. The nomogram incorporated of clinicopathological parameters, radiographic features and radiomics signature was developed through multivariate logistic regression. Finally, the predictive performance of the clinical model, radiomics models, and nomogram was evaluated in both training and testing groups.ResultsIn total, 1,218 radiomics features were extracted from the ROIs on three-phrase CT images, and then 14 optimal features, including one original first-order feature and eight wavelet-transformed features and five LoG-transformed features, were identified and selected to construct the radiomics models. In the training group, the AUC of the Logistic, SVM, Bayes and Random Forest model was 0.940, 0.940, 0.780 and 0.927, respectively, and the corresponding AUC in the testing group was 0.909, 0.909, 0.729, 0.851, respectively. There was no significant difference among the Logistic, SVM and Random Forest model, but all better than the Bayes model (p <0.005). The predictive performance of the Logistic radiomics model based on three-phrase is similar to nomogram, but both better than the clinical model and radiomics model based on single venous phase.ConclusionThe CT-based radiomics signature is able to predict MYCN amplification of pediatric abdominal NB with high accuracy based on SVM, Logistic and Random Forest classifiers, while Bayes classifier yields lower predictive performance. When combined with clinical and radiographic qualitative features, the clinics-radiomics nomogram can improve the performance of predicting MYCN amplification.

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High level MYCN amplification and distinct methylation signature define an aggressive subtype of spinal cord ependymoma.

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High level MYCN amplification and distinct methylation signature define an aggressive subtype of spinal cord ependymoma.

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