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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.
BACKGROUND: The analysis of microarray time series promises a deeper insight into the dynamics of the cellular response following stimulation. A common observation in this type of data is that some genes respond with quick, transient dynamics, while other genes change their expression slowly over time. The existing methods for detecting significant expression dynamics often fail when the expression dynamics show a large heterogeneity. Moreover, these methods often cannot cope with irregular and sparse measurements.
RESULTS: The method proposed here is specifically designed for the analysis of perturbation responses. It combines different scores to capture fast and transient dynamics as well as slow expression changes, and performs well in the presence of low replicate numbers and irregular sampling times. The results are given in the form of tables including links to figures showing the expression dynamics of the respective transcript. These allow to quickly recognise the relevance of detection, to identify possible false positives and to discriminate early and late changes in gene expression. An extension of the method allows the analysis of the expression dynamics of functional groups of genes, providing a quick overview of the cellular response. The performance of this package was tested on microarray data derived from lung cancer cells stimulated with epidermal growth factor (EGF).
CONCLUSION: Here we describe a new, efficient method for the analysis of sparse and heterogeneous time course data with high detection sensitivity and transparency. It is implemented as R package TTCA (transcript time course analysis) and can be installed from the Comprehensive R Archive Network, CRAN. The source code is provided with the Additional file 1.
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.