Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA354936 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:DNA methylation-based classification of human central nervous system tumors [validation set]
| PRJNA430724 | ENA
Project description:DNA methylation-based classification of human central nervous system tumors
| PRJNA430715 | ENA
Project description:The 2021 WHO Classification of Tumors of the Central Nervous System includes several tumor types and subtypes for which the diagnosis is at least partially reliant on utilization of whole genome methylation profiling. The current approach to array DNA methylation profiling utilizes a reference library of tumor DNA methylation data, and a machine learning-based tumor classifier. This approach was pioneered and popularized by the German Cancer Research Network (DKFZ) and University Hospital Heidelberg. This research group has kindly made their classifier for central nervous system tumors freely available as a research tool via a web-based portal. However, this classifier is not maintained in a clinical testing environment. Therefore, we validated our own DNA methylation-based classifier of central nervous system tumors. We validated our classifier using the same training and validation datasets as the DKFZ group. In addition, we performed a validation of samples tested in our own laboratory and compared the performance of both classifiers. Using the validation data set, our classifier’s performance showed high concordance (92%) and comparable accuracy (specificity 94.0% v. 84.9% for DKFZ, sensitivity 88.6% v. 94.7% for DKFZ). Receiver operator curve showed areas under the curve of 0.964 v. 0.966 for NM and DKFZ classifiers, respectively. Our classifier performed comparably well with samples tested in our own laboratory and is currently offered for clinical testing.
2022-03-19 | GSE198855 | GEO
Project description:DNA methylation arrays were performed to molecularly subtype these samples based on Capper D, Jones DTW, Sill M, et al. DNA methylation-based classification of central nervous system tumours. Nature. 2018;555(7697):469-474. doi:10.1038/nature26000
| EGAD00010002017 | EGA
Project description:Ependymal tumors across age groups have been classified and graded solely by histopathology. It is, however, commonly accepted that this classification scheme has limited clinical utility based on its lack of reproducibility in predicting patient outcome. We aimed at establishing a reliable molecular classification using DNA methylation fingerprints and gene expression data of the tumors on a large cohort of 500 tumors. Nine robust molecular subgroups, three in each anatomic compartment of the central nervous system (CNS), were identified.
2015-05-21 | GSE64415 | GEO
Project description:Ependymal tumors across age groups have been classified and graded solely by histopathology. It is, however, commonly accepted that this classification scheme has limited clinical utility based on its lack of reproducibility in predicting patient outcome. We aimed at establishing a reliable molecular classification using DNA methylation fingerprints and gene expression data of the tumors on a large cohort of 500 tumors. Nine robust molecular subgroups, three in each anatomic compartment of the central nervous system (CNS), were identified. Total RNA from 209 ependymal tumor samples were hybridised to the Affymetrix HG U133 Plus 2.0 microarrays.
2015-05-21 | E-GEOD-64415 | biostudies-arrayexpress
Project description:Ependymal tumors across age groups have been classified solely by histopathology. It is, however, commonly accepted that this classification has limited clinical utility based on its poor reliability. We aimed at establishing a reliable and reproducible molecular classification using DNA methylation fingerprints of the tumors. Studying a cohort of 500 tumors allowed for the delineation of nine robust molecular subgroups, three in each anatomic compartment of the central nervous system (CNS). Two of the supratentorial subgroups are characterized by prototypic fusion genes involving RELA and YAP1, respectively. Regarding clinical associations, the molecular classification proposed herein outperforms the current histopathological classification by far and thus might serve as a basis for the upcoming update of the WHO classification of CNS tumors. DNA methylation patterns in tumors have been shown to represent a very stable molecular memory of the respective cell of origin throughout the disease course, thus making them particularly suitable for tumor classification purposes. Methylation fingerprinting of a large series of ependymal tumors of all grades revealed a highly reliable way of classifying this clinically extremely heterogeneous group of malignancies. In fact, out of nine highly reproducible molecular subgroups identified in the supratentorial, infratentorial and spinal regions, only two harbor the vast majority of clinical high-risk patients (mostly children) for whom novel therapeutic concepts are desperately needed. Since this analysis can be performed from minute amounts of DNA extracted from archived material, it is ideally suited for routine clinical application. We investigated a set of 562 ependymal tumors using the Illumina 450k methylation array.
2015-05-21 | E-GEOD-65362 | biostudies-arrayexpress
Project description:DNA methylation profiling has become a powerful tool for neuro-oncology diagnostics. We investigated the value of using DNA methylation profiling to achieve molecular diagnosis in adult primary diffuse lower-grade gliomas according to WHO 2016 classification system of central nervous system tumors. We further evaluated the use of methylation profiling for improved molecular characterization of the tumors and identify prognostic differences beyond histological grade and molecular markers (IDH mutation and 1p/19q codeletion status).
2023-02-27 | GSE175877 | GEO
Project description:Genomewide DNA methylation array profiling of 37 BCOR altered tumors and 37 non-BCOR altered tumors to study the rare tumor entity of EP300::BCOR fusion in central nervous system. The raw methylation idat files and processed beta values were provided here.
2022-10-09 | GSE211156 | GEO
Project description:Multifocal synchronous or metachronous central nervous system (CNS) and extra-CNS malignant rhabdoid tumors (MRTs) are rare and deadly cancers. To further understand these cancers, we performed genome-wide DNA methylation and CNA analysis in 27 tumors (16 of which were paired samples). 26 samples were newly generated and one sample was from a previously published cohort of MRTs. We compared our results with the previously published reference group of 150 atypical teratoid rhabdoid tumors. We showed that that CNS and extra-CNS MRTs for the most part clustered in distinct methylation groups and had heterogeneous molecular characteristics.
2017-12-12 | GSE107946 | GEO