DKFZ-B080_DMG
Ontology highlight
ABSTRACT:
PROVIDER: EGAO00000000661 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Organisation EGAO00000001381
| EGAO00000001381 | EGA
Project description:Organisation EGAO00000001147
| EGAO00000001147 | EGA
Project description:Organisation EGAO00000000298
| EGAO00000000298 | EGA
Project description:Diagnosing bone and soft tissue neoplasms remains challenging because of the large number of subtypes, many of which lack diagnostic biomarkers. DNA methylation profiles have proven to be a reliable basis for the classification of brain tumours and, following this success, a DNA methylation-based sarcoma classification tool from the Deutsches Krebsforschungszentrum (DKFZ) in Heidelberg has been developed. In this study, we assessed the performance of their classifier on DNA methylation profiles of an independent data set of 986 bone and soft tissue tumours and controls. We found that the 'DKFZ Sarcoma Classifier' was able to produce a diagnostic prediction for 55% of the 986 samples, with 83% of these predictions concordant with the histological diagnosis. On limiting the validation to the 820 cases with histological diagnoses for which the DKFZ Classifier was trained, 61% of cases received a prediction, and the histological diagnosis was concordant with the predicted methylation class in 88% of these cases, findings comparable to those reported in the DKFZ Classifier paper. The classifier performed best when diagnosing mesenchymal chondrosarcomas (CHSs, 88% sensitivity), chordomas (85% sensitivity), and fibrous dysplasia (83% sensitivity). Amongst the subtypes least often classified correctly were clear cell CHSs (14% sensitivity), malignant peripheral nerve sheath tumours (27% sensitivity), and pleomorphic liposarcomas (29% sensitivity). The classifier predictions resulted in revision of the histological diagnosis in six of our cases. We observed that, although a higher tumour purity resulted in a greater likelihood of a prediction being made, it did not correlate with classifier accuracy. Our results show that the DKFZ Classifier represents a powerful research tool for exploring the pathogenesis of sarcoma; with refinement, it has the potential to be a valuable diagnostic tool.
| S-EPMC8185366 | biostudies-literature
Project description:This experiment contains a subset of data from the BLUEPRINT Epigenome project ( http://www.blueprint-epigenome.eu ), which aims at producing a reference haemopoetic epigenomes for the research community. 29 samples of primary cells or cultured primary cells of different haemopoeitc lineages from cord blood are included in this experiment. This ArrayExpress record contains only meta-data. Raw data files have been archived at the European Genome-Phenome Archive (EGA, www.ebi.ac.uk/ega) by the consortium, with restricted access to protect sample donors' identity. The relevant accessions of EGA data sets is EGAD00001001165. Details on how to apply for data access via the BLUEPRINT data access committee are on the EGA data set pages. The mapping of samples to these EGA accessions can be found in the 'Sample Data Relationship Format' file of this ArrayExpress record. Information on individual samples and sequencing libraries can also be found on the BLUEPRINT data coordination centre (DCC) website: http://dcc.blueprint-epigenome.eu
2015-09-30 | E-MTAB-3819 | biostudies-arrayexpress
Project description:This experiment contains a subset of data from the BLUEPRINT Epigenome project ( http://www.blueprint-epigenome.eu ), which aims at producing a reference haemopoetic epigenomes for the research community. 4 samples of primary cells from tonsil with cell surface markes CD20med/CD38high in young individuals (3 to 10 years old) are included in this experiment. This ArrayExpress record contains only meta-data. Raw data files have been archived at the European Genome-Phenome Archive (EGA, www.ebi.ac.uk/ega) by the consortium, with restricted access to protect sample donors' identity. The relevant accessions of EGA data sets is EGAD00001001523. Details on how to apply for data access via the BLUEPRINT data access committee are on the EGA data set pages. The mapping of samples to these EGA accessions can be found in the 'Sample Data Relationship Format' file of this ArrayExpress record. Information on individual samples and sequencing libraries can also be found on the BLUEPRINT data coordination centre (DCC) website: http://dcc.blueprint-epigenome.eu
2016-05-12 | E-MTAB-4754 | biostudies-arrayexpress