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Koelsche, Christian; Schrimpf, Daniel; Stichel, Damian; Sill, Martin; Sahm, Felix; Reuss, David E.; Blattner, Mirjam; Worst, Barbara; Heilig, Christoph E.; Beck, Katja; Horak, Peter; Kreutzfeldt, Simon; Paff, Elke; Stark, Sebastian; Johann, Pascal; Selt, Florian; Ecker, Jonas; Sturm, Dominik; Pajtler, Kristian W.; Reinhardt, Annekathrin; Wefers, Annika K.; Sievers, Philipp; Ebrahimi, Azadeh; Suwala, Abigail; [...]

Sarcoma classification by DNA methylation profiling

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  • Media type: E-Article
  • Title: Sarcoma classification by DNA methylation profiling
  • Contributor: Koelsche, Christian; Schrimpf, Daniel; Stichel, Damian; Sill, Martin; Sahm, Felix; Reuss, David E.; Blattner, Mirjam; Worst, Barbara; Heilig, Christoph E.; Beck, Katja; Horak, Peter; Kreutzfeldt, Simon; Paff, Elke; Stark, Sebastian; Johann, Pascal; Selt, Florian; Ecker, Jonas; Sturm, Dominik; Pajtler, Kristian W.; Reinhardt, Annekathrin; Wefers, Annika K.; Sievers, Philipp; Ebrahimi, Azadeh; Suwala, Abigail; [...]
  • imprint: Springer Science and Business Media LLC, 2021
  • Published in: Nature Communications
  • Language: English
  • DOI: 10.1038/s41467-020-20603-4
  • ISSN: 2041-1723
  • Keywords: General Physics and Astronomy ; General Biochemistry, Genetics and Molecular Biology ; General Chemistry ; Multidisciplinary
  • Origination:
  • Footnote:
  • Description: <jats:title>Abstract</jats:title><jats:p>Sarcomas are malignant soft tissue and bone tumours affecting adults, adolescents and children. They represent a morphologically heterogeneous class of tumours and some entities lack defining histopathological features. Therefore, the diagnosis of sarcomas is burdened with a high inter-observer variability and misclassification rate. Here, we demonstrate classification of soft tissue and bone tumours using a machine learning classifier algorithm based on array-generated DNA methylation data. This sarcoma classifier is trained using a dataset of 1077 methylation profiles from comprehensively pre-characterized cases comprising 62 tumour methylation classes constituting a broad range of soft tissue and bone sarcoma subtypes across the entire age spectrum. The performance is validated in a cohort of 428 sarcomatous tumours, of which 322 cases were classified by the sarcoma classifier. Our results demonstrate the potential of the DNA methylation-based sarcoma classification for research and future diagnostic applications.</jats:p>
  • Access State: Open Access