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Nature Research, Nature Communications, 1(12), 2021

DOI: 10.1038/s41467-020-20603-4

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Sarcoma classification by DNA methylation profiling

Journal article published in 2021 by Christian Koelsche ORCID, Daniel Schrimpf, Damian Stichel, Martin Sill, Felix Sahm ORCID, David E. Reuss, Mirjam Blattner, Barbara Worst, Christoph E. Heilig ORCID, Katja Beck, Peter Horak ORCID, Simon Kreutzfeldt ORCID, Elke Paff, Sebastian Stark, Pascal Johann and other authors.
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

AbstractSarcomas 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.