Sarcoma classification by DNA methylation profiling
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
Abstract
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.
Details
Original language | English |
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Article number | 498 |
Journal | Nature communications |
Volume | 12 |
Issue number | 1 |
Publication status | Published - 1 Dec 2021 |
Peer-reviewed | Yes |
External IDs
PubMed | 33479225 |
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