Sarcoma classification by DNA methylation profiling.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
21 01 2021
21 01 2021
Historique:
received:
23
03
2020
accepted:
08
12
2020
entrez:
22
1
2021
pubmed:
23
1
2021
medline:
9
2
2021
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 33479225
doi: 10.1038/s41467-020-20603-4
pii: 10.1038/s41467-020-20603-4
pmc: PMC7819999
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
498Subventions
Organisme : NCI NIH HHS
ID : P30 CA008748
Pays : United States
Organisme : NCI NIH HHS
ID : P50 CA217694
Pays : United States
Organisme : Medical Research Council
Pays : United Kingdom
Organisme : Department of Health
ID : BRC399/NS/RB/101410
Pays : United Kingdom
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