In:
Nature Communications, Springer Science and Business Media LLC, Vol. 12, No. 1 ( 2021-01-21)
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.
Type of Medium:
Online Resource
ISSN:
2041-1723
DOI:
10.1038/s41467-020-20603-4
Language:
English
Publisher:
Springer Science and Business Media LLC
Publication Date:
2021
detail.hit.zdb_id:
2553671-0
Permalink