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Sarcoma Classification by DNA Methylation Profiling
Christian Kölsche
Daniel Schrimpf
Damian Stichel
Martin Sill
Ori Staszewski
Marco Prinz
Andreas von Deimling
出版
Universität
, 2021
URL
http://books.google.com.hk/books?id=G7CHzgEACAAJ&hl=&source=gbs_api
註釋
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