Artículo
Sarcoma classification by DNA methylation profiling
Autor/es | Koelsche, Christian
Schrimpf, Daniel Stichel, Damian Sill, Martin Sahm, Felix Reuss, David E. Romero Pérez, Laura Álava Casado, Enrique de Idoate Gastearena, Miguel Ángel Hohenberger, Peter |
Departamento | Universidad de Sevilla. Departamento de Citología e Histología Normal y Patológica |
Fecha de publicación | 2021 |
Fecha de depósito | 2022-09-19 |
Publicado en |
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Resumen | 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. ... 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. |
Cita | Koelsche, C., Schrimpf, D., Stichel, D., Sill, M., Sahm, F., Reuss, D.E.,...,Hohenberger, P. (2021). Sarcoma classification by DNA methylation profiling. Nature Communications, 21 (1) |
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