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Sarcoma classification by DNA methylation profiling

Nature communications, 2021-01, Vol.12 (1), p.498-498, Article 498 [Peer Reviewed Journal]

The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2021 ;ISSN: 2041-1723 ;EISSN: 2041-1723 ;DOI: 10.1038/s41467-020-20603-4 ;PMID: 33479225

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Title:
Sarcoma classification by DNA methylation profiling
Author: Stichel, Damian ; Sill, Martin ; Sahm, Felix ; Reuss, David E ; Blattner, Mirjam ; Worst, Barbara ; Heilig, Christoph E ; Horak, Peter ; Kreutzfeldt, Simon ; Paff, Elke ; Stark, Sebastian ; Johann, Pascal ; Selt, Florian ; Ecker, Jonas ; Sturm, Dominik ; Pajtler, Kristian W ; Wefers, Annika K ; Ebrahimi, Azadeh ; Suwala, Abigail ; Fernández-Klett, Francisco ; Casalini, Belén ; Korshunov, Andrey ; Hovestadt, Volker ; Kommoss, Felix K F ; Kriegsmann, Mark ; Schick, Matthias ; Milde, Till ; Witt, Olaf ; Kulozik, Andreas E ; Kool, Marcel ; Romero-Pérez, Laura ; Grünewald, Thomas G P ; Kirchner, Thomas ; Platten, Michael ; Unterberg, Andreas ; Uhl, Matthias ; Abdollahi, Amir ; Debus, Jürgen ; Hasselblatt, Martin ; Paulus, Werner ; Hartmann, Christian ; Staszewski, Ori ; Prinz, Marco ; Hench, Jürgen ; Frank, Stephan ; Versleijen-Jonkers, Yvonne M H ; Weidema, Marije E ; Mentzel, Thomas ; Griewank, Klaus ; de Álava, Enrique ; Martín, Juan Díaz ; Gastearena, Miguel A Idoate ; Chang, Kenneth Tou-En ; Low, Sharon Yin Yee ; Cuevas-Bourdier, Adrian ; Mittelbronn, Michel ; Mynarek, Martin ; Rutkowski, Stefan ; Schüller, Ulrich ; Mautner, Viktor F ; Schittenhelm, Jens ; Serrano, Jonathan ; Snuderl, Matija ; Büttner, Reinhard ; Klingebiel, Thomas ; Buslei, Rolf ; Gessler, Manfred ; Wesseling, Pieter ; Dinjens, Winand N M ; Brandner, Sebastian ; Jaunmuktane, Zane ; Lyskjær, Iben ; Schirmacher, Peter ; Stenzinger, Albrecht ; Brors, Benedikt ; Glimm, Hanno ; Heining, Christoph ; Tirado, Oscar M ; Sáinz-Jaspeado, Miguel ; Mora, Jaume ; Alonso, Javier ; Del Muro, Xavier Garcia ; Moran, Sebastian ; Esteller, Manel ; Ladanyi, Marc ; Wardelmann, Eva ; Antonescu, Cristina ; Flanagan, Adrienne ; Dirksen, Uta ; Hohenberger, Peter ; Baumhoer, Daniel ; Hartmann, Wolfgang ; Flucke, Uta ; Petersen, Iver ; Mechtersheimer, Gunhild ; Capper, David ; Jones, David T W ; Fröhling, Stefan ; Pfister, Stefan M ; von Deimling, Andreas
Subjects: Adolescents ; Algorithms ; Bone cancer ; Bone Neoplasms - classification ; Bone Neoplasms - diagnosis ; Bone Neoplasms - genetics ; Bone tumors ; Children ; Classification ; Classifiers ; Cohort Studies ; Deoxyribonucleic acid ; Diagnostic software ; Diagnostic systems ; DNA ; DNA Copy Number Variations - genetics ; DNA fingerprinting ; DNA Methylation ; Humans ; Internet ; Learning algorithms ; Machine Learning ; Reproducibility of Results ; Sarcoma ; Sarcoma - classification ; Sarcoma - diagnosis ; Sarcoma - genetics ; Sensitivity and Specificity ; Soft Tissue Neoplasms - classification ; Soft Tissue Neoplasms - diagnosis ; Soft Tissue Neoplasms - genetics ; Soft tissues ; Tissues ; Tumors
Is Part Of: Nature communications, 2021-01, Vol.12 (1), p.498-498, Article 498
Description: 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.
Publisher: England: Nature Publishing Group
Language: English
Identifier: ISSN: 2041-1723
EISSN: 2041-1723
DOI: 10.1038/s41467-020-20603-4
PMID: 33479225
Source: Open Access: PubMed Central
DOAJ Directory of Open Access Journals
AUTh Library subscriptions: ProQuest Central
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Sarcoma classification by DNA methylation profiling

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