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Sarcoma classification by DNA methylation profiling

  • Christian Koelsche
  • , Daniel Schrimpf
  • , Damian Stichel
  • , Martin Sill
  • , Felix Sahm
  • , David E. Reuss
  • , Mirjam Blattner
  • , Barbara Worst
  • , Christoph E. Heilig
  • , Katja Beck
  • , Peter Horak
  • , Simon Kreutzfeldt
  • , Elke Paff
  • , Sebastian Stark
  • , Pascal Johann
  • , Florian Selt
  • , Jonas Ecker
  • , Dominik Sturm
  • , Kristian W. Pajtler
  • , Annekathrin Reinhardt
  • Annika K. Wefers, Philipp Sievers, Azadeh Ebrahimi, Abigail Suwala, Francisco Fernández-Klett, Belén Casalini, Andrey Korshunov, Volker Hovestadt, Felix K. F. Kommoss, Mark Kriegsmann, Matthias Schick, Melanie Bewerunge-Hudler, Till Milde, Olaf Witt, Andreas E. Kulozik, Marcel Kool, Laura Romero-Pérez, Thomas G. P. Grünewald, Thomas Kirchner, Wolfgang Wick, Michael Platten, Andreas Unterberg, Matthias Uhl, Amir Abdollahi, J. rgen Debus, Burkhard Lehner, Christian Thomas, Martin Hasselblatt, Werner Paulus, Christian Hartmann, Ori Staszewski, Marco Prinz, J. rgen Hench, Stephan Frank, Yvonne M. H. Versleijen-Jonkers, Marije E. Weidema, Thomas Mentzel, Klaus Griewank, Enrique de Álava, Juan D. az Martín, Miguel A. Idoate Gastearena, Kenneth Tou-En Chang, Sharon Yin Yee Low, Adrian Cuevas-Bourdier, Michel Mittelbronn, Martin Mynarek, Stefan Rutkowski, Ulrich Schüller, Viktor F. Mautner, Jens Schittenhelm, Jonathan Serrano, Matija Snuderl, Reinhard Büttner, Thomas Klingebiel, Rolf Buslei, Manfred Gessler, Pieter Wesseling, Winand N. M. Dinjens, Sebastian Brandner, Zane Jaunmuktane, Iben Lyskjær, Peter Schirmacher, Albrecht Stenzinger, Benedikt Brors, Hanno Glimm, Christoph Heining, Oscar M. Tirado, Miguel Sáinz-Jaspeado, Jaume Mora, Javier Alonso, Xavier Garcia del Muro, Sebastian Moran, Manel Esteller, Jamal K. Benhamida, Marc Ladanyi, Eva Wardelmann, Cristina Antonescu, Adrienne Flanagan, Uta Dirksen, Peter Hohenberger, Daniel Baumhoer, Wolfgang Hartmann, Christian Vokuhl, Uta Flucke, Iver Petersen, Gunhild Mechtersheimer, David Capper, David T. W. Jones, Stefan Fröhling, Stefan M. Pfister, Andreas von Deimling*
*Corresponding author for this work
  • German Cancer Research Center
  • Heidelberg University 
  • Hopp Children’s Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
  • Broad Institute
  • Harvard University
  • Ludwig Maximilian University of Munich
  • Heidelberg Institute of Radiation Oncology (HIRO), National Center for Radiation Research in Oncology (NCRO), Heidelberg, Germany
  • Heidelberg Ion-Beam Therapy Center (HIT), Heidelberg, Germany
  • University of Münster
  • Hannover Medical School
  • University of Freiburg
  • University of Basel
  • Radboud University Medical Center
  • Dermatopathology Bodensee, Friedrichshafen, Germany
  • University of Duisburg-Essen
  • Hospital Universitario Virgen del Rocio
  • University of Seville
  • University of Navarra
  • KK Women's and Children's Hospital
  • National Neuroscience Institute of Singapore
  • National Center of Pathology (NCP), Laboratoire National de Santé (LNS), Dudelange, Luxembourg
  • Luxembourg Center of Neuropathology (LCNP), Luxembourg, Luxembourg
  • University of Luxembourg
  • Luxembourg Institute of Health
  • University of Hamburg
  • University of Tübingen
  • New York University
  • University of Cologne
  • Department of Pediatric Hematology and Oncology, University Children’s Hospital, Frankfurt/Main, Germany
  • Institute of Pathology, Sozialstiftung Bamberg, Klinikum am Bruderwald, Bamberg, Germany
  • University of Würzburg
  • Princess Maxima Center for Pediatric Oncology, 3584 CS, Utrecht, The Netherlands
  • Amsterdam UMC - University of Amsterdam
  • Erasmus University Rotterdam
  • University College London
  • National Hospital for Neurology and Neurosurgery, London, United Kingdom
  • Technische Universität Dresden
  • German Cancer Consortium (DKTK), Dresden, Germany
  • Bellvitge Biomedical Research Institute
  • Department of Hematology and Oncology, Hospital Sant Joan de Déu, Barcelona, Spain
  • Instituto de Salud Carlos III
  • University of Barcelona
  • Josep Carreras Leukaemia Research Institute 
  • Centro de Investigacion Biomedica en Red Cancer (CIBERONC), Madrid, Spain
  • ICREA
  • Memorial Sloan-Kettering Cancer Center
  • Royal National Orthopaedic Hospital NHS Trust
  • Kiel University
  • Institute of Pathology, SRH Poliklinik Gera GmbH, Gera, Germany
  • Friedrich Schiller University Jena
  • Charité – Universitätsmedizin Berlin
  • National Center for Tumor Diseases Heidelberg
  • Heidelberg University Hospital
  • Hopp Children’s Cancer Center Heidelberg (KiTZ)
  • Brigham and Women’s Hospital
  • National Center for Radiation Research in Oncology (NCRO)
  • University Hospital Münster
  • Albert-Ludwigs-University Freiburg
  • Radboud University Nijmegen
  • Luxembourg Centre of Neuropathology (LCNP)
  • University Medical Center Hamburg-Eppendorf
  • University Hospital of Cologne
  • Princess Máxima Center for Pediatric Oncology
  • University of Amsterdam
  • Great Ormond St Hospital for Children NHS Trust
  • Department of Pediatric Onco-Hematology and Developmental Tumor Biology Laboratory, Hospital Sant Joan de Déu, Barcelona, Catalonia, Spain

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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.
Original languageEnglish
Article number498
JournalNature communications
Volume12
Issue number1
DOIs
Publication statusPublished - 1 Dec 2021

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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