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Lyskjaer I, De Noon S, Tirabosco R, et al. DNA methylation-based profiling of bone and soft tissue tumours: a validation study of the 'DKFZ Sarcoma Classifier'. J Pathol Clin Res. 2021;7(4):350-360doi: 10.1002/cjp2.215.
Lyskjaer, I., De Noon, S., Tirabosco, R., Rocha, A. M., Lindsay, D., Amary, F., Ye, H., Schrimpf, D., Stichel, D., Sill, M., Koelsche, C., Pillay, N., Von Deimling, A., Beck, S., & Flanagan, A. M. (2021). DNA methylation-based profiling of bone and soft tissue tumours: a validation study of the 'DKFZ Sarcoma Classifier'. The journal of pathology. Clinical research, 7(4), 350-360. https://doi.org/10.1002/cjp2.215
Lyskjaer, Iben, et al. "DNA methylation-based profiling of bone and soft tissue tumours: a validation study of the 'DKFZ Sarcoma Classifier'." The journal of pathology. Clinical research vol. 7,4 (2021): 350-360. doi: https://doi.org/10.1002/cjp2.215
Lyskjaer I, De Noon S, Tirabosco R, Rocha AM, Lindsay D, Amary F, Ye H, Schrimpf D, Stichel D, Sill M, Koelsche C, Pillay N, Von Deimling A, Beck S, Flanagan AM. DNA methylation-based profiling of bone and soft tissue tumours: a validation study of the 'DKFZ Sarcoma Classifier'. J Pathol Clin Res. 2021 Jul;7(4):350-360. doi: 10.1002/cjp2.215. Epub 2021 May 05. PMID: 33949149; PMCID: PMC8185366.
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J Pathol Clin Res. 2021 Jul;7(4):350-360. doi: 10.1002/cjp2.215. Epub 2021 May 05.

DNA methylation-based profiling of bone and soft tissue tumours: a validation study of the 'DKFZ Sarcoma Classifier'.

The journal of pathology. Clinical research

Iben Lyskjaer, Solange De Noon, Roberto Tirabosco, Ana Maia Rocha, Daniel Lindsay, Fernanda Amary, Hongtao Ye, Daniel Schrimpf, Damian Stichel, Martin Sill, Christian Koelsche, Nischalan Pillay, Andreas Von Deimling, Stephan Beck, Adrienne M Flanagan

Affiliations

  1. Research Department of Pathology, University College London, UCL Cancer Institute, London, UK.
  2. Medical Genomics Research Group, University College London, UCL Cancer Institute, London, UK.
  3. Department of Histopathology, Royal National Orthopaedic Hospital, Stanmore, UK.
  4. Department of Neuropathology, University of Heidelberg, Heidelberg, Germany.
  5. Clinical Cooperation Unit Neuropathology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany.
  6. Hopp-Children's Cancer Center (KiTZ), Heidelberg, Germany.
  7. Division of Pediatric Neurooncology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany.
  8. Department of General Pathology, University of Heidelberg, Heidelberg, Germany.

PMID: 33949149 PMCID: PMC8185366 DOI: 10.1002/cjp2.215

Abstract

Diagnosing bone and soft tissue neoplasms remains challenging because of the large number of subtypes, many of which lack diagnostic biomarkers. DNA methylation profiles have proven to be a reliable basis for the classification of brain tumours and, following this success, a DNA methylation-based sarcoma classification tool from the Deutsches Krebsforschungszentrum (DKFZ) in Heidelberg has been developed. In this study, we assessed the performance of their classifier on DNA methylation profiles of an independent data set of 986 bone and soft tissue tumours and controls. We found that the 'DKFZ Sarcoma Classifier' was able to produce a diagnostic prediction for 55% of the 986 samples, with 83% of these predictions concordant with the histological diagnosis. On limiting the validation to the 820 cases with histological diagnoses for which the DKFZ Classifier was trained, 61% of cases received a prediction, and the histological diagnosis was concordant with the predicted methylation class in 88% of these cases, findings comparable to those reported in the DKFZ Classifier paper. The classifier performed best when diagnosing mesenchymal chondrosarcomas (CHSs, 88% sensitivity), chordomas (85% sensitivity), and fibrous dysplasia (83% sensitivity). Amongst the subtypes least often classified correctly were clear cell CHSs (14% sensitivity), malignant peripheral nerve sheath tumours (27% sensitivity), and pleomorphic liposarcomas (29% sensitivity). The classifier predictions resulted in revision of the histological diagnosis in six of our cases. We observed that, although a higher tumour purity resulted in a greater likelihood of a prediction being made, it did not correlate with classifier accuracy. Our results show that the DKFZ Classifier represents a powerful research tool for exploring the pathogenesis of sarcoma; with refinement, it has the potential to be a valuable diagnostic tool.

© 2021 The Authors. The Journal of Pathology: Clinical Research published by The Pathological Society of Great Britain and Ireland & John Wiley & Sons, Ltd.

Keywords: bone; classifier; methylation profiling; sarcoma; soft tissue

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