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.
Highlights
Bone and soft tissue tumours are rare, with sarcomas, comprising approximately 100 different subtypes, representing no more than 2% of all cancers
DNA methylation profiles are regularly employed as part of the toolkit for classifying brain tumours [3,4], the success of which prompted a similar approach to classify sarcomas resulting in the recently published ‘Deutsches Krebsforschungszentrum (DKFZ) Sarcoma Classifier’ [5]
The performance of the DKFZ Classifier was evaluated against a total of 986 of our samples (935 tumour and 51 controls), of which 3 tumour samples failed the quality control employed in the DKFZ Classifier [5] and were excluded from further analysis (Figure 1A and supplementary material, Table S1)
Summary
Bone and soft tissue tumours are rare, with sarcomas, comprising approximately 100 different subtypes, representing no more than 2% of all cancers. DNA methylation profiles are regularly employed as part of the toolkit for classifying brain tumours [3,4], the success of which prompted a similar approach to classify sarcomas resulting in the recently published ‘Deutsches Krebsforschungszentrum (DKFZ) Sarcoma Classifier’ [5] This classifier was built using methylation profiles of 1,077 reference samples representing 54 bone and soft tissue tumour subtypes as well as common mimics of sarcoma and normal control tissues. Based on their initial validation cohort of 428 samples, Koelsche et al reported that 75% of cases obtained a successful diagnostic prediction based on their methylation profiles. The majority of predicted methylation classes (91%) were concordant with the original histological diagnosis, and 9% of predictions resulting in a revised histological diagnosis in favour of the predicted methylation class after histological review and confirmation by relevant molecular tests [5]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
