Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany.
Clinical Cooperation Unit Neuropathology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany.
Nat Commun. 2021 Jan 21;12(1):498. doi: 10.1038/s41467-020-20603-4.
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.
肉瘤是一种影响成人、青少年和儿童的恶性软组织和骨肿瘤。它们代表了一类形态上异质性的肿瘤，有些肿瘤缺乏明确的组织病理学特征。因此，肉瘤的诊断存在观察者间变异性大、分类错误率高的问题。在这里，我们使用基于阵列生成的 DNA 甲基化数据的机器学习分类器算法来对软组织和骨肿瘤进行分类。该肉瘤分类器是使用一个包含 1077 个甲基化谱的数据集进行训练的，这些数据集来自经过全面特征分析的病例，其中包括 62 个肿瘤甲基化类别，涵盖了整个年龄谱中广泛的软组织和骨肉瘤亚型。该分类器在一个包含 428 个肉瘤性肿瘤的队列中进行了验证，其中 322 个病例被肉瘤分类器进行了分类。我们的结果表明，基于 DNA 甲基化的肉瘤分类具有用于研究和未来诊断应用的潜力。
