病理
周围神经鞘恶性肿瘤
肉瘤
滑膜肉瘤
软组织肉瘤
DNA甲基化
平滑肌肉瘤
生物
免疫组织化学
医学
癌症研究
生物化学
基因表达
基因
作者
Markku Miettinen,Zied Abdullaev,Rust Turakulov,Martha Quezado,Alejandro Contreras,Claudia Curcio,Janusz Ryś,Małgorzata Chłopek,Jerzy Lasota,Kenneth Aldape
标识
DOI:10.1097/pas.0000000000002138
摘要
Diagnostic classification of soft tissue tumors is based on histology, immunohistochemistry, genetic findings, and radiologic and clinical correlations. Recently, a sarcoma DNA methylation classifier was developed, covering 62 soft tissue and bone tumor entities. The classifier is based on large-scale analysis of methylation sites across the genome. It includes DNA copy number analysis and determines O 6 methylguanine DNA methyl-transferase methylation status. In this study, we evaluated 619 well-studied soft tissue and bone tumors with the sarcoma classifier. Problem cases and typical examples of different entities were included. The classifier had high sensitivity and specificity for fusion sarcomas: Ewing, synovial, CIC -rearranged, and BCOR -rearranged. It also performed well for leiomyosarcoma, malignant peripheral nerve sheath tumors (MPNST), and malignant vascular tumors. There was low sensitivity for diagnoses of desmoid fibromatosis, neurofibroma, and schwannoma. Low specificity of matches was observed for angiomatoid fibrous histiocytoma, inflammatory myofibroblastic tumor, Langerhans histiocytosis, schwannoma, undifferentiated sarcoma, and well-differentiated/dedifferentiated liposarcoma. Diagnosis of lipomatous tumors was greatly assisted by the detection of MDM2 amplification and RB1 loss in the copy plot. The classifier helped to establish diagnoses for KIT-negative gastrointestinal stromal tumors, MPNSTs with unusual immunophenotypes, and undifferentiated melanomas. O 6 methylguanine DNA methyl-transferase methylation was infrequent and most common in melanomas (35%), MPNSTs (11%), and undifferentiated sarcomas (11%). The Sarcoma Methylation Classifier will likely evolve with the addition of new entities and refinement of the present methylation classes. The classifier may also help to define new entities and give new insight into the interrelationships of sarcomas.
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