Malignant fibrous histiocytoma and fibrosarcoma of bone: A re-assessment in the light of currently employed morphological, immunohistochemical and molecular approaches

摘要

Malignant fibrous histiocytoma (MFH) and fibrosarcoma (FS) of bone are rare malignant tumours and contentious entities. Sixty seven cases labelled as bone MFH (57) and bone FS (10) were retrieved from five bone tumour referral centres and reviewed to determine whether recent advances allowed for reclassification and identification of histological subgroups with distinct clinical behaviour. A panel of immunostains was applied: smooth muscle actin, desmin, h-caldesmon, cytokeratin AE1-AE3, CD31, CD34, CD68, CD163, CD45, S100 and epithelialmembrane antigen. Additional fluorescence in situ hybridisation and immunohistochemistry were performed whenever appropriate. All cases were reviewed by six bone and soft tissue pathologists and a consensus was reached. Follow-up for 43 patients (median 42 months, range 6-223 months) was available. Initial histological diagnosis was reformulated in 18 cases (26.8%). Seven cases were reclassified as leiomyosarcoma, six as osteosarcoma, three as myxofibrosarcoma and one each as embryonal rhabdomyosarcoma and interdigitating dendritic cell sarcoma. One case showed a peculiar biphasic phenotype with epithelioid nests and myofibroblastic spindle cells. Among the remaining 48 cases, which met the WHO criteria for bone FS and bone MFH, we identified five subgroups. Seven cases were reclassified as undifferentiated pleomorphic sarcoma (UPS) and 11 as UPS with incomplete myogenic differentiation due to positivity for at least one myogenic marker. Six were reclassified as spindle cell sarcoma not otherwise specified. Among the remaining 24 cases, we identified a further two recurrent morphologic patterns: eight cases demonstrated a myoepithelioma-like phenotype and 16 cases a myofibroblastic phenotype. One of the myoepithelioma-like cases harboured a EWSR1-NFATC2 fusion. It appears that bone MFH and bone FS represent at best exclusion diagnoses.