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Emerging mesenchymal tumour types and biases in the era of ubiquitous sequencing.

Emily Anne ToweryDavid James Papke
Published in: Journal of clinical pathology (2023)
New tumour types are being described at increasing frequency, and most new tumour types are now identified via retrospective review of next-generation sequencing data. This contrasts with the traditional, morphology-based method of identifying new tumour types, and while the sequencing-based approach has accelerated progress in the field, it has also introduced novel and under-recognised biases. Here, we discuss tumour types identified based on morphology, including superficial CD34-positive fibroblastic tumour, pseudoendocrine sarcoma and cutaneous clear cell tumour with melanocytic differentiation and ACTIN::MITF fusion. We also describe tumour types identified primarily by next-generation sequencing, including epithelioid and spindle cell rhabdomyosarcoma, round cell neoplasms with EWSR1::PATZ1 fusion, cutaneous melanocytic tumour with CRTC1::TRIM11 fusion, clear cell tumour with melanocytic differentiation and MITF::CREM fusion and GLI1 -altered mesenchymal neoplasms, including nested glomoid neoplasm.
Keyphrases
  • stem cells
  • bone marrow
  • clear cell
  • machine learning
  • low grade
  • deep learning