Related Experiment Videos
Synovial sarcoma (SS): new perspectives supported by modern technology
A Llombart-Bosch1, J A Lopez-Guerrero, A Peydro-Olaya
1Department of Pathology, Medical School, University of Valencia, Spain.
Arkhiv Patologii
|September 2, 2004
Summary
Synovial sarcoma (SS) is a complex tumor with diverse histological patterns. Molecular analysis, particularly the SYT-SSX fusion gene, aids diagnosis and predicts patient outcomes.
Area of Science:
- Oncology
- Pathology
- Molecular Biology
Background:
- Synovial sarcoma (SS) is a rare and poorly understood soft tissue sarcoma.
- Histological classification includes biphasic and monophasic subtypes, with several variants described.
- Tumors often exhibit microcalcifications and squamous metaplasia.
Purpose of the Study:
- To analyze the structural, biological, and molecular pathology of synovial sarcoma.
- To correlate molecular findings with clinical outcomes.
- To highlight diagnostic markers for SS.
Main Methods:
- Review of 256 synovial sarcoma cases.
- Histopathological and ultrastructural analysis.
- Immunohistochemistry for epithelial markers (EMA, cytokeratin) and vimentin.
- Molecular analysis of chromosomal translocation t(X;18)(p11.2;q11.2) and SYT-SSX gene fusions.
- Nude-mice xenografts and in vitro cell line studies.
Main Results:
- SS displays multiphenotypic histology with epithelial and spindle cell components.
- Immunohistochemistry is crucial for diagnosis, with EMA and cytokeratin positivity in epithelial cells and vimentin in spindle cells.
- The specific chromosomal translocation t(X;18)(p11.2;q11.2) leading to SYT-SSX gene fusions is a hallmark of SS.
- SYT-SSX1 fusion is associated with poor prognosis, while SYT-SSX2 fusion indicates a better survival rate.
Conclusions:
- Synovial sarcoma exhibits significant histological and molecular heterogeneity.
- Molecular diagnostics, specifically identifying SYT-SSX fusion variants, are vital for accurate diagnosis and prognostic assessment.
- Understanding the molecular subtypes of SS can guide clinical management and improve patient outcomes.