Expression profiling in soft tissue sarcomas with emphasis on synovial sarcoma, gastrointestinal stromal tumor, and leiomyosarcoma

Department of Pathology, Stanford University Medical Center, Stanford, CA 94305, USA.
Advances in anatomic pathology (Impact Factor: 3.23). 09/2010; 17(5):366-73. DOI: 10.1097/PAP.0b013e3181ec7428
Source: PubMed


Sarcomas are defined as malignant neoplasms derived from mesenchymal tissues. A variety of different molecular approaches, including gene expression profiling, have identified candidate biomarkers and insights into sarcoma biology that will aid in the diagnosis and treatment of these tumors. Many gene expression profiling findings have been translated into immunohistochemical tests for diagnostic, prognostic, or predictive purposes. This review details gene expression studies done in 3 sarcomas, synovial sarcoma, gastrointestinal stromal tumor, and leiomyosarcoma.

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    ABSTRACT: Background Undifferentiated Pleomorphic Sarcoma (UPS) and high-grade Leiomyosarcoma (LMS) are soft tissue tumors with an aggressive clinical behavior, frequently developing local recurrence and distant metastases. Despite several gene expression studies involving soft tissue sarcomas, the potential to identify molecular markers has been limited, mostly due to small sample size, in-group heterogeneity and absence of detailed clinical data. Materials and Methods Gene expression profiling was performed for 22 LMS and 22 UPS obtained from untreated patients. To assess the relevance of the gene signature, a meta-analysis was performed using five published studies. Four genes (BAD, MYOCD, SRF and SRC) selected from the gene signature, meta-analysis and functional in silico analysis were further validated by quantitative PCR. In addition, protein-protein interaction analysis was applied to validate the data. SRC protein immunolabeling was assessed in 38 UPS and 52 LMS. Results We identified 587 differentially expressed genes between LMS and UPS, of which 193 corroborated with other studies. Cluster analysis of the data failed to discriminate LMS from UPS, although it did reveal a distinct molecular profile for retroperitoneal LMS, which was characterized by the over-expression of smooth muscle-specific genes. Significantly higher levels of expression for BAD, SRC, SRF, and MYOCD were confirmed in LMS when compared with UPS. SRC was the most value discriminator to distinguish both sarcomas and presented the highest number of interaction in the in silico protein-protein analysis. SRC protein labeling showed high specificity and a positive predictive value therefore making it a candidate for use as a diagnostic marker in LMS. Conclusions Retroperitoneal LMS presented a unique gene signature. SRC is a putative diagnostic marker to differentiate LMS from UPS.
    PLoS ONE 07/2014; 9(7):e102281. DOI:10.1371/journal.pone.0102281 · 3.23 Impact Factor
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    ABSTRACT: The emergence of high-throughput molecular technologies has accelerated the discovery of novel diagnostic, prognostic and predictive molecular markers. Clinical implementation of these technologies is expected to transform the practice of surgical pathology. In soft tissue tumor pathology, accurate interpretation of comprehensive genomic data provides useful diagnostic and prognostic information, and informs therapeutic decisions. This article reviews recently developed molecular technologies, focusing on their application to the study of soft tissue tumors. Emphasis is made on practical issues relevant to the surgical pathologist. The concept of genomically-informed therapies is presented as an essential motivation to identify targetable molecular alterations in sarcoma. Copyright © 2015 Elsevier Inc. All rights reserved.
    09/2015; 8(3):525-37. DOI:10.1016/j.path.2015.06.001


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