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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/117390
Title: 
Gene expression profiling in leiomyosarcomas and undifferentiated pleomorphic sarcomas: SRC as a new diagnostic marker
Author(s): 
Institution: 
  • AC Camargo Canc Ctr
  • Universidade de São Paulo (USP)
  • Universidade Estadual Paulista (UNESP)
  • Barretos Canc Hosp
ISSN: 
1932-6203
Sponsorship: 
  • Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
  • Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
  • Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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.
Issue Date: 
16-Jul-2014
Citation: 
Plos One. San Francisco: Public Library Science, v. 9, n. 7, 8 p., 2014.
Time Duration: 
8
Publisher: 
Public Library Science
Source: 
http://dx.doi.org/10.1371/journal.pone.0102281
URI: 
Access Rights: 
Acesso aberto
Type: 
outro
Source:
http://repositorio.unesp.br/handle/11449/117390
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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