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Mapping and Identification of the Urine Proteome of Prostate Cancer Patients by 2D PAGE/MS

Proteome analysis of the urine has shown that urine contains disease-specific information for a variety of urogenital system disorders, including prostate cancer (PCa). The aim of this study was to determine the protein components of urine from PCa patients. Urine from 8 patients with clinically and...

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Detalles Bibliográficos
Autores principales: Kiprijanovska, Sanja, Stavridis, Sotir, Stankov, Oliver, Komina, Selim, Petrusevska, Gordana, Polenakovic, Momir, Davalieva, Katarina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4158146/
https://www.ncbi.nlm.nih.gov/pubmed/25215235
http://dx.doi.org/10.1155/2014/594761
Descripción
Sumario:Proteome analysis of the urine has shown that urine contains disease-specific information for a variety of urogenital system disorders, including prostate cancer (PCa). The aim of this study was to determine the protein components of urine from PCa patients. Urine from 8 patients with clinically and histologically confirmed PCa was analyzed by conventional 2D PAGE. The MS identification of the most prominent 125 spots from the urine map revealed 45 distinct proteins. According to Gene Ontology, the identified proteins are involved in a variety of biological processes, majority of them are secreted (71%), and half of them are enzymes or transporters. Comparison with the normal urine proteome revealed 11 proteins distinctive for PCa. Using Ingenuity Pathways Analysis, we have found 3 proteins (E3 ubiquitin-protein ligase rififylin, tumor protein D52, and thymidine phosphorylase) associated with cellular growth and proliferation (p = 8.35 × 10(−4) − 3.41 × 10(−2)). The top network of functional associations between 11 proteins was Cell Death and Survival, Cell-To-Cell Signaling and Interaction, and System Development and Function (p = 10(−30)). In summary, we have created an initial proteomic map of PCa patient's urine. The results from this study provide some leads to understand the molecular bases of prostate cancer.