Affiliations: National Cancer Research Institute, Genoa, Italy | Department of Oncology, Biology and Genetics, University of Genoa, Italy | Institute Giannina Gaslini, Genoa, Italy | Department of Urology, University of Genoa, Italy
Note: [] Corresponding author: Cecilia Balbi, Tumor Urology Laboratory, National Cancer Research Institute, Largo Rosanna Benzi, 10, 16132 Genoa, Italy. Tel.: +39 010 5737510; Fax: +39 010 5737368; E-mail: [email protected].
Abstract: Introduction: Although several molecular markers for bladder cancer have been identified, at present little information on prognostic biomarkers is available in the literature. Prognostication of this tumor is largely based on clinicopathological characteristics. Our aim was to identify nuclear matrix (NM) proteins that might serve to better characterize the phenotype of the invasive bladder cancer and to investigate their diagnostic and prognostic roles. Methods: NM proteins expressed in normal (n=3) or non-tumoral (n=9) tissue specimens and muscle-invasive bladder cancer (n=21) specimens were analyzed by two dimensional (2D) gel electrophoresis. PDQuest image analysis software was used to generate a comparative NM proteome analysis. Selected spots were characterized by liquid chromatography coupled to tandem mass spectrometry and Western blot. Results: We detected over 800 protein spots in each 2D map and 43 spots were identified. 30 proteins were differentially expressed by bladder tumor cells; among these, 19 proteins were detected in bladder tumoral tissues but not in normal and non-tumoral tissues and seven proteins correlated with tumor stage. One protein (p54nrb) was strongly correlated with vascular invasions and appeared to be also significantly (P<0.0001) associated with a decreased probability of survival. Conclusion: Important alterations in NM proteins occur in muscle-invasive bladder cancer. The differentially expressed proteins include biomarkers potentially useful for disease diagnosis, progression and prognosis. Our findings beyond improving the understanding of the biology of bladder cancer, could help to stratify patients into different prognostic subgroups and to select those who might be better candidate to multimodal therapeutic approaches.
