Renal cell carcinoma (RCC), the most common neoplasm affecting the adult kidney, is characterised by heterogeneity of histological subtypes, drug resistance, and absence of molecular markers. Two-dimensional difference gel electrophoresis (2-D DIGE) technology in combination with mass spectrometry (MS) was applied to detect differentially expressed proteins in 20 pairs of RCC tissues and matched adjacent normal kidney cortex (ANK), in order to search for RCC markers. After gel analysis by DeCyder 6.5 and EDA software, differentially expressed protein spots were excised from Deep Purple stained preparative 2DE gel. A total of 100 proteins were identified by MS out of 2500 spots, 23 and 77 of these were, respectively, over- and down-expressed in RCC. The Principal Component Analysis applied to gels and protein spots exactly separated the two sample classes in two groups: RCC and ANK. Moreover, some spots, including ANXA2, PPIA, FABP7 and LEG1, resulted highly differential. The DIGE data were also confirmed by immunoblotting analysis for these proteins. In conclusion, we suggest that applying 2-D DIGE to RCC may provide the basis for a better molecular characterization and for the discovery of candidate biomarkers.
Proteomic analysis in clear cell renal cell carcinoma : identification of differentially expressed protein by 2-D DIGE / F. Raimondo, C. Salemi, C. Chinello, D. Fumagalli, L. Morosi, F. Rocco, S. Ferrero, R. Perego, C. Bianchi, C. Sarto, M. Pitto, P. Brambilla, F. Magni. - In: MOLECULAR BIOSYSTEMS. - ISSN 1742-206X. - 8:4(2012), pp. 1040-1051. [10.1039/C2MB05390J]
Proteomic analysis in clear cell renal cell carcinoma : identification of differentially expressed protein by 2-D DIGE
F. Rocco;S. Ferrero;
2012
Abstract
Renal cell carcinoma (RCC), the most common neoplasm affecting the adult kidney, is characterised by heterogeneity of histological subtypes, drug resistance, and absence of molecular markers. Two-dimensional difference gel electrophoresis (2-D DIGE) technology in combination with mass spectrometry (MS) was applied to detect differentially expressed proteins in 20 pairs of RCC tissues and matched adjacent normal kidney cortex (ANK), in order to search for RCC markers. After gel analysis by DeCyder 6.5 and EDA software, differentially expressed protein spots were excised from Deep Purple stained preparative 2DE gel. A total of 100 proteins were identified by MS out of 2500 spots, 23 and 77 of these were, respectively, over- and down-expressed in RCC. The Principal Component Analysis applied to gels and protein spots exactly separated the two sample classes in two groups: RCC and ANK. Moreover, some spots, including ANXA2, PPIA, FABP7 and LEG1, resulted highly differential. The DIGE data were also confirmed by immunoblotting analysis for these proteins. In conclusion, we suggest that applying 2-D DIGE to RCC may provide the basis for a better molecular characterization and for the discovery of candidate biomarkers.Pubblicazioni consigliate
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