Comparative proteomic profiling identifies potential prognostic factors for human clear cell renal cell carcinoma

The identification of markers for disease diagnostic, prognostic, or predictive purposes will have a great effect in improving patient management. Proteomic-based approaches for biomarker discovery are promising strategies used in cancer research. In this study, we performed quantitative proteomic analysis on four patients including clear cell renal cell carcinoma (ccRCC) and paired adjacent non-cancerous renal tissues using label-free quantitative proteomics and liquid chromatography-tandem mass spectrometry (LC-MS/MS) to identify differentially expressed proteins. Among 3,061 identified non-redundant proteins, we found that 210 proteins were differentially expressed (83 overexpressed and 127 underexpressed) in ccRCC tissue when compared with normal kidney tissues. Two most significantly dysregulated proteins (PCK1 and SNRPF) were chosen to be confirmed by western blotting. Pathway analysis of 210 differentially expressed proteins showed that dysregulated proteins are related to many cancer-related biological processes such as oxidative phosphorylation, glycolysis and amino acid synthetic pathways. Online survival analysis indicated the prognostic value of these dysregulated proteins. In conclusion, we identified some potential diagnostic biomarkers for ccRCC and an in-depth understanding of their involved biological pathways may help pave the way to discover new therapeutic strategies for ccRCC.