Proteomics profiling predicts poor prognosis in patients with muscle invasive urothelial carcinoma

Abstract

Background: Despite platinum-based chemotherapy nearly 40% of patients ( pts) with localized muscle-invasive urothelial carcinoma (MIUC) will develop recurrent disease following surgical resection. The aim of this analysis was to identify whether differentially expressed protein biomarkers in tumor tissue may predict disease recurrence. Methods: Tissue samples were obtained from 57 pts who underwent curative surgical resection at "Universitary Hospital 12 Octubre" between 2006 and 2012. Medical records were reviewed for histology, stage, adjuvant chemotherapy, disease-free survival, and overall survival. We have analyzed the proteome applying a high-throughput proteomics approach to routinely archived formalin-fixed, paraffin-embedded tumor (FFPE) tissue. Protein extracts from FFPE samples were prepared in 2% SDS buffer and digested with trypsin. SDS was removed from digested lysates, and resulting peptides were analyzed in a Q-Exactive mass spectrometer. Protein abundance was calculated on the basis of the normalized spectral protein intensity (LFQ intensity) using MaxQuant. A prognostic protein signature was built. Data analysis was done using MeV, BRBArray Tools, R and Cytoscape software suites and Uniprot (http://www.uniprot.org/) and DAVID (http://david.abcc.ncifcrf.gov) webtools. Results: 57 pts with a median age of 65.9 years were included in the analysis. After a median follow up of 38 months, 26 (45%) pts relapsed. We were able to identify and quantify 1,456 proteins. Supervised analyses identified 6 proteins associated with higher risk of relapse (5 year DFS 70% vs. 20% [p < 0.001], HR 3.53, [95% CI 1.8 - 6.7]). By stage status at time of surgery the protein profile remained significant: stage III (5 year DFS 67% vs. 20%, [p = 0.05]) and stage IV (5 year DFS 70% vs.20%, [p = 0.01]) Conclusions: The discovery of proteins as biomarkers in bladder cancer is feasible. In this preliminary analysis we identified 6 proteins that can predict the outcome of patients with MIUC as prognostic factor. Additional validation analysis will be performed.