Abstract

Abstract Current approaches in proteomics techniques and MS systems have revived the quest for novel biomarkers in prostate cancer (PCa) boosting the molecular characterization of the disease. To reveal fundamental differences between benign and malignant growth of prostate cells, we combined a new protein extraction procedure that disrupts the crosslinked proteins from the previously formaldehyde-fixed, paraffin-embedded tissue samples with in-depth proteomic analysis (ESI-MS/MS). Human PCa and benign prostatic hyperplasia (BPH) tissue samples were obtained using phase-transfer surfactant-aided extraction/tryptic digestion of formalin-fixed and paraffin-embedded sections mounted on microscope slides. Data analysis was based on label-free spectral counting, identifying with a minimum of two peptides, 1331 and 1239 proteins in PCa and BPH tissue proteomes, respectively. 71 proteins were exclusively present in PCa samples, while 122 proteins where exclusively present in BPH samples. In order to prioritize candidate markers for PCa, we compared protein expression based on normalized spectral counts between tissue samples. We set as cut-offs proteins that were found with a minimum of three peptides within the PCa and BPH proteomes. This filter resulted in the selection of two clusters of 11 and 16 proteins, respectively. The data sets highlighted distinct proteins that were previously studied in the context of prostate cancer progression, including SSBP1, GDF15, NDRG1, C4A, and APOE for PCa and DUSP3, MME, SRI, and DSG1 for BPH, thus providing further confirmation for the robustness of our quantification method. We next subjected our candidate list to bioinformatics analysis (Oncomine). Accordingly, the 5 proteins mentioned for PCa were significantly upregulated (fold change >1.5, P≤0.05) in prostate adenocarcinoma vs. normal prostate gland. Whole-exome analysis (cBioportal) revealed amplification as the most frequent genetic alteration and RNASeq data also confirmed a significant upregulation for these proteins (P≤0.05). Strikingly, proteins associated with BPH were significantly downregulated (fold change >1.5, P≤0.05) across the same comparison and RNA-seq data also confirmed a significant downregulation for these proteins (P≤0.05). This report showcases significant and extensive differences in protein expression patterns between BPH and prostate carcinoma. Proteome analysis of prostate tissues should help to disclose the molecular mechanisms underlying prostate malignant growth, resulting in new sets of biomarkers for diagnostic, prognostic, and therapeutic use. Citation Format: Sofia Lage Vickers, Juan Antonio Bizzotto, Alejandra Paez, Javier Cotignola, Carlos Scorticati, Osvaldo Mazza, Pia Valacco, Geraldine Gueron, Elba Vazquez. Integrative prostate cancer tissue proteomics dissects clear and distinct proteomes for human prostate cancer and benign prostatic hyperplasia [abstract]. In: Proceedings of the AACR Special Conference: Prostate Cancer: Advances in Basic, Translational, and Clinical Research; 2017 Dec 2-5; Orlando, Florida. Philadelphia (PA): AACR; Cancer Res 2018;78(16 Suppl):Abstract nr A058.

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