Abstract 1293: A high through approach to delineate protein complexes in adenocarcinoma tissues
Authors: Vickers Sofia Lage , Bizzotto Juan , Ortiz Emiliano , Paez Alejandra , Anselmino Nicolás , Brandani Javier , Abbate Mercedes , Cotignola Javier , Valacco Maria Pía , Vazquez Elba , Gueron Geraldine 
Published: August 2018

Although it is well known that prostate cancer (PCa) is a progressive disease involving multiple gene alterations, little is known at the proteome level. Most of the functional information of the cancer-associated genes relies in the proteome, an exceptionally complex biological system involving several proteins that function through dynamic protein-protein interactions and post-translational modifications. To identify potential PCa protein biomarkers, we carried out an in depth proteomic analysis (ESI-MS/MS) using human PCa and BPH tissue. Samples were obtained using phase-transfer surfactant-aided extraction/tryptic digestion of formalin-fixed and paraffin-embedded sections mounted on microscope slides. We identified 1331 and 1239 proteins in PCa and BPH tissue proteomes respectively. 71 proteins were present in at least 50% of PCa samples and not in BPH samples, while 122 proteins where present in at least 50% of BPH samples and not in carcinoma samples. In order to prioritize candidate markers for PCa, we compared the differential 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 our PCa proteomes. This filter resulted in the selection of 11 proteins. The list contained proteins that were previously studied in the context of prostate cancer progression, including SSBP1, GDF15, NDRG1, C4A & APOE, thus providing further confirmation for the robustness of our quantification method. Bioinformatics analysis (Oncomine) showed that the proteins aforementioned were significant up-regulated (fold change &gt;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 up-regulation for these proteins (P≤0.05).

To contextualize the proteomic data, we utilized protein complexes information from CORUM database. Utilizing biological complexes as a cluster vector, we calculate a Proteomics Signature Profile (PSP) for each sample based on the hit rates of its reported proteins, against the cluster vector. We identified 25 complexes differentially expressed between PCa and BPH. Among those, the top ranked cluster upregulated in PCa was EIF3 (p-value= 4,37x10-5), a protein complex that functions during the initiation phase of eukaryotic translation, composed of EIF3B, EIF3J and EIF3I.

We hereby report and offer a new set of biomarkers in addition to the existing diagnostic tests that could significantly improve sensitivity and specificity in PCa diagnosis.

Citation Format: Sofia Lage Vickers, Juan Bizzotto, Emiliano Ortiz, Alejandra Paez, Nicolás Anselmino, Javier Brandani, Mercedes Abbate, Javier Cotignola, Maria Pía Valacco, Elba Vazquez, Geraldine Gueron. A high through approach to delineate protein complexes in adenocarcinoma tissues [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1293.