A high throughput approach to delineate protein complexes enriched in Prostate Adenocarcinoma formalin-fixed paraffin-embedded tissue samples

BIZZOTTO, JUAN; LAGE-VICKERS, SOFIA; PIA VALACCO,; SANCHIS, PABLO; OSVALDO MAZZA; CARLOS SCORTICATI; SERGIO NEMIROVSKY; COTIGNOLA JAVIER; ELBA VAZQUEZ.; GERALDINE GUERON

Virtual

Simposio; 27th Annual PCF Scientific Retreat; 2020

Prostate Cancer Foundation

"Formalin-fixed, paraffin-embedded (FFPE) tissues are highly valuable resources for translational proteomics studies. 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 differential protein complexes associated with PCa we carried out an in-depth proteomics analysis. PCa and Benign Prostatic Hyperplasia (BPH) samples were obtained from the Hospital de Clínicas ?José de San Martín?, Buenos Aires, Argentina (with written informed consent and institutional review board approval). Proteins were obtained using phase-transfer surfactant-aided extraction/tryptic digestion of formalin-fixed, paraffin-embedded (FFPE) tissue sections mounted on microscope slides. Samples were subjected to mass spectrometry analysis (ESI-MS/MS). We found 109 proteins enriched in PCa compared with BPH samples We took a departure from conventional analysis approaches utilizing biological networks. We utilized CORUM, a database of human protein complexes formed by physically interacting proteins, to identify protein complexes differentially expressed in PCa and BPH tissues. These protein complexes (PC) may be regarded as units of biological function, hence suitable for contextualizing proteomics data. In this regard, using PC as a cluster vector, we calculated a Proteomics Signature Profile (PSP) for each sample based on the hit rates (H) of their reported proteins (H= number of proteins found in the sample / number of proteins in the cluster vector) , against the cluster vector. Our results show 5 differentially expressed protein complexes in PCa compared with BPH (P