Towards an Animal Model of Ovarian Cancer: Cataloging Chicken Blood Proteins Using Combinatorial Peptide Ligand Libraries Coupled with Shotgun Proteomic Analysis for Translational Research

Abstract

Epithelial ovarian cancer is the most deadly gynecological cancer around the world, with high morbidity in industrialized countries. Early diagnosis is key in reducing its morbidity rate. Yet, robust biomarkers, diagnostics, and animal models are still limited for ovarian cancer. This calls for broader omics and systems science oriented diagnostics strategies. In this vein, the domestic chicken has been used as an ovarian cancer animal model, owing to its high rate of developing spontaneous epithelial ovarian tumors. Chicken blood has thus been considered a surrogate reservoir from which cancer biomarkers can be identified. However, the presence of highly abundant proteins in chicken blood has compromised the applicability of proteomics tools to study chicken blood owing to a lack of immunodepletion methods. Here, we demonstrate that a combinatorial peptide ligand library (CPLL) can efficiently remove highly abundant proteins from chicken blood samples, consequently doubling the number of identified proteins. Using an integrated CPLL-1DGE-LC-MSMS workflow, we identified a catalog of 264 unique proteins. Functional analyses further suggested that most proteins were coagulation and complement factors, blood transport and binding proteins, immune-and defense-related proteins, proteases, protease inhibitors, cellular enzymes, or cell structure and adhesion proteins. Semiquantitative spectral counting analysis identified 10 potential biomarkers from the present chicken ovarian cancer model. Additionally, many human homologs of chicken blood proteins we have identified have been independently suggested as diagnostic biomarkers for ovarian cancer, further triangulating our novel observations reported here. In conclusion, the CPLL-assisted proteomic workflow using the chicken ovarian cancer model provides a feasible platform for translational research to identify ovarian cancer biomarkers and understand ovarian cancer biology. To the best of our knowledge, we report here the most comprehensive survey of the chicken blood proteome to date.

The Seminal fluid proteome of the polyandrous Red junglefowl offers insights into the molecular basis of fertility, reproductive ageing and domestication

“…To examine the contribution of transparent fluid to the RJF SF proteome, we investigated overlap with existing proteomic data from domestic chicken blood plasma36. This revealed that 52.1% (137 out of 263) of identified blood plasma proteins were present in RJF SF (Table S1, Supporting Information).…”

“…The same analysis pipeline was used to reanalyze available raw MS/MS data from fractionated domestic chicken SF samples24. SF proteomes were compared to the chicken blood plasma proteome36, the exosome ExoCarta high quality protein marker dataset47, human blood plasma37, human sperm41, mouse epididymal sperm42 and human seminal plasma35 using orthology relationships in Ensembl Genes 84 (Galgal4). Composition of protein datasets were analyzed using the DAVID Bioinformatics Resource (6.7)8081, including statistical analyses of functional enrichment using the G. gallus genome as the background dataset for comparisons.…”

Quantitative Proteomic Profiling Reveals That Diverse Metabolic Pathways Are Influenced by Melatonin in an in Vivo Model of Ovarian Carcinoma

“…The knowledge of OC proteome into different conditions is essential for planning future treatment strategies. Although a considerable number of proteomic approaches in animal models with OC have recently been tested, ,, clinical applications remain lower than optimal. Thus we performed a comparative analysis between OC and OC treated with melatonin and reported an extensive catalogue of differentially expressed proteins that are affected by melatonin treatment.…”