title: Enhancing the Biological Relevance of Secretome-Based Proteomics by Linking Tumor Cell Proliferation and Protein Secretion.
abstract: Secretome profiling has become a methodology of choice for the identification of tumor biomarkers. We hypothesized that due to the dynamic nature of secretomes cellular perturbations could affect their composition but also change the global amount of protein secreted per cell. We confirmed our hypothesis by measuring the levels of secreted proteins taking into account the amount of proteome produced per cell. Then, we established a correlation between cell proliferation and protein secretion that explained the observed changes in global protein secretion. Next, we implemented a normalization correcting the statistical results of secretome studies by the global protein secretion of cells into a generalized linear model (GLM). The application of the normalization to two biological perturbations on tumor cells resulted in drastic changes in the list of statistically significant proteins. Furthermore, we found that known epithelial-to-mesenchymal transition (EMT) effectors were only statistically significant when the normalization was applied. Therefore, the normalization proposed here increases the sensitivity of statistical tests by increasing the number of true-positives. From an oncology perspective, the correlation between protein secretion and cellular proliferation suggests that slow-growing tumors could have high-protein secretion rates and consequently contribute strongly to tumor paracrine signaling.
authors.affiliation: Vall d'Hebron Institute of Oncology (VHIO), Universitat Autònoma de Barcelona (UAB) , Psg. Vall d'Hebron 119-129, 08035 Barcelona, Spain.|Statistics Department, University of Barcelona (UB) , Avda Diagonal 643, 08028 Barcelona, Spain.
authors.forename: Josep
authors.initials: J
authors.lastname: Gregori
authors.affiliation: Vall d'Hebron Institute of Oncology (VHIO), Universitat Autònoma de Barcelona (UAB) , Psg. Vall d'Hebron 119-129, 08035 Barcelona, Spain.
authors.forename: Olga
authors.initials: O
authors.lastname: Méndez
authors.affiliation: Vall d'Hebron Institute of Oncology (VHIO), Universitat Autònoma de Barcelona (UAB) , Psg. Vall d'Hebron 119-129, 08035 Barcelona, Spain.
authors.forename: Theodora
authors.initials: T
authors.lastname: Katsila
authors.affiliation: Vall d'Hebron Institute of Oncology (VHIO), Universitat Autònoma de Barcelona (UAB) , Psg. Vall d'Hebron 119-129, 08035 Barcelona, Spain.
authors.forename: Mireia
authors.initials: M
authors.lastname: Pujals
authors.affiliation: Vall d'Hebron Institute of Oncology (VHIO), Universitat Autònoma de Barcelona (UAB) , Psg. Vall d'Hebron 119-129, 08035 Barcelona, Spain.
authors.forename: Cándida
authors.initials: C
authors.lastname: Salvans
authors.affiliation: Vall d'Hebron Institute of Oncology (VHIO), Universitat Autònoma de Barcelona (UAB) , Psg. Vall d'Hebron 119-129, 08035 Barcelona, Spain.
authors.forename: Laura
authors.initials: L
authors.lastname: Villarreal
authors.affiliation: Vall d'Hebron Institute of Oncology (VHIO), Universitat Autònoma de Barcelona (UAB) , Psg. Vall d'Hebron 119-129, 08035 Barcelona, Spain.
authors.forename: Joaquin
authors.initials: J
authors.lastname: Arribas
authors.affiliation: Vall d'Hebron Institute of Oncology (VHIO), Universitat Autònoma de Barcelona (UAB) , Psg. Vall d'Hebron 119-129, 08035 Barcelona, Spain.
authors.forename: Josep
authors.initials: J
authors.lastname: Tabernero
authors.affiliation: Statistics Department, University of Barcelona (UB) , Avda Diagonal 643, 08028 Barcelona, Spain.|Statistics and Bioinformatics Unit, Vall d'Hebron Institut de Recerca , Psg. Vall d'Hebron 119-129, 08035 Barcelona, Spain.
authors.forename: Alex
authors.initials: A
authors.lastname: Sánchez
authors.affiliation: Vall d'Hebron Institute of Oncology (VHIO), Universitat Autònoma de Barcelona (UAB) , Psg. Vall d'Hebron 119-129, 08035 Barcelona, Spain.
authors.forename: Josep
authors.initials: J
authors.lastname: Villanueva
keywords: Biomarker Discovery; epidermal growth factor receptor (EGFR); epithelial to mesenchymal transition (EMT); generalized linear model (GLM); secretome; spectral count