Enhancing the Biological Relevance of Secretome-Based Proteomics by Linking Tumor Cell Proliferation and Protein Secretion

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.