Assessing proteolytic events in bioinformatic reanalysis of public secretome data from melanoma cell lines

Abstract

Autocrine and paracrine signals are of paramount importance in both normal and oncogenic events and the composition of such secreted molecular signals (i.e the secretome) designate the communication status of cells. In this context, the analysis of post-translational modifications in secreted proteins may unravel biological circuits regulated by irreversible modifications such as proteolytic processing. In the present study, we have performed a bioinformatic reanalysis of public proteomics data on melanoma cell line secretomes, changing database searching parameters to allow for the identification of proteolytic events generated by active proteases. Such approach enabled the identification of proteolytic signatures which suggested active proteases and whose expression profiles might be targeted in patient tissues or liquid biopsies, as well as their cleaved substrates. Although N-terminomics approaches continue to be the method of choice for the evaluation of proteolytic signaling events in complex samples, the simple approach performed in this work resulted in the gain of biological insights derived from shotgun proteomics data.