Mass Spectrometric/Bioinformatic Identification of a Protein Subset That Characterizes the Cellular Activity of Anticancer Peptides

The
preclinical study of the mechanism of action of anticancer
small molecules is challenging due to the complexity of cancer biology
and the fragmentary nature of available data. With the aim of identifying
a protein subset characterizing the cellular activity of anticancer
peptides, we used differential mass spectrometry to identify proteomic
changes induced by two peptides, LR and [d-Gln4]­LR, that inhibit cell growth and compared them with the changes
induced by a known drug, pemetrexed, targeting the same enzyme, thymidylate
synthase. The quantification of the proteome of an ovarian cancer
cell model treated with LR yielded a differentially expressed protein
data set with respect to untreated cells. This core set was expanded
by bioinformatic data interpretation, the biologically relevant proteins
were selected, and their differential expression was validated on
three cis-platinum sensitive and resistant ovarian cancer cell lines.
Via clustering of the protein network features, a broader view of
the peptides’ cellular activity was obtained. Differences from
the mechanism of action of pemetrexed were inferred from different
modulation of the selected proteins. The protein subset identification
represents a method of general applicability to characterize the cellular
activity of preclinical compounds and a tool for monitoring the cellular
activity of novel drug candidates.