A high-content screen for small-molecule regulators of epithelial cell-adhesion molecule (EpCAM) cleavage yields a robust inhibitor.

Epithelial cell-adhesion molecule (EpCAM) is a transmembrane protein that regulates cell cycle progression and differentiation and is overexpressed in many carcinomas. The EpCAM-induced mitogenic cascade is activated via regulated intramembrane proteolysis (RIP) of EpCAM by ADAM and -secretases, generating the signaling-active intracellular domain EpICD. Because of its expression pattern and molecular function, EpCAM is a valuable target in prognostic and therapeutic approaches for various carcinomas. So far, several immunotherapeutic strategies have targeted the extracellular domain of EpCAM. However, targeting the intracellular signaling cascade of EpCAM holds promise for specifically interfering with EpCAM’s proliferation-stimulating signaling cascade. Here, using a yellow fluorescence protein–tagged version of the C-terminal fragment of EpCAM, we established a high-content screening (HCS) of a small-molecule compound library (n 27,280) and characterized validated hits that target EpCAM signaling. In total, 128 potential inhibitors were initially identified, of which one compound with robust inhibitory effects on RIP of EpCAM was analyzed in greater detail. In summary, our study demonstrates that the development of an HCS for small-molecule inhibitors of the EpCAM signaling pathway is feasible. We propose that this approach may also be useful for identifying chemical compounds targeting other disorders involving membrane cleavage-dependent signaling pathways

Intelligent structuring and reducing of association rules with formal concept analysis

Colloque avec actes et comité de lecture. internationale.International audienceAssociation rules are used to investigate large databases. The analyst is usually confronted with large lists of such rules and has to find the most relevant ones for his purpose. Based on results about knowledge representation within the theoretical framework of Formal Concept Analysis, we present relatively small bases for association rules from which all rules can be deduced. We also provide algorithms for their calculation