A combination of solid-state NMR and MD simulations reveals the binding mode of a rhomboid protease inhibitor.

Intramembrane proteolysis plays a fundamental role in many biological and pathological processes. Intramembrane proteases thus represent promising pharmacological targets, but few selective inhibitors have been identified. This is in contrast to their soluble counterparts, which are inhibited by many common drugs, and is in part explained by the inherent difficulty to characterize the binding of drug-like molecules to membrane proteins at atomic resolution. Here, we investigated the binding of two different inhibitors to the bacterial rhomboid protease GlpG, an intramembrane protease characterized by a Ser-His catalytic dyad, using solid-state NMR spectroscopy. H/D exchange of deuterated GlpG can reveal the binding position while chemical shift perturbations additionally indicate the allosteric effects of ligand binding. Finally, we determined the exact binding mode of a rhomboid protease-inhibitor using a combination of solid-state NMR and molecular dynamics simulations. We believe this approach can be widely adopted to study the structure and binding of other poorly characterized membrane protein-ligand complexes in a native-like environment and under physiological conditions.

High Ep-CAM expression is associated with poor prognosis in node-positive breast cancer.

Previous studies in small series of patients with invasive breast cancer suggested a prognostic value of Ep-CAM overexpression in primary tumor tissue. To corroborate these findings, we performed a retrospective analysis of Ep-CAM expression using a tissue microarray containing tissue specimens from a large patient set. Ep-CAM expression was evaluated by immunohistochemistry in breast cancer tissue from 1715 patients with documented raw survival data. High level Ep-CAM expression (overexpression) was found in 41.7% of tumor samples, low level expression was found in 48.0% and no expression in 10.3% of tumor samples. Ep-CAM expression predicted poor overall survival in this patient cohort (p < 0.0001). Overall survival decreased significantly with increasing Ep-CAM expression. However, in this patient sample Ep-CAM expression was not an independent prognostic marker by multivariate analysis. Subgroup analysis revealed that Ep-CAM expression was a prognostic marker in node-positive (p < 0.0001) but not in node-negative (p = 0.58) breast cancer patients. Intriguingly, Ep-CAM expression was predictive for a dismal prognosis in patients receiving adjuvant cytotoxic (p = 0.03) or hormonal therapy (p < 0.0001) but not in untreated patients (p = 0.41). In summary, this study provides strong evidence that expression of Ep-CAM is a powerful marker of poor prognosis in node-positive invasive breast carcinoma and a potential predictive marker of sensitivity to adjuvant hormonal and/or cytotoxic treatment modalities.