Sophie A. Lelièvre

ErbB2, but not ErbB1, reinitiates proliferation and induces luminal repopulation in epithelial acini

Both ErbB1 and ErbB2 are overexpressed or amplified in breast tumours. To examine the effects of activating ErbB receptors in a context that mimics polarized epithelial cells in vivo, we activated ErbB1 and ErbB2 homodimers in preformed, growth-arrested mammary acini cultured in three-dimensional basement membrane gels. Activation of ErbB2, but not that of ErbB1, led to a reinitiation of cell proliferation and altered the properties of mammary acinar structures. These altered structures share several properties with early-stage tumours, including a loss of proliferative suppression, an absence of lumen, retention of the basement membrane and a lack of invasive properties. ErbB2 activation also disrupted tight junctions and the cell polarity of polarized epithelia, whereas ErbB1 activation did not have any effect. Our results indicate that ErbB receptors differ in their ability to induce early stages of mammary carcinogenesis in vitro and this three-dimensional model system can reveal biological activities of oncogenes that cannot be examined in vitro in standard transformation assays.

Communication Between the Cell Membrane and the Nucleus: Role of Protein Compartmentalization

Understanding how the information is conveyed from outside to inside the cell is a critical challenge for all biologists involved in signal transduction. The flow of information initiated by cell‐cell and cell‐extracellular matrix contacts is mediated by the formation of adhesion complexes involving multiple proteins. Inside adhesion complexes, connective membrane skeleton (CMS) proteins are signal transducers that bind to adhesion molecules, organize the cytoskeleton, and initiate biochemical cascades. Adhesion complex‐mediated signal transduction ultimately directs the formation of supramolecular structures in the cell nucleus, as illustrated by the establishment of multi complexes of DNA‐bound transcription factors, and the redistribution of nuclear structural proteins to form nuclear subdomains. Recently, several CMS proteins have been observed to travel to the cell nucleus, suggesting a distinctive role for these proteins in signal transduction. This review focuses on the nuclear translocation of structural signal transducers of the membrane skeleton and also extends our analysis to possible translocation of resident nuclear proteins to the membrane skeleton. This leads us to envision the communication between spatially distant cellular compartments (i.e., membrane skeleton and cell nucleus) as a bidirectional flow of information (a dynamic reciprocity) based on subtle multilevel structural and biochemical equilibria. At one level, it is mediated by the interaction between structural signal transducers and their binding partners, at another level it may be mediated by the balance and integration of signal transducers in different cellular compartments. J. Cell. Biochem. Suppls. 30/31:250–263, 1998.

Cell phenotype classification based on 3D cell image analysis

Summary form only given. The accuracy of the histological classification of cells plays a determining role in disease diagnosis and treatment. Recent studies have shown that the distribution of chromatin-associated proteins reflects alterations in cell phenotype. Using 3D fluorescence images of cultured human breast epithelial cells with multiple known phenotypes, we have developed an automated method to classify the phenotype of epithelial cells based on their nuclear protein distribution. Features which describe the distribution of specific nuclear proteins are first measured, on a per nucleus basis, by our local bright feature (LBF) analysis technique. Features from thousands of nuclei with multiple, known phenotypes were then grouped by a novel voting-based clustering method into a number of clusters of similar pattern. This allows us to establish the statistical link between clusters and the phenotypes of the cells. Finally, we used this statistical link to predict the probable phenotype of individual or groups of nuclei. The results show that the combined use of 3D confocal imaging, image feature analysis, and clustering analysis provides an efficient way to predict the phenotype of epithelial cells based on the nuclear distribution of chromatin-associated proteins.