Pascale Jackers

DECREASED EXPRESSION OF GALECTIN-3 IS ASSOCIATED WITH PROGRESSION OF HUMAN BREAST CANCER

Galectin‐3, a member of the β‐galactoside‐binding lectin family, is involved in several biological events including binding to the basement membrane glycoprotein laminin. Although the exact role of galectin‐3 during the interactions between cells and laminin is not yet known, it has recently been observed that its expression is down‐regulated at both the protein and the mRNA level in colon cancer tissues in correlation with progression of the disease. This study investigated the possibility that breast cancer cells might also exhibit decreased galectin‐3 expression in association with their aggressiveness. The expression of galectin‐3 was examined by immunoperoxidase staining, using a polyclonal antibody raised against recombinant galectin‐3, in a collection of 98 human breast lesions including 12 fibroadenomas, 15 fibrocystic disease lesions, 22 in situ carcinomas, and 49 infiltrating ductal carcinomas, 19 of which had positive axillary lymph nodes. Normal breast tissue adjacent to the lesions was present in 59 biopsies. Normal breast tissue expressed high levels (3+) of galectin‐3. High expression (2+ to 3+) was also found in most benign lesions examined. The expression of galectin‐3 was significantly decreased in in situ carcinoma and this down‐regulation was more pronounced in invasive ductal carcinoma, particularly when associated with infiltration of axillary lymph nodes. These data constitute the first observation that galectin‐3 is down‐regulated in breast cancer and suggest the decreased expression of this galactoside‐binding lectin is associated with the acquisition of the invasive and metastatic phenotype.

Differential expression of Galectin‐1 and Galectin‐3 during first trimester human embryogenesis

Development of complex organisms requires specific temporospatial differentiation and expression of the correct phenotype through activation of a variety of genes. Galectins are mammalian lectins able to interact with various extracellular matrix glycoconjugates and have been implicated in several biological events including cell attachment, differentiation, apoptosis, embryogenesis, and cancer invasion and metastasis. In this study, we have examined the expression of galectin‐1 and galectin‐3 during human first trimester embryogenesis using immunohistochemistry and Western blotting. Variable amounts of galectin‐1 and galectin‐3 were detected in all tissue protein extracts. Galectin‐1 expression was demonstrated in the connective tissue and derived tissues such as smooth and striated muscle cells, and in some epithelia, such as in the basal layers of the skin after 14 weeks and in the epithelial cells of the gonads. Galectin‐3 was detected mainly in epithelia, such as the skin, epithelial lining of the digestive and respiratory tract, and urothelium and excretory tubes of the kidney, but also in the myocardial cells, in the peripheral and pre‐ossifying hypertrophic chondrocytes, and in the notochord and in the liver. Our study constitutes the first demonstration of galectin‐1 and galectin‐3 during human embryogenesis. The differential expression of these two lectins suggests that they could participate in the complex processes of tissue differentiation. Dev. Dyn. 209:399–405, 1997.

In Silico Dynamic Molecular Interaction Networks for the Discovery of New Therapeutic Targets

Systems biology has emerged as a major trend in biological research during the past decade. As living organisms are described in more and more detail, it aims at filling the gap between understanding basic molecular processes and complex biological systems in which new properties often emerge from the combination of these elementary processes. This approach culminates in the development of computer-based mathematical models of physiological and pathophysiological processes. We review the state of the art in dynamic modelling, with emphasis on two complementary approaches: the modelling of small systems that is mostly developed by academic teams and aims at understanding generic biological properties, and the modelling of large systems that is mostly implemented by industrial companies and aims at the generation of new therapeutic strategies. We also provide an example of such large-scale modelling applied to the identification of drug targets for neurodegeneration.