Endogenous Heterogeneity of Signaling Pathways in Cancer

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Cancer is classically modeled as a malignant transformation with genetic mutation of oncogenes or tumor suppressor genes driving uncontrolled cellular growth. However, epigenetic or even stochastic endogenous variations in the expression levels of these genes may be sufficient to disregulate proliferation and apoptosis pathways, and drive tumorigenesis. Thus, there may exist cancers whose origin and maintenance stem from non-genetic perturbations of normal pathways. In this project, we focus on Chronic Lymphocytic Leukemia (CLL), a lymphoproliferative disease characterized by the clonal expansion of mature B lymphocytes arrested in the G0/G1 phase of the cell cycle. To date, there is no known mutation conferring dominant-positive or dominant negative activities to signaling regulators that would account for the resistance to apoptosis and enhanced proliferation of B cells in CLL. Differential expression of signaling components (e.g. upregulation of CDS and ZAP70) is used to predict clinical prospects for CLL patients, but there is limited understanding of their relevance to the growth dysregulation and disease progression. The goal of this research project is to study the heterogeneity of B cell signaling sustaining proliferation and apoptosis in CLL. For that purpose, we will introduce a systems biology platform that combines theoretical modeling of B cell signaling (under activation by antigens, cytokines or others) with experimental measurements on single primary cells. More specifically, we plan to rely on the natural heterogeneity of B cells (in CLL patients or in healthy individuals), to map out the variability of CLL disease states. We will develop a theoretical biochemical model, to identify key signaling regulators in B cell signaling. We will also apply a new experimental methodology to correlate, at the single cell level, B cell responsiveness with expression levels of these key signaling regulators. Ultimately, we aim at introducing multivariate parameters of individual cells within a population (from markers to functional response) to better characterize CLL phenotypes and offer new therapeutic approaches taking into account the variability in CLL B cells.