B-cell chronic lymphocytic leukemia (CLL), the most prevalent leukemia among adult Caucasians, is a disease characterized by the clonal expansion of B lymphocytes expressing CD5. The B-cell receptor (BCR) plays a critical role in CLL development and progression as indicated by the efficacy of drugs blocking BCR signaling. However, the mechanism(s) underneath BCR responsiveness are not well-defined and CLL remains incurable. In the classical view, an interaction between BCR and extrinsic antigen is responsible for such signalling. The discovery that CLL BCRs can self-associate and signal in the absence of extrinsic antigens (intrinsic binding) highlighted a novel mechanism for BCR engagement and signalling. Growing amount of evidences suggest that both extrinsic and intrinsic engagement are required for leukemia development and progression.
Herein, we aim to better define the selectiveness of the two BCR engagement mechanisms and their association with specific biological and clinical characteristics. To better define such elusive associations, machine learning algorithms will be developed and used to define the specific links among the biological data.
Specifically, we will i) assess BCR engagement features associated with CLL clinical aggressiveness and responsiveness to stimuli; ii) identify normal B cells expressing CLL-like BCRs and evaluate their engagement features and similarity with CLL B cells; iii) identify genes and genetic pathways distinctly associated with either mechanism of BCR engagement and/or CLL aggressiveness.
The successful outcome of this proposal would generate biologically and clinically relevant information for prevention, prognosis and therapy of CLL.
Call for proposal
See other projects for this call