Top-Down Proteomics of Chronic Lymphocytic Leukemia
Chronic lymphocytic leukemia (CLL) is the most common leukemia in western society, accounting for over 35% of adult leukemias with over 15,000 new cases diagnosed per year [22-23]. It is characterized by an accumulation of CD5+ monoclonal B-lymphocytes in the blood, bone marrow, and lymphoid tissues (>5000/μL) . CLL is an ideal model to study the biological variability of primary tumor samples from individual patients, which will ultimately guide personalized therapy. The relatively indolent nature of the disease and the watchful waiting periods between treatments give the opportunity to collect tumor samples at various points of the patient’s disease course, thus allowing observation of biological changes over time. The Northwestern University Robert H. Lurie Comprehensive Cancer Center (P30 CA060553, L. Platanias, PI) has been systematically collecting detailed patient information and banking PBMC samples from over 200 CLL patients throughout their disease and treatment course. In this driving biomedical project, we propose a top-down approach to study differences between normal B-cells and those from CLL patients with and without hypermutated IgVH  and to investigate the underlying mechanisms of ibrutinib cytotoxicity in CLL .
In collaboration with the Ma lab, we will perform top-down proteomics and histone epiproteomics (TR&D 4) to compare the protein expression profiles of normal B lymphocytes and primary leukemia cells from CLL patients with and without IgVH hypermutation (occurs in 50% of CLL patients). In Task 2, we will perform a comprehensive top-down analysis of differential protein expression profiles and PTMs of proteins critical for mediating CLL’s in vitro response to anti-leukemic treatments using clinical samples. In this task, we will perform a similar top-down proteomic analysis as described above to investigate the mechanism of ibrutinib-induced cytotoxicity by comparing the protein expression profiles of primary CLL patient samples before and after ibrutinib treatment. Top-down proteomics should allow us to first discover specific proteoforms predictive of a strong response when treated with ibrutinib. Once candidate biomarkers are identified in this discovery mode, we will use technologies developed in TR&D 1 and TR&D 2 to validate those biomarkers. The number of individual samples will require the use of the integrated command and control environment proposed in TR&D 3. These studies will help to shine light onto the mechanism determining treatment-responsiveness.
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