Interplay Between Cancer and Immune Cells on Targeted Therapy

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DESCRIPTION (provided by applicant): The role of the host immune response in relation to current therapies in controlling cancer remains unclear. We hypothesize that novel molecular targeted therapies, such as imatinib for chronic myelogenous leukemia (CML), may render leukemic cells immunogenic as patients enter remission. This relates to the relative selectivity of imatinib over standard chemotherapy for leukemic cells, thus sparing normal immune cells. In addition, cancer has potent immunosuppressive activity. As leukemic cell population decreases with imatinib, immune function may be restored while cancer antigens are still present at significant levels, thus leading to an endogenous anti-tumor immune response. Such an immune response may synergize with imatinib to maintain disease control (remission), and may be further expanded to eliminate residual leukemic cells for a durable cure. In preliminary studies, we used a novel combined experimental and modeling approach to address the immune response to leukemia. We showed that the majority of CML patients develop robust anti-leukemia T cell responses upon remission on imatinib. Intriguingly, CD4+ T cells producing TNF-a J represent the dominant response, with levels reaching 40% in one patient. Analysis of IFN-y production by CD8+ T cells alone, as commonly done today, would not reveal the entire anti-leukemia T cell response. We studied the dynamics of these responses and showed that they peak around the time patients enter cytogenetic remission, but wane to undetectable levels shortly thereafter. We utilized mathematical modeling to gain insights into the dynamics of leukemia and the immune response, and the complex interplay between these populations. Our results suggest that anti-leukemia T cell responses may contribute to the maintenance of remission under imatinib therapy. The goal of this proposal is to expand on these findings by conducting and integrating additional experiments and mathematical modeling. We will analyze in detail 10 patients per year over 5 years, for a total of 50 patients using an array of novel immunological techniques (Aim 1). We will develop new mathematical models of the interplay between leukemia and immune cells. These models will extend our preliminary findings to independently consider CD4 T cells, CDST cells, NK cells, B cell response (antibodies), and different cytokine patterns (Aim 2). We will use the new experimental data for evaluating patient-dependent model parameters, and study whether the magnitude, timing, and dynamics of the immune response can be correlated with the clinical outcome. Lastly, we will develop novel therapeutic strategies in silico (Aim 3). Using our mathematical models and real patient parameters, we will study cancer vaccines, structured treatment interruptions, and mini-transplants. If successful, this work will provide important insights into the role of the host immune response in CML under targeted therapy, and may lead to novel treatment strategies combining targeted therapy with immunotherapv.