Interplay Between Cancer and Immune Cells on Targeted Therapy

描述（由申请人提供）：宿主免疫应答与当前治疗在控制癌症中的作用仍不清楚。我们假设，新型分子靶向治疗，如伊马替尼治疗慢性粒细胞白血病（CML），可能使白血病细胞免疫原性，因为患者进入缓解。这与伊马替尼相对于标准化疗对白血病细胞的相对选择性有关，因此保留了正常的免疫细胞。此外，癌症具有强大的免疫抑制活性。随着伊马替尼降低白血病细胞群体，免疫功能可能恢复，而癌抗原仍以显著水平存在，从而导致内源性抗肿瘤免疫应答。这种免疫应答可以与伊马替尼协同作用以维持疾病控制（缓解），并且可以进一步扩大以消除残留的白血病细胞以实现持久的治愈。在初步研究中，我们使用了一种新的实验和建模相结合的方法来解决对白血病的免疫反应。我们发现，大多数CML患者在伊马替尼缓解后产生了强大的抗白血病T细胞应答。有趣的是，产生TNF-α的CD 4 + T细胞代表了主要的反应，在一名患者中水平达到40%。如今天通常所做的那样，单独通过CD 8 + T细胞分析IFN-γ产生不会揭示整个抗白血病T细胞应答。我们研究了这些反应的动力学，发现它们在患者进入细胞遗传学缓解期时达到峰值，但此后不久就下降到无法检测的水平。我们利用数学建模来深入了解白血病和免疫反应的动态，以及这些人群之间复杂的相互作用。我们的研究结果表明，抗白血病T细胞反应可能有助于维持缓解伊马替尼治疗。该提案的目标是通过进行和整合额外的实验和数学建模来扩展这些发现。我们将在5年内每年详细分析10例患者，总共50例患者使用一系列新的免疫学技术（目标1）。我们将开发白血病和免疫细胞之间相互作用的新数学模型。这些模型将扩展我们的初步发现，独立考虑CD 4 T细胞，CDST细胞，NK细胞，B细胞反应（抗体），和不同的细胞因子模式（目标2）。我们将使用新的实验数据来评估患者依赖性模型参数，并研究免疫应答的幅度、时间和动态是否与临床结果相关。最后，我们将在计算机上开发新的治疗策略（目标3）。使用我们的数学模型和真实的患者参数，我们将研究癌症疫苗，结构化治疗中断和微型移植。如果成功，这项工作将提供重要的见解宿主免疫反应在CML靶向治疗的作用，并可能导致新的治疗策略结合靶向治疗与免疫治疗。

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.