Interplay Between Cancer and Immune Cells on Targeted Therapy

描述（由申请人提供）：宿主免疫反应在当前控制癌症治疗中的作用尚不清楚。我们假设新的分子靶向疗法，如伊马替尼治疗慢性粒细胞白血病（CML），可能使白血病细胞在患者进入缓解期时产生免疫原性。这与伊马替尼相对于白血病细胞的标准化疗的选择性有关，从而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。随着伊马替尼的使用，白血病细胞数量减少，免疫功能可能会恢复，而癌症抗原仍然显著存在，从而导致内源性抗肿瘤免疫反应。这种免疫反应可能与伊马替尼协同作用以维持疾病控制（缓解），并可能进一步扩大以消除残留的白血病细胞以实现持久治愈。在初步研究中，我们使用了一种新的结合实验和建模的方法来解决白血病的免疫反应。我们发现，大多数CML患者在伊马替尼缓解后产生强大的抗白血病T细胞反应。有趣的是，产生TNF-a - J的CD4+ T细胞代表了主要反应，在一名患者中其水平达到40%。目前通常只分析CD8+ T细胞产生IFN-y，并不能揭示整个抗白血病T细胞反应。我们研究了这些反应的动态，并表明它们在患者进入细胞遗传学缓解期时达到峰值，但此后不久就减弱到无法检测到的水平。我们利用数学模型来深入了解白血病和免疫反应的动力学，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伊马替尼治疗下缓解的维持。本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技术（目的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CD4 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（目的2）。我们将使用新的实验数据来评估患者依赖的模型参数，并研究免疫反应的大小、时间和动态是否与临床结果相关。最后，我们将开发新的硅片治疗策略（目标3）。利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，这项工作将为宿主免疫反应在靶向治疗CML中的作用提供重要的见解，并可能导致将靶向治疗与免疫治疗相结合的新治疗策略。

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.