Engineering synthetic immune cells with modular sentinel and therapeutic functions for T1D

项目总结 我们的长期目标是设计治疗性免疫细胞，能够报告和治疗早期1型 糖尿病(T1D)。理想情况下，这些细胞应该是胰岛的家园，检测和整合早期- 疾病阶段，作为回应，诱导局部免疫抑制以阻止β细胞的破坏。虽然 这似乎是一个非常困难的多层次挑战，这是工程免疫方面的显著进步 识别和杀死癌症的细胞已经产生了一系列广泛的新技术和方法，这些技术和方法可能 针对T1D的基于细胞的疗法。在这里，我们建议重新定位、重定向和扩展单元 构建能够感知和治疗的合成免疫细胞(CD4+T细胞)的工程方法 像T1D这样的早期自身免疫性疾病。鉴于实现这一目标面临多重挑战，我们建议 采用模块化方法-我们已经将理想的抗T1D细胞疗法必须实现的目标分解为 三个截然不同的子任务。我们的重点将是独立设计和验证单元电路模块， 可以实现这些子任务，然后可以将这些子任务以多个组合链接在一起，以开发 全面治疗。这些模块目标在我们的具体目标中概述： 目标1.胰岛感知/靶向|设计合成免疫细胞哨兵，识别和 在胰腺/胰岛建立驻留/活动。胰岛特异性抗原传感器；胰岛 使用synNotch受体限制激活；通过合成黏附蛋白进行胰岛运输。 目的2.自身免疫性疾病感知|设计合成免疫细胞，感知并报告 与T1D发病相关的局部免疫紊乱。工程传感器检测到是否存在 自身反应性T细胞与局部特异炎性细胞因子水平升高 目标3.免疫抑制输出：设计治疗性细胞，通过诱导局部诱导保护胰岛 对疾病感知的免疫抑制输出。工程师的输出响应包括 诱导局部产生抑制性细胞因子(IL10、TGFb)、炎性细胞因子下沉(CD25)等 β细胞保护因子。我们将测试连接AIMS的疾病传感电路的多种配置 1和2到目标3的抑制输出。 为了开发治疗T1D的创新细胞工程平台，我们建议将重点放在人类多能性上 干细胞(HPSC)来源的胰岛作为一种高度灵活的系统来评估免疫保护功能。 HPSC-细胞可以很容易地生成和转基因，以添加方便的模式抗原用于检测或 终止，允许上述电路模块的快速设计-构建-测试迭代循环(即， 使每个目标不依赖于其他目标)。HPSC胰岛也可用于评估免疫保护作用 体外和体内对多种胰岛靶向细胞毒性T细胞的反应(植入小鼠体内) 肾胶囊)，使该平台成为原理验证评估和细胞电路优化的理想选择。

PROJECT SUMMARY Our long-term goal is to engineer therapeutic immune cells that can report on and treat early-stage type 1 diabetes (T1D). Ideally, these cells should home to islets, detect and integrate multi-factor signatures of early- stage disease and, in response, induce localized immunosuppression to block destruction of beta cells. Although this seems like an extraordinarily difficult multi-level challenge, the remarkable progress in engineering immune cells to recognize and kill cancer has generated a broad set of new technologies and approaches that could be brought to bear on cell-based therapies for T1D. Here we propose to repurpose, redirect, and extend cell engineering approaches to construct synthetic immune cells (CD4+ T cells) capable of sensing and treating early-stage autoimmune disorders like T1D. Given the multiple challenges in achieving this goal, we propose to take a modular approach – we have broken up what an ideal anti-T1D cell therapy would have to achieve into three distinct subtasks. Our focus will be on independently engineering and validating cell circuit modules that can achieve these subtasks, which can then be linked together in multiple combinations to develop options for a full therapy. These modular objectives are outlined in our specific aims: Aim 1. ISLET SENSING/TARGETING | Engineer synthetic immune cell sentinels that recognize and establish residence/activity in the pancreas/islets. Sensors of pancreatic/islet specific antigens; islet restricted activation using synNotch receptors; and islet trafficking via synthetic adhesion proteins. Aim 2. AUTOIMMUNE DISEASE SENSING | Engineer synthetic immune cells that sense and report on local immune perturbations associated with T1D onset. Engineer sensors that detect presence of autoreactive T cells and elevated local levels of specific inflammatory cytokines Aim 3. IMMUNO-SUPPRESSIVE OUTPUT: Engineer therapeutic cells that protect islets by inducing local immunosuppressive outputs in response to disease sensing. Engineer output responses encompassing induced local production of suppressive cytokines (IL10, TGFb), inflammatory cytokine sinks (CD25), and other beta-cell protective factors. We will test multiple configurations of linking the disease sensing circuits from Aims 1 and 2 to the suppressive outputs from Aim 3. To develop innovative cell engineering platforms for treating T1D, we propose to focus on human pluripotent stem cell (hPSC)-derived islets as a highly flexible system in which to evaluate the immunoprotective function. hPSC-cells can be readily generated and genetically modified to add convenient model antigens for sensing or killing, allowing for the rapid design-build-test iterative cycles for the circuit modules described above (i.e., making each aim non-dependent on the others). hPSC islets can also be used to assess immunoprotective responses against a variety of islet-targeted cytotoxic T cells, both in vitro and in vivo (implantation in mouse kidney capsule), making this platform ideal for proof-of-principle evaluation and cell circuit optimization.