Redesigning the T cell: Using Synthetic Biology to Engineer Therapeutic Cells

描述（由申请人提供）：工程化细胞具有作为强大的“智能”治疗剂的潜力，但我们缺乏工程化细胞的系统框架，以优化其功效并最小化其不良反应。例如，表达人工肿瘤定向受体（嵌合抗原受体-汽车）的T细胞在治疗某些白血病方面取得了意想不到的成功。但是，工程细胞缺乏天然T细胞的精确性和控制力：脱靶细胞杀伤以及免疫系统的过度激活导致大多数患者出现严重的不良反应。实现对这些工程化T细胞的控制仍然是一个重大挑战，使其成为一种安全可靠的疗法，可以扩展到更广泛的疾病。我们建议应用合成生物学的方法来系统地设计具有更定制和精确控制行为的治疗性免疫细胞。我们将运用我们的细胞信号传导知识来设计可用于控制这些治疗细胞的模块化开关和电路。我们的项目将跨越两个互补的方法，由以下目标代表：目标1。开发用于精确控制CAR T细胞的电路模块工具箱。我们将构建可以与汽车组合以增加其特异性和安全性的模块，包括：通过小分子或光远程控制T细胞。为医生提供控制移植治疗细胞活性的安全开关。B.可调反馈电路。通过调整剂量反应阈值、动力学校正和反应的幅度/持续时间来优化CAR T细胞反应。C.多抗原触发激活。增加癌细胞靶向的辨别力。D.用户引导的细胞迁移。将T细胞靶向特定的作用部位，提高精确度。e. 合成细胞间通讯工程师自分泌和多细胞决策电路。目标二。重构T细胞：识别T细胞应答网络中可用于构建自定义应答程序的子模块。目前的汽车复制T细胞活化的天然程序，但响应于新的输入。我们假设有许多替代方法可以插入T细胞信号网络并产生定制的反应。我们将扫描重新连接的T细胞信号蛋白的组合库，以确定可以通过诱导复合物组装（光或药物）激活的替代控制点。这个网络重新布线库应该揭示模块化的子网络，这些子网络可以用作构建模块来构建自定义响应程序，包括：单独的诱导型控制：i）T细胞增殖，ii）肿瘤细胞杀伤，和iii）记忆细胞建立B。对癌症治疗理想的替代性细胞因子应答程序的诱导（例如诱导Th 1程序）c.诱导定制的“点菜”杂交细胞因子应答程序，其针对癌症治疗进行优化。

DESCRIPTION (provided by applicant): Engineered cells have the potential to serve as powerful "smart" therapeutic agents, but we lack a systematic framework for engineering cells to optimize their efficacy and minimize their adverse effects. For example, T cells expressing artificial tumor-directed receptors (Chimeric Antigen Receptors - CARs) have achieved unexpected success in treating certain leukemias. But the engineered cells lack the precision and control of native T cells: off-target cell killing as well as hyperactivation of the immune system lead to severe adverse effects in most patients. Achieving control over these engineered T cells remains a major challenge to making this a safe and reliable therapy that can be extended to a wider range of diseases. We propose to apply the approaches of synthetic biology to systematically engineer therapeutic immune cells with far more tailored and precisely controlled behaviors. We will apply our knowledge of cell signaling to engineer modular switches and circuits that can be used to control these therapeutic cells. Our project will span two complementary approaches, represented by the following aims: Aim 1. Develop toolbox of circuit modules for precision control of CAR T cells. We will construct modules that can be combined with CARs to increase their specificity and safety, including: a. Remote control of T cells via small molecules or light. Provide physicians with safety switches for controlling activiy of transplanted therapeutic cells. b. Tunable feedback circuits. Optimize CAR T cell responses by tuning dose-response thresholds, kinetic proofreading, and the amplitude/duration of response. c. Multi-antigen triggered activation. Increase discrimination of cancer cell targeting. d. User-guided cell migration. Target T cells to specific sites of action, increasing precision. e. Synthetic cell-cell communication. Engineer autocrine and multi-cell decision-making circuits. Aim 2. Refactoring T cells: identify submodules in the T cell response network that can be used to construct custom response programs. Current CARs replicate the native program of T cell activation, but in response to a novel input. We postulate that there are many alternative ways to plug into the T cell signaling network and to generate custom tailored responses. We will scan combinatorial libraries of rewired T cell signaling proteins to identify alternative control points that can be activated through induced complex assembly (light or drugs). This network-rewiring library should reveal modular subnetworks that can be used as building blocks to construct custom response programs, including: a. Separate inducible control of: i) T cell proliferation, ii) tumor cell killing, and iii) memory cell establishment b. Induction of alternatie cytokine response programs ideal for cancer treatment (e.g. induce Th1 program) c. Induction of custom "a la carte" hybrid cytokine response programs that are optimized for cancer treatment.