Personalization and Failure Testing of Dual Switch Gene Drives in Lung Cancer

项目摘要 不同的非小细胞肺癌(NSCLC)患者可能携带导致结构性疾病的突变。 可精确靶向的酪氨酸激酶的激活版本(如EGFR、RET、ALK、ROS1、TRK) 抑制剂。然而，酪氨酸激酶抑制剂对现有的、已知的和未知的耐药性都是脆弱的。 在肿瘤中发现的机制。这导致了一场分子“打地鼠”的游戏，由此，抗性进化 出现后，机制被隔离，药物被用来对抗耐药性，然后是耐药性 重新出现，直到没有有效的治疗方法存在。这种反向工程抗药性的过程已经成为一种 输掉了与患者高昂成本的战斗。一种应对抗药性进化挑战的有希望的方法 是设计和测试细胞疗法，这种疗法可以感知治疗环境并通过合成的 生物回路可以重复地控制进化轨迹。我们提出了一种合成生物技术 在哺乳动物细胞中具有概念验证功能，我们称之为“双开关选择驱动”。这些驱动器使用 可诱导的抗药性创造了一种细胞疗法，可以在原位设计肿瘤的进化。第一个交换机 感应二聚体分子的存在，以产生可逆的抗药性。使用数学规则 生物物理学和进化论，我们的细胞疗法计算出对小分子的反应，并产生可调的 与肿瘤中预先存在的耐药变异体竞争的细胞适合度。第二个交换机 随着自杀基因有效载荷的增加，这种进化引导了细胞治疗，直到选择驱动细胞包括 肿瘤的大部分。然后，按下第二个开关，就会产生一种局部可扩散的毒素，杀死所有人 细胞--基因驱动或任何分子来源的预先存在的抗性突变体--通过旁观者效应。这 技术与非小细胞肺癌现有护理药物标准合作，生产本地化联合疗法 这可以消除预先存在的耐药性，无论其分子机制如何。因此，与其如此，不如 为了应对和对抗进化，我们使用细胞疗法的正向工程来指导进化。在AIM 1我们将使用随机模型对我们设计的进化稳定性的非直观洞察力来提出 进一步优化选择驱动器。目标2通过推动我们的模型驱动扩展了我们的正向工程方法 针对存在的空间、蜂窝和微环境异质性的安全性和有效性设计 非小细胞肺癌。目标3建议将进化概念验证实验转移到初级人类有机类化合物中 伴有EGFR激活突变的非小细胞肺癌患者。除了实际测试一项技术外，我们还将“构建 了解“癌症耐药进化的基本生物学”。

Project Summary Different patients with Non-small-cell lung cancers (NSCLC) can harbor mutations that result in constitutively activated versions of tyrosine kinases (e.g. EGFR, RET, ALK, ROS1, TRK) that can be precisely targeted with inhibitors. However, tyrosine kinase inhibitors are vulnerable to existing, known and unknown, drug resistance mechanisms found in tumors. This results in a game of molecular “whack-a-mole” whereby, resistance evolution appears, the mechanism is isolated, drugs are administered to combat that drug resistance, and then resistance re-emerges until no effective therapies remain. This process of reverse engineering drug resistance has been a losing battle with a high cost for patients. A promising approach to combat the challenge of resistance evolution is to design and test cell therapies that can sense the therapeutic environment and respond through synthetic biology circuits to reproducibly control evolutionary trajectories. We propose a synthetic biological technology with proof-of-concept function in mammalian cells that we term “dual-switch selection drives”. These drives use inducible drug resistance to create a cell therapy that can engineer a tumor’s evolution in situ. The first switch senses the presence of a dimerizer molecule to create reversible drug resistance. Using the mathematical rules of biophysics and evolution, our cell therapy calculates a response to small molecules and produces a tunable amount of cellular fitness that competes with pre-existing drug resistance variants in a tumor. A second switch with a suicide gene payload hitchhikes on this evolution guided cell therapy until the selection drive cells comprise the majority of the tumor. Then, at the flip of a second switch, a locally diffusible toxin is produced that kills all cells--gene drive or pre-existing resistance mutants of any molecular origin--through a bystander effect. This technology works with the existing standard of care drugs in NSCLC to produce localized combination therapy that can eradicate pre-existing resistance regardless of the molecular mechanism. Therefore, instead of responding to and combatting evolution, we use forward engineering of cell therapies to direct evolution. In Aim 1 we will use nonintuitive insights from stochastic models of the evolutionary stability of our designs to propose further optimized selection drives. Aim 2 expands our forward engineering approach by pushing our model driven design of safety and efficacy towards the spatial, cellular, and microenvironmental heterogeneity present in NSCLC. Aim 3 proposes to move evolutionary proof-of-concept experiments into primary human organoids from NSCLC patients with activating mutations in EGFR. Beyond practical testing of a technology, we will also “build to understand” the basic cancer biology of resistance evolution.