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

肺癌双开关基因驱动的个性化和故障测试

基本信息

批准号：
10818053
负责人：
Justin Pritchard
金额：
$ 9.55万
依托单位：
PENNSYLVANIA STATE UNIVERSITY, THE
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-10 至 2026-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10818053
关键词：
3-Dimensional Biological Biophysics Bystander Effect Cancer Biology Cancer Patient Cancer cell line Cell Therapy Cells Chemicals Clinical Collaborations Combined Modality Therapy Compensation Coupled Cues Data Diffusion Dimerization Directed Molecular Evolution Drug resistance Endothelial Cells Engineering Environment Epidermal Growth Factor Receptor Evolution Exhibits Extracellular Matrix Failure Fibroblasts Gene Library Genes Goals Grant Heterogeneity Human Immune In Situ Investigation Lead Learning Left Lung Malignant Neoplasms Malignant neoplasm of lung Mammalian Cell Mathematics Measurement Measures Modeling Mole the mammal Molecular Mutation Non-Small-Cell Lung Carcinoma Oncogenes Oncologist Organoids Patients Performance Pharmaceutical Preparations Process Prodrugs Protein Tyrosine Kinase ROS1 gene Reproducibility Resistance Resistance development Resolution Reverse engineering Risk SWI1 Safety Suicide Gene Therapy Switch Genes Tacrolimus Binding Protein 1A Techniques Technology Testing Therapeutic Toxicity Tests Toxin Tyrosine Kinase Inhibitor Validation Variant Work arms race cancer cell cell killing combat cost design drug development drug discovery dual switch selection gene drive effective therapy efficacy evaluation engineering design experimental study fighting fitness gene drive system improved inhibitor insight kinase inhibitor mimetics mutant neoplastic cell novel therapeutics parent grant pharmacologic prevent programs prototype resistance mechanism resistance mutation response simulation small molecule standard of care suicide gene synthetic biology systemic toxicity treatment response tumor tumor microenvironment

项目摘要

Project Summary/Abstract (Parent Grant) 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.

项目摘要/摘要（家长资助）不同的非小细胞肺癌 (NSCLC) 患者可能存在导致组成性突变的突变酪氨酸激酶的激活版本（例如 EGFR、RET、ALK、ROS1、TRK），可精确靶向然而，酪氨酸激酶抑制剂很容易受到现有的、已知的和未知的耐药性的影响。在肿瘤中发现的机制，这导致了分子“打地鼠”的游戏，因此，耐药性进化。出现后，该机制被隔离，施用药物来对抗耐药性，然后耐药性重新出现，直到没有有效的治疗方法为止。这种逆向工程耐药性的过程一直是一个过程。与失去患者的高成本作斗争是应对耐药性进化挑战的一种有前途的方法。是设计和测试可以感知治疗环境并通过合成做出反应的细胞疗法我们提出了一种合成生物技术来可重复地控制进化轨迹。在哺乳动物细胞中具有概念验证功能，我们称之为“双开关选择驱动器”。诱导耐药性，以创造一种可以原位设计肿瘤进化的细胞疗法。使用数学规则感知二聚分子的存在以产生可逆的耐药性。结合生物物理学和进化论，我们的细胞疗法计算对小分子的反应并产生可调节的与肿瘤中预先存在的耐药性变异体竞争的细胞适应性的数量第二次转换。带有自杀基因有效负载的进化引导细胞疗法会搭便车，直到选择驱动细胞包含然后，在第二个开关打开时，会产生一种局部扩散的毒素，杀死所有肿瘤。细胞——基因驱动或任何分子起源的预先存在的抗性突变体——通过旁观者效应。技术与非小细胞肺癌现有治疗药物标准相结合，产生局部联合疗法无论分子机制如何，都可以消除预先存在的耐药性。为了响应和对抗进化，我们使用细胞疗法的正向工程来指导进化。 1 我们将使用我们设计的进化稳定性随机模型的非直观见解来提出目标 2 通过推动我们的模型驱动来扩展我们的正向工程方法。针对空间、细胞和微环境异质性的安全性和有效性设计目标 3 提议将进化概念验证实验转移到原代人类类器官中。 EGFR 激活突变的 NSCLC 患者除了对技术进行实际测试之外，我们还将“构建”。了解“耐药性进化的基本癌症生物学”。

项目成果

期刊论文数量（3）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Excessive concentrations of kinase inhibitors in translational studies impede effective drug repurposing.

DOI：
10.1016/j.xcrm.2023.101227
发表时间：
2023-10-17
期刊：
CELL REPORTS MEDICINE
影响因子：
14.3
作者：
Liu, Chuan;Leighow, Scott M.;Mcilroy, Kyle;Lu, Mengrou;Dennis, Kady A.;Abello, Kerry;Brown, Donovan J.;Moore, Connor J.;Shah, Anushka;Inam, Haider;Rivera, Victor M.;Pritchard, Justin R.
通讯作者：
Pritchard, Justin R.

Materials-driven approaches to understand extrinsic drug resistance in cancer.