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Engineering tumor-targeting bacteria to sense and deliver therapeutics

工程化肿瘤靶向细菌来感知和提供治疗

基本信息

批准号：
10706350
负责人：
Tetsuhiro Harimoto
金额：
$ 8.86万
依托单位：
HARVARD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-08-10 至 2026-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10706350
关键词：
3-Dimensional Acceleration Address Animal Model Antibiotics Attenuated Bacteria Bacterial Genes Bacteriophages Biosensor CT26 Cancer Model Cell Death Cells Chemoresistance Coculture Techniques Colon Colorectal Colorectal Cancer Colorectal Neoplasms Complex Computer Models Coupled Development Disease Progression Dose Engineered Gene Engineering Environment Feedback Fusobacterium nucleatum Genes Goals Growth Homing Human body Hypoxia Immunologic Surveillance In Situ In Vitro Intelligence Libraries Malignant Neoplasms Mammalian Cell Methods Microbe Microscopy Modeling Monitor Mus Necrosis Oncogenic Organism Oxygen Patients Peptides Phase Plasmids Population Postdoctoral Fellow Prevalence Production Proliferating Rapid screening Repression Research Research Project Grants Research Proposals Risk Role Salmonella typhimurium Solid Neoplasm Specificity System Technology Testing Therapeutic Therapeutic Agents Time Tissues Toxic effect Treatment Efficacy Tropism Tumor Promotion Tumor Tissue Work cancer cell cancer therapy clinical candidate clinical translation colorectal cancer progression colorectal cancer treatment commensal microbes cytotoxic delivery vehicle dynamic system effective therapy gut microbes gut microbiota improved in vivo microbial microbiome research microbiota mouse model next generation novel novel strategies pathogen response sensor skills spatiotemporal synthetic biology therapeutic candidate therapy outcome tool tumor tumor hypoxia tumor microbiota tumor microenvironment tumor progression

项目摘要

Project Summary The ability to engineer living cells as intelligent therapeutic agents is poised to transform current cancer treatment paradigms. Based on the inherent growth specificity of some natural and exogenous bacteria to solid tumors, microbes have been explored as programmed vehicles to deliver therapeutics to tumor environments. However, a universal challenge for developing this next-generation living therapy is the lack of tools to study the dynami- cally interacting population of bacteria and cancer cells. Consequently, the vast majority of the past studies have relied on animal models that only test a handful of therapeutic candidates and provide limited spatiotemporal information. To address this challenge, I have recently developed a 3D multicellular coculture platform that ena- bles high-throughput characterization of bacteria in tumor spheroids, assessing dynamics of multicellular inter- actions and predicting therapeutic efficacy in vivo. In this proposal, I will leverage the 3D coculture technologies and synthetic biology tools to construct novel bacterial systems that sense and express therapeutics specifically in tumors. In the F99 phase, I will engineer tumor-homing bacteria to dynamically regulate production of cytotoxic molecules in response to tumor shrinkage. Specifically, as the cancer cell death increases the level of oxygen in the tumor core, I will engineer a bacterial biosensor circuit to monitor this change in the tumor microenvironment. By detecting rises in oxygen levels, which indicate extensive therapeutic progression, this gene circuit will reduce the therapeutic level produced, minimizing off-target toxicity. In the K00 phase, I will repurpose tumor-homing bacteria to target and eradicate oncogenic F. nucleatum in colorectal cancer. I will apply the 3D coculture platform to screen anti-F. nucleatum peptides delivered by bacteria to tumor spheroids. Orthotropic mouse cancer models will be used to assess the F. nucleatum elimination, effect on commensal microbiota, and cancer progression. Collectively, the proposed work will utilize a novel engineering framework to develop effective bacterial cancer therapies towards clinical translation.

项目摘要将活细胞作为智能治疗剂的能力有望改变目前的癌症治疗范例基于某些天然细菌和外源性细菌对实体瘤固有的生长特异性，微生物已被探索为将治疗剂递送至肿瘤环境的程序化载体。然而，在这方面，开发这种下一代活体疗法的一个普遍挑战是缺乏研究动力学的工具，细菌和癌细胞之间的相互作用。因此，过去的绝大多数研究都依赖于动物模型，只测试少数治疗候选人，并提供有限的时空信息.为了应对这一挑战，我最近开发了一个3D多细胞共培养平台， bles肿瘤球体中细菌的高通量表征，评估多细胞间的动力学，作用和预测体内治疗效果。在这个提案中，我将利用3D共培养技术和合成生物学工具来构建新的在肿瘤中特异性感知和表达治疗药物的细菌系统。在F99阶段，我将设计肿瘤归巢细菌响应肿瘤缩小而动态调节细胞毒性分子的产生。具体来说，随着癌细胞死亡增加肿瘤核心的氧气水平，我将设计一种细菌，生物传感器电路来监测肿瘤微环境中的这种变化。通过检测氧气水平的上升，这表明广泛的治疗进展，该基因电路将降低产生的治疗水平，最小化脱靶毒性。在K00阶段，我将重新利用肿瘤归巢细菌，致癌F.结直肠癌中的核仁。我将应用三维共培养平台筛选抗F。具核由细菌递送至肿瘤球状体的肽。正交各向异性小鼠癌症模型将用于评估 F.核质消除、对肠道微生物群的影响和癌症进展。总体而言，拟议的这项工作将利用一种新的工程框架，开发有效的细菌癌症疗法，翻译.