Program the Immune System against RAS-driven Cancer

对免疫系统进行编程以对抗 RAS 驱动的癌症

基本信息

批准号：
10612257
负责人：
Xiaojing J Gao
金额：
$ 21.8万
依托单位：
STANFORD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-06-01 至 2026-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10612257
关键词：
Ablation Abscopal effect Address Adverse effects Amino Acid Sequence Antibodies Antigen Targeting Antigen-Presenting Cells Antineoplastic Agents Binding Biological Process Biological Products Cancer Detection Cancer Model Cancerous Cell Death Cell Transplantation Cells Collection Cultured Cells DNA-Protein Interaction Data Dedications Distant Engineering Equus caballus Event Excision Exhibits Generations Genes Goals Grant Human Immune Immune response Immune system Immunity Immunologic Stimulation Immunotherapy In Vitro Innovative Therapy Intervention KRAS oncogenesis KRAS2 gene Learning Lentivirus Vector Libraries Malignant Neoplasms Mediating Medicine Methods Modality Molecular Mutation Oncogenic Outcome Output Pancreatic Ductal Adenocarcinoma Patients Peptide Hydrolases Performance Pharmaceutical Preparations Philosophy Physicians Positioning Attribute Primary Neoplasm Process Protein Engineering Protein Secretion Proteins Public Health Quality of life RAS driven cancer Radiation therapy Research Personnel Signal Transduction System T-Cell Activation T-Lymphocyte Technology Testing Therapeutic Time Vaccination Vaccines Variant bioluminescence imaging cancer cell cancer type cell type chemotherapy conventional therapy design experience immunogenic improved in vivo intercellular communication laboratory experience mouse model mutant neoantigen vaccine neoantigens novel novel strategies novel therapeutic intervention novel therapeutics operation pancreatic ductal adenocarcinoma cell pancreatic ductal adenocarcinoma model pre-clinical programs sensor small molecule synergism tool tumor

项目摘要

Abstract Despite the great progress in recent decades, many types of cancer remain almost fatal. Pancreatic ductal adenocarcinoma (PDAC) is a remarkable example. One of the challenges is that the vast majority (95%) of PDACs are driven by mutations within a gene called KRAS, and these KRAS mutations are notoriously difficult to target with conventional drugs. The first generation of cancer drugs are based on small molecules, the second generation biologics (large biomolecules such as antibodies that specifically bind to cancer cells), and the latest generation cells (engineered to recognize and ablate cancer cells). Here our long-term goal is to demonstrate a new generation of therapeutics, using “circuits” as medicine. Circuits metaphorically refer to collections of biomolecules engineered to regulate each other and process information inside living cells. While conventional analyses output metrics to inform physicians, who then make therapeutic decisions, our circuits close the loop, and will serve as both the analytic and the therapeutic tools. It is a molecular and cellular analysis technology that queries living cells and actuates therapeutic outputs in real time without human intervention. Specifically, we will create circuits to program the immune system and emulate the “abscopal effect”, the occasional observation that distant tumors shrink when local tumors are treated, most likely due to the immune system learning the “signature” of the treated tumors and then extrapolating. We will first create the building blocks for such circuits: sensors that can interrogate whether a cell is in a cancerous state, actuators that can control the signals sent by cells to engage the immune system, and processors that connect the sensors and the actuators. These efforts will benefit from our experience of building circuits exclusively using proteins, which features technical advantages, such as ease of delivery and robustness of functionality in different cellular contexts, compared to more conventional ways of building circuits based on protein-DNA interactions. We will then assemble these building blocks into circuits, and quantify and optimize their operation in cultured cells. Leveraging our expertise in mouse models of PDACs, we will finally test these circuits’ efficacy in vivo. The premise is to program the outputs specifically from cancer cells to mobilize the immune system and then lyse these cells to grant the immune system access to all protein sequences that are uniquely present in cancer. These dead cancer cells will serve essentially as vaccines against other cells that exhibit similar protein sequence profiles. We will achieve this vaccination effect by either mimicking a specific type of cell death known to mobilize the immune system, or program the cancer cells to directly and artificially activate T cells – immune cells responsible for recognizing and ablating cancer cells. The expected outcomes of this proposal are not only preclinical evidence supporting a novel, powerful therapy for KRAS-driven PDAC, but also a proof of principle for the biomedical promise of synthetic biomolecular circuits for other recalcitrant types of cancer and beyond.

抽象的尽管近几十年来取得了巨大进展，但许多类型的胰腺癌仍然几乎是致命的。导管腺癌（PDAC）就是一个显着的例子，挑战之一是绝大多数（95%）。的 PDAC 是由 KRAS 基因内的突变驱动的，而这些 KRAS 突变是出了名的困难第一代癌症药物是基于小分子的，第二代是基于小分子的。一代生物制剂（大生物分子，例如特异性结合癌细胞的抗体），以及最新的一代细胞（旨在识别和消除癌细胞）。新一代疗法，使用“电路”作为药物。电路隐喻地指的是集合。生物分子被设计为在活细胞内相互调节和处理信息。分析输出指标以告知医生，然后医生做出治疗决策，我们的电路闭合循环，并将作为分析和治疗工具。它是一种分子和细胞分析技术。无需人工干预即可实时查询活细胞并启动治疗输出。具体来说，我们将创建电路来对免疫系统进行编程并模拟“远隔效应”，即偶尔观察到，当局部肿瘤得到治疗时，远处的肿瘤会缩小，这很可能是由于免疫系统的作用系统学习所治疗肿瘤的“特征”，然后进行推断，我们将首先创建建筑物。此类电路的模块：可以询问细胞是否处于癌变状态的传感器，可以控制细胞发送的信号以吸引免疫系统，以及连接传感器和处理器的处理器这些努力将受益于我们专门使用蛋白质构建电路的经验。具有技术优势，例如易于交付和在不同蜂窝中的功能稳健性与基于蛋白质-DNA 相互作用构建电路的更传统方法相比。然后将这些构建块组装成电路，并量化和优化它们在培养细胞中的运行。利用我们在 PDAC 小鼠模型方面的专业知识，我们最终将测试这些电路在体内的功效。前提是专门对癌细胞的输出进行编程，以动员免疫系统，然后裂解这些细胞使免疫系统能够接触到癌症中独特存在的所有蛋白质序列。这些死亡的癌细胞本质上将充当针对具有类似蛋白质的其他细胞的疫苗我们将通过模仿已知的特定类型的细胞死亡来实现这种疫苗接种效果。调动免疫系统，或对癌细胞进行编程，直接人工激活 T 细胞 – 免疫负责识别和消除癌细胞的细胞。该提案的预期结果不仅是支持新颖、强大的临床前证据 KRAS 驱动的 PDAC 疗法，也是合成生物分子生物医学前景的原理证明其他顽固性癌症及其他癌症的回路。