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.

抽象的尽管最近几十年取得了长足的进步，但许多类型的癌症几乎仍然致命。胰导管腺癌（PDAC）是一个了不起的例子。挑战之一是绝大多数（95％） PDAC的PDAC是由一个称为KRAS的基因中的突变驱动的，这些KRAS突变非常困难靶向常规药物。第一代癌症药物基于小分子，第二代生成生物制剂（大型生物分子，例如专门结合癌细胞的抗体），最新的产生细胞（设计用于识别和烧毁癌细胞）。在这里，我们的长期目标是证明新一代理论，使用“电路”作为医学。电路隐喻是指生物分子设计旨在相互调节并处理活细胞内的信息。而常规分析输出指标以告知医生，然后做出热决定，我们的电路关闭循环，并将作为分析和治疗工具。这是一种分子和细胞分析技术这是对活细胞的询问，并无需人工干预即可实时实时进行治疗输出。具体而言，我们将创建电路以编程免疫系统并模仿“脱离效应”，即偶尔观察到治疗局部肿瘤时远处肿瘤收缩，很可能是由于免疫引起的系统学习处理过的肿瘤的“签名”，然后再推断。我们将首先创建建筑物此类电路的块：传感器可以询问单元是否处于取消状态，执行器可以控制细胞发送的信号接合免疫系统，以及连接传感器和连接的处理器执行者。这些努力将受益于我们专门使用蛋白质建筑电路的经验，具有技术优势，例如在不同蜂窝中的功能易于交付和鲁棒性与基于蛋白-DNA相互作用的更常规的建筑电路方式相比，环境。我们将然后将这些构建块组装成圆圈，并量化和优化它们在培养的细胞中的运行。利用我们在PDAC鼠标模型中的专业知识，我们最终将测试这些电路在体内的效率。这前提是专门从癌细胞编程输出以动员免疫系统，然后弄液化这些细胞允许免疫系统访问癌症中所有独特的蛋白质序列。这些死的癌细胞将基本用作暴露于类似蛋白的其他细胞的疫苗序列轮廓。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作用动员免疫系统，或对癌细胞进行编程以直接和人为地激活T细胞 - 免疫负责识别和擦除癌细胞的细胞。该提案的预期结果不仅是支持小说，有力的临床前证据 KRAS驱动的PDAC的治疗，但也证明了合成生物分子的生物医学承诺的原理其他顽固类型的癌症及其他类型的电路。