Integrated Immune Engineering for Poor Prognosis Cancers

综合免疫工程治疗预后不良的癌症

基本信息

批准号：
10700921
负责人：
DAVID ANDREW LARGAESPADA
金额：
$ 186.91万
依托单位：
UNIVERSITY OF MINNESOTA
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：
2021-09-16 至 2026-07-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10700921
关键词：
Acceleration Accounting Antitumor Response Apoptosis Area Benefits and Risks Biomedical Engineering Biophysics Blood CAR T cell therapy Cancer Control Cancer Patient Cancer Prognosis Cells Chemicals Clinical Clinical Trials Collaborations Complex Computers Cytoskeleton Development Diagnosis Economics Effectiveness Engineering Environment Explosion Failure Genetic Genetic Engineering Genetically Engineered Mouse Genome engineering Glioblastoma Growth Health Benefit Image Immune Immune response Immune system Immunocompetent Immunologics Immunologist Immunooncology Immunotherapeutic agent Immunotherapy In Vitro Liquid substance Malignant Neoplasms Malignant neoplasm of brain Malignant neoplasm of pancreas Measures Mechanics Microfabrication Modeling Oncology Pancreatic Ductal Adenocarcinoma Patients Phase Physics Plants Process Prognosis Proliferating Risk Signal Transduction Solid Neoplasm Stream System T-Lymphocyte Technology Testing Therapy trial Time Tissues Translations Tumor-infiltrating immune cells anti-tumor immune response biophysical model cancer cell cancer therapy cell motility clinical risk computational platform cost cytotoxic engineered T cells exhaustion high resolution imaging high risk immune cell infiltrate immunoengineering immunotherapy clinical trials improved in vivo live cell microscopy model development models and simulation nanoscale optical imaging optimism patient population pharmacologic physical science pre-clinical assessment pre-clinical research preclinical development programs response success tumor tumor immunology tumor progression

项目摘要

ABSTRACT A key limitation to effective immunotherapy is the physical access of immune cells to the cancer cells. We propose to develop a multiscale tumor simulator to predict tumor dynamics based on immune and cancer cell migration and net proliferation as measured quantitatively from live cell microscopy. The tumor simulator will be developed by biomedical engineers working in close collaboration with immunologists and genetic engineers who are developing immunotherapies for pancreatic ductal adenocarcinoma and glioblastoma. The tumor simulator will be a computational platform that will help guide immunotherapy development and so will evolve to become an immunotherapy simulator. In addition, we will integrate state- of-the-art genome engineering and microenvironmental engineering to bring a full suite of engineering approaches to bear on the simulator development. Together, the simulator will be used to make quantitative, testable predictions that are then tested experimentally using pharmacological and genetic perturbations. By iterative model development we will test our central hypothesis that immune cell proximity is a major determinant of effective anti-tumoral immune response, and limiting to effective immunotherapy of solid tumors. Altogether, our Program Project will develop a comprehensive biophysics-based simulator to predict tumor progression and accelerate immunotherapy development.

抽象的有效免疫疗法的一个关键限制是免疫细胞与癌细胞的物理接触。我们提议开发多尺度肿瘤模拟器来预测基于免疫和癌症的肿瘤动态通过活细胞显微镜定量测量细胞迁移和净增殖。肿瘤模拟器将由生物医学工程师与免疫学家密切合作开发正在开发胰腺导管腺癌免疫疗法的基因工程师和胶质母细胞瘤。肿瘤模拟器将成为一个有助于指导免疫治疗的计算平台开发，因此将发展成为免疫治疗模拟器。此外，我们将整合国家最先进的基因组工程和微环境工程带来全套工程影响模拟器开发的方法。模拟器将一起用于制作定量的、可测试的预测，然后使用药理学和遗传学进行实验测试扰动。通过迭代模型开发，我们将测试我们的中心假设，即免疫细胞接近是有效抗肿瘤免疫反应的主要决定因素，并限制有效的免疫治疗实体瘤。总之，我们的项目将开发一个基于生物物理学的综合模拟器预测肿瘤进展并加速免疫疗法的开发。