The tumor ecosystem in cancer progression and immunotherapeutic response

癌症进展和免疫治疗反应中的肿瘤生态系统

基本信息

批准号：
9980809
负责人：
Alexander Y Rudensky
金额：
$ 63.87万
依托单位：
SLOAN-KETTERING INST CAN RESEARCH
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-08-26 至 2022-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9980809
关键词：
Adaptive Immune System Antigen-Presenting Cells Biological Biopsy Blood CD8-Positive T-Lymphocytes CTLA4 blockade Cancer Model Cancer Patient Cell Communication Cell model Cells Client Clinical Communication Computer Models Data Data Set Dendritic Cells Ecology Ecosystem Endothelial Cells Epithelial Cells Experimental Models Fibroblasts Gene Expression Gene Expression Profiling Goals Hepatocyte Human Immune Immunology Immunotherapeutic agent In Vitro Lymphoid Cell Malignant Neoplasms Malignant neoplasm of lung Mediator of activation protein Memorial Sloan-Kettering Cancer Center Modality Modeling Modeling of Functional Interactions Molecular Mus Myeloid Cells NCI Center for Cancer Research Natural Killer Cells Organ Organism Outcome PD-1 blockade Patients Physiological Population Regulatory Element Regulatory T-Lymphocyte Role Skin Cancer Smooth Muscle Myocytes Stress Structure System Systems Analysis Therapeutic Tissues Tumor Immunity Validation alveolar epithelium base cancer immunotherapeutics cell type eosinophil high throughput analysis in silico in vitro Model macrophage mathematical model melanocyte melanoma mimetics mouse model neoplastic cell neutrophil novel predictive modeling protein expression protein metabolite response tumor tumor microenvironment tumor progression

项目摘要

Project II. The tumor ecosystem in cancer progression and immunotherapeutic response PROJECT SUMMARY The goal of this project is to identify the ecological interactions between cancer and immune cells that govern cancer dynamics and response to therapy. We start from the idea that a tumor can be considered an ecosystem or organ, where multiple accessory cell types are interconnected and communicate with each other and with tumor cells, which serve as their clients. Through systems analysis and modeling of functional interactions in the tumor ecosystem on different scales including cellular, protein, and gene expression dynamics at a population and single cell levels this proposal will seek to identify key cellular and molecular regulatory elements in the tumor microenvironment and potential means of their manipulation for therapeutic benefit. We will explore features of, and relationships between, multiple accessory cell types and tumor cells, in experimental models of skin and lung cancer in mice and in human cancer patients (Aim 1). The accessory cells include myeloid cells, dendritic cells, innate lymphoid cells (ILC), neutrophils, eosinophils, endothelial cells, fibroblasts, and regulatory T (Treg) cells. We will also investigate features of mediators of anti-tumor immunity including NK cells, CD4 and CD8 T cells and their specialized subsets. We will use perturbation of the tumor ecology impacting its progression in mice and human patients by established and novel immunotherapeutic modalities including PD1 and CTLA4 blockade and Treg cell depletion. The impact of these perturbations will be assessed through comprehensive analysis of cellular dynamics and states in relation to biological and clinical outcomes to generate predictive models from the data (Aim 2). We will then validate key interaction components in the tumor ecosystem by modeling cell-cell interactions in vitro using tissue mimetic systems and in silico using agent-based models (Aim 3). 1

项目 II. 癌症进展和免疫治疗反应中的肿瘤生态系统项目概要该项目的目标是确定癌症和免疫细胞之间的生态相互作用我们从肿瘤可以被视为一种癌症的想法开始。生态系统或器官，其中多种辅助细胞类型相互连接并相互通信以及作为其客户的肿瘤细胞，通过系统分析和功能建模。肿瘤生态系统中不同尺度的相互作用，包括细胞、蛋白质和基因表达该提案将寻求在群体和单细胞水平上确定关键的细胞和分子动力学肿瘤微环境中的调控元件及其治疗的潜在调控手段我们将探索多种辅助细胞类型和肿瘤细胞的特征以及它们之间的关系。小鼠和人类癌症患者的皮肤癌和肺癌实验模型（目标 1）。细胞包括骨髓细胞、树突状细胞、先天性淋巴细胞 (ILC)、中性粒细胞、嗜酸性粒细胞、内皮细胞我们还将研究抗肿瘤介质的特征。免疫，包括 NK 细胞、CD4 和 CD8 T 细胞及其特殊亚群，我们将使用扰动。肿瘤生态学通过已建立的和新颖的方法影响小鼠和人类患者的进展免疫治疗方式包括 PD1 和 CTLA4 阻断以及 Treg 细胞耗竭的影响。这些扰动将通过对细胞动力学和状态的综合分析来评估然后，我们将与生物学和临床结果相关，以根据数据生成预测模型（目标 2）。通过使用体外细胞间相互作用建模来验证肿瘤生态系统中的关键相互作用成分组织模拟系统并使用基于代理的模型进行计算机模拟（目标 3）。 1