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Quantitative modeling of the phenotypic variability of individual T cells and the

个体 T 细胞表型变异的定量建模和

基本信息

批准号：
8115954
负责人：
Gregoire Altan-Bonnet
金额：
$ 47.94万
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：
2009
资助国家：
美国
起止时间：
2009-08-05 至 2013-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8115954
关键词：
Accounting Affect Agonist Antigen Receptors Antigens Autoantigens Biological Biological Assay Blast Cell Cell Proliferation Cells Cessation of life Chimeric Proteins Communication Computer Simulation Computers Conflict (Psychology)Coupled Cues Cytokine Signaling Data Discrimination Down-Regulation Feedback Fluorescence Frequencies Genetic Goals Health Heterogeneity IL2 gene Immune System Diseases Immune response Immune system Individual Infection Interleukin-15 Interleukin-2 Knowledge Libraries Ligands Maps Measurement Methods Modeling Monitor Mutate Pathway interactions Peripheral Phenotype Phosphotransferases Physiological Population Population Heterogeneity Property Proteins RNA Interference Receptor Signaling Regulation Regulatory Pathway Regulatory T-Lymphocyte Research Shapes Signal Pathway Signal Transduction Signaling Protein Sorting - Cell Movement Specificity Staging System T cell response T-Cell Activation T-Lymphocyte Testing Tissues Translating Update Variant Work analog antigen challenge base cDNA Library cancer immunotherapy chemokine clinical application cytokine density deprivation digital overexpression pathogen protein expression quorum sensing receptor expression response synergism thymocyte

项目摘要

DESCRIPTION (provided by applicant): Our long-term goal is to probe theoretically and experimentally how reliable immune responses emerge at the system level from the unreliable responses of individual T cells. Our first project aims at probing how heterogeneity in the expression levels of key signaling proteins generates phenotypic variability in T cells' responsiveness to ligands. We will also probe how such stochasticity of signaling responses translates into functional phenotypic variability. Our second aim tests how multiplexed signals (e.g. T cell ligands and IL15 cytokine) can activate signaling crosstalks that modulate the levels and/or activity of key signaling proteins and make T cells hyperresponsive to self-derived ligands. Our third aim probes how cytokine regulation integrates cell variability in antigen response at the individual cell level towards a regulated collective response. This project focuses on Interleukin-2 as a critical cytokine that controls quorum sensing among effector T cells and suppression by regulatory T cells. Our approach is fundamentally interdisciplinary with concomitant computational modeling and experimental testing. It consists in making and validating theoretical predictions to quantify and control how immune responses emerge as dynamically- and collectively-regulated properties of individual T cells. PUBLIC HEALTH RELEVANCE: Our project focuses on developing experimentally-validated computer models of T cell activation. Our goal is to identify how reliable immune responses emerge dynamically from the unreliable activation of individual T cells. The long-term impact of our research is in a better control of immune responses towards immunotherapies for cancer and auto- immune disorders.

描述(由申请人提供)：我们的长期目标是从理论和实验上探索如何在系统水平上从单个T细胞的不可靠反应中产生可靠的免疫反应。我们的第一个项目旨在探索关键信号蛋白表达水平的异质性如何在T细胞对配体的反应中产生表型差异。我们还将探索信号响应的这种随机性如何转化为功能表型可变性。我们的第二个目标是测试多路信号(例如T细胞配体和IL15细胞因子)如何激活信号串扰，从而调节关键信号蛋白的水平和/或活性，并使T细胞对自身衍生的配体产生高度反应。我们的第三个目标是探索细胞因子调节如何在单个细胞水平上整合抗原反应中的细胞变异性，以实现受调控的集体反应。本项目的重点是IL-2作为一种关键的细胞因子，它控制效应T细胞之间的群体感应和调节性T细胞的抑制。我们的方法基本上是跨学科的，伴随着计算建模和实验测试。它包括做出和验证理论预测，以量化和控制免疫反应如何作为单个T细胞的动态和集体调节属性出现。公共卫生相关性：我们的项目专注于开发经过实验验证的T细胞激活的计算机模型。我们的目标是确定可靠的免疫反应是如何从个体T细胞的不可靠激活中动态出现的。我们研究的长期影响是更好地控制对癌症和自身免疫性疾病免疫疗法的免疫反应。