Systems Biology of Fibroblast Activation Following Myocardial Infarction

 描述（由申请人提供）：约四分之一的心肌梗死（MI）患者进展为充血性心力衰竭，其5年死亡率为50%。该项目的目标是通过建立和验证成纤维细胞激活的时间演变的计算机模拟计算模型来了解MI后成纤维细胞的作用。我们的初步结果表明，成纤维细胞进行了一系列的激活配置文件超过第一个 心肌梗死后28天，改变成纤维细胞反应可以改变左心室（LV）的重塑。我们假设成纤维细胞经历时间表型演变以协调MI后LV重塑表型。我们的具体目标是：1）构建模拟MI后时间过程中成纤维细胞活化模式的计算机模拟计算模型; 2）干扰内源性细胞因子和生长因子信号传导途径以评估系统并优化模型稳健性。（3）检查内源ECM影响以评估模型的可预测性。这个建议的创新在于成纤维细胞调节重塑作为一个连续的表型的概念，实验和计算方法的整合将使我们能够建立一个预测的计算工具。这些研究的潜在结果将是：1）开发模拟MI后成纤维细胞活化的计算工具; 2）鉴定预测V重塑结果的成纤维细胞活化标志物; 3）识别可通过治疗调节来调节成纤维细胞活化的关键纤维化机制。

 DESCRIPTION (provided by applicant): About one in four myocardial infarction (MI) patients progress to develop congestive heart failure, which has a 50% 5-year mortality rate. The goal of this project is to understand post-MI roles of the fibroblast by establishing and validating an in silico computational model of the temporal evolution of fibroblast activation. Our preliminary results demonstrate that fibroblasts proceed through a series of activation profiles over the first 28 days post-MI and that modifying fibroblast responses can alter remodeling of the left ventricle (LV). We hypothesize that fibroblasts undergo a temporal phenotype evolution to coordinate the post-MI LV remodeling phenotype. Our specific aims are: 1) construct an in silico computational model that simulates fibroblast activation patterns over the post-MI time course; 2) Perturb endogenous cytokine and growth factor signaling pathways to evaluate the system and optimize model robustness.; and 3) Examine endogenous ECM influences to evaluate model predictability. The innovation of this proposal lies in both the concept that fibroblasts regulate remodeling as a continuum of phenotypes and that integration of experimental and computational approaches will allow us to establish a predictive computational tool. The potential outcome of these studies will be 1) the development of a computational tool to simulate fibroblast activation post-MI; 2) the identification of fibroblast activation markers that predict V remodeling outcomes; and 3) recognition of key fibrotic mechanisms that can be therapeutically modulated to regulate fibroblast activation.