Suppression of Mammary Tumorigenesis by Stromal p53

项目总结(见说明)： 肿瘤间质是肿瘤的组成部分，通过未知的机制重新编程，与上皮性肿瘤细胞共同进化，为肿瘤的发生和发展提供有利的环境。这种多样性是如何建立起来的，以及促进肿瘤发生所必需的细胞之间的特定通信机制是完全未知的。 我们建议采用鼠-人结合的方法，利用新的遗传、基因组和蛋白质组技术来揭示乳腺癌初期间质成纤维细胞中的P53如何与肿瘤细胞和其他肿瘤微环境进行沟通。最重要的假设是： 间质成纤维细胞中P53通路的破坏改变了肿瘤与间质的联系，加速了乳腺肿瘤的发生和发展，并导致了乳腺癌患者肿瘤的多样性和异质性。 该项目包括三个目标。第一个目标将使用小鼠模型来识别在肿瘤进展的特定阶段的四个不同的乳腺/肿瘤细胞间隔中的P53调节的转录(mRNA和miR)程序。AIM 2也是一个基于发现的AIM，它将定义从AIM 1中描述的小鼠乳腺/肿瘤中分离的激光捕获显微解剖(LCM)基质和肿瘤间隔的蛋白质组学特征。转录组和蛋白质组数据集将被整合，以开发肿瘤微环境中跨细胞类型的信号机制模型。AIM 3将结合来自AIMS 1和2的小鼠数据集与来自患者乳腺肿瘤间质的转录组和蛋白质组数据集，以识别提供对乳腺癌生物学的洞察的信号，并指导患者亚型分层，预测临床结果，并开发专门针对肿瘤间质的小化合物。 我们项目的一个重要方面是结合使用遗传小鼠模型和人类模型来确定与人类乳腺癌生物学最相关的间质-肿瘤串扰的机制。 这种鼠人结合的方法交叉分析小鼠和人类患者间质数据集，有望改善间质亚类和分子患者亚型的分层，预测临床结果的能力，并与新的生物信息学方法一起，指导针对肿瘤-间质对话意外过程的化合物的识别。

PROJECT SUMMARY (See instructions): The tumor stroma is an integral part of the tumor that becomes reprogrammed by unknown mechanisms to co-evolve with epithelial tumor cells and provide an environment conducive for tumor initiation and progression. The mechanisms involved in how this diversity is established and the specific communication between cells that is necessary for fostering tumorigenesis is completely unknown. We propose to take a combined mouse-human approach that utilizes novel genetic, genomic and proteomic technologies to expose how p53 in stromal fibroblasts communicate with tumor cells and the rest of the tumor microenvironment during the initial stages of breast cancer. The Overarching Hypothesis is: Disruption of the p53 pathway in stromal fibroblasts alters tumor-stroma communication, accelerates the initiation and progression of mammary tumors and contributes to the diversity and heterogeneity observed in tumors of human breast cancer patients. This Project includes three aims. The first aim will use mouse models to identify p53-regulated transcriptional (mRNA and miR) programs in four separate cell compartments of mammary glands/tumors at defined stages of tumor progression. AIM 2 is also a discovery-based aim that will define proteomic profiles of laser-capture microdissected (LCM) stroma and tumor compartments isolated from mammary glands/tumors of mice described in AIM 1. Transcriptome and proteomic data sets will be integrated to develop mechanistic models of signaling across cell types in the tumor microenvironment. AIM 3 will combine mouse derived data sets from AIMs 1 & 2 with transcriptome and proteomic data sets derived from patient breast tumor stroma to identify signatures that provide insights into the biology of breast cancer, and to instruct patient subtype stratification, predict clinical outcome and develop small compounds that specifically target the tumor stroma. A significant aspect of our project is the combined use of genetic mouse models and human models to identify the mechanisms of stroma-tumor crosstalk that are most relevant to human breast cancer biology. This combined mouse-human approach to cross-analyze mouse and human patient stroma data sets holds the promise to improve the stratification of stromal subclasses and molecular patient subtypes, the ability to predict clinical outcome, and together with novel bioinformatics approaches, to guide the identification of compounds that target unexpected processes of the tumor-stroma dialogue.