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，其通过未知机制重新编程以与上皮肿瘤细胞共同进化并提供有利于肿瘤起始和进展的环境。这种多样性是如何建立的机制以及促进肿瘤发生所必需的细胞之间的特定通信是完全未知的。 我们建议采取一种结合小鼠-人的方法，利用新的遗传学，基因组学和蛋白质组学技术来揭示在乳腺癌的初始阶段，基质成纤维细胞中的p53如何与肿瘤细胞和肿瘤微环境的其余部分进行通信。Overseas Hypothesis是： 间质成纤维细胞中p53通路的破坏改变了肿瘤-间质通讯，加速了乳腺肿瘤的发生和发展，并有助于在人类乳腺癌患者的肿瘤中观察到的多样性和异质性。 该项目包括三个目标。第一个目标将使用小鼠模型，以确定在肿瘤进展的定义阶段，在乳腺/肿瘤的四个单独的细胞区室中p53调节的转录（mRNA和miR）程序。AIM 2也是一个基于发现的目标，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切割（LCM）基质和肿瘤区室的蛋白质组学谱。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传导机制模型。AIM 3将结合联合收割机小鼠从AIM 1和2的数据集与转录组和蛋白质组数据集从患者乳腺肿瘤间质，以确定签名，提供深入了解乳腺癌的生物学，并指导患者亚型分层，预测临床结果和开发小的化合物，特异性靶向肿瘤间质。 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基质-肿瘤串扰机制。 这种结合小鼠-人的方法来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鉴定靶向肿瘤-间质对话的意外过程的化合物。

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.