Genetic Analysis of the Breast Tumor Microenvironment

描述（由申请人提供）：肿瘤基质是肿瘤的一个组成部分，通过未知机制与上皮肿瘤细胞共同进化，并提供有利于肿瘤发生和进展的环境。然而，基质的改变是否有助于乳腺癌表型的多样性、异质性和可塑性，以及患者的治疗反应和临床结果尚不清楚。我们结合小鼠模型的初步数据表明，Pten和p53通路在乳腺间质成纤维细胞中发挥关键和独特的肿瘤抑制作用。与此同时，人类乳腺肿瘤基质的基因表达谱已经确定了不同的基质亚类，可以独立于既定的临床变量和既定的分子肿瘤亚型预测患者的预后。将Pten-null和p53-null小鼠成纤维细胞的基因特征与人类肿瘤间质特征进行比较表明，小鼠特征存在于人类肿瘤间质中，可以帮助对主要与非腔内乳腺癌相关的基质亚类进行分层，并可以预测患者预后不良。

DESCRIPTION (provided by applicant): 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. However, whether alterations in the stroma contribute to the diversity, heterogeneity and plasticity of breast cancer phenotypes, and to the therapeutic responses and clinical outcome in patients is unknown. Our combined preliminary data using mouse models suggests that the Pten and p53 pathways play key and distinct tumor suppressor roles in stromal fibroblasts of the mammary gland. In parallel, gene expression profiling of human breast tumor stroma has identified distinct subclasses of stroma that can predict patient outcomes independent of established clinical variables and the established molecular tumor subtypes. Comparison of gene signatures from Pten-null and p53-null mouse fibroblasts to human tumor stroma signatures show that the mouse signatures are present in human tumor stroma, can help stratify stromal subclasses associated with predominantly non-luminal breast cancers, and can predict poor patient outcome. The overall hypothesis for this proposal is that defining the pathways that regulate tumor-stroma crosstalk will lead to better stratification of breast cancer patients, better informed application of current therapies to patients that are most likely to benefit from them, and to the development of new therapies that target the tumor-stromal interactions uncovered by our studies. Our combined mouse-human approach will utilize novel genetic, genomic and proteomic technologies developed by our groups to 1) expose how stromal cells use integrated transcriptional programs to communicate between themselves and with tumor cells during the initial stages of malignancy, and 2) to identify stromal expression profiles that can better stratify breast cancer patients, predict clinical outcome and be used for serum-based diagnostics. The synergistic efforts between the three projects, utilizing a combined mouse-human approach, is only effective because of the unique expertise and technologies provided by each group with a focus on the single task of understanding the tumor-stroma dialogue in human breast cancer, and in translating such basic information to stratify stroma subclasses, predict clinical outcome and develop specific treatments for individual patients.