Paracrine TGF-Beta Signaling in Tumor Initiation and Progression

该提案旨在建立范德比尔特大学肿瘤微环境网络(VUTMEN)，以 有助于全面了解肿瘤间质在癌症中的作用 发病、进展和转移。VUTMEN使用的战略是将我们的努力集中在 了解宿主的关键生物介质--肿瘤所使用的下游机制 互动：TGFBeta。项目1使用复杂的小鼠遗传学和先进的蛋白质组技术来 确定影响乳腺的肿瘤下游效应因子和间质转化生长因子|3信号通路 腺体肿瘤的发生。项目2使用了人类前列腺癌和小鼠模型的组合 细胞和组织重组模型研究TGFP调节前列腺的效应 致癌。转化生长因子β在调控乳腺转移瘤生长的恶性循环中的作用 在骨骼是项目3的主题。所有结果都将在人类肿瘤样本中进行跟踪。VUTMEN 支持3个带来最先进技术和系统生物学的综合共享资源 三个VUTMEN项目的方法。蛋白质收集和蛋白质组学核心提供蛋白质组学 与肿瘤微环境特别相关的技术，包括微透析和成像质量 光谱学。图像融合核心致力于新的成像策略，以增强 对肿瘤微环境的理解，包括多参数和多模式方法 这就是众所周知的图像融合。生物数学和生物信息学核心开发了新的方法 分析复杂的数据集，并为迭代假设生成和生成数学模型 测试。我们认为，公认的肿瘤微环境的复杂性可以通过 将重点放在TGFbeta的关键调控途径上的策略。这将通过以下方式实现 对已知的TGFβ下游分子调节器的系统检查和发现 使用蛋白质组学方法的新方法，实时检测体内的生物效应，并将 使用遗传操作和图像融合技术的分子参数结果，使用 迭代地生成假设并通过实验验证它们的数学建模，并比较 导致了三个不同但相关的器官部位。我们的目标是全面了解 转化生长因子β控制肿瘤与其相互作用的机制 微环境。

This proposal seeks to establish the Vanderbilt University Tumor Microenvironment Network (VUTMEN) to contribute to the generation of a comprehensive understanding of the role of the tumor stroma in cancer initiation, progression, and metastasis. The strategy used by the VUTMEN is to focus our efforts on understanding the downstream mechanisms used by a critical biological mediator of host:tumor interactions.TGFbeta. Project 1 uses sophisticated mouse genetics and advanced proteomic technologies to identify the downstream effectors of tumor and stromal TGF|3 signaling pathways that influence mammary gland tumorigenesis. Project 2 uses a combination of human prostate cancer and mouse model-derived cells and the tissue recombination model to examine the effectors of TGFp that modulate prostatic carcinogenesis. The role of TGFbeta in driving the vicious cycle that regulates the growth of breast metastases in bone is the topic of Project 3. All results will be followed up in human tumor samples. The VUTMEN supports 3 "Integrative Shared Resources" that bring state-of-the-art technologies and a systems biology approach to the three VUTMEN projects. The Protein Collection and Proteomics Core provides proteomic technologies specifically relevant to the tumor microenvironment, including microdialysis and imaging mass spectroscopy. The Image Fusion Core is devoted to novel imaging strategies that enhance the understanding of the tumor microenvironment, including a multi-parametric and multi-modality approach known as image fusion. The Biomathematics and Bioinformatics Core develops new approaches to analyzing complex data sets and generates mathematical models for iterative hypothesis generation and testing. We propose that the acknowledged complexity of the tumor microenvironment can be unraveled by the strategy of focusing our efforts on the key regulatory pathway of TGFbeta. This will be achieved through the systematic examination of known molecular modulators that are downstream of TGFbeta and the discovery of new ones using proteomic approaches, examining biological effects in vivo in real time and correlating the results with molecular parameters using genetic manipulation and image fusion technologies, using mathematical modeling to iteratively generate hypotheses and test them experimentally, and comparing the results in three distinct but related organ sites. Our goal is to generate a comprehensive understanding of the mechanisms used by TGFbeta to control the reciprocal interactions between a tumor and its microenvironment.