Clinically-Relevant Regulatory Networks in the Lung Tumor Microenvironment

描述（由申请人提供）：肺癌是美国癌症死亡的主要原因，2009年约有16万人死亡。涉及肺癌发生和进展的分子机制尚不清楚。最近的证据表明，恶性细胞与其微环境之间存在复杂的相互作用。然而，我们对肿瘤微环境作用的大部分知识来自于分离恶性细胞与微环境单一组分之间沿单一途径相互作用的研究。我们将重建肺腺癌的第一个肿瘤微环境相互作用组（Tumor Microenvironment Interactome， TMI），它将识别人类恶性细胞及其相关浸润性免疫细胞、内皮细胞和成纤维细胞之间的细胞内和细胞间的全局调节相互作用。TMI将来源于使用荧光激活细胞分选直接从人肺癌标本中获得的特定肿瘤微环境细胞群的全局基因表达分析（specific Aim 1）。TMI将使用新的计算方法来推断基因模块之间的调节（Specific Aim 2）。从TMI，我们将确定候选的介导因子，如分泌细胞因子，调节过程跨越多个细胞亚群。我们将特别关注与生存结果最相关的因素，通过利用具有长期生存结果的公共领域表达数据（Specific Aim 2）。我们将在验证研究中使用细胞系和动物模型的组合来测试候选介导因子对肿瘤行为的影响（Specific Aim 3）。通过重建的TMI，我们将对肺肿瘤微环境有更全面的了解。我们的最终目标是确定生物学和临床相关的分子靶点，用于开发更有效的肺癌治疗方法。肺腺癌TMI也将向科学研究界公开，作为评估感兴趣基因作用的假设生成工具。

DESCRIPTION (provided by applicant): Lung cancer is the leading cause of cancer death in the United States, accounting for approximately 160,000 deaths in 2009. The molecular mechanisms implicated in lung cancer development and progressions are not well understood. Recent evidence points to a complex interaction between the malignant cells and their microenvironment. However, much of our knowledge of the role of the tumor microenvironment comes from studies isolating the interactions between the malignant cells and a single component of the microenvironment, along a single pathway. We will reconstruct the first Tumor Microenvironment Interactome (TMI) of lung adenocarcinoma, which will identify global intra- and inter-cellular regulatory interactions between human malignant cells and their associated infiltrating immune cells, endothelial cells and fibroblasts. The TMI will be derived from global gene expression analysis of specific tumor microenvironment cell populations directly obtained from human lung cancer specimens using fluorescence-activated cell sorting (Specific Aim 1). The TMI will be reconstructed using novel computational approaches for inferring regulation among modules of genes (Specific Aim 2). From the TMI, we will identify candidate mediating factors, such as secreted cytokines, that regulate processes across the multiple cell subpopulations. We will specifically focus on the factors most associated with survival outcomes, by leveraging public domain expression data with long term survival outcomes (Specific Aim 2). We will use a combination of cell lines and animal models in the validation studies to test the effect of the candidate mediating factors on tumor behavior (Specific Aim 3). Through the reconstructed TMI, we will create a more global understanding of the lung tumor microenvironment. Our ultimate goal is to identify biologically and clinically relevant molecular targets that could be used to develop more effective therapies for lung cancer. The lung adenocarcinoma TMI will also be made publically available to the scientific research community as a hypothesis generation tool for evaluating the role of genes of interest.