Dissection of the Modular Structure of Cancer Signaling Systems

描述（由申请人提供）： 人类癌症的发展是一个多步骤的过程，其中未来的癌细胞获得原癌基因、肿瘤抑制基因和其他调控基因的突变等位基因。这些基因中的许多或大多数是信号相关蛋白，我们在这里关注的是控制癌症相关增殖，迁移和内吞过程的信号网络的设计原则。我们将测试以下关键问题：1）这些癌症相关的信号网络是否具有模块化结构; 2）癌细胞是否具有在正常细胞中无法观察到的缺失或添加的信号模块。 我们已经取得了重大进展，以回答这些问题，通过开发一种方法来创建2304体外切丁酶产生的siRNA对人类信号蛋白的核心集。使用这些siRNA，我们已经发现了STIM 1的功能，STIM 1是ER腔中的一种Ca 2+传感器，控制Ca 2+流入细胞，也可以作为肿瘤抑制因子。我们还开发了基于定量显微镜的测量工具来跟踪信号传递过程和细胞功能。该提案的第一阶段将证明使用基于显微镜的siRNA策略来研究多种癌症相关细胞功能的总体可行性。第2阶段将使用6000个siRNA的扩展组来解决上述问题，重点关注6种细胞类型、3种非转化细胞系和3种乳腺癌上皮细胞系。我们将筛选以确定改变增殖，细胞迁移或内吞作用的信号siRNA，然后利用我们开发的活细胞生物传感器进行后续研究，以测量不同细胞周期阶段的持续时间，以及迁移速度和其他动力学参数。然后，我们将使用二次siRNA筛选将改变这些细胞功能的基因与癌症相关信号通路的子集联系起来。 基于这些功能和信号数据集，我们将使用聚类方法创建信号系统的模块化地图。我们将实验性地测试使用有效siRNA对的扰动的模块化图的预测能力。我们将展示信号系统中的模块化是否以及如何用于预测如何使用siRNA的组合来操纵细胞功能，并了解是否存在以及存在哪些区别特征来定义癌症与非癌细胞中信号系统的模块化。这将可能导致新的癌症药物靶点和新的治疗策略的确定。

DESCRIPTION (provided by applicant): The development of human cancer is a multistep process in which future cancer cells acquire mutant alleles of proto-oncogenes, tumor-suppressor genes, and other regulatory genes. Many or most of these genes are signaling related proteins and we are focusing here on the design principles of signaling networks that control the cancer related processes of proliferation, migration and endocytosis. We will test the key questions of 1) whether these cancer related signaling networks have a modular structure and 2) whether cancer cells have missing or added signaling modules that cannot be observed in normal cells. We have made significant advances to answer these questions by developing a method to create 2304 in vitro Dicer generated siRNAs against a core set of human signaling proteins. Using these siRNAs, we have already discovered the function of STIM1, a Ca2+ sensor in the ER lumen that controls Ca2+ influx into cells, and which also acts as a tumor suppressor. We have also developed quantitative microscopy- based measurement tools to track signaling processes and cell functions. Phase 1 of the proposal will demonstrate the overall feasibility of using a microscopy-based siRNA strategy to investigate multiple cancer-related cell functions. Phase 2 will address the questions posed above using an expanded set of 6000 siRNAs and a focus on six cell-types, 3 non-transformed and three breast cancer epithelial cell lines. We will screen to identify signaling siRNAs that alter proliferation, cell migration or endocytosis and then utilize follow-up studies with live cell biosensors that we developed to measure the duration of different cell cycle phases, as well as migration velocity and other kinetic parameters. We will then link genes that alter these cell functions to a subset of cancer-relevant signaling pathways using secondary siRNA screens. Based on these functional and signaling datasets, we will create a modular map of signaling systems using clustering methods. We will experimentally test the predictive power of modular maps using perturbations with pairs of effective siRNAs. We will show if and how modularity in a signaling system can be used to predict how cell functions can be manipulated using combinations of siRNAs and learn if and what distinguishing features exist that define modularity of signaling systems in cancer versus non-cancer cells. This will likely lead to the identification of new cancer drug targets and new therapeutic strategies.