Molecular wiring and therapeutic targeting of the TSC-Rheb signaling network

项目总结（见说明）：详细了解常见的致癌信号通路如何组装成更大的信号网络，对于制定治疗策略以正确靶向癌症中的这些通路以及解释靶向治疗的临床结果至关重要。虽然在不同类型的人类癌症中占主导地位的受影响的癌基因和肿瘤抑制因子可能差异很大，但在大多数人类癌症中，少数高度整合的信号传导节点受到影响，而不管起源的组织如何。重要的是要了解这些关键信号节点是如何调节的，以及下游对肿瘤发展、进展和治疗的影响。在这个项目中，我们专注于一个这样的节点，涉及TSC 1-TSC 2复合物和Ras相关的小G蛋白Rheb，它在几乎所有的遗传肿瘤综合征和最常见的散发性癌症中受到异常调节。目前，这种小G蛋白开关的唯一已知下游靶标是雷帕霉素的哺乳动物靶标（mTOR）。该项目的目标将采用基于P01前4年研究的假设驱动方法，以及无偏倚的基因组和蛋白质组筛选。目的是1）揭示TSC-Rheb信号网络中的新组分，连接和下游靶标，2）鉴定和表征以前未探索的治疗策略，以靶向肿瘤中的该网络，3）鉴定新的生物标志物以预测和监测治疗反应，4）作为基于发现的平台，以推动该计划项目2和3中的临床前元素，以及5）生物信息学地分析和整合在该计划的所有项目中产生的大型跨物种数据集。为了实现这些目标，我们将在果蝇（Perrimon实验室）中紧密结合高通量技术，在哺乳动物细胞和肿瘤模型（Manning实验室）中进行机制表征和验证

PROJECT SUMMARY (See instructions): A detailed understanding of how common oncogenic signaling pathways are assembled into larger signaling networks is essential to developing therapeutic strategies to properly target these pathways in cancer and for interpreting clinical outcomes from targeted therapeutics. While the effected oncogenes and tumor suppressors that predominate different classes of human cancer can vary greatly, a small number of highly integrated signaling nodes are affected in the majority of human cancers, regardless of tissue of origin. It is important to understand how these key signaling nodes are regulated and what the downstream consequences are for tumor development, progression, and treatment. In this project, we focus on one such node, involving the TSC1-TSC2 complex and the Ras-related small G protein Rheb, which is aberrantly regulated in nearly all genetic tumor syndromes and the most common forms of sporadic cancer. Currently, the only known downstream target of this small G protein switch is the mammalian target of rapamycin (mTOR). The aims of this project will employ both hypothesis-driven approaches, based on studies from the first 4 years of this P01, and unbiased genomic and proteomic screens. The aims are designed to 1) reveal new components, connections, and dowstream targets within the TSC-Rheb signaling network, 2) identify and characterize previously unexplored therapeutic strategies to target this network in tumors, 3) identify novel biomarkers to predict and monitor therapeutic responses, 4) serve as a discovery-based platform to fuel the preclinical elements in projects 2 and 3 of this program, and 5) bioinformatically analyze and integrate the large cross-species data sets generated within all projects of the program. To achieve these goals, we will closely integrate high-throughput technologies in Drosophila (Perrimon laboratory) with mechanistic characterization and validation in mammalian cell and tumor models (Manning laboratory