Functionally Validated Lentiviral siRNA libraries

描述（由申请人提供）：尽管在阐明人类疾病的分子基础方面取得了快速进展，但表面上更困难的后基因组挑战是疾病特异性信号通路的功能注释，并将这些信息整合到新药开发中。RNA干扰（RNAi）现在使得使用大规模功能基因组策略进行靶标鉴定成为可能。不幸的是，虽然RNAi已经为改善药物发现过程开辟了许多潜在的途径，但这些途径仍然只是潜在的机会，直到我们开发出强大的RNAi筛选技术，以及用于数据验证和将这些信息整合到基于操作细胞的模型中的实验和生物信息学工具。为了解决这些问题，在第一阶段，我们开发了第二代功能验证（FV）人类可药物基因组慢病毒15K shRNA文库，并且我们已经证明了它们在破译细胞信号通路方面的实用性。II期研究的最终目标是开发和建立一个具有成本效益的新型功能基因组学平台，以促进治疗性分子靶点的发现。具体而言，我们建议扩大开发和商业化一套全面的人类和小鼠全基因组FV shRNA文库。这些文库将具有更高的性能，并设计用于高通量（HT）测序具有成本效益的池格式筛选和效应物鉴定。作为支持工具，我们将开发方案、试剂和软件工具，用于体外和体内筛选命中验证和治疗靶点优先排序。为了测试我们的功能基因组学平台的性能，我们建议使用我们新的RNAi资源来描述乳腺上皮细胞中肿瘤发生的过程。我们将在一组独特的等基因人乳腺上皮细胞（HMEC）系中进行合成致死性筛选，这些细胞系包含最相关的乳腺癌遗传改变。此外，我们将在使用完全转化的hmec和普通乳腺癌细胞系的异种移植模型中验证我们的体外筛选结果。然后，我们的发现将与从科学出版物中收集的数据相结合，并在公开的知识库中呈现，最终目标是开发特异性控制乳腺癌细胞增殖和存活的信号通路模型。这些开发的RNAi筛选、验证和软件工具将作为产品和定制服务商业化，为研究界提供高度模块化、具有成本效益的研究方法，旨在理解和整合信号转导网络的动态变化，并最终描绘疾病特异性表型。因此，我们预见这些工具集将显著提高阐明和建模疾病特异性信号转导网络的效率、经济性和便利性，并为基础研究人员提供现有商用试剂和软件的首选、成本效益高的替代方案。所提出的RNAi筛选和生物信息学策略具有相当大的潜力，可以系统地识别新的抗癌靶点进行治疗干预，并促进高度特异性药物、生物标志物和新治疗概念的发展。

DESCRIPTION (provided by applicant): Despite rapid advances in elucidating the molecular basis of human diseases, an ostensibly more difficult post-genomic challenge is the functional annotation of disease-specific signaling pathways and integration of this information into the development of novel drugs. RNA interference (RNAi) now makes it possible to use large-scale functional genomic strategies for target identification. Unfortunately, while RNAi has opened many potential avenues for improving the drug discovery process, these avenues remain only potential opportunities until we develop robust RNAi screening technologies, as well as experimental and bioinformatics tools for data validation and integration of this information into operational cell-based models. To address these issues, in Phase I, we developed second generation functionally validated (FV) human druggable genome lentiviral 15K shRNA libraries, and we have demonstrated their utility for deciphering cell- signaling pathways. The ultimate goal of the Phase II studies is to develop and establish a cost-effective novel functional genomics platform to facilitate the discovery of therapeutic molecular targets en masse. Specifically, we propose to scale-up development of and commercialize a comprehensive set of human and mouse genome- wide FV shRNA libraries. These libraries will have improved performance and be designed for cost-effective pooled-format screening and identification of effectors by high-throughput (HT) sequencing. As supporting tools, we will develop protocols, reagents and software tools for in vitro and in vivo screening hit validation and therapeutic target prioritization. To test the performance of our functional genomics platform, we propose to use our novel RNAi resource to delineate the processes that underlie tumorigenesis in breast epithelial cells. We will perform synthetic lethality screens in a unique panel of isogenic human mammary epithelial cell (HMEC) lines that comprise the most relevant breast cancer genetic alterations. Furthermore, we will validate the results of our in vitro screens in xenograft models using both fully transformed HMECs and common breast cancer cell lines. Our findings will then be combined with data collected from scientific publications and presented in a publicly available knowledge base, with the ultimate goal of developing models of signaling pathways that specifically control the proliferation and survival of breast cancer cells. These developed RNAi screening, validation and software tools will be commercialized as products and custom services to provide the research community with highly modular, cost-effective approaches for studies aimed at understanding and integrating dynamic changes in signal transduction networks and ultimately delineating disease-specific phenotypes. As a result, we foresee that these toolsets will significantly improve the efficiency, economy and ease of elucidating and modeling disease-specific signal transduction networks and provide basic researchers with preferred, cost-effective alternatives to existing commercially available reagents and software. The proposed RNAi screening and bioinformatics strategies harbor considerable potential to systematically identify new anti-cancer targets for therapeutic intervention and to facilitate the development of highly specific drugs, biomarkers and novel therapeutic concepts. PUBLIC HEALTH RELEVANCE: The ultimate goal of the Phase II project is to develop and make commercially available a novel orthogonal functional genomics platform to facilitate discovery and validation of therapeutic molecular targets en masse. As a first step, we propose to develop and make commercially available a set of second generation of functionally-validated genome-wide human and mouse 65K pooled shRNA lentiviral libraries with improved performance and optimized design for cost-effective genetic screens. As a confirmation tool, we will develop protocols for high-throughput in-vitro and ex-vivo validation of drug target candidates identified in the screen with pooled shRNA sublibraries. From a bioinformatics viewpoint, we will make software tools for integration of RNAi screening data with transcriptome profiling and molecular network information mined from scientific literature. The proposed functional genomics platform will be applied and validated for the discovery of novel cancer therapeutic targets in a unique collection of isogenic human mammary epithelial cell (HMEC) lines, comprising the most common breast cancer genetic alterations. As a result of these studies we will reconstruct synthetic lethality pathways and make publicly available breast cancer knowledge database. These developed RNAi screening, validation and software tools will be commercialized as products and custom services to provide the research community with highly modular, cost-effective approaches for studies aimed at understanding and integrating dynamic changes in signal transduction networks and ultimately delineating disease-specific phenotypes. As a result, we foresee that these toolsets will significantly improve the efficiency, economy and ease of elucidating and modeling disease-specific signal transduction networks and provide basic researchers with preferred, cost-effective alternatives to existing commercially available reagents and software. The proposed RNAi screening and bioinformatics strategies harbor considerable potential to systematically identify new anti-cancer targets for therapeutic intervention and to facilitate the development of highly specific drugs, biomarkers and novel therapeutic concepts.