Integrated genomic approaches to identify and validate cancer targets

描述(申请人提供)：大多数人类肿瘤，特别是那些源自上皮癌的肿瘤，表现出全球基因组变化，这使得识别对细胞转化至关重要的突变和定义特定癌症相关突变的后果变得困难。最近在识别人类癌症结构变化的技术上的进步使人们有可能考虑列举特定肿瘤所包含的所有基因变化。尽管在注释癌症基因组的结构变化方面取得了这些进展，但识别特定扩增或缺失事件的靶向基因并破译靶向基因突变的功能仍然是一个重大挑战。事实上，同时开发有效的方法来注释癌症相关基因的功能，对于从癌症基因组的结构描述中提取有效的癌症靶点是必要的。 这项提议的重点是整合新开发的高通量方法来对癌症基因组进行功能注释。具体地说，进行大规模功能丧失、功能获得和蛋白质-蛋白质网络分析的方法将被结合在一个新的集成计划中，以识别和验证重要的功能癌症基因。具体地说，这些研究建立在我们实验室开发和实施基因组规模的RNA干扰文库、完整的人类开放阅读框架(ORF)集合和全面的蛋白质-蛋白质相互作用图的先前工作的基础上。尽管进行大规模研究所需的基本工具现在已经可用，但这种全基因组方法的整合代表着一项全新的努力，需要进一步开发这些新兴技术，制造全面的试剂，并创造新的方法来连接这些数据集，以实现比以前所做的更大的规模。因此，R33应用程序的首要目标是以集成的方式应用这些技术，同时识别和验证治疗靶向的特定前景基因。这些研究的长期目标是为在基因组规模上扩大这些努力提供基础。

DESCRIPTION (provided by applicant): Most human tumors, particularly those derived from epithelial cancers, exhibit global genomic alterations that make it difficult to identify mutations critical for cell transformation and to define the consequences of specific cancer-associated mutations. Recent advances in technologies to identify structural changes in human cancers now make it possible to consider enumerating all of the genetic alterations harbored by a particular tumor. Despite these advances in annotating structural alterations in cancer genomes, identifying the genes targeted by specific amplification or deletion events and deciphering the function of targeted gene mutations remains a major challenge. Indeed, the parallel development of efficient methods to annotate the function of cancer-associated genes is necessary to distill validated cancer targets from this structural description of cancer genomes. This proposal focuses on the integration of newly developed, high throughput methods to functionally annotate the cancer genome. Specifically, methods to perform large scale loss-of function, gain-of-function, and protein-protein network analyses will be combined in a novel integrated program to identify and validate functionally important cancer genes. Specifically, these studies build upon prior work by our laboratories to develop and implement genome scale RNA interference libraries, complete collections of human open reading frames (ORFs) and comprehensive protein-protein interaction maps. Although the basic tools required to perform large-scale studies are now available, the integration of such whole genome approaches represents an entirely new endeavor that requires the further development of these nascent technologies, the fabrication of comprehensive reagents and the creation of new ways to connect these datasets to achieve a scale beyond what has been previously performed. As such, the overarching goals of this R33 application is to apply these technologies in an integrated manner while simultaneously identifying and validating genes of particular promise for therapeutic targeting. The long-term goal of these studies is to provide a foundation for the expansion of these efforts at genome scale.