Integrated genomic approaches to identify and validate cancer targets

描述（由申请人提供）：大多数人类肿瘤，特别是那些来自上皮性癌症的肿瘤，表现出全局基因组改变，这使得很难识别对细胞转化至关重要的突变，也很难确定特定癌症相关突变的后果。识别人类癌症结构变化的技术最近取得了进展，现在可以考虑列举特定肿瘤所包含的所有遗传改变。尽管在癌症基因组的结构改变注释方面取得了这些进展，但识别特定扩增或缺失事件靶向的基因以及破译靶向基因突变的功能仍然是一个主要挑战。事实上，为了从癌症基因组的结构描述中提炼出经过验证的癌症靶点，有必要同时开发有效的方法来注释癌症相关基因的功能。

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.