COMPUTATIONAL AND FUNCTIONAL APPROACHES TO VALIDATING CANCER GENOME TARGETS

描述（由申请人提供）：该提议的CTDD计划将有助于将高通量癌症基因组表征的巨大资源转化为功能验证的基于癌症基因型的治疗靶标。在过去的几年里，该项目的成员已经开发出功能注释癌症基因组的强大工具和策略。这些已经使得能够识别和验证超过50个癌症基因，其中一些是引人注目的治疗靶点。在这里，我们建议将这些策略综合和优化成一个统一的蓝图，可以应用于许多肿瘤类型。我们哲学的核心是使用强大的计算工具来缩小必须进行功能调查的基因组范围。这使得能够使用更精确的人类和小鼠模型来评估无法在全基因组范围内进行的驱动因素和依赖性以及组合相互作用的方法。我们将应用这些工具来选择癌症类型和基因集，以确定新的致癌驱动因素，基因型特异性癌症依赖性，并测试系统识别联合治疗靶点的策略。我们设想我们项目的影响不仅是确定几种肿瘤类型的基因组信息靶点，而且还提供了可在整个联盟和社区使用的工具和策略。 公共卫生相关性：基因组学的技术突破使许多人类肿瘤类型的遗传异常的全面表征成为可能。现在需要的是同样强大的方法，用于将这些基因组特征转化为功能验证的癌症治疗靶点，并最终成为新的治疗方法。我们建议将信息学、功能学和体内策略综合并优化为统一的蓝图 可以应用于多种肿瘤类型。

DESCRIPTION (provided by applicant): This proposed CTDD program will help translate the enormous resource of high- throughput cancer genome characterizations into functionally validated, cancer-genotype based therapeutic targets. Over the past several years, members of this project have developed powerful tools and strategies for functionally annotating cancer genomes. These have enabled the identification and validation over fifty cancer genes, several of which are compelling therapeutic targets. Here, we propose to synthesize and optimize those strategies into a unified blueprint that can be applied across many tumor types. At the core of our philosophy is the use of powerful computational tools to narrow the extent of the genome that must be surveyed functionally. This enables the use of more precise human and mouse models to assess drivers and dependencies and approaches to combinatorial interactions that could not be carried out on a genome wide scale. We will apply these tools to select cancer types and gene sets in order to identify new oncogenic drivers, genotype-specific cancer dependencies, and to test strategies for the systematic identification of targets for combination therapies. We envision the impact of our project not only as the identification of genomically informed targets for several tumor types but also as providing tools and strategies that can be used throughout the consortium and the community. PUBLIC HEALTH RELEVANCE: Technological breakthroughs in genomics have enabled a comprehensive characterization of the genetic abnormalities in many human tumor types. What is needed now are equally powerful methods for translating these genomic characterizations into functionally validated cancer therapeutic targets and ultimately new treatments. We propose to synthesize and optimize informatics, functional, and in vivo strategies into a unified blueprint that can be applied across many tumor types.