COMPUTATIONAL AND FUNCTIONAL APPROACHES TO VALIDATING CANCER GENOME TARGETS

验证癌症基因组目标的计算和功能方法

• 批准号: 8464686
• 负责人: Scott Powers
• 金额: $ 130.73万
• 依托单位: COLD SPRING HARBOR LABORATORY
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-05-01 至 2017-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8464686
• 关键词: Area; Bioinformatics; Biological; Biological Assay; Cancer Model; Cancer cell line; Collaborations; Combined Modality Therapy; Communities; Complementary DNA; Custom; Data Set; Dependency; Development; Drug Combinations; Drug Targeting; Drug resistance; Epidermal Growth Factor Receptor; Epigenetic Process; Exclusion; Feedback; Genes; Genome; Genomics; Genotype; Goals; Human; Individual; Informatics; Lesion; Lethal Genes; Libraries; Lung Adenocarcinoma; Malignant Neoplasms; Malignant neoplasm of lung; Malignant neoplasm of ovary; Methods; Modeling; Molecular Abnormality; Mus; Mutation; Oncogenes; Oncogenic; Ovarian Serous Adenocarcinoma; Pathway interactions; Philosophy; Process; Property; RNA Interference; Reagent; Recording of previous events; Research Personnel; Resources; Serous; Stem cells; Surveys; Technology; Testing; Therapeutic Agents; Translating; Validation; Work; base; cancer cell; cancer genome; cancer therapy; cancer type; candidate identification; combinatorial; computerized tools; functional genomics; genome-wide; improved; in vivo; inhibitor/antagonist; innovation; member; method development; mouse model; neoplastic cell; new therapeutic target; programs; public health relevance; screening; small hairpin RNA; success; therapeutic target; tool; tumor

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.

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。