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

基本信息

批准号：
8874159
负责人：
Scott Powers
金额：
$ 142.05万
依托单位：
COLD SPRING HARBOR LABORATORY
依托单位国家：
美国
项目类别：
财政年份：
2012
资助国家：
美国
起止时间：
2012-05-01 至 2016-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8874159
关键词：
Area Bioinformatics Biological Biological Assay Cancer Model Cancer cell line Collaborations Combined Modality Therapy Communities Complementary DNA Custom DNA Sequence Alteration Data Set Dependency Development Drug Combinations Drug Targeting Drug resistance Epidermal Growth Factor Receptor Epigenetic Process Exclusion Feedback Genes Genome Genomic approach Genomics Genotype Goals Health 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 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 screening small hairpin RNA success targeted cancer therapy therapeutic target tool tumor

项目摘要

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）：该提出的CTDD程序将有助于将高吞吐量癌症基因组特征的巨大资源转化为基于功能验证的基于癌症的治疗靶标。在过去的几年中，该项目的成员开发了有力的工具和策略来在功能上注释癌症基因组。这些使五十个癌症基因的鉴定和验证是令人信服的治疗靶标。在这里，我们建议将这些策略合成并优化为可以在许多肿瘤类型中应用的统一蓝图中。我们哲学的核心是使用强大的计算工具来缩小必须在功能上进行调查的基因组的程度。这使得使用更精确的人和小鼠模型可以评估无法在基因组大规模上进行的驱动因素和依赖关系和方法。我们将应用这些工具选择癌症类型和基因组，以识别新的致癌驱动因素，基因型特异性癌症依赖性以及测试合并疗法靶标的系统鉴定策略。我们将项目的影响不仅鉴定为对几种肿瘤类型的基因组知情目标的识别，而且还提供了可以在整个财团和社区中使用的工具和策略。