Center for Systems Analysis of the Cancer Regulome

癌症调节组系统分析中心

• 批准号: 8925186
• 负责人: ILYA SHMULEVICH
• 金额: $ 110万
• 依托单位: INSTITUTE FOR SYSTEMS BIOLOGY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-28 至 2016-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8925186
• 关键词: Address; Algorithms; Cells; Clinical; Complex; Data; Data Set; Disease; Drug Targeting; Evaluation; Functional disorder; Genetic; Genomics; Goals; Hereditary Disease; Imagery; Knowledge; Lead; Malignant Neoplasms; Maps; Modeling; Molecular; Morbidity - disease rate; Process; Regulation; System; Systems Analysis; The Cancer Genome Atlas; Therapeutic Intervention; United States; base; cancer type; clinically relevant; epigenomics; insight; mortality; novel; tool; transcriptomics; tumor progression

DESCRIPTION (provided by applicant): Cancer onset and progression involves disruptions of complex networks of biomolecular interactions in cells, as a result of genomic and epigenomic aberrations. To achieve a deeper understanding of the genetic basis of cancer and to identify novel translational directions requires moving beyond detecting simple associations between genomic aberrations and clinical endpoints. However, little is known about how the states of disease-perturbed regulatory networks are altered by such aberrations, or how aberrations ultimately lead to cellular dysfunction. The goal of the Center for Systems Analysis of the Cancer Regulome is to address this challenge by developing and applying advanced algorithms and model-based approaches to enable the interpretation of TCGA data at the level of regulatory mechanisms; and to use such knowledge for enabling principled and systematic approaches for drug target discovery and therapeutic intervention in a clinically relevant manner. The Center will build three computational pipelines that will carry out integrated analyses of TCGA-derived high-throughput experimental data sets. These pipelines will: 1) identify potential mechanisms of genomic-transcriptomic regulation associated with specific cancers and clinical parameters; 2) infer networks that explain cancer type-specific transcriptional profiles, and identify molecules that may be important control nodes in these networks as a means to prioritize drug targets for therapeutic intervention; and 3) compare cancer-associated features across all cancer types within TCGA to gain insight into the regulatory basis for cancer progression in different cancer types. The results of these pipelines will be rapidly disseminated through TCGA, together with visualization tools that facilitate the exploration and evaluation of each derived regulatory mechanism.

描述(由申请人提供)：癌症的发生和发展涉及细胞中生物分子相互作用的复杂网络的破坏，作为基因组和表观基因组异常的结果。为了更深入地了解癌症的遗传基础并确定新的翻译方向，需要超越检测基因组异常和临床终点之间的简单关联。然而，关于这种异常如何改变疾病扰动的调控网络的状态，或者异常如何最终导致细胞功能障碍，人们知之甚少。癌症规则组系统分析中心的目标是通过开发和应用先进的算法和基于模型的方法来应对这一挑战，以便能够在调控机制水平上解释TCGA数据；并利用这些知识以临床相关的方式实现原则性和系统性的药物靶点发现和治疗干预方法。该中心将建造三条计算管道，对TCGA衍生的高通量实验数据集进行综合分析。这些管道将：1)确定与特定癌症和临床参数相关的基因组转录调控的潜在机制；2)推断解释癌症类型特异性转录谱的网络，并确定这些网络中可能是重要控制节点的分子，以此作为确定治疗干预的优先药物靶点的手段；3)比较TCGA内所有癌症类型的癌症相关特征，以深入了解不同癌症类型中癌症进展的调控基础。这些管道的结果将通过TCGA以及可视化工具迅速传播，这些工具有助于探索和评估每个派生的监管机制。