Center for Systems Analysis of the Cancer Regulome

癌症调节组系统分析中心

• 批准号: 7942769
• 负责人: ILYA SHMULEVICH
• 金额: $ 152.73万
• 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 2014-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7942769
• 关键词: Address; Algorithms; Cells; Clinical; Complex; Data; Data Set; Disease; Drug Delivery Systems; Evaluation; Functional disorder; Genetic; Genomics; Goals; Imagery; Knowledge; Lead; Malignant Neoplasms; Modeling; Regulation; Systems Analysis; Therapeutic Intervention; base; cancer type; clinically relevant; epigenomics; insight; 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）：由于基因组和表观基因组畸变，癌症的发病和进展涉及细胞内生物分子相互作用的复杂网络的破坏。为了更深入地了解癌症的遗传基础并确定新的转化方向，需要超越检测基因组畸变和临床终点之间的简单关联。然而，人们对疾病扰动的调节网络的状态如何因这种畸变而改变，或者畸变最终如何导致细胞功能障碍知之甚少。癌症调节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，从而能够在监管机制层面解释 TCGA 数据；并利用这些知识以临床相关的方式实现药物靶标发现和治疗干预的原则性和系统性方法。该中心将建立三个计算管道，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组调控的潜在机制； 2）推断解释癌症类型特异性转录谱的网络，并识别可能是这些网络中重要控制节点的分子，作为优先考虑治疗干预药物靶点的手段； 3) 比较 TCGA 中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监管基础。这些管道的结果将通过 TCGA 以及有助于探索和评估每个派生监管机制的可视化工具快速传播。