Center for Systems Analysis of the Cancer Regulome

描述（由申请人提供）：由于基因组和表观基因组畸变，癌症的发生和进展涉及细胞中生物分子相互作用复杂网络的破坏。为了更深入地了解癌症的遗传基础，并确定新的翻译方向，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，对于这种畸变如何改变受疾病干扰的调节网络的状态，或者畸变最终如何导致细胞功能障碍，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解决这一挑战，从而能够在调节机制的层面上解释TCGA数据；并利用这些知识以临床相关的方式实现药物靶点发现和治疗干预的原则性和系统性方法。该中心将建立三条计算管道，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，并确定这些网络中可能是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癌症进展的调控基础。这些管道的结果将通过TCGA迅速传播，以及可视化工具，以促进对每种衍生监管机制的探索和评估。

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.