Oncogenic Gene Regulatory Networks

描述(由申请人提供)：人类癌症的表型异质性对促进我们对疾病机制的理解以及开发有效的治疗设计策略提出了重大挑战。这种异质性也反映在控制细胞生长和决定细胞命运的细胞信号通路的活性变化上，这些通路是驱动癌症表型的关键过程。本提案中所述工作的主要目标是利用基因组规模的基因表达测量方法的最新发展，以及先进的计算工具，以更详细地了解与各种致癌活动的行动相关的基因调控网络。我们的重点是两个方面：更好地了解细胞信号通路的功能和相互联系；第二，利用这些信息转化为临床实践中的机会。我们工作的一个中心焦点是发展表达签名作为生物状态的代表，在这种情况下是一种途径的激活。这些信号将被扩展到与癌症表型相关的大量通路集合；我们还将开发和利用新的统计方法来剖析细胞信号通路的复杂性，开发一个经过验证的通路亚标志库。此外，反映细胞信号途径激活的基因表达特征，包括路径亚特征，将被用来定义癌症亚组，作为定义不同疾病机制的基础。最后，全基因组siRNA靶向将被用于识别影响细胞信号通路活性的细胞。 与公共卫生相关：最近的研究描述了对一些人类癌症的基因突变的深入分析，强调了癌症的复杂性和异质性，以及将这种分析置于特定途径的背景下的重要性。我们工作的一个主要焦点是使用基因表达信号来定义和预测与致癌表型有关的各种细胞信号通路的活性。重要的是，这些信号不仅提供了一种机制来剖析人类癌症的异质性，而且它们还提供了对与这种异质性相关的事件的理解。此外，由于这些信号还预测对各种靶向治疗药物的敏感性，这些工具为制定个别患者的治疗策略提供了一个框架。

DESCRIPTION (provided by applicant): The phenotypic heterogeneity of human cancers presents major challenges to advancing our understanding of disease mechanisms as well as to developing effective strategies for therapeutic design. This heterogeneity is also reflected in the variation in activity of cell signaling pathways that control cell growth and determine cell fate, processes critical for driving the cancer phenotype. The primary goal of the work described in this proposal is to take advantage of recent developments in the use of genome-scale measures of gene expression, together with advanced computational tools, to develop a more detailed understanding of the gene regulatory networks associated with the action of various oncogenic activities. Our focus is two-fold: develop a better understanding of the function and inter-connection of cell signaling pathways and second, utilize this information to translate to opportunities in clinical practice. A central focus of our work has been the development of expression signatures as a representation of a biological state, in this instance the activation of a pathway. These signatures will be expanded to a large collection of pathways relevant for cancer phenotypes; we will also develop and utilize novel statistical methodologies to dissect the complexity of cell signaling pathways, developing a library of verified pathway sub-signatures. In addition, the gene expression signatures reflecting cell signaling pathway activation, including pathway sub-signatures, will be used to define subgroups of cancer as the basis for defining distinct mechanisms of disease. And finally, genome-wide siRNA targeting will be used to identify cellular that influence the activity of cell signaling pathways. PUBLIC HEALTH RELEVANCE: Recent studies describing in-depth analyses of gene mutations in a number of human cancers have emphasized the complexity and heterogeneity of cancer and the importance of placing such analyses in pathway-specific contexts. A major focus of our work has been the use of gene expression signatures to define and predict the activity of a variety of cell signaling pathways that contribute to the oncogenic phenotype. Importantly, not only do these signatures provide a mechanism to dissect the heterogeneity of human cancers but they also provide an understanding of the events associated with this heterogeneity. Furthermore, since these signatures also predict sensitivity to various targeted therapeutics, these tools provide a framework for developing a strategy for treatment of individual patients.