Exploiting Biological Networks to Improve Clinical Treatment of Ovarian Cancer

描述(申请人提供)：在报告发表时，大多数卵巢癌不再依赖于单一的基因决定因素来生长和/或生存。作为单一药物使用的靶向治疗在这种疾病中不起作用，因此第二部位致死性筛查将有助于识别与新生物药物相结合的靶向关键途径。我们的目标是获取通过我们的合成致命siRNA筛选获得的基因，并使用它们来绘制与EoC相关的靶向治疗的敏化网络，并设计有意义的siRNA与药物或药物与药物的组合，这些组合可以快速转化到临床上。我们已经使用RNAi方法来识别有选择性地增强Src靶向剂达沙替尼(也称为BMS-354825，Sprycel“)杀伤力的候选药物。将命中模式映射回网络图显示了密切相互作用的蛋白质簇，这意味着关键生存节点的识别。提出的三个目标将系统地发展我们的初步研究，以确定共同抑制的生产性靶点，最终目标是确定将极大地提高妇女EoC治疗的新药物组合。因此，AIMS 1和AIMS 2旨在应用一系列体外过滤器，帮助在动物模型中优先选择与临床相关的治疗靶向的最佳蛋白质组合。具体地说，目标1将通过筛选一组卵巢癌患者腹水中产生的EOC细胞株和原代培养物，并基于网络建模、体外药物协同研究和为实现这一目标而完成的功能研究，将这些敏感基因分组为协调组，从而完善我们验证的达沙替尼增敏siRNA的高价值列表。在目标2中，我们将探索在目标1中确定的精制HITS在患者样本中的蛋白质和转录本的表达模式，以评估它们的病理和临床相关性。在目标3中，对于最优先的HITS，我们将在动物身上进行药物药代动力学和毒性研究，使用我们的体外协同作用数据所指示的不同比率评估的药物-药物组合。我们将在异种移植动物模型中确定最佳给药方案并评估其治疗效果。对于缺乏临床开发药物的HIT，我们将在动物模型中进行siRNA-药物组合。我们相信，这种尖端方法将产生一种范例，随后可以应用于多种治疗应用。

DESCRIPTION (provided by applicant): At the time of presentation, most ovarian cancers are no longer dependent on single genetic determinants for growth and/or survival. Targeted therapies used as single agents will not work in this disease and thus second site lethality screens will help identify critical pathways to target in combination with novel biologics. Our objectives are to take genes obtained through our synthetic lethal siRNA screens, and use them to map the sensitization network for targeted therapeutics relevant to EOC, and design meaningful combinations of siRNAs with drugs, or drugs with drugs, that can be rapidly translated to the clinic. We have used RNAi approaches to identify candidates that selectively enhance killing by the Src-targeting agent, dasatinib (also known as BMS-354825, Sprycel"). Mapping the pattern of hits back to the network map revealed suggestive clusters of closely interacting proteins, implying identification of key survival nodes. The three Aims proposed will systematically develop our preliminary studies to identify productive targets of co-inhibition, with the ultimate goal of identifying new drug combinations that will greatly enhance the treatment of women with EOC. Hence, Aims 1 & 2 are designed to apply a series of in vitro filters to help prioritize selection of the optimal combination of proteins to target using clinically relevant therapies in animal models. Specifically, Aim 1 will refine our high-value list of validated dasatinib-sensitizing siRNAs by screening a set of EOC cell lines and primary cultures generated from ascites obtained from patient with ovarian cancer and cluster these sensitizing genes into coordinated groups based on network modeling, in vitro drug-drug synergy studies, and functional studies to be completed in this Aim. In Aim 2, we will explore the expression patterns of proteins and transcripts for the refined hits identified in Aim 1 in patient samples to assess their pathological and clinical relevance. In Aim 3, for the highest priority hits we will conduct drug pharmacokinetic and toxicity studies in animals using drug-drug combinations evaluated at various ratios as dictated by our in vitro synergy data. We will identify optimal dosage regimens and evaluate their therapeutic efficacy in xenograft animal models. For hits lacking clinically developed agents, we will perform siRNA-drug combinations in the animal models. We believe that this cutting-edge approach will yield a paradigm that can subsequently be applied for multiple therapeutic applications.