Exploiting Biological Networks to Improve Clinical Treatment of Ovarian Cancer

描述（由申请人提供）：在提交时，大多数卵巢癌不再依赖于生长和/或生存的单一遗传决定因素。作为单一药物使用的靶向治疗对这种疾病不起作用，因此第二位点致命性筛选将有助于确定与新型生物制剂联合靶向的关键途径。我们的目标是获取通过我们的合成致死siRNA筛选获得的基因，并利用它们绘制与EOC相关的靶向治疗的致敏网络，并设计siRNA与药物或药物与药物的有意义的组合，这些组合可以快速转化为临床。我们已经使用RNAi方法来识别选择性增强src靶向药物达沙替尼（也称为BMS-354825， Sprycel）杀伤的候选药物。将命中模式映射回网络地图，揭示了密切相互作用的蛋白质的提示簇，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，以确定共同抑制的有效靶点，最终目标是确定新的药物组合，从而大大加强对女性EOC的治疗。因此，Aims 1和2旨在应用一系列体外过滤器，以帮助优先选择最佳蛋白质组合，以便在动物模型中使用临床相关疗法。具体来说，Aim 1将通过筛选一组EOC细胞系和从卵巢癌患者的腹水中产生的原代培养物，来完善我们验证的高价值达沙替尼致敏sirna列表，并基于网络建模、体外药物-药物协同研究和本Aim将完成的功能研究，将这些致敏基因聚类成协调组。在目标2中，我们将探索在目标1中确定的患者样本中精炼命中的蛋白质和转录本的表达模式，以评估其病理和临床相关性。在Aim 3中，对于最优先的命中目标，我们将在动物中进行药物药代动力学和毒性研究，使用根据体外协同作用数据规定的不同比例评估的药物-药物组合。我们将在异种移植动物模型中确定最佳剂量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 -药物联合。我们相信这种尖端的方法将产生一种范例，可以随后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.