Exploiting Biological Networks to Improve Clinical Treatment of Ovarian Cancer

描述（由申请人提供）：在出现时，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在这种疾病中不起作用，因此第二部位致死性筛选将有助于确定与新型生物制剂组合靶向的关键途径。我们的目标是通过我们的合成致命siRNA筛选获得基因，并使用它们来绘制与EOC相关的靶向治疗的致敏网络，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为临床。我们已经使用RNAi方法来鉴定选择性增强Src靶向剂达沙替尼（也称为BMS-354825，Sprycel）的杀伤的候选物。将命中模式映射到网络图，揭示了密切相互作用的蛋白质的暗示性集群，这意味着识别关键的生存节点。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，这将大大提高对EOC女性的治疗。因此，目标1和2旨在应用一系列体外过滤器，以帮助优先选择在动物模型中使用临床相关疗法靶向的蛋白质的最佳组合。具体而言，目标1将通过筛选一组从卵巢癌患者腹水中产生的EOC细胞系和原代培养物，并基于网络建模、体外药物-药物协同作用研究和本目标中待完成的功能研究，将这些致敏基因聚类为协调组，来完善我们经验证的达沙替尼致敏siRNA的高价值列表。在目标2中，我们将探索目标1中确定的患者样本中精确命中的蛋白质和转录物的表达模式，以评估其病理和临床相关性。在目标3中，对于最高优先级的命中，我们将使用药物-药物组合在动物中进行药物药代动力学和毒性研究，所述药物-药物组合以我们的体外协同数据所指示的各种比率进行评价。我们将确定最佳的剂量方案，并评估其在异种移植动物模型中的治疗效果。对于缺乏临床开发药物的命中，我们将在动物模型中进行siRNA-药物组合。我们相信，这种尖端的方法将产生一个范例，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.