Validation of a genomic signature that predicts for sub-optimal debulking of epithelial ovarian cancer

项目摘要 在美国，上皮性卵巢癌(EOC)每年影响大约21,000名妇女，导致13,000人 死亡。标准的治疗方法包括手术，然后辅以化疗。对于80%的 女性这种治疗是有效的，并延长了生存时间。然而，在20%的女性中，癌症广泛存在 手术时通过腹膜播散，使手术过程复杂化 不允许最理想的肿瘤剥离。对于这些女性来说，肿瘤剔除并不有效，她们经历了 术后恢复复杂，持续时间长。 最近的一项随机III期试验表明，间隔除瘤的新辅助化疗 手术是卵巢癌患者的有效替代治疗方法，可能是治疗卵巢癌的理想方法 不能进行最佳前期清理的患者。因此，有必要对患者进行识别和分层 根据他们对手术的反应，开发更有效的手术和化疗 以次优肿瘤为靶点的治疗方法 为了满足这一需求，我们使用公开可用的配置文件对基因表达数据进行了荟萃分析 在1,525个卵巢癌中发现了198个在肿瘤中高表达的基因 被揭穿了。我们将这些基因称为“隐藏签名”。消解的本体论路径分析 签名显示与恶性肿瘤有关的特定致癌信号的过度激活 转移耐药等行为，即转化生长因子-途径。因此，签名可以 作为患者的预测性生物标志物，这些患者将从前期手术中受益，并提供 对不能以最佳方式揭穿的肿瘤进行新的靶向治疗的理由。 该项目的目标是开发一种有效的基因组签名，该签名可以开发为 临床诊断，并在卵巢癌小鼠模型上测试是否靶向之一 这种信号的丰富途径转化生长因子-β是有效的。我们将验证198个被鉴定为高度 在EOC中表达，而不是使用两个独立的组织阵列以最佳方式去除，并建立 可用于这些肿瘤的术前诊断的最佳基因组标记(目标1)。到时候我们会的 进行临床前研究，测试目前正在临床试验中使用的转化生长因子-途径的抑制剂 对于其他癌症，改进对小鼠播散性卵巢癌模型的管理(目标2)。 总之，我们将建立一个预测性生物标记物，帮助外科医生和患者选择最好的 应用于卵巢癌患者的外科手术，以及确定新的辅助化疗方案 这会改善治疗结果。如果成功，这些研究将使女性免于治疗痛苦。 并延长他们的寿命。

Project Summary Epithelial ovarian cancer (EOC) affects approximally 21,000 women a year in the USA resulting in 13,000 deaths. Standard treatment includes debulking surgery followed by adjuvant chemotherapy. For 80% of women this treatment is effective and prolongs survival. However, in 20% of women the cancer is extensively disseminated through the peritoneum at time of surgery which complicates the surgical procedure and does not allow optimal tumor debulking. For these women, tumor debulking is not effective and they experience complicated and prolonged postoperative recovery. A recent randomized phase III trial demonstrated that neoadjuvant chemotherapy with interval debulking surgery is an effective alternative treatment for ovarian cancer patients and may be the ideal approach for patients who cannot undergo optimal up front debulking. Thus there is a need to identify and stratify patients based on their response to debulking surgery and develop more effective surgical and chemotherapeutic approaches targeting sub-optimally debulked tumors To address this need, we performed a meta-analysis of gene expression data using publicly available profiles of 1,525 ovarian cancers and identified 198 genes that were highly expressed in tumors that were not optimally debulked. We refer to these genes as “debulking signature. Ontologic pathway analysis of the debulking signature showed hyper-activation of a specific oncogenic signaling responsible for malignant cancer behaviors such as dissemination resistance to chemotherapy, i.e. the TGF- pathway. Thus, the signature may serve as a predictive biomarker for patients who would benefit from up-front surgery and provide a biological rationale for novel targeted therapies of tumors that cannot be optimally debulked. The goal of this project is to develop a validated genomic signature which can be developed into clinical diagnosis, and test in ovarian cancer mouse models whether targeting one of the most enriched pathways of this signature, TGF-β, is effective. We will validate the 198 genes identified as highly expressed in EOC that are not optimally debulked using two independent tissue arrays and establish an optimal genomic signature that can be used for pre-operative diagnosis of these tumors (aim 1). We will then perform preclinical studies testing whether inhibitors of the TGF- pathway currently being used in clinical trials for other cancers, improve management of disseminated ovarian cancer models in mice (aim 2). Altogether, we will establish a predictive biomarker that assists the surgeon and patient to choose the best surgical procedure to be applied to an EOC patient, as well as identify a new adjuvant chemotherapeutic option that improves therapeutic outcome. If successful, these studies will spare women from therapeutic suffering and prolong their lives.