Exploiting the Ref-1 node in pancreatic cancer: tailoring new pancreatic cancer therapy using multi-targeted combinations

胰腺导管腺癌或PDAC是一种致死性疾病，5年死亡率约为93%， 尽管出现了几种靶向的选择性试剂，但已经取得了改进。一种新 方法是必要的。我们将追求转录组学指导的联合治疗，以及目标， 上游的几个信号通路，从而影响多个下游细胞过程和潜在的 抵抗机制氧化还原因子-1（Ref-1）就是这样一种蛋白，因为Ref-1调节多种转录因子， 胰腺癌的生存和耐药性的关键因素（TF）。在上一个供资期间， 我们已经推进了APX 3330，一种Ref-1抑制剂和第一种靶向Ref-1的药物进入癌症临床试验（IND 125360）作为一种新型的口服的一流药物用于人类。我们已经证明APX 3330可以减少肿瘤生长， 在PDAC的几种模型中作为单一药物，并增强吉西他滨介导的细胞生长抑制。的 APX 3330的作用机制已经被我们的团队广泛研究和表征。通过 通过抑制Ref-1，可以阻断STAT 3、AP-1、NFkB和HIF-1 α的活性，从而导致 存活蛋白表达和对缺氧反应。认识到联合治疗将是必要的， PDAC，我们建议利用转录组学数据来确定FDA批准的可能与PDAC协同作用的药物。 APX3330。药物合成致死性定义为分子靶点的联合治疗，其双重抑制 导致比作为单一药剂施用时更显著地增强细胞死亡。单细胞 RNA-seq数据鉴定了HIF-1信号通路在Ref-1敲低后显著下调 （p=0.0008）。因此，我们测试了Ref-1抑制和HIF-1靶标碳酸酐酶（CA 9）的组合。 在我们的三维（3D）肿瘤共培养模型中。Ref-1诱导的细胞杀伤的显著增强是 在双重靶向Ref-1和CA 9时观察到。我们的假设是为了延长PDAC的存活时间 患者的多靶点，联合治疗是必不可少的;因此，我们将使用原始的，路径驱动的 筛选方法，以发现合适的FDA批准的药物与我们的Ref-1抑制剂合作。AIM 1- 使用体内方法评估同时抑制Ref-1和HIF-1途径的机制和功效 PDAC模型目的2-研究Ref-1在PDAC对目前用于化疗的化疗增敏中的作用。 PDAC治疗。吉西他滨（Gem），单细胞RNA-seq表达谱预测的药物之一， 应与APX 3330一起使用，将在1B期试验中与APX 3330联合使用。AIM 3-筛选 在经验证的3D模型系统中，使用计算和 转录组学途径分析。单个分子效应物的选择性破坏具有明显的局限性; 方法侧重于多靶点联合治疗。因此，该项目有可能扩大 通过使用适当的疾病相关模型如3D共培养球状体， 原位和GEM模型。

Pancreatic ductal adenocarcinoma or PDAC is a lethal disease with a 5 year mortality rate of ~93% and little improvement has been made despite the emergence of several targeted, selective agents. Therefore, a new approach is needed. We will pursue transcriptomic-guided combination therapy as well as targets that are upstream of several signaling pathways, thereby affecting multiple downstream cellular processes and potential resistance mechanisms. Redox factor-1 (Ref-1) is one such protein, as Ref-1 regulates multiple transcriptional factors (TFs) that are critical to pancreatic cancer survival and drug resistance. In the previous funding period, we have advanced APX3330, a Ref-1 inhibitor and the first drug targeting Ref-1 to cancer clinical trials (IND 125360) as a novel, oral, first-in-class drug in humans. We have shown that APX3330 reduces tumor growth in several models of PDAC as a single agent and potentiates gemcitabine-mediated inhibition of cell growth. The mechanism of action of APX3330 has been extensively investigated and characterized by our team. Through inhibition of Ref-1, the activity of STAT3, AP-1, NFkB, and HIF-1 can be blocked leading to a decrease in survival protein expression and response to hypoxia. Recognizing that combination therapy will be necessary in PDAC, we propose to utilize transcriptomic data to identify FDA-approved agents that are likely to synergize with APX3330. Drug synthetic lethality is defined as combination therapy of molecular targets whose dual inhibition leads to potentiation of cell death much more dramatically than when administered as single agents. Single cell RNA-seq data identified HIF-1 signaling pathways as significantly down-regulated following Ref-1 knockdown (p=0.0008). Therefore, we tested the combination of Ref-1 inhibition and HIF-1 target, carbonic anhydrase (CA9) in our 3-Dimensional (3D) tumor co-culture model. Dramatic enhancement of Ref-1-induced cell killing is observed upon dual-targeting of Ref-1 and CA9. Our hypothesis is that in order to extend the survival of PDAC patients multi-targeted, combination therapy is essential; therefore we will use original, pathway-driven screening approaches to discover appropriate FDA approved agents to partner with our Ref-1 inhibitor. AIM 1- Evaluate the mechanism and efficacy of simultaneous inhibition of the Ref-1 and HIF-1 pathways using in vivo models of PDAC. AIM 2- Investigate the role of Ref-1 in sensitizing PDAC to chemotherapy currently used in PDAC treatment. Gemcitabine (Gem), one of the agents that single cell RNA-seq expression profiling predicted should work with APX3330, will be used in combination with APX3330 in the phase 1B trial. AIM 3- Screen for drug synthetic lethal hits following Ref-1 inhibition in a validated 3D model system utilizing computational and transcriptomics pathway analysis. Selective disruption of individual molecular effectors has clear limitations; our approach focuses on multi-targeted combination treatments. Thus, this project has the potential to extend pancreatic cancer survival by using appropriate disease-relevant models such as 3D co-culture spheroids, orthotopic, and GEM models.