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

胰腺导管腺癌是一种致命性疾病，5年死亡率约为93%。 尽管出现了几种靶向、选择性的药物，但情况还是有所改善。因此，一个新的 方法是必要的。我们将寻求转录引导的联合治疗，以及 上游的几个信号通路，从而影响多个下游的细胞过程和潜力 抗性机制。氧化还原因子-1(Redox factor1，Ref-1)就是这样一种蛋白质，因为Ref-1调节多种转录。 对胰腺癌生存和耐药性至关重要的因子(TF)。在上一次筹资期间， 我们有先进的APX3330，一种Ref-1抑制剂，也是第一种靶向Ref-1到癌症临床试验(IND)的药物 125360)作为一种新型的、口服的、人类一流的药物。我们已经证明APX3330可以减少肿瘤的生长 在几种模型中，PDAC作为单一药物，并加强吉西他滨介导的细胞生长抑制。这个 我们的团队已经对APX3330的作用机理进行了广泛的研究和表征。穿过 抑制Ref-1、STAT3、AP-1、NFkB和HIF-1的活性可以被阻断，导致 存活蛋白的表达和对低氧的反应。认识到联合治疗将是必要的 PDAC，我们建议利用转录数据来识别FDA批准的药物，这些药物可能与 APX3330。药物合成杀伤力被定义为分子靶点的双重抑制的联合治疗 导致细胞死亡的增强比作为单一药物使用时要明显得多。单细胞 RNA-seq数据表明，在Ref-1被敲除后，HIF-1信号通路显著下调 (P=0.0008)。因此，我们测试了Ref-1抑制和HIF-1靶点碳酸酐酶(CA9)的结合。 在我们的三维(3D)肿瘤共培养模型中。显著增强Ref-1诱导的细胞杀伤作用 在双靶向REF-1和CA9时观察到。我们的假设是，为了延长PDAC的生存时间 患者的多靶点、联合治疗是必不可少的；因此我们将使用原创、路径驱动的方法 筛选方法，以发现适当的FDA批准的药物与我们的Ref-1抑制剂合作。目标1- 体内同时抑制REF-1和HIF-1通路的机制和效果 PDAC的模型。目的2-研究Ref-1在增敏PDAC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APX3330配合使用，将在1B阶段试验中与APX3330结合使用。AIM 3-屏幕显示 在一个有效的3D模型系统中，利用计算和 转录转录途径分析。选择性地破坏单个分子效应器有明显的局限性；我们的 方法侧重于多靶点联合治疗。因此，该项目具有扩展的潜力 使用适当的疾病相关模型，如3D共培养球体， 正位模型和宝石模型。

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.