Targeting Fluid Stress-induced Chemoresistance in a 3D Carcinomatosis Perfusion Model Using Mechanism-based Photo-immunoconjugate Nanoparticles

摘要 多年来，晚期和复发卵巢癌患者的预后仍然很差。 几十年。较低的应答率部分是由于对化疗的耐药性，特别是铂类药物--以及 紫杉烷类药物。卵巢癌常常沿着腹水流通过体腔途径转移 腹膜腔内的液体。我们设计了一种3D贴壁灌注模型来模拟卵巢结节 它可以固定腹膜表面，重现抗药性疾病，从而提供了一个独特的开发平台 有针对性的治疗。我们的研究表明，生理上相关的流体剪应力(FSS)会导致一种积极的。 转移表型，并对铂类药物产生耐药性。光免疫疗法(PIT)显示 在选择性成像和治疗播散性肿瘤方面很有希望，它可以使化疗耐药癌症重新敏感 从细胞到铂金特工。然而，细胞所需的高阈值细胞内光免疫偶联 在生理学相关模型中，死亡阻碍了PIT的有效性。因此，主要目标是 这项提议是开发一种多用途纳米平台，打破选择性与摄取之间的权衡 光免疫结合并在腹膜FSS下实现多层癌症靶向。我们最近做了 研究表明，成功地将光免疫偶联物偶联到纳米颗粒上可以有效地增强 光免疫结合物瘤内传递和改善小鼠的PIT结局。我们假设 纳米工程使光免疫结合物和化疗的高负载联合输送成为可能 在克服FSS诱导的化疗耐药方面安全有效的方式。这一方法将 显著提高铂类药物对卵巢癌患者的治疗指数。在Aim 1中，一组 光免疫偶联纳米结构(PICNC)将被开发成针对FSS改变的三维生物标记物 卵巢癌的血流灌注模型。在目标2中，我们将评估对化疗增敏、T细胞节省、 FSS下PICNC-PIT对免疫支持性肿瘤相关巨噬细胞的破坏作用 灌流模型。在目标3中，为了提高治疗的安全性和一致性，我们将开发图像- 指导策略，告知小鼠模型中PICNC-PIT的时机和剂量。在《目标4》中，抗肿瘤 PICNC-PIT的有效性将在基于细胞系的同基因(免疫活性)小鼠和异种移植小鼠中进行评估 模型，以及PDX模型，用于卵巢癌。PI设想了一个简单可行的修改 标准治疗框架，其中PICNC将在手术除髓后通过腹膜腔给予，以及 被光激活，触发凹坑，释放化疗。所获得的知识可能会对 在改进的治疗方案的开发中的变革性作用，该方案是根据分子图谱量身定做的 个体患者中的播散性肿瘤。为了实现这些目标，我们将部署我们的多学科 纳米粒子工程团队，三维肿瘤灌注模型，肿瘤生物学，肿瘤免疫学，生物统计学， 和妇科肿瘤学专家一起检查我们的技术对卵巢癌治疗的影响。

ABSTRACT The prognosis for patients with advanced stage and recurrent ovarian cancer has remained dismal for decades. The poor response rates result in part from resistance to chemotherapy, particularly platinum- and taxane-based agents. Ovarian cancer often metastasizes via transcoelomic routes along currents of ascitic fluid in the peritoneal cavity. We have engineered a 3D adherent perfusion model to mimic ovarian nodules that stud peritoneal surfaces and recapitulate resistant disease, thereby providing a unique platform to develop targeted therapies. Our studies showed that physiologically relevant fluid shear stress (FSS) induces a pro- metastatic phenotype and confers resistance to platinum agents. Photoimmunotherapy (PIT) has shown promise in selectively imaging and treating disseminated tumors, and it can resensitize chemoresistant cancer cells to platinum agents. However, the high thresholds of intracellular photoimmunoconjugate required for cell death have hindered the effectiveness of PIT in physiologically relevant models. Therefore, the main goal of this proposal is to develop a multi-purpose nanoplatform that breaks the selectivity-uptake trade-off of photoimmunoconjugates and enables multi-tier cancer targeting under peritoneal FSS. We have recently shown that successful conjugation of photoimmunoconjugates onto nanoparticles can effectively enhance intratumoral photoimmunoconjugate delivery and improve PIT outcomes in mice. We hypothesize that nanoscale engineering enables high-payload co-delivery of photoimmunoconjugate and chemotherapy in a manner that is safe and efficacious in overcoming FSS-induced chemoresistance. This approach will significantly enhance the therapeutic index of platinum agents for ovarian cancer patients. In Aim 1, a panel of photoimmunoconjugate-nanoconstructs (PICNC) will be developed to target biomarkers altered by FSS in a 3D perfusion model of ovarian cancer. In Aim 2, we will assess the effects on chemosensitization, T cell sparing, and destruction of immune supporting tumor-associated macrophages following PICNC-PIT under FSS in 3D perfusion models. In Aim 3, to improve the safety and consistency of the treatment, we will develop image- guided strategies to inform the timing and dosing of PICNC-PIT in mouse models. In Aim 4, the anti-tumor efficacy of PICNC-PIT will be evaluated in cell line-based syngeneic (immunocompetent) and xenograft mouse models, as well as PDX models, for ovarian cancer. The PIs envision a simple and feasible modification to the standard treatment framework, where PICNC will be delivered intraperitoneally after surgical debulking, and activated by light, triggering PIT and releasing chemotherapy. The knowledge gained could play a transformative role in the development of improved therapeutic regimens tailored to the molecular profile of disseminated tumors in individual patients. To accomplish these aims, we will deploy our multi-disciplinary team of nanoparticle engineering, 3D tumor perfusion model, cancer biology, tumor immunology, biostatistics, and gynecologic oncology experts to examine the impact of our technology on ovarian cancer treatment.