Heterocellular 3D ovarian tumor arrays for imaging and mechanistic combinations

描述（由申请人提供）：几十年来，晚期发现和耐药性使卵巢癌（OvCa）的严峻统计数据保持稳定。采用机制不同成分的联合疗法的新方法被认为是最有效的。这项研究的长期目标是开发、整合和验证关键平台技术，以筛选基于机制的联合方案和光动力疗法（PDT）治疗残余和复发的OvCa。异质细胞3D打印肿瘤阵列结合了OvCa生物学的关键决定因素（内皮细胞和间皮细胞，巨噬细胞和成纤维细胞）以及用于多种生物标志物同时定量成像的高光谱显微镜，将在高通量平台上提供对OvCa生长和治疗反应的独特见解。为了解决导致OvCa相关死亡的严重毒性和频繁复发，我们利用纳米技术计划制造纳米结构，用于细胞内递送靶向抑制剂，并提供合理的PDT联合方案，PDT是FDA批准的一种基于光化学的治疗方法，已显示出OvCa的临床前景。PDT对化疗和放射耐药细胞有效，并与化疗和生物制剂协同作用，从而提高疗效。在异细胞3D阵列中优化的治疗结果将在体内和离体患者组织来源的3D培养中进行严格验证，以证明基于生物和成像的筛选平台的预测能力。目标将在三个具体目标中实现：1)开发和表征用于微转移性OvCa的异细胞3D打印肿瘤阵列，以及用于细胞内递送治疗剂的纳米结构。2)采用异细胞肿瘤阵列，评估细胞毒性和分子对两层治疗方法的反应——i)一线PDT +残余疾病化疗，ii)二线PDT +靶向生物治疗化疗耐药复发疾病。3)在体内验证三维肿瘤阵列的治疗反应，并在体外组织源性细胞中进行三维培养。该提案的主要成果将是i)用于多药物细胞内递送的异细胞3D OvCa肿瘤阵列和纳米结构，ii)缓解再生的最佳组合递送策略和条件，以及iii)在转移性OvCa的临床相关小鼠模型和患者组织来源的3D培养背景下严格验证异细胞肿瘤阵列数据。这项研究的结果将影响晚期（II-IV期）和耐药OvCa患者以及接受补救性治疗的患者的预后。通过这种高度集成的方法开发的基础设施将创建一个新的框架，以快速评估和优化新的治疗策略，这些策略将适用于广泛的转移性肿瘤和分子靶点。由于分子表达和反应可能是特异的，因此提出的对生物标志物表达和治疗诱导的生物标志物变化的快速监测为未来患者定制治疗创造了可能。

DESCRIPTION (provided by applicant): Late detection and drug resistance have maintained the grim statistics for ovarian cancer (OvCa) steady over decades. New approaches using combination therapies with mechanistically distinct components are hypothesized to be most effective. The long term goal of this research is to develop, integrate and validate key platform technologies to screen mechanism-based combination regimens with photodynamic therapy (PDT) for residual and recurrent OvCa. Heterocellular 3D printed tumor arrays that incorporate critical determinants of OvCa biology (endothelial and mesothelial cells with macrophages and fibroblasts) along with hyperspectral microscopy for simultaneous quantitative imaging of multiple biomarkers will provide exceptional insight into OvCa growth and treatment response on a high throughput platform. To address the grueling toxicities and frequent recurrence that cause OvCa-related deaths, we leverage our nanotechnology program to fabricate nanoconstructs for intracellular delivery of targeted inhibitors, and deliver rational combination regimens with PDT, an FDA approved photochemistry-based treatment that has shown clinical promise for OvCa. PDT is effective on chemo and radiation resistant cells and synergizes with chemotherapeutic and biologic agents resulting in improved efficacy. Treatment results optimized in the heterocellular 3D arrays will be rigorously validated in vivo and in ex vivo patient tissue-derived 3D cultures to demonstrate the predictive capabilities of the bio- and imaging-based screening platform. The goals will be realized in 3 specific aims: 1) Develop and characterize heterocellular 3D printed tumor arrays for micrometastatic OvCa, and nanoconstructs for intracellular delivery of therapeutic agents. 2) Deploy heterocellular tumor arrays for assessment of cytotoxic and molecular responses to a two-tiered therapeutic approach- i) first-line PDT + chemotherapy of residual disease followed by ii) second-line treatment of chemoresistant recurrent disease with PDT + targeted biological therapies. 3) Validate treatment response of 3D tumor arrays in vivo, and in ex-vivo tissue derived cells in 3D culture. Major deliverables of this proposal will be i) Heterocellular 3D OvCa tumor arrays and nanoconstructs for multi-agent intracellular delivery, ii) Optimal combination delivery strategies and conditions to mitigate regrowth, and iii) Rigorous validation of the heterocellular tumor array data in the context of both a clinically-relevant murine model for metastatic OvCa, and in patient tissue-derived 3D cultures. The findings from this study will impact outcomes for patients with advanced (stage II-IV) and resistant OvCa and those receiving salvage therapy. The infrastructure developed through this highly integrated approach will create a new framework to rapidly evaluate and optimize new therapeutic strategies that will be adaptable to a broad array of metastatic tumors and molecular targets. Because molecular expressions and responses can be idiosyncratic, the proposed rapid monitoring of biomarkers expression and treatment-induced biomarkers changes creates the possibility of patient-customized treatments in the future.