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首页> 外文会议>Optical methods for tumor treatment and detection: mechanisms and techniques in photodynamic therapy XX >Biologically-relevant 3D Tumor Arrays: Treatment Response and the Importance of Stromal Partners
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Biologically-relevant 3D Tumor Arrays: Treatment Response and the Importance of Stromal Partners

机译：生物相关的3D肿瘤阵列：治疗反应和基质伴侣的重要性。

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The development and translational potential of therapeutic strategies for cancer is limited, in part, by a lack of biological models that capture important aspects of tumor growth and treatment response. It is also becoming increasingly evident that no single treatment will be curative for this complex disease. Rationally-designed combination regimens that impact multiple targets provide the best hope of significantly improving clinical outcomes for cancer patients. Rapidly identifying treatments that cooperatively enhance treatment efficacy from the vast library of candidate interventions is not feasible, however, with current systems. There is a vital, unmet need to create cell-based research platforms that more accurately mimic the complex biology of human tumors than monolayer cultures, while providing the ability to screen therapeutic combinations more rapidly than animal models. We have developed a highly reproducible in vitro three-dimensional (3D) tumor model for micrometastatic ovarian cancer (OvCa), which in conjunction with quantitative image analysis routines to batch-process large datasets, serves as a high throughput reporter to screen rationally-designed combination regimens. We use this system to assess mechanism-based combination regimens with photodynamic therapy (PDT), which sensitizes OvCa to chemo and biologic agents, and has shown promise in clinic trials. We show that PDT synergistically enhances carboplatin efficacy in a sequence dependent manner. In printed heterocellular cultures we demonstrate that proximity of fibroblasts enhances 3D tumor growth and investigate co-cultures with endothelial cells. The principles described here could inform the design and evaluation of mechanism-based therapeutic options for a broad spectrum of metastatic solid tumors.
机译：癌症治疗策略的发展和转化潜力部分受到缺乏捕捉肿瘤生长和治疗反应重要方面的生物学模型的限制。越来越明显的是，没有一种单一的治疗方法可以治愈这种复杂的疾病。合理设计的可影响多个目标的联合方案为显着改善癌症患者的临床结局提供了最大希望。但是，在当前系统中，从庞大的候选干预库中快速识别出可以协同提高治疗功效的治疗方法是不可行的。建立基于细胞的研究平台比单层培养更准确地模拟人类肿瘤的复杂生物学，同时提供比动物模型更快速地筛选治疗组合的能力，这是亟待解决的需求。我们已经为微转移性卵巢癌（OvCa）开发了高度可复制的体外三维（3D）肿瘤模型，该模型与定量图像分析例程结合使用以批量处理大型数据集，可作为高通量报告基因以合理设计筛选联合疗法。我们使用该系统评估基于机制的联合疗法与光动力疗法（PDT），该疗法可使OvCa对化学和生物制剂敏感，并在临床试验中显示出希望。我们显示，PDT以序列依赖性方式协同增强卡铂功效。在印制的异源细胞培养物中，我们证明成纤维细胞的接近会增强3D肿瘤的生长，并研究与内皮细胞的共培养。这里描述的原理可以为广泛的转移性实体瘤的基于机制的治疗选择的设计和评估提供依据。

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