Personalized Organoid-Chip Model For Drug Testing in Pancreatic Cancer

摘要 为了改善癌症患者的预后，下一代癌症治疗方法应该结合 有针对性的治疗，能够预测个人肿瘤从给定的 治疗。该项目的重点是推进基于个人肿瘤的个性化平台 行为不仅由癌上皮决定，而且由整个肿瘤微环境决定 (TME)。TME在疾病进展甚至治疗药物反应中的作用在多种情况下都得到了充分的证实 预后不佳的癌症，包括胰腺导管腺癌(PDA)，五年生存率 不到10%。在这里，结合3D患者衍生的有机化合物(PDO)和微流体技术，我们将 开发一种新型肿瘤芯片设备，具有产生个性化治疗反应预测的潜力 体外实验。在目标1中，使用多个组织和功能读出，我们将展示我们的多细胞平台 概述了肿瘤及其微环境。在目标2中，我们将展示我们的系统作为一个 个性化的体外平台，从功能上表征肿瘤对常规和新型的反应 治疗。我们的长期目标是优化针对患者的体外药物反应分析技术，以便 它可用于快速、准确和可靠地告知个性化治疗决定。作为证明 概念，该项目涉及开发个性化的胰腺癌模型；然而，这项技术可以 扩展到其他具有丰富TME的实体肿瘤类型(即乳腺癌)，以改善分子和/或细胞 癌症生物学和治疗学的特征。

ABSTRACT In order to improve cancer patient outcomes, the next generation of cancer therapeutics should combine targeted treatments with the ability to predict the likelihood of an individual’s tumor to benefit from a given treatment. The focus of this project is on advancing a personalized platform based on the individual’s tumor behavior which is determined not only by the cancerous epithelium but the entire tumor microenvironment (TME). The role of TME in disease progression or even therapeutic drug response is well established in variety of cancers with poor outcome including pancreatic ductal adenocarcinoma (PDA) with a five year survival rate of less than 10%. Here, combining 3D patient-derived organoids (PDO) and microfluidic technologies, we will develop a novel tumor-chip device with the potential to generate individualized treatment response predictions ex vivo. In Aim 1, using multiple tissue and functional read outs we will show that our multicellular platform recapitulates the tumor and its microenvironment. In Aim 2, we will show the utility of our system as an individualized ex vivo platform to functionally characterize the tumor response to conventional and novel therapies. Our long-term goal is to optimize patient-specific ex vivo drug response assay technology such that it may be used to rapidly, accurately, and reliably inform individualized treatment decisions. As a proof of concept, the project involves developing a personalized pancreatic cancer model; however this technology can be extended to other solid tumor types with rich TME (i.e., breast cancer) to improve molecular and/or cellular characterizations of cancer biology and therapeutics.