Personalized Organoid-Chip Model For Drug Testing in Pancreatic Cancer

用于胰腺癌药物测试的个性化类器官芯片模型

基本信息

批准号：
10570699
负责人：
Faraz Bishehsari
金额：
$ 22.88万
依托单位：
RUSH UNIVERSITY MEDICAL CENTER
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-02-01 至 2025-01-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10570699
关键词：
3-Dimensional Adjuvant Antineoplastic Agents Basic Science Biological Assay CD8-Positive T-Lymphocytes Cancer Biology Cancer Patient Cancerous Cell Communication Cell Differentiation process Cells Characteristics Clinical Clinical Trials Complex Decision Making Devices Disease Progression Drug Delivery Systems Drug Modelings Drug Targeting Elements Endothelium Environment Epithelium Failure Fibroblasts Fibrosis Genes Goals Human Immune Immunotherapy Individual Interruption Macrophage Malignant Neoplasms Malignant neoplasm of pancreas Modeling Molecular Molecular Profiling Organ Organoids Outcome Pancreatic Ductal Adenocarcinoma Pathogenicity Pathology Pathway interactions Patient-Focused Outcomes Patients Pharmaceutical Preparations Phenotype Prediction of Response to Therapy Resistance Role Series Solid Neoplasm Source Survival Rate System T-Lymphocyte Technology Testing Therapeutic Tissues Tumor Immunity Tumor Promotion Vascularization cancer immunotherapy cancer therapy cancer type cell type chemotherapy cohort conventional therapy design drug development drug efficacy drug testing experimental study functional outcomes improved in vivo individual response individualized medicine innovation malignant breast neoplasm microfluidic technology molecular modeling next generation novel novel therapeutics organ on a chip pancreatic cancer model pancreatic stellate cell patient subsets personalized medicine personalized strategies pre-clinical protein expression real time monitoring research and development response stellate cell stem cells targeted treatment therapy resistant treatment response tumor tumor behavior tumor microenvironment tumor progression

项目摘要

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.

抽象的为了改善癌症患者的结局，下一代癌症治疗应结合有针对性的治疗能够预测个人肿瘤的可能性治疗。该项目的重点是基于个体的肿瘤来推进个性化平台行为不仅由取消上皮决定，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样性中得到了很好的确定预后不良的癌症包括胰腺导管腺癌（PDA），生存率为五年小于10％。在这里，组合3D患者衍生的类器官（PDO）和微流体技术，我们将开发一种新型的肿瘤芯片装置，具有产生个性化治疗反应预测的潜力前体。在AIM 1中，使用多个组织和功能读取量，我们将表明我们的多细胞平台概括肿瘤及其微环境。在AIM 2中，我们将显示系统的实用性个性化的离体平台以在功能上表征肿瘤对常规和新颖的反应疗法。我们的长期目标是优化特定于患者的离体药物反应测定技术，以便它可以用来快速，准确且可靠地为个性化的治疗决策提供信息。作为证明概念，该项目涉及开发个性化的胰腺癌模型；但是这项技术可以扩展到具有丰富TME（即乳腺癌）的其他实体瘤类型，以改善分子和/或细胞癌症生物学和治疗的特征。