在 3D 组织工程平台中模拟动态免疫细胞调节，以增强肺癌患者特异性免疫治疗-猫眼课题宝

在 3D 组织工程平台中模拟动态免疫细胞调节，以增强肺癌患者特异性免疫治疗

批准号：

10672244

负责人：

Jessy Satyadas Deshane

金额：

$17.01万

依托单位：

UNIVERSITY OF ALABAMA AT BIRMINGHAM

依托单位国家：

美国

项目类别：

财政年份：

2022

资助国家：

美国

项目状态：

已结题

起止时间：

2022-07-27 至 2024-06-30

来源：

https://reporter.nih.gov/project-details/10672244

关键词：

3-Dimensional Address Affect Antigens Apoptotic Architecture Atlases Attenuated Autologous Benchmarking Biochemical Biological Markers Biological Models Bioreactors Blocking Antibodies CD8-Positive T-Lymphocytes Cancer Etiology Cancer Patient Cell Culture Techniques Cell Density Cell model Cell physiology Cells Ceramides Cessation of life Characteristics Clinical Combined Modality Therapy Complex Data Diagnosis Dimensions Effector Cell Equilibrium Evaluation Growth Heterogeneity Homeostasis Human Human Engineering Hypoxia Immune Immune Targeting Immune checkpoint inhibitor Immune response Immunoglobulin G Immunosuppression Immunosuppressive Agents Immunotherapeutic agent Immunotherapy In Vitro Intervention Lung Neoplasms Lymphoid Cell Malignant neoplasm of lung Maps Mediator Metabolism Modeling Molecular Molecular Profiling Mus Mutation Myeloid-derived suppressor cells Non-Small-Cell Lung Carcinoma Oncogenic Outcome Pathway interactions Patients Peripheral Blood Mononuclear Cell Preclinical Testing Prediction of Response to Therapy Production Prognosis Prognostic Marker Proliferating Resistance Signal Pathway Signal Transduction Sphingolipids Sphingosine Stromal Neoplasm Suppressor-Effector T-Lymphocytes System Systemic Therapy T cell infiltration T cell response T-Lymphocyte Technology Testing Therapeutic Tissue Engineering Tissue Model Tissues Treatment Efficacy Treatment Protocols Tumor-infiltrating immune cells United States anti-PD-1 cancer immunotherapeutics cancer immunotherapy checkpoint therapy clinical translation density digital dihydroceramide desaturase driver mutation effector T cell enzyme pathway exhaustion genetic signature glucose metabolism human disease human model human tissue immune cell infiltrate immune resistance immunoregulation improved individualized medicine inhibitor inhibitor therapy insight metabolic fitness mimetics molecular diagnostics nano-string neoplastic cell novel patient population patient response peripheral blood personalized diagnostics pharmacologic predicting response predictive marker programmed cell death ligand 1 recruit resistance mechanism response spatial relationship sphingosine 1-phosphate sphingosine kinase targeted treatment therapy design three-dimensional modeling transcriptome translational approach treatment strategy tumor tumor growth tumor immunology tumor microenvironment two-dimensional

项目摘要

项目成果

Jessy Satyadas Deshane的其他基金

相似基金

相关文献

中文摘要

翻译

项目摘要/摘要免疫抑制和对免疫检查点抑制物(Ici)的抵抗是成功的主要障碍。非小细胞肺癌的免疫治疗。在非小细胞肺癌中，肿瘤侵袭的密度和多样性肿瘤微环境中的免疫细胞与预后、治疗预测密切相关 ICI一线综合治疗的疗效和良好的存活率。患者的异质性在 TME内的免疫细胞组成表明，免疫浸润物的组成和它们的 TME内的功能状态对于诊断和设计治疗策略以及预测生物标志物。这个项目的中心目标是利用我们新的三维人体组织模型 (3D-LTB)，概括了人类肺癌的组织维度和微环境，以测试假设影响肿瘤-间质串扰和鞘磷脂信号通路的调制免疫抑制髓系来源的抑制细胞(MDSCs)在肺TME中的渗透改变了空间分布驻留和招募效应细胞的动态变化以增强对非小细胞肺癌免疫靶向治疗的反应。在Aim1中，将利用患者来源的肿瘤和前沿的GeoMx数字空间概况平台来定义免疫治疗后3D-LTB内效应T细胞的动态和空间分布。研究在Aim 2中，将确定鞘磷脂变阻器的药理学靶向是否改变肿瘤-间质串扰和使用目标1中描述的相同平台增强对免疫疗法的反应。据我们所知，这是第一个完全开发的非小细胞肺癌3D模型，完全概括了肺癌与免疫之间的相互作用。我们的研究有能力定义患者的异质性并识别空间信息的生物标记物，以响应ICI 非小细胞肺癌。这个优化的模型系统模拟了可外推的生长特征和分子特征人类疾病中的抵抗机制。

英文摘要

PROJECT SUMMARY/ABSTRACT Immune suppression and resistance to immune checkpoint inhibitors (ICI) are major obstacles for successful immunotherapy for non small cell lung cancer (NSCLC). In NSCLC, the density and diversity of tumor-infiltrating immune cells in the tumor microenvironment (TME) are closely related to prognosis, prediction of treatment efficacy of frontline combination therapies with ICI and favorable survival. The patient heterogeneity in the immune cell composition within the TME indicates that mapping the composition of immune infiltrates and their functional state within the TME is important for diagnosing and designing treatment strategies and for predicting biomarkers. The central objective of this project is to utilize our novel three dimensional human tissue model (3D-LTB) that recapitulates tissue dimensionality and microenvironment of human lung tumors to test the hypothesis that modulation of tumor-stromal crosstalk and sphingolipid signaling pathways that influence infiltration of immune suppressive myeloid-derived suppressor cells (MDSCs) in the lung TME alters the spatial dynamics of resident and recruited effector cells to enhance response to immune targeted therapies for NSCLC. In Aim1, patient-derived tumors and cutting edge GeoMx Digital Spatial Profiling platform will be utilized to define the dynamics and spatial profiles of effector T cells within the 3D-LTBs in response to immunotherapy. Studies in Aim 2 will determine if pharmacological targeting of sphingolipid rheostat alters tumor-stromal crosstalk and enhances response to immunotherapy using the same platform described in Aim 1. To our knowledge, this is the first fully developed 3D model of NSCLC that fully recapitulate lung cancer-immune interactions. Our studies have the power to define patient heterogeneity and identify spatially informed biomarkers in response to ICI in NSCLC. This optimized model system mimics extrapolatable growth characteristics and molecular signatures of resistance mechanisms in the human disease.

期刊论文(0)

专著(0)

科研奖励(0)

会议论文