Integrating Spatial Omics and Drug Imaging to Dissect the Role of Pancreatic Tumor Microenvironment in Drug Resistance

整合空间组学和药物成像来剖析胰腺肿瘤微环境在耐药性中的作用

• 批准号: 10525954
• 负责人: Guolan Lu
• 金额: $ 14.73万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10525954
• 关键词: Academic Training; Advisory Committees; Antibodies; Antibody Binding Sites; Antibody Therapy; Antibody-drug conjugates; Antineoplastic Agents; Architecture; Automobile Driving; Cancer Detection; Career Mobility; Cell Communication; Cells; Cetuximab; Clinic; Clinical; Clinical Research; Clinical Trials; Complex; Computing Methodologies; Cytotoxic T-Lymphocytes; Data; Dendritic Cells; Development; Diagnosis; Disease; Dose; Drug Delivery Systems; Drug Interactions; Drug resistance; Encapsulated; Environment; Epidermal Growth Factor Receptor; Extracellular Matrix; Extracellular Matrix Proteins; Fibroblasts; Fluorescence; Goals; Human; Image; Immune; Immune checkpoint inhibitor; Immunologics; Immunosuppression; Intravenous; Lead; Machine Learning; Malignant Neoplasms; Malignant neoplasm of pancreas; Measures; Mediating; Mentors; Mentorship; Methods; Molecular; Monoclonal Antibodies; Mus; Operative Surgical Procedures; Pancreatic Ductal Adenocarcinoma; Pathway interactions; Patient-Focused Outcomes; Patients; Penetration; Pharmaceutical Preparations; Phase; Phenotype; Physicians; Play; Primary Neoplasm; Program Development; Research; Research Personnel; Research Project Grants; Resistance; Resolution; Role; Scientist; Solid Neoplasm; Structure; T-Lymphocyte; Techniques; Technology; Testing; Therapeutic Monoclonal Antibodies; Therapeutic antibodies; Thick; Tissues; Training; Transgenic Mice; Tumor-associated macrophages; Tumor-infiltrating immune cells; anti-PD-L1 antibodies; base; cancer cell; cancer surgery; cancer therapy; cancer type; career; career development; cell type; cellular imaging; chemotherapy; clinical efficacy; clinical imaging; computerized tools; deep learning; drug action; fibrogenesis; first-in-human; graduate student; imaging modality; imaging platform; immunoregulation; improved; insight; mouse model; multiple omics; multiplexed imaging; novel; novel anticancer drug; overexpression; pancreatic ductal adenocarcinoma model; pancreatic neoplasm; panitumumab; patient derived xenograft model; periostin; preclinical efficacy; programs; resistance mechanism; response; transcriptomics; treatment strategy; tumor; tumor microenvironment; tumor-immune system interactions; uptake

PROJECT SUMMARY This proposal describes a career development program to prepare Dr. Lu for an independent research career that focuses on developing computational and experimental methods to improve cancer detection, diagnosis, and treatment. This program will provide Dr. Lu with new expertise in single-cell spatial omics, integrating with her background in machine learning-based image computation (gained as a graduate student) and clinical single- cell drug imaging (gained as a postdoctoral researcher) to advance our understanding of the mechanism that drives drug resistance of pancreatic cancer. Dr. Lu will be mentored by Dr. Garry Nolan, who invented the CODEX technology for highly multiplexed single-cell imaging, and co-mentored by Dr. Eben Rosenthal, a physician-scientist who pioneered the first-in-human clinical studies for fluorescence-guided cancer surgery, and Dr. Robert West, who developed the Smart-3SEQ technology for spatial transcriptomics. The K99 phase of Dr. Lu’s training will consist of (i) structured mentorship by the primary mentor and co-mentors, (ii) close interactions with advisory committee and collaborators, (iii) technical and academic training, (iv) a provocative research project, and (v) a program of career transition. Elucidating the role of the tumor microenvironment (TME) in drug resistance is critical to developing effective cancer therapies, but quantifying the drug delivery and action together with host environment factors within clinical tumors remains technically challenging. Antibody-based therapeutics, such as antibody-drug conjugates (ADCs) and immune checkpoint inhibitors (ICIs), are especially susceptible to blockade by TME barriers. The overall objective of this project is to identify the TME factors driving drug resistance in pancreatic ductal adenocarcinoma (PDAC) by integrating single-cell geospatial mapping of therapeutic antibodies with the deep spatial profiling of the TME. The central hypothesis is that periostin and tumor-associated macrophages (TAMs) play a key role in inhibiting drug delivery and response in PDAC. The central hypothesis will be tested by pursuing three aims: (Aim 1) establish a computational spatial omics platform by integrating CODEX and Smart-3SEQ to chart the baseline architecture of PDAC TME in an unbiased way; (Aim 2) combine single-cell drug imaging with spatial omics to determine the impact of stromal barriers to antibody delivery into PDAC and evaluate whether inhibiting periostin improves the delivery of anti-EGFR antibodies and ADCs in patient-derived xenograft mouse models; and (Aim 3) examine the role of chemotherapy in altering the phenotype and function of TAMs in human and mouse PDAC; identify chemo-induced alterations in TAM-ICI interactions in PDAC patients infused with a fluorescent anti-PD-L1 antibody; and validate whether inhibiting TAM-ICI interactions improves response to ICI plus chemotherapy in a transgenic mice model of PDAC. This project will provide novel computational tools to quantify cell-cell and cell-drug interactions in clinical tumors, offer new mechanistic insights on drug resistance in pancreatic cancer, and lead to new treatment strategies to improve patient survival.

项目摘要 这份建议书描述了一个职业发展计划，为陆博士的独立研究生涯做准备 该项目致力于开发计算和实验方法，以改善癌症检测，诊断， 和治疗。该计划将为Lu博士提供单细胞空间组学的新专业知识， 她在基于机器学习的图像计算（作为研究生获得）和临床单方面的背景， 细胞药物成像（作为博士后研究人员获得），以促进我们对 导致了胰腺癌的抗药性卢博士将由加里·诺兰博士指导，他发明了 用于高度多路复用单细胞成像的CODEX技术，由Eben Rosenthal博士共同指导， 医生兼科学家，开创了荧光引导癌症手术的首次人体临床研究， 博士Robert West开发了用于空间转录组学的Smart-3SEQ技术。博士的K99阶段。 卢的培训将包括（i）由主要导师和共同导师进行的结构化指导，（ii）密切互动 与咨询委员会和合作者，（iii）技术和学术培训，（iv）挑衅性研究 项目，（五）职业转型计划。 阐明肿瘤微环境（TME）在耐药性中的作用对于开发有效的抗肿瘤药物至关重要。 癌症治疗，但量化药物输送和行动连同宿主环境因素， 临床肿瘤在技术上仍然具有挑战性。基于抗体的治疗剂，例如抗体-药物缀合物 ADC和免疫检查点抑制剂（ICI）特别容易受到TME屏障的阻断。的 该项目的总体目标是确定在胰腺导管中驱动耐药性的TME因素 通过将治疗性抗体的单细胞地理空间映射与深度免疫组织化学相结合， TME的空间分布。核心假设是骨膜蛋白和肿瘤相关巨噬细胞（TAM） 在PDAC中抑制药物递送和反应中起关键作用。中心假设将通过以下方式进行检验： 三个目标：（目标1）整合CODEX和Smart-3SEQ，建立计算空间组学平台， 以无偏的方式绘制PDAC TME的基线结构;（目标2）将联合收割机单细胞药物成像与 空间组学，以确定间质屏障对抗体递送至PDAC的影响，并评估是否 抑制骨膜蛋白改善抗EGFR抗体和ADC在患者来源的异种移植小鼠中的递送 目的3：研究化疗对人TAM表型和功能的影响 和小鼠PDAC;在输注了抗肿瘤药物的PDAC患者中鉴定化学诱导的TAM-ICI相互作用的改变。 荧光抗PD-L1抗体;并验证抑制TAM-ICI相互作用是否改善对ICI的应答 在PDAC的转基因小鼠模型中加化疗。该项目将提供新的计算工具， 量化临床肿瘤中的细胞-细胞和细胞-药物相互作用，为耐药性提供新的机制见解 并导致新的治疗策略，以提高患者的生存率。