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: 10674023
• 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/10674023
• 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; Machine Learning; Malignant Neoplasms; Malignant neoplasm of pancreas; Maps; 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; Postdoctoral Fellow; Predisposition; Primary Neoplasm; Program Development; Research; Research Personnel; Research Project Grants; Resistance; Resolution; Role; Scientist; Shapes; Solid Neoplasm; Structure; T-Lymphocyte; Techniques; Technology; Testing; Therapeutic antibodies; Thick; Tissues; Training; Transgenic Mice; Tumor-associated macrophages; anti-PD-L1 antibodies; 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; immune cell infiltrate; immunoregulation; improved; insight; invention; mouse model; multiple omics; multiplexed imaging; novel; novel anticancer drug; novel therapeutic intervention; overexpression; pancreatic ductal adenocarcinoma model; pancreatic neoplasm; panitumumab; patient derived xenograft model; periostin; preclinical efficacy; programs; resistance mechanism; response; spatial integration; transcriptomics; 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.

项目概要 该提案描述了一个职业发展计划，旨在为卢博士的独立研究生涯做好准备 专注于开发计算和实验方法来改善癌症检测、诊断、 该项目将为陆博士提供单细胞空间组学方面的新专业知识，并将其与 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（作为博士后研究员获得）以增进我们对细胞药物成像机制的理解 驱动胰腺癌耐药性的研究将由发明者 Garry Nolan 博士指导。 用于高度多重单细胞成像的 CODEX 技术，由 Eben Rosenthal 博士共同指导 开创了荧光引导癌症手术首次人体临床研究的医师科学家， Robert West 博士，开发了用于空间转录组学的 Smart-3SEQ 技术。 Lu 的培训将包括 (i) 主要导师和共同导师的结构化指导，(ii) 密切互动 与咨询委员会和合作者一起，(iii) 技术和学术培训，(iv) 一项具有挑战性的研究 项目，以及 (v) 职业转型计划。 阐明肿瘤微环境 (TME) 在耐药性中的作用对于提高疗效至关重要 癌症治疗，但量化药物输送和作用以及宿主环境因素 临床肿瘤在技术上仍然具有挑战性。基于抗体的治疗，例如抗体药物缀合物。 （ADC）和免疫检查点抑制剂（ICIs）特别容易受到 TME 屏障的阻断。 该项目的总体目标是确定导致胰腺导管耐药的 TME 因素 通过将治疗性抗体的单细胞地理空间映射与深部腺癌（PDAC）相结合 TME 的空间分析的中心假设是骨膜素和肿瘤相关巨噬细胞（TAM）。 在抑制 PDAC 的药物递送和反应中发挥关键作用 将通过追求来检验中心假设。 三个目标：（目标 1）通过集成 CODEX 和 Smart-3SEQ 建立计算空间组学平台 以公正的方式绘制 PDAC TME 的基线架构（目标 2），将单细胞药物成像与 空间组学，以确定基质屏障对抗体递送至 PDAC 的影响，并评估是否 抑制骨膜素可改善患者来源的异种移植小鼠中抗 EGFR 抗体和 ADC 的递送 模型；以及（目标 3）检查化疗在改变人类 TAM 表型和功能中的作用 和小鼠 PDAC；识别化疗引起的 PDAC 患者 TAM-ICI 相互作用的改变 荧光抗 PD-L1 抗体；以及验证抑制 TAM-ICI 相互作用是否可以改善对 ICI 的反应 在 PDAC 转基因小鼠模型中加上化疗 该项目将为 PDAC 提供新的计算工具。 细胞量化临床肿瘤中的细胞和细胞-药物相互作用，为耐药性提供新的机制见解 胰腺癌，并带来新的治疗策略以提高患者的生存率。