Comparative analysis between patient-derived models of pancreatic ductal adenocarcinomas and matched tumor specimens

患者来源的胰腺导管腺癌模型与匹配肿瘤标本之间的比较分析

• 批准号: 10454908
• 负责人: Jonathan Brody
• 金额: $ 54.7万
• 依托单位: OREGON HEALTH & SCIENCE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-12 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10454908
• 关键词: 3-Dimensional; Affect; Algorithms; Automobile Driving; Bioinformatics; Biologic Characteristic; Biological; Biological Models; Biology; CDKN2A gene; Cancer Biology; Cancer Etiology; Cancer Model; Cell Death; Cell Proliferation; Cells; Cessation of life; Clinical; Clinical Oncology; Clinical Trials; Communities; Complement; Complex; Computational Biology; Computational algorithm; Critical Pathways; DNA Damage; DNA Repair; Data; Database Management Systems; Development; Disease; Disease model; Drug resistance; Elements; Endothelium; Enrollment; Ensure; Epigenetic Process; Generations; Genes; Genetic; Genetic Heterogeneity; Human; Human Characteristics; Immune; Inflammation; Inter-tumoral heterogeneity; KRAS2 gene; Knowledge; Laboratories; Libraries; MADH4 gene; Malignant Neoplasms; Malignant neoplasm of pancreas; Measures; Mesenchymal; Metadata; Metastatic Neoplasm to the Liver; Modeling; Molecular; Molecular Profiling; Mutation; Oncogenic; Oregon; Organoids; Outcome; Pancreas; Pancreatic Adenocarcinoma; Pancreatic Ductal Adenocarcinoma; Parents; Pathology; Pathway interactions; Patient-Focused Outcomes; Patients; Periodicity; Pharmaceutical Preparations; Phenotype; RNA; Regulator Genes; Regulatory Pathway; Research; Resistance; Sampling; Signal Pathway; Specimen; Standardization; Stromal Cells; Survival Rate; Synapses; TP53 gene; Testing; Therapeutic; Translating; Tumor Immunity; United States; Work; arm; base; bioprinting; cancer cell; cell type; chemotherapy; cohort; comparative; data harmonization; design; drug response prediction; drug sensitivity; exome sequencing; improved; in vivo; inhibitor; insight; multidisciplinary; multiple omics; neoplastic; neoplastic cell; novel therapeutic intervention; pancreatic cancer model; pancreatic ductal adenocarcinoma model; patient derived xenograft model; patient response; phosphoproteomics; resistance mechanism; response; sample collection; standard of care; targeted treatment; therapeutically effective; three dimensional structure; tissue registry; tool; transcriptome sequencing; treatment response; tumor; tumor microenvironment; wiki

PROJECT SUMMARY Pancreatic ductal adenocarcinoma (PDA) is a lethal cancer, with a 5-year survival rate of < 10%; it is predicted to become the 2nd leading cause of cancer-related deaths in the US by 2020. Somatic alterations of four driver genes (KRAS, TP53, CDKN2A, and SMAD4) are common among many cases of PDA; however, PDA can be phenotypically categorized into multiple neoplastic subtypes, each with myriad types of stroma and anti-tumor immunity. Only incremental clinical advances have been made in the treatment of PDA, potentially due to the paucity of well-annotated and validated patient-derived models of pancreatic cancer available to the research community. As a first step to translating the use of patient-derived models of cancer (PDMCs), we must identify the strengths and limitations of each type of PDMC, including whether PDMCs mirror genetic and biologic characteristics of the human, parent tumor. Herein, we propose a multi-institutional project designed to extend our existing library of PDA PDMCs and depict which model(s) best represent specific aspects of their parent tumors. PDMCs that capture an inter-tumor heterogeneity and can maintain pro-oncogenic regulatory pathways are critically needed to better enhance current therapies and identify novel therapeutic strategies. We are currently collecting PDA specimens and generating conditionally re-programmed cells (CRC), organoids (ORG), and patient-derived xenografts (PDX) through the Oregon Pancreas Tissue Registry and from a targeted therapy (i.e., PARP inhibitor-based) clinical trial. The PDMCs generated have well-annotated clinical outcomes and drug response data. Here, we will systematically and thoroughly profile matched PDMCs to determine the significance of key molecular networks (including KRAS, MYC, DDR, HuR, and inflammation) and phenotypic subpopulations that best match their respective tumors from patients. We will also build more complex PDMCs by adding elements of the parent tumor microenvironment that can restore phenotypes absent in simple PDMCs. Complementary drug sensitivity studies will be tested in both simple and complex PDMCs as another metric of their relatedness to the parent tumor and patient responses. To perform this work, we have assembled a multi- disciplinary team with expertise in clinical oncology, specimen collection/processing, pathology, cancer model generation, tumor microenvironment, computational biology, RNA biology, DNA repair, and database management. Work will be performed in three specific aims: Aim 1, generate and validate PDMCs; determine if key PDA signaling pathways are conserved with the matched parent tumor; Aim 2, identify PDMCs from clinically tracked specimens that best predict drug responses in patients; identify and target key pathways of resistance; Aim 3: identify signaling pathways and drug responses that are lost in simple PDMCs but that can be restored by adding known elements of the parent tumor (e.g., stromal mesenchymal, endothelial and immune cells). An overarching deliverable of this study will be to share well-characterized, validated PDMCs and molecular insights into PDA biology and drug responses with the pancreatic cancer community.

项目摘要 胰腺导管腺癌（PDA）是一种致死性癌症，5年生存率< 10%; 到2020年，它将成为美国癌症相关死亡的第二大原因。四个驱动器的体细胞改变 基因（KRAS、TP 53、CDKN 2A和SMAD 4）在许多PDA病例中是常见的;然而，PDA可以是 表型上分为多种肿瘤亚型，每种亚型都有无数类型的基质和抗肿瘤细胞。 免疫力在PDA的治疗方面仅取得了渐进的临床进展，这可能是由于 缺乏可用于研究的注释良好且经验证的胰腺癌患者模型 社区作为转化患者来源的癌症模型（PDMC）的第一步，我们必须确定 每种类型PDMC的优势和局限性，包括PDMC是否反映遗传和生物学 人类肿瘤的特征在此，我们提出了一个多机构的项目，旨在扩大 我们现有的PDA PDMC库，并描述哪些模型最能代表其父模型的特定方面 肿瘤的PDMC捕获肿瘤间异质性并可维持促癌基因调控途径 迫切需要更好地加强目前的治疗和确定新的治疗策略。我们 目前正在收集PDA标本并产生条件重编程细胞（CRC），类器官（ORG）， 以及通过俄勒冈州胰腺组织登记处和靶向治疗获得的患者源性异种移植物（PDX） (i.e.,基于PARP的临床试验。生成的PDMC具有良好注释的临床结局和药物敏感性。 响应数据。在这里，我们将系统地和彻底地分析匹配的PDMC，以确定其重要性。 关键分子网络（包括KRAS、MYC、DDR、HuR和炎症）和表型亚群 最符合他们各自肿瘤的样本我们还将构建更复杂的PDMC， 可以恢复在简单PDMC中缺失的表型的母体肿瘤微环境的元素。 补充药物敏感性研究将在简单和复杂的PDMC中进行测试，作为另一个衡量指标。 它们与母体肿瘤和患者反应的相关性。为了完成这项工作，我们已经组装了一个多- 具有临床肿瘤学、标本采集/处理、病理学、癌症模型方面专业知识的学科团队 肿瘤微环境，计算生物学，RNA生物学，DNA修复和数据库 管理将在三个具体目标下开展工作：目标1，生成和验证PDMC;确定 关键的PDA信号通路与匹配的母体肿瘤是保守的;目的2，从临床上鉴定PDMC， 跟踪最能预测患者药物反应的样本;识别并瞄准耐药的关键途径; 目标3：识别在简单PDMC中丢失但可以恢复的信号通路和药物反应 通过添加母体肿瘤的已知成分（例如，基质间充质细胞、内皮细胞和免疫细胞）。一个 本研究的总体交付成果将是分享经过充分表征、验证的PDMC和分子见解 PDA生物学和胰腺癌社区的药物反应。