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

基本信息

批准号：
10670310
负责人：
Jonathan Brody
金额：
$ 54.67万
依托单位：
OREGON HEALTH & SCIENCE UNIVERSITY
依托单位国家：
美国
项目类别：
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/10670310
关键词：
3-Dimensional Affect Algorithms Automobile Driving Bioinformatics Biologic Characteristic Biological Biological Models Biology CDKN2A gene Cancer Biology Cancer Etiology Cancer Model Categories 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 Data Correlations Database Management Systems Development Disease Disease model Drug Compounding Drug resistance Elements Endothelium Enrollment Ensure Epigenetic Process Generations Genes Genetic Genetic Heterogeneity Human Human Characteristics Immune Inflammation Institution 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 Poly(ADP-ribose) Polymerase Inhibitor RNA Recommendation 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 bioprinting cancer cell cell type chemotherapy cohort comparative data harmonization design drug response prediction drug sensitivity exome sequencing improved in vivo insight multidisciplinary multiple omics neoplastic neoplastic cell novel therapeutic intervention pancreatic cancer model pancreatic ductal adenocarcinoma model patient derived xenograft model patient response phosphoproteomics programs resistance mechanism response sample collection standard of care targeted treatment therapeutically effective three dimensional structure tissue registry tool transcriptome sequencing treatment response tumor tumor initiation tumor microenvironment wiki

项目摘要

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.

项目概要胰腺导管腺癌（PDA）是一种致命的癌症，5年生存率<10%；据预测到 2020 年，将成为美国癌症相关死亡的第二大原因。四名司机的躯体改变基因（KRAS、TP53、CDKN2A 和 SMAD4）在许多 PDA 病例中很常见；然而，PDA 可以表型分为多种肿瘤亚型，每种亚型都有多种基质类型和抗肿瘤作用免疫。 PDA 的治疗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过验证的源自患者的胰腺癌模型社区。作为转化患者衍生癌症模型 (PDMC) 使用的第一步，我们必须确定每种类型的 PDMC 的优点和局限性，包括 PDMC 是否反映遗传和生物学人类母体肿瘤的特征。在此，我们提出了一个多机构项目，旨在扩展我们现有的 PDA PDMC 库并描述哪些模型最能代表其父级的特定方面肿瘤。 PDMC 捕获肿瘤间异质性并可以维持促癌调控途径迫切需要更好地增强现有疗法并确定新的治疗策略。我们是目前正在收集 PDA 样本并生成条件重编程细胞 (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来源的异种移植物 (PDX) （即基于 PARP 抑制剂的）临床试验。生成的 PDMC 具有详细注释的临床结果和药物响应数据。在这里，我们将系统、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）和表型亚群与患者各自的肿瘤最匹配。我们还将通过添加来构建更复杂的 PDMC 亲本肿瘤微环境的元素可以恢复简单 PDMC 中缺乏的表型。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，我们组装了一个多拥有临床肿瘤学、标本采集/处理、病理学、癌症模型专业知识的学科团队生成、肿瘤微环境、计算生物学、RNA生物学、DNA修复和数据库管理。工作将围绕三个具体目标进行：目标 1，生成并验证 PDMC；确定是否关键的 PDA 信号通路与相匹配的亲本肿瘤是保守的；目标 2，从临床中鉴定 PDMC 追踪最能预测患者药物反应的样本；识别并瞄准关键的耐药途径；目标 3：识别简单 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）。一个这项研究的首要成果将是分享经过充分表征、经过验证的 PDMC 和分子见解与胰腺癌界一起研究 PDA 生物学和药物反应。