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: 10238080
• 负责人: Jonathan Brody
• 金额: $ 71.43万
• 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/10238080
• 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/antagonist; 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; 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.

项目总结 胰腺导管腺癌(Pda)是一种致命的癌症，据预测，5年生存率为10%。 到2020年成为美国癌症相关死亡的第二大原因。四名驾驶员的躯体改变 基因(KRAS、TP53、CDKN2A和Smad4)在许多PDA病例中是常见的；然而，PDA可以 表型分为多个肿瘤亚型，每个亚型都有无数类型的间质和抗肿瘤 豁免权。在治疗PDA方面只取得了渐进的临床进展，可能是由于 这项研究缺乏经过充分注释和验证的胰腺癌患者来源的模型 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是否反映了遗传和生物 人类亲代肿瘤的特征。在此，我们提出了一个多机构项目，旨在扩大 我们现有的PDA PDMC库，并描绘了哪个模型(S)最能代表其父代的特定方面 肿瘤。捕捉肿瘤间异质性并能维持致癌调控通路的PDMC 迫切需要更好地加强目前的治疗方法和确定新的治疗策略。我们是 目前正在收集PDA标本并生成条件重编程细胞(CRC)、器官(ORG)、 和患者来源的异种移植(PDX)通过俄勒冈州胰腺组织注册中心和靶向治疗 (即，基于PARP抑制剂的)临床试验。产生的PDMCs具有良好的临床结果和药物注释 响应数据。在这里，我们将系统和彻底地剖析匹配的PDMC，以确定其意义 关键分子网络(包括KRAS、MYC、DDR、HUR和炎症)和表型亚群 与患者的肿瘤最匹配。我们还将通过添加以下内容构建更复杂的PDMC 亲本肿瘤微环境的要素，可恢复单纯PDMC中缺失的表型。 互补性药物敏感性研究将在简单和复杂的PDMC中进行测试，作为 它们与亲代肿瘤和患者反应的相关性。为了执行这项工作，我们已经组装了一支多 拥有临床肿瘤学、标本采集/处理、病理学、癌症模型方面的专业知识的学科团队 代、肿瘤微环境、计算生物学、RNA生物学、DNA修复和数据库 管理层。将在三个具体目标中开展工作：目标1，生成和验证私营部门会计准则；确定是否 关键的PDA信号通路与匹配的亲本肿瘤是保守的；目的2，从临床上鉴定PDMCs 跟踪样本，最好地预测患者的药物反应；识别和定位关键的耐药途径； 目标3：确定在简单的PDMC中丢失但可以恢复的信号通路和药物反应 通过添加亲本肿瘤的已知元素(例如，间质间充质细胞、内皮细胞和免疫细胞)。一个 这项研究的主要成果将是分享经过充分表征和验证的PDMC和分子洞察力 胰腺癌社区对PDA生物学和药物反应的研究。