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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.

项目总结