High-Throughput Screen of Advanced Prostate Cancer Organoids and PDX Preclinical Trials to Identify Single and Combination Therapies Correlated with Genotype
Abstract
Despite the advances in our knowledge of prostate cancer (PC) biology and the widespread use of new Food and Drug Administration (FDA)-approved drugs (e.g., abiraterone acetate, enzalutamide, cabazitaxel, radium-223, and sipuleucel), approximately 27,000 men will still die this year of advanced PC. Essentially no patients with metastatic PC are cured of their disease. Thus, substantial research efforts continue to be directed toward identifying new targets and therapeutics for metastatic castration-resistant PC, but the ability to develop new effective therapies for advanced PC is greatly limited by the models used. The goal of our proposal is to identify new, highly effective agents and combinatorial therapies and identify biomarkers of responsive tumors for clinical trial patient selection. To achieve this goal, we have developed new methodology, and our research will provide validation of a platform that will allow fast, economic testing of new treatment strategies that provide highly translational results. We are proposing one of the first comprehensive screens with clinically relevant models of advanced PC. Our models, patient-derived xenografts, were established directly from patient tumors and grown in mice. These tumors were shown to look like and behave like tumors in the patients. However, because these models are growing in mice, they cannot readily be used for large-scale studies. To address this shortcoming, we have recently optimized the conditions to take these tumors from mice and grow them in three-dimensional cultures (organoids) in the laboratory. Moreover, in preliminary experiments, we have achieved reproducible results screening drugs with these organoids in a robot-assisted drug screening facility. The use of advanced prostate patient-derived xenografts, the robust growth of prostate organoid cultures, and the use of organoids in high-throughput screening approaches are all tremendous advances for the field. In this proposal, we will capitalize on these advances to accomplish the following: 1. Perform a high-throughput drug screen across 30 organoid tumor cultures using 110 clinically actionable drugs, and validate “hits” using mouse studies. 2. Test promising drugs in combination with each other. 3. Integrate molecular characteristics and therapeutic responses to identify predictors of response and candidate biomarkers. In our pilot screen, we found about 20% of drugs are effective against most tumor models. Already, we are seeing differences from common cell line models. For example, inhibitors of the BCLXL protein that works in PC-3 and other cell lines are not effective in organoid models, but inhibitors of a related protein (MCL1) are broadly effective. Another 20% of drugs are effective in select tumors. For drugs with select activity, we will work to identify predictive biomarkers that could be used to match the right patient with the right drug. We will use bioinformatics to match many genetic features and other molecular characteristics of the organoids and mouse tumors with their drug responses. The objective of our study is two-fold: 1. We seek to identify effective drugs and drug combinations that can be used to prioritize therapies for clinical trials. To that end, we focus on drugs that are either already in clinical trials for other diseases or targeting specific pathways implicated in advanced PC. By the end of 3 years, we expect to have nominated a drug or drug combination with high-quality laboratory and mouse data sufficient to justify a randomized phase II trial in patients with CRPC. 2. We will provide the PC research community with a large data set comprised of 30 well-characterized, diverse tumor models and their responses to 110 therapies targeting many different pathways thought to be important in PC. Given the breadth of tumor models we are examining and their clinical relevance, these data will be valuable to the research community
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Oct 29, 2018
- Source ID
- W81XWH1810767
Entities
People
- Kathleen Kelly
Organizations
- National Cancer Institute
- United States Army