High-Throughput Screen of Advanced Prostate Cancer Organoids and PDX Preclinical Trials to Identify Single and Combination Therapies Correlated with Genotype

Abstract

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 prostate cancer. 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.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2019
Accession Number
AD1098876

Entities

People

  • Kathleen Kelly

Organizations

  • Geneva Foundation

Tags

DTIC Thesaurus Topics

  • Androgen Receptors
  • Biological Markers
  • Biomedical Research
  • Cancer
  • Clinical Trials
  • Combination Therapy
  • Correlation Analysis
  • Genetics
  • Genotypes
  • Neoplasms
  • Platforms
  • Prostate
  • Prostate Cancer
  • Therapy
  • Three Dimensional
  • Throughput
  • Xenografts

Fields of Study

  • Medicine

Readers

  • Oncology

Technology Areas

  • AI & ML
  • Autonomy