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High-Throughput In Vitro Assay using Patient-Derived Tumor Organoids
06:25

High-Throughput In Vitro Assay using Patient-Derived Tumor Organoids

Published on: June 14, 2021

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A simple high-throughput approach identifies actionable drug sensitivities in patient-derived tumor organoids

Nhan Phan1,2, Jenny J Hong1, Bobby Tofig3

  • 1Division of Hematology-Oncology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA.

Communications Biology
|March 2, 2019
PubMed

Insights

We developed a miniaturized, automated method for high-throughput screening of tumor organoids. This approach enables rapid identification of personalized drug responses for ovarian cancer patients within a week of surgery.

Area of Science:

  • Oncology
  • Biotechnology
  • Drug Discovery

Background:

  • Tumor organoids replicate patient-specific tumor characteristics, including heterogeneity and drug response.
  • Organoid models are promising for drug development and personalized medicine but face technical hurdles for high-throughput screening.
  • Current methods require extensive manipulation, limiting their application in rapid clinical decision-making.

Purpose of the Study:

  • To develop a miniaturized, automated, high-throughput screening method for patient-derived tumor organoids.
  • To enable rapid assessment of drug efficacy in ovarian cancer models.
  • To facilitate timely therapeutic decision-making for cancer patients.

Main Methods:

  • A novel miniaturized method using a simplified 'mini-ring' geometry for seeding cells.
  • Automation of high-throughput screening using patient-derived tumor organoids (ovarian, peritoneal).
  • Assessment of organoid viability, number, and size after exposure to 240 kinase inhibitors.

Main Results:

  • Demonstrated a miniaturized, automated platform compatible with high-throughput screening of tumor organoids.
  • Successfully identified personalized drug responses in four patient-derived ovarian cancer organoid models.
  • Obtained results within one week from sample collection, a clinically relevant timeframe.

Conclusions:

  • The developed method overcomes technical limitations of current organoid screening techniques.
  • This automated platform facilitates rapid, personalized drug response profiling for ovarian cancer.
  • The approach supports timely therapeutic strategy adjustments in clinical oncology.

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