Real-Time Apoptosis and Viability High-Throughput Screening of 3D Multicellular Tumor Spheroids Using the Celigo

Sarah Kessel1, Scott Cribbes1, Surekha Bonasu1

  • 11 Department of Technology R&D, Nexcelom Bioscience LLC, Lawrence, MA, USA.

Insights

This study introduces a real-time assay for evaluating cancer drug compounds in 3D tumor models. The method categorizes drug effects, improving the selection of qualified drug candidates for streamlined drug discovery.

Area of Science:

  • Oncology
  • Pharmacology
  • Biotechnology

Background:

  • Three-dimensional tumor spheroid models are crucial for cancer drug discovery.
  • The Celigo image cytometer facilitates high-throughput screening of 3D multicellular tumor spheroids (MCTS).
  • Real-time kinetic assays for apoptosis and viability enhance secondary screening of drug candidates.

Purpose of the Study:

  • To develop and validate a real-time kinetic assay for characterizing drug effects in 3D MCTS.
  • To categorize the apoptotic and cytotoxic effects of 14 compounds on glioblastoma U87MG MCTS.
  • To improve the secondary screening process for identifying qualified drug candidates and streamlining R&D.

Main Methods:

  • Utilized 3D MCTS derived from the U87MG glioblastoma cell line in 384-well plates.
  • Monitored kinetic apoptotic (caspase 3/7) and viability (propidium iodide) effects over 9 days.
  • Employed real-time screening to categorize compound effects as early/late cytotoxic, apoptotic, cytostatic, or none.

Main Results:

  • Successfully categorized the kinetic effects of 14 compounds on U87MG 3D MCTS.
  • Distinguished between early and late cytotoxic, apoptotic, and cytostatic responses.
  • Demonstrated the utility of real-time kinetic assays for detailed compound characterization.

Conclusions:

  • The real-time apoptosis and viability screening method serves as an improved secondary screen for drug discovery.
  • This approach enhances the understanding of drug mechanisms of action.
  • Streamlines the identification of qualified drug candidates, optimizing the research and development process.

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