Journal article
Multiplexed Live-Cell Imaging for Drug Responses in Patient-Derived Organoid Models of Cancer
Journal of visualized experiments, Vol.203, e66072
01/05/2024
DOI: 10.3791/66072
PMCID: PMC11256050
PMID: 38251777
Abstract
Patient-derived organoid (PDO) models of cancer are a multifunctional research system that better recapitulates human disease as compared to cancer cell lines. PDO models can be generated by culturing patient tumor cells in extracellular basement membrane extracts (BME) and plating them as three-dimensional domes. However, commercially available reagents that have been optimized for phenotypic assays in monolayer cultures often are not compatible with BME. Herein, we describe a method to plate PDO models and assess drug effects using an automated live-cell imaging system. In addition, we apply fluorescent dyes that are compatible with kinetic measurements to quantify cell health and apoptosis simultaneously. Image capture can be customized to occur at regular time intervals over several days. Users can analyze drug effects in individual Z-plane images or a Z Projection of serial images from multiple focal planes. Using masking, specific parameters of interest are calculated, such as PDO number, area, and fluorescence intensity. We provide proof-of-concept data demonstrating the effect of cytotoxic agents on cell health, apoptosis, and viability. This automated kinetic imaging platform can be expanded to other phenotypic readouts to understand diverse therapeutic effects in PDO models of cancer.
Details
- Title: Subtitle
- Multiplexed Live-Cell Imaging for Drug Responses in Patient-Derived Organoid Models of Cancer
- Creators
- Kaitriana E. CollingEmily L. Symons - University of IowaLorenzo Buroni - Royal Marsden NHS Foundation TrustHiruni K. Sumanasiri - University of IowaJessica Andrew-Udoh - University of IowaEmily Witt - University of IowaHaley A. Losh - University of IowaAbigail M. Morrison - University of IowaKimberly K. Leslie - University of New MexicoChristopher J. Dunnill - Agilent TechnologiesJohann S. de Bono - Royal Marsden NHS Foundation TrustKristina W. Thiel - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Journal of visualized experiments, Vol.203, e66072
- Publisher
- MyJove Corporation
- DOI
- 10.3791/66072
- PMID
- 38251777
- PMCID
- PMC11256050
- ISSN
- 1940-087X
- eISSN
- 1940-087X
- Language
- English
- Date published
- 01/05/2024
- Academic Unit
- Radiation Oncology; Obstetrics and Gynecology
- Record Identifier
- 9984543132402771
Metrics
28 Record Views