Multiplexed Live-Cell Imaging for Drug Responses in Patient-Derived Organoid Models of Cancer
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-dim...
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Published in | Journal of visualized experiments no. 203 |
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Main Authors | , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
05.01.2024
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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. |
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AbstractList | 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. |
Author | Dunnill, Christopher J Sumanasiri, Hiruni K Losh, Haley A Andrew-Udoh, Jessica Leslie, Kimberly K Symons, Emily L Thiel, Kristina W Witt, Emily de Bono, Johann S Colling, Kaitriana E Buroni, Lorenzo Morrison, Abigail M |
Author_xml | – sequence: 1 givenname: Kaitriana E surname: Colling fullname: Colling, Kaitriana E organization: Department of Obstetrics and Gynecology, Carver College of Medicine, University of Iowa; Cancer Biology Graduate Program, Carver College of Medicine, University of Iowa – sequence: 2 givenname: Emily L surname: Symons fullname: Symons, Emily L organization: Department of Obstetrics and Gynecology, Carver College of Medicine, University of Iowa – sequence: 3 givenname: Lorenzo surname: Buroni fullname: Buroni, Lorenzo organization: The Institute of Cancer Research: and the Royal Marsden NHS Foundation Trust – sequence: 4 givenname: Hiruni K surname: Sumanasiri fullname: Sumanasiri, Hiruni K organization: Department of Obstetrics and Gynecology, Carver College of Medicine, University of Iowa – sequence: 5 givenname: Jessica surname: Andrew-Udoh fullname: Andrew-Udoh, Jessica organization: Department of Obstetrics and Gynecology, Carver College of Medicine, University of Iowa – sequence: 6 givenname: Emily surname: Witt fullname: Witt, Emily organization: Department of Obstetrics and Gynecology, Carver College of Medicine, University of Iowa; Department of Radiation Oncology, Carver College of Medicine, University of Iowa – sequence: 7 givenname: Haley A surname: Losh fullname: Losh, Haley A organization: Department of Obstetrics and Gynecology, Carver College of Medicine, University of Iowa – sequence: 8 givenname: Abigail M surname: Morrison fullname: Morrison, Abigail M organization: Department of Obstetrics and Gynecology, Carver College of Medicine, University of Iowa – sequence: 9 givenname: Kimberly K surname: Leslie fullname: Leslie, Kimberly K organization: Division of Molecular Medicine, Departments of Internal Medicine and Obstetrics and Gynecology, University of New Mexico Comprehensive Cancer Center, University of New Mexico Health Sciences Center – sequence: 10 givenname: Christopher J surname: Dunnill fullname: Dunnill, Christopher J organization: Agilent Technologies – sequence: 11 givenname: Johann S surname: de Bono fullname: de Bono, Johann S organization: The Institute of Cancer Research: and the Royal Marsden NHS Foundation Trust – sequence: 12 givenname: Kristina W surname: Thiel fullname: Thiel, Kristina W email: kristina-thiel@uiowa.edu organization: Department of Obstetrics and Gynecology, Carver College of Medicine, University of Iowa; Holden Comprehensive Cancer Center, University of Iowa; kristina-thiel@uiowa.edu |
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Title | Multiplexed Live-Cell Imaging for Drug Responses in Patient-Derived Organoid Models of Cancer |
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