Automated microfluidic platform for dynamic and combinatorial drug screening of tumor organoids

Brooke Schuster, Michael Junkin, Sara Saheb Kashaf, Isabel Romero-Calvo, Kori Kirby, Jonathan Matthews, Christopher R. Weber, Andrey Rzhetsky, Kevin P. White and Savaş Tay ()
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Brooke Schuster: The University of Chicago
Michael Junkin: The University of Chicago
Sara Saheb Kashaf: The University of Chicago
Isabel Romero-Calvo: The University of Chicago
Kori Kirby: The University of Chicago
Jonathan Matthews: The University of Chicago
Christopher R. Weber: The University of Chicago Medicine
Andrey Rzhetsky: The University of Chicago
Kevin P. White: The University of Chicago
Savaş Tay: The University of Chicago

Nature Communications, 2020, vol. 11, issue 1, 1-12

Abstract: Abstract Three-dimensional (3D) cell culture technologies, such as organoids, are physiologically relevant models for basic and clinical applications. Automated microfluidics offers advantages in high-throughput and precision analysis of cells but is not yet compatible with organoids. Here, we present an automated, high-throughput, microfluidic 3D organoid culture and analysis system to facilitate preclinical research and personalized therapies. Our system provides combinatorial and dynamic drug treatments to hundreds of cultures and enables real-time analysis of organoids. We validate our system by performing individual, combinatorial, and sequential drug screens on human-derived pancreatic tumor organoids. We observe significant differences in the response of individual patient-based organoids to drug treatments and find that temporally-modified drug treatments can be more effective than constant-dose monotherapy or combination therapy in vitro. This integrated platform advances organoids models to screen and mirror real patient treatment courses with potential to facilitate treatment decisions for personalized therapy.

Date: 2020
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DOI: 10.1038/s41467-020-19058-4

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