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


Journal

Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555

Informations de publication

Date de publication:
19 10 2020
Historique:
received: 03 01 2020
accepted: 25 09 2020
entrez: 20 10 2020
pubmed: 21 10 2020
medline: 11 11 2020
Statut: epublish

Résumé

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.

Identifiants

pubmed: 33077832
doi: 10.1038/s41467-020-19058-4
pii: 10.1038/s41467-020-19058-4
pmc: PMC7573629
doi:

Substances chimiques

Antineoplastic Agents 0

Banques de données

figshare
['10.6084/m9.figshare.12424673', '10.6084/m9.figshare.12424733']

Types de publication

Evaluation Study Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

5271

Subventions

Organisme : NIDDK NIH HHS
ID : P30 DK042086
Pays : United States
Organisme : NIGMS NIH HHS
ID : R01 GM127527
Pays : United States
Organisme : NICHD NIH HHS
ID : T32 HD007009
Pays : United States

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Auteurs

Brooke Schuster (B)

Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, 60637, USA.
Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL, 60637, USA.
Department of Chemistry, The University of Chicago, Chicago, IL, 60637, USA.

Michael Junkin (M)

Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, 60637, USA.
Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL, 60637, USA.

Sara Saheb Kashaf (SS)

Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, 60637, USA.
Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL, 60637, USA.

Isabel Romero-Calvo (I)

Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL, 60637, USA.

Kori Kirby (K)

Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL, 60637, USA.

Jonathan Matthews (J)

Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, 60637, USA.
Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL, 60637, USA.

Christopher R Weber (CR)

Department of Pathology, The University of Chicago Medicine, Chicago, IL, 60637, USA.

Andrey Rzhetsky (A)

Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL, 60637, USA.
Committee on Genetics, Genomics and Systems Biology, Departments of Medicine and Human Genetics, The University of Chicago, Chicago, IL, 60637, USA.

Kevin P White (KP)

Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL, 60637, USA.
Tempus Labs, Chicago, IL, 60654, USA.

Savaş Tay (S)

Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, 60637, USA. tays@uchicago.edu.
Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL, 60637, USA. tays@uchicago.edu.

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Classifications MeSH