Morphological screening of mesenchymal mammary tumor organoids to identify drugs that reverse epithelial-mesenchymal transition

Na Zhao, Reid T. Powell, Xueying Yuan, Goeun Bae, Kevin P. Roarty, Fabio Stossi, Martina Strempfl, Michael J. Toneff, Hannah L. Johnson, Sendurai A. Mani, Philip Jones, Clifford C. Stephan and Jeffrey M. Rosen ()
Additional contact information
Na Zhao: Baylor College of Medicine
Reid T. Powell: Center for Translational Cancer Research, Texas A&M Health Science Center, Institute of Biosciences and Technology
Xueying Yuan: Baylor College of Medicine
Goeun Bae: Center for Translational Cancer Research, Texas A&M Health Science Center, Institute of Biosciences and Technology
Kevin P. Roarty: Baylor College of Medicine
Fabio Stossi: Baylor College of Medicine
Martina Strempfl: Graz University of Technology, NAWI Graz
Michael J. Toneff: Department of Biology, Widener University
Hannah L. Johnson: Integrated Microscopy Core, Baylor College of Medicine
Sendurai A. Mani: University of Texas MD Anderson Cancer Center
Philip Jones: Institute of Applied Cancer Science (IACS), University of Texas MD Anderson Cancer Center
Clifford C. Stephan: Center for Translational Cancer Research, Texas A&M Health Science Center, Institute of Biosciences and Technology
Jeffrey M. Rosen: Baylor College of Medicine

Nature Communications, 2021, vol. 12, issue 1, 1-13

Abstract: Abstract The epithelial-mesenchymal transition (EMT) has been implicated in conferring stem cell properties and therapeutic resistance to cancer cells. Therefore, identification of drugs that can reprogram EMT may provide new therapeutic strategies. Here, we report that cells derived from claudin-low mammary tumors, a mesenchymal subtype of triple-negative breast cancer, exhibit a distinctive organoid structure with extended “spikes” in 3D matrices. Upon a miR-200 induced mesenchymal-epithelial transition (MET), the organoids switch to a smoother round morphology. Based on these observations, we developed a morphological screening method with accompanying analytical pipelines that leverage deep neural networks and nearest neighborhood classification to screen for EMT-reversing drugs. Through screening of a targeted epigenetic drug library, we identified multiple class I HDAC inhibitors and Bromodomain inhibitors that reverse EMT. These data support the use of morphological screening of mesenchymal mammary tumor organoids as a platform to identify drugs that reverse EMT.

Date: 2021
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-021-24545-3 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-24545-3

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-021-24545-3

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().