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A pan-cancer organoid platform for precision medicine

Authors :
Brian M. Larsen
Madhavi Kannan
Lee F. Langer
Benjamin D. Leibowitz
Aicha Bentaieb
Andrea Cancino
Igor Dolgalev
Bridgette E. Drummond
Jonathan R. Dry
Chi-Sing Ho
Gaurav Khullar
Benjamin A. Krantz
Brandon Mapes
Kelly E. McKinnon
Jessica Metti
Jason F. Perera
Tim A. Rand
Veronica Sanchez-Freire
Jenna M. Shaxted
Michelle M. Stein
Michael A. Streit
Yi-Hung Carol Tan
Yilin Zhang
Ende Zhao
Jagadish Venkataraman
Martin C. Stumpe
Jeffrey A. Borgia
Ashiq Masood
Daniel V.T. Catenacci
Jeremy V. Mathews
Demirkan B. Gursel
Jian-Jun Wei
Theodore H. Welling
Diane M. Simeone
Kevin P. White
Aly A. Khan
Catherine Igartua
Ameen A. Salahudeen
Source :
Cell Reports, Vol 36, Iss 4, Pp 109429- (2021)
Publication Year :
2021
Publisher :
Elsevier, 2021.

Abstract

Summary: Patient-derived tumor organoids (TOs) are emerging as high-fidelity models to study cancer biology and develop novel precision medicine therapeutics. However, utilizing TOs for systems-biology-based approaches has been limited by a lack of scalable and reproducible methods to develop and profile these models. We describe a robust pan-cancer TO platform with chemically defined media optimized on cultures acquired from over 1,000 patients. Crucially, we demonstrate tumor genetic and transcriptomic concordance utilizing this approach and further optimize defined minimal media for organoid initiation and propagation. Additionally, we demonstrate a neural-network-based high-throughput approach for label-free, light-microscopy-based drug assays capable of predicting patient-specific heterogeneity in drug responses with applicability across solid cancers. The pan-cancer platform, molecular data, and neural-network-based drug assay serve as resources to accelerate the broad implementation of organoid models in precision medicine research and personalized therapeutic profiling programs.

Subjects

Subjects :
Biology (General)
QH301-705.5

Details

Language :
English
ISSN :
22111247
Volume :
36
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Cell Reports
Publication Type :
Academic Journal
Accession number :
edsdoj.9e05120e2cf8481abf4978520140395c
Document Type :
article
Full Text :
https://doi.org/10.1016/j.celrep.2021.109429