Cell Reports (Jul 2021)
A pan-cancer organoid platform for precision medicine
- 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
Affiliations
- Brian M. Larsen
- Tempus Labs, Chicago, IL 60654, USA
- Madhavi Kannan
- Tempus Labs, Chicago, IL 60654, USA
- Lee F. Langer
- Tempus Labs, Chicago, IL 60654, USA
- Benjamin D. Leibowitz
- Tempus Labs, Chicago, IL 60654, USA
- Aicha Bentaieb
- Tempus Labs, Chicago, IL 60654, USA
- Andrea Cancino
- Tempus Labs, Chicago, IL 60654, USA
- Igor Dolgalev
- Perlmutter Cancer Center NYU Langone Health, New York City, NY 10016, USA
- Bridgette E. Drummond
- Tempus Labs, Chicago, IL 60654, USA
- Jonathan R. Dry
- Tempus Labs, Chicago, IL 60654, USA
- Chi-Sing Ho
- Tempus Labs, Chicago, IL 60654, USA
- Gaurav Khullar
- Tempus Labs, Chicago, IL 60654, USA
- Benjamin A. Krantz
- Perlmutter Cancer Center NYU Langone Health, New York City, NY 10016, USA
- Brandon Mapes
- Tempus Labs, Chicago, IL 60654, USA
- Kelly E. McKinnon
- Tempus Labs, Chicago, IL 60654, USA
- Jessica Metti
- Tempus Labs, Chicago, IL 60654, USA
- Jason F. Perera
- Tempus Labs, Chicago, IL 60654, USA
- Tim A. Rand
- Tempus Labs, Chicago, IL 60654, USA
- Veronica Sanchez-Freire
- Tempus Labs, Chicago, IL 60654, USA
- Jenna M. Shaxted
- Tempus Labs, Chicago, IL 60654, USA
- Michelle M. Stein
- Tempus Labs, Chicago, IL 60654, USA
- Michael A. Streit
- Tempus Labs, Chicago, IL 60654, USA
- Yi-Hung Carol Tan
- Department of Medicine, University of Chicago, Chicago, IL 60637, USA
- Yilin Zhang
- Tempus Labs, Chicago, IL 60654, USA
- Ende Zhao
- Department of Medicine, University of Chicago, Chicago, IL 60637, USA
- Jagadish Venkataraman
- Tempus Labs, Chicago, IL 60654, USA
- Martin C. Stumpe
- Tempus Labs, Chicago, IL 60654, USA
- Jeffrey A. Borgia
- Department of Cell & Molecular Medicine, Department of Pathology, Rush University Medical Center, Chicago, IL 60612, USA
- Ashiq Masood
- Department of Internal Medicine, Rush University Medical Center, Chicago, IL 60612, USA
- Daniel V.T. Catenacci
- Perlmutter Cancer Center NYU Langone Health, New York City, NY 10016, USA
- Jeremy V. Mathews
- Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
- Demirkan B. Gursel
- Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
- Jian-Jun Wei
- Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
- Theodore H. Welling
- Perlmutter Cancer Center NYU Langone Health, New York City, NY 10016, USA
- Diane M. Simeone
- Perlmutter Cancer Center NYU Langone Health, New York City, NY 10016, USA
- Kevin P. White
- Tempus Labs, Chicago, IL 60654, USA
- Aly A. Khan
- Tempus Labs, Chicago, IL 60654, USA; Department of Pathology, Biological Sciences Division, University of Chicago, Chicago, IL 60637, USA; Corresponding author
- Catherine Igartua
- Tempus Labs, Chicago, IL 60654, USA; Corresponding author
- Ameen A. Salahudeen
- Tempus Labs, Chicago, IL 60654, USA; Corresponding author
- Journal volume & issue
-
Vol. 36,
no. 4
p. 109429
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.
