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. 2023 Dec 29;21(1):297.
doi: 10.1186/s12915-023-01799-5.

Leveraging the predictive power of 3D organoids in dogs to develop new treatments for man and man's best friend

Affiliations

Leveraging the predictive power of 3D organoids in dogs to develop new treatments for man and man's best friend

Karin Allenspach et al. BMC Biol. .

Abstract

Recent progress in adult stem cell technology, along with interdisciplinary collaboration in the field of One Health, has accelerated the development of 3D organoid cultures in non-model animals, such as dogs. These advancements have the potential to significantly impact disease modeling and drug development for many diseases shared between man and man’s best friend.

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Conflict of interest statement

KA and JPM are co-founders of 3D Health Solutions, Inc., a startup entity that commercializes drug screening assays using 3D canine organoids. CZ is an employee of 3D Health Solutions, Inc.

Figures

Fig. 1
Fig. 1
Immunofluorescent staining of canine bladder cancer organoids showing similar expression profiles of dog and human bladder cancer. A PAX8 (marker commonly identified in human bladder cancer, in red); DAPI (cell nuclei, blue) overlay. B CK5 (cytokeratin marker often positive in human bladder cancer, in red; UPK1 (uroplakin 1 marker, identifies bladder cancer origin, in green; DAPI (cell nuclei, in blue) overlay. C P53 (tumor suppressor gene marker often positive in human bladder cancer, in red; DAPI (cell nuclei, in blue) overlay. Scalebars: 100 μm (A), 500 μm (B and C)
Fig. 2
Fig. 2
Canine mammary tumor organoids. Tumor organoids derived from a canine malignant mammary tumor on day 3 of culture,  showing spherical structures typical of early organoid cultures (left), and after 3 passages, showing proliferation of the organoids  (right). Scale bar 300 μm
Fig. 3
Fig. 3
Simulated concentration-response relationship in 3D canine bladder cancer organoids after 24-h exposure to a candidate chemotherapeutic drug. The virtual simulations were based on a Sigmoid Imax model and included two patient sub-populations: (1) an example of a “responder” to the drug with a steep concentration-response curve (closed circles, GAM = 2) and (2) a non-responder who showed minimal changes in cell survival when increasing drug concentrations (open circles, GAM = 0.5). Virtual experimental data are represented as dots, while continuous lines represent model-derived simulations. GAM, gamma parameter (Hill coefficient) from the Sigmoid Imax model

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