Abstract
Purpose of Review
Cancer is often a complicated and dynamic disease, which makes determining the optimal treatment for a given patient a difficult endeavor. Moreover, even within a particular cancer type, different patients often have varying responses to the same therapies. Bioengineered tumor model systems specific to patients would allow preemptive screening of personalized therapies, facilitating identification of the most effective treatments prior to administration in the patients. Here, we provide an overview of organoid technology, and how these bioengineered tumor models can be harnessed for patient-centric personalized oncology.
Recent Findings
Organoid models have ranged from simple cell spheroids to more complex tumor-on-a-chip systems. The earliest of these models were comprised of easy to culture cell lines, but recent advances in 3D cell culture approaches have facilitated generation of human primary cell-based organoids. Importantly, recent efforts have been made to employ tumor biospecimens from human patients to create personalized tumor models for patient-specific predictive drug screening.
Summary
Bioengineering and tissue engineering technologies have advanced significantly in recent years, culminating in the capability to biofabricate tissue and tumor organoids derived from individual human patients. In the near future, we anticipate such models being implemented in parallel with clinical practice as patient-oriented screening tools, thereby improving the success rates of oncology.
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Andrea Mazzocchi and Konstantinos Votanopoulos declare that they have no conflict of interest.
Aleksander Skardal reports a pending patent on cancer modeling platforms and methods of using the same.
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This article does not contain any studies with human or animal subjects performed by any of the authors.
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This article is part of the Topical Collection on Artificial Tissues
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Mazzocchi, A., Votanopoulos, K. & Skardal, A. Personalizing Cancer Treatments Empirically in the Laboratory: Patient-Specific Tumor Organoids for Optimizing Precision Medicine. Curr Stem Cell Rep 4, 97–104 (2018). https://doi.org/10.1007/s40778-018-0122-z
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DOI: https://doi.org/10.1007/s40778-018-0122-z