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Organoid Technology for Personalized Pancreatic Cancer Therapy

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Publisher Springer
Date 2021 Jan 25
PMID 33492660
Citations 9
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Abstract

Background: Pancreatic ductal adenocarcinoma has the lowest survival rate among all major cancers and is the third leading cause of cancer-related mortality. The stagnant survival statistics and dismal response rates to current therapeutics highlight the need for more efficient preclinical models. Patient-derived organoids (PDOs) offer new possibilities as powerful preclinical models able to account for interpatient variability. Organoid development can be divided into four different key phases: establishment, propagation, drug screening and response prediction. Establishment entails tailored tissue extraction and growth protocols, propagation requires consistent multiplication and passaging, while drug screening and response prediction will benefit from shorter and more precise assays, and clear decision-making tools.

Conclusions: This review attempts to outline the most important challenges that remain in exploiting organoid platforms for drug discovery and clinical applications. Some of these challenges may be overcome by novel methods that are under investigation, such as 3D bioprinting systems, microfluidic systems, optical metabolic imaging and liquid handling robotics. We also propose an optimized organoid workflow inspired by all technical solutions we have presented.

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References
1.
Kacarevic Z, Rider P, Alkildani S, Retnasingh S, Smeets R, Jung O . An Introduction to 3D Bioprinting: Possibilities, Challenges and Future Aspects. Materials (Basel). 2018; 11(11). PMC: 6266989. DOI: 10.3390/ma11112199. View

2.
Hafner M, Niepel M, Chung M, Sorger P . Growth rate inhibition metrics correct for confounders in measuring sensitivity to cancer drugs. Nat Methods. 2016; 13(6):521-7. PMC: 4887336. DOI: 10.1038/nmeth.3853. View

3.
Siegel R, Miller K, Jemal A . Cancer statistics, 2020. CA Cancer J Clin. 2020; 70(1):7-30. DOI: 10.3322/caac.21590. View

4.
Rahib L, Smith B, Aizenberg R, Rosenzweig A, Fleshman J, Matrisian L . Projecting cancer incidence and deaths to 2030: the unexpected burden of thyroid, liver, and pancreas cancers in the United States. Cancer Res. 2014; 74(11):2913-21. DOI: 10.1158/0008-5472.CAN-14-0155. View

5.
Bian B, Juiz N, Gayet O, Bigonnet M, Brandone N, Roques J . Pancreatic Cancer Organoids for Determining Sensitivity to Bromodomain and Extra-Terminal Inhibitors (BETi). Front Oncol. 2019; 9:475. PMC: 6560163. DOI: 10.3389/fonc.2019.00475. View