Prostate Cancer Organoids

Establishing experimental model systems for prostate cancer (PCa) that accurately simulate both the genetic divergence and lineage specificity of cancer is essential for perceiving the function of cancer-related genetic changes in tumorigenesis, tumor maintenance, and therapeutic sensitivity or resistance.

PCa is the most common malignancy and the second most common cause of cancer death in Western men. PCa represents a complex organ-like multicellular structure maintained by dynamic interactions of tumoral cells with parenchymal stroma, endothelial and immune cells, and components of the extracellular matrix (ECM). The lack of PCa models that recapitulate this complex system has hindered progress toward understanding disease progression and lackluster therapeutic responses. Monolayer cultures fail to mimic the complexities of the PCa microenvironment or reproduce the diverse mechanisms of treatment resistance. Patient derived xenografts (PDXs) are expensive, time- consuming, difficult to establish for prostate cancer, lack immune cell-tumor regulation, and usually tumors undergo selective engraftments. The development of three-dimensional (3D) organoid culture system makes it possible to outline the convolution of organogenesis in vitro, thereby promoting the generation of novel and more representative cancer models.

Organoid model possesses a number of advantages compared with the PDX systems. For example, organoids are more easily amenable to genetic modification. While PDXs are not suitable for gene manipulation studies, these assays can be readily performed on organoid models. In addition, PDX models cannot be subjected to high-throughput drug screening, which can be easily performed on organoids to identify drug candidates. Once identified, such drug candidates can be tested on corresponding PDX models to confirm therapeutic efficacy in vivo.

Our team has taken the effort to generate human prostate cancer patient-derived organoids, aiming to fill the gap between or even replace traditional cancer cell lines and PDXs. These preclinical models can more accurately retain the histologic, molecular, and genetic characteristics of the primary patient’s tumor, and predict drug responses more precisely. In general, following the procurement of a patient sample, (pathologically assessed) tissue pieces are dissected and subjected to enzymatic digestion. The dissociated cells are then incorporated into a basement membrane matrix and covered with tissue-specific medium. With our prostate cancer organoids, OrganoLab can provide excellent insights into the basic research and the development of novel therapeutics for prostate cancer. If you have any questions or specific needs, please feel free to contact us.

References

1. Risbridger, G. P. et al.; Preclinical models of prostate cancer: Patient-derived xenografts, organoids, and other explant models. Cold Spring Harbor Perspectives in Medicine, 2018, 8(8).
2. Hepburn A. C. et al.; Engineering Prostate Cancer from Induced Pluripotent Stem Cells-New Opportunities to Develop Preclinical Tools in Prostate and Prostate Cancer Studies. Int J Mol Sci. 2020, 21(3): 905.
3. Bartucci, M. et al.; Personalized Medicine Approaches in Prostate Cancer Employing Patient Derived 3D Organoids and Humanized Mice. Frontiers in Cell and Developmental Biology, 4:64.
4. Gleave, A. M. et al.; A synopsis of prostate organoid methodologies, applications, and limitations. The Prostate, 2020, 80(6): 518-526.
5. Elbadawy M. et al.; Development of Prostate Cancer Organoid Culture Models in Basic Medicine and Translational Research. Cancers (Basel), 2020, 12(4): 777.
6. Puca, L. et al.; Patient derived organoids to model rare prostate cancer phenotypes. Nat Commun, 2018, 9, 2404.
7. Drost, J. et al.; Organoid culture systems for prostate epithelial and cancer tissue. Nature Protocols. 2016, 11(2): 347-358.
8. Van H. A. et al.; Novel patient-derived 3D culture models to guide clinical decision-making in prostate cancer. Current Opinion in Endocrine and Metabolic Research, 2020, 10: 7-15.