Abstract
Androgen deprivation therapy has a central role in the treatment of advanced prostate cancer, often causing initial tumour remission before increasing independence from signal transduction mechanisms of the androgen receptor and then eventual disease progression. Novel treatment approaches are urgently needed, but only a fraction of promising drug candidates from the laboratory will eventually reach clinical approval, highlighting the demand for critical assessment of current preclinical models. Such models include standard, genetically modified and patient-derived cell lines, spheroid and organoid culture models, scaffold and hydrogel cultures, tissue slices, tumour xenograft models, patient-derived xenograft and circulating tumour cell eXplant models as well as transgenic and knockout mouse models. These models need to account for inter-patient and intra-patient heterogeneity, the acquisition of primary or secondary resistance, the interaction of tumour cells with their microenvironment, which make crucial contributions to tumour progression and resistance, as well as the effects of the 3D tissue network on drug penetration, bioavailability and efficacy.
Key points
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Ideally, tumour models will reflect inter-patient and intra-patient heterogeneity, primary and/or secondary resistance, the interaction of tumour cells with their microenvironment, and the effects of the 3D tissue architecture on drug penetration, bioavailability and efficacy.
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Various in vitro, ex vivo and in vivo models exist, each associated with defined advantages and disadvantages.
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In vitro and ex vivo models include standard, genetically modified and patient-derived cell lines, spheroid and organoid culture models, scaffold and hydrogel cultures, and tissue slice models.
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In vivo models — including tumour xenografts, patient-derived xenografts and circulating tumour cell eXplant models, as well as transgenic and knockout mouse models — are still indispensable for prostate cancer research.
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Successful experimental prostate cancer research will require exploration of the full complexity of the disease, relying on the combined use of the broad spectrum of models.
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Novel approaches will be required for holistic and sophisticated analyses, for example, characterizations at a single-cell level in vivo or the extensive integration of computational and/or artificial intelligence-based approaches.
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Acknowledgements
The authors‘ own research related to the topics of this article was supported by the Deutsche Forschungsgemeinschaft (DFG; AI 24/26-1 (A.A.), TA 145/17-1 (H.T.), WE 5844/5-1 (St.W.), SPP2048 ‘microbone’ SA 3254/1-1 (V.S.), SPP2048 ‘microbone’ (Project-ID 401179983; S.P.), Ki 672/6-1 (J.K.), SPP ‘microbone’ and ERC Advanced Investigator Grant INJURMET (No. 834974; K.P.) as well as SFB 992 (Project-ID 403222702), SFB 1381 (Project-ID 89986987), SFB 850 and Schu688/15-1 to R.S.). The work was further supported by a grant of the Rudolf Becker-Foundation (T0321/36080/2020/kg) to S.P. and J.K., by the Federal Ministry for Economic Affairs and Climate Action (S.D.), by a fellowship of the University of Lübeck and by a Gerok fellowship within the SPP 2084 to S.P.
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Sailer, V., von Amsberg, G., Duensing, S. et al. Experimental in vitro, ex vivo and in vivo models in prostate cancer research. Nat Rev Urol 20, 158–178 (2023). https://doi.org/10.1038/s41585-022-00677-z
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DOI: https://doi.org/10.1038/s41585-022-00677-z
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