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Patient-derived tumour models for personalized therapeutics in urological cancers

Nature Reviews Urology volume 18, pages 33–45 (2021)Cite this article

Subjects

Abstract

Preclinical knowledge of dysregulated pathways and potential biomarkers for urological cancers has undergone limited translation into the clinic. Moreover, the low approval rate of new anticancer drugs and the heterogeneous drug responses in patients indicate that current preclinical models do not always reflect the complexity of malignant disease. Patient-derived tumour models used in preclinical uro-oncology research include 3D culture systems, organotypic tissue slices and patient-derived xenograft models. Technological innovations have enabled major improvements in the capacity of these tumour models to reproduce the clinical complexity of urological cancers. Each type of patient-derived model has inherent advantages and limitations that can be exploited, either alone or in combination, to gather specific knowledge on clinical challenges and address unmet clinical needs. Nevertheless, few opportunities exist for patients with urological cancers to benefit from personalized therapeutic approaches. Clinical validation of experimental data is needed to facilitate the translation and implementation of preclinical knowledge into treatment decision making.

Key points

  • Personalized therapeutic approaches currently have limited use in uro-oncology clinics.

  • Discrepancies between preclinical data and clinical outcomes, high drug attrition rates and heterogeneous drug responses indicate the need for additional clinically relevant patient-derived tumour models including 3D cultures, organotypic tissue slices and patient-derived xenograft models.

  • Each patient-derived model has advantages and limitations and can be used alone or in combination to gather knowledge on clinical challenges in uro-oncology.

  • Co-clinical trials and cross-validation of preclinical results with patient outcomes are expected to advance the implementation of patient-derived models in treatment decision-making.

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Fig. 1: 3D culture systems.
Fig. 2: Organotypic tissue slice models.
Fig. 3: PDX models.
Fig. 4: Contribution and translational value of preclinical patient-derived models.

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Acknowledgements

The authors’ research work is supported by a personalized medicine grant from the Dutch Cancer Society (KWF) and Alpe D’Huzes (UL2014-7058) (to A.F.v.d.M., G.v.d.H. and G.v.d.P.).

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  1. Department of Urology, Leiden University Medical Center, Leiden, Netherlands

    Arjanneke F. van de Merbel, Geertje van der Horst & Gabri van der Pluijm

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  1. Arjanneke F. van de Merbel
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A.F.v.d.M researched data for the manuscript, A.F.v.d.M, G.v.d.H and G.v.d.P. wrote the manuscript, and all authors made substantial contributions to discussions of content and reviewed and edited the manuscript before submission.

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Correspondence to Gabri van der Pluijm.

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Nature Reviews Urology thanks C.-X. Pan and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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National Cancer Institute Patient-Derived Models Repository: https://pdmr.cancer.gov

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van de Merbel, A.F., van der Horst, G. & van der Pluijm, G. Patient-derived tumour models for personalized therapeutics in urological cancers. Nat Rev Urol 18, 33–45 (2021). https://doi.org/10.1038/s41585-020-00389-2

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