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Patient-derived tumour models for personalized therapeutics in urological cancers
Arjanneke F van de Merbel1, Geertje van der Horst1, Gabri van der Pluijm2
1Department of Urology, Leiden University Medical Center, Leiden, Netherlands.
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.
Insights
Patient-derived tumor models in uro-oncology show promise for understanding cancer complexity. Further clinical validation is crucial for translating these preclinical findings into personalized treatments for urological cancers.
Area of Science:
- Uro-oncology
- Cancer research
- Translational medicine
Background:
- Limited translation of preclinical knowledge for urological cancers into clinical practice.
- Current preclinical models often fail to capture the complexity of malignant diseases, leading to low drug approval rates and varied patient responses.
- Urological cancer research faces challenges in developing personalized therapeutic strategies.
Purpose of the Study:
- To review the advancements and limitations of patient-derived tumor models in preclinical uro-oncology.
- To highlight the potential of these models in addressing unmet clinical needs in urological cancers.
- To emphasize the necessity of clinical validation for translating preclinical data into treatment decisions.
Main Methods:
- Review of patient-derived tumor models including 3D cultures, organotypic tissue slices, and patient-derived xenografts.
- Analysis of technological innovations enhancing the clinical relevance of these models.
- Discussion of the advantages and limitations of each model type.
Main Results:
- Technological advancements have significantly improved the ability of patient-derived models to mimic clinical complexity.
- Different model systems offer unique advantages for investigating specific clinical challenges.
- Despite progress, opportunities for personalized therapy in urological cancers remain limited.
Conclusions:
- Patient-derived tumor models are valuable tools for preclinical uro-oncology research.
- Combining different model systems can provide comprehensive insights into urological cancer.
- Clinical validation of experimental findings is essential for effective translation into patient care and personalized medicine.
