Kidney Cancer Models for Pre-Clinical Drug Discovery: Challenges and Opportunities.

Autor:	Pohl L; Molecular Urooncology, Department of Urology, University Hospital Heidelberg, Heidelberg, Germany., Friedhoff J; Molecular Urooncology, Department of Urology, University Hospital Heidelberg, Heidelberg, Germany., Jurcic C; Molecular Urooncology, Department of Urology, University Hospital Heidelberg, Heidelberg, Germany., Teroerde M; Molecular Urooncology, Department of Urology, University Hospital Heidelberg, Heidelberg, Germany., Schindler I; Molecular Urooncology, Department of Urology, University Hospital Heidelberg, Heidelberg, Germany., Strepi K; Molecular Urooncology, Department of Urology, University Hospital Heidelberg, Heidelberg, Germany., Schneider F; Molecular Urooncology, Department of Urology, University Hospital Heidelberg, Heidelberg, Germany., Kaczorowski A; Molecular Urooncology, Department of Urology, University Hospital Heidelberg, Heidelberg, Germany., Hohenfellner M; Department of Urology, University Hospital Heidelberg and National Center for Tumor Diseases (NCT) Heidelberg, Heidelberg, Germany., Duensing A; Department of Urology, University Hospital Heidelberg and National Center for Tumor Diseases (NCT) Heidelberg, Heidelberg, Germany.; Precision Oncology of Urological Malignancies, Department of Urology University Hospital Heidelberg, Heidelberg, Germany.; Cancer Therapeutics Program, UPMC Hillman Cancer Center, Pittsburgh, PA, United States.; Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States., Duensing S; Molecular Urooncology, Department of Urology, University Hospital Heidelberg, Heidelberg, Germany.; Department of Urology, University Hospital Heidelberg and National Center for Tumor Diseases (NCT) Heidelberg, Heidelberg, Germany.
Jazyk:	angličtina
Zdroj:	Frontiers in oncology [Front Oncol] 2022 May 10; Vol. 12, pp. 889686. Date of Electronic Publication: 2022 May 10 (Print Publication: 2022).
DOI:	10.3389/fonc.2022.889686
Abstrakt:	Renal cell carcinoma (RCC) is among the most lethal urological malignancies once metastatic. The introduction of immune checkpoint inhibitors has revolutionized the therapeutic landscape of metastatic RCC, nevertheless, a significant proportion of patients will experience disease progression. Novel treatment options are therefore still needed and in vitro and in vivo model systems are crucial to ultimately improve disease control. At the same time, RCC is characterized by a number of molecular and functional peculiarities that have the potential to limit the utility of pre-clinical model systems. This includes not only the well-known genomic intratumoral heterogeneity (ITH) of RCC but also a remarkable functional ITH that can be shaped by influences of the tumor microenvironment. Importantly, RCC is among the tumor entities, in which a high number of intratumoral cytotoxic T cells is associated with a poor prognosis. In fact, many of these T cells are exhausted, which represents a major challenge for modeling tumor-immune cell interactions. Lastly, pre-clinical drug development commonly relies on using phenotypic screening of 2D or 3D RCC cell culture models, however, the problem of "reverse engineering" can prevent the identification of the precise mode of action of drug candidates thus impeding their translation to the clinic. In conclusion, a holistic approach to model the complex "ecosystem RCC" will likely require not only a combination of model systems but also an integration of concepts and methods using artificial intelligence to further improve pre-clinical drug discovery. Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (Copyright © 2022 Pohl, Friedhoff, Jurcic, Teroerde, Schindler, Strepi, Schneider, Kaczorowski, Hohenfellner, Duensing and Duensing.)
Databáze:	MEDLINE
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