| Autor: |
Ahmed, Basant H., Zdyrski, Christopher, Cheville, John, Rancilio, Nicholas, Abel, Alex M., Wierson, Wesley A., McGill, Jodi L., Mochel, Jonathan P., Allenspach, Karin |
| Předmět: |
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| Zdroj: |
Clinical & Translational Discovery; Oct2023, Vol. 3 Issue 5, p1-19, 19p |
| Abstrakt: |
Background: Bladder cancer is a significant malignancy in humans and canines, with high death rates and devastating clinical symptoms. Despite significant advances in therapeutic management over the years, only a small fraction of bladder cancer patients respond to immunotherapies as a second line of treatment. Since immunotherapies act on various cellular and molecular targets in the bladder cancer tumour microenvironment (TME), a greater understanding of the various types of immune cells, immune checkpoint molecules and cytokines involved in antitumour immunity will help to improve the success rate of current and novel immunotherapies, therefore enhancing the patients quality of life. Accumulating evidence shows fundamental similarities between human and canine muscle-invasive bladder cancer (MIBC) in their clinical, histological and molecular features. Aim: This review focuses on comparative aspects of MIBC in both species, highlighting the role that canines can play as a model for studying MIBC. Additionally, we discuss the various types of immune cells within bladder cancer TME that can influence the prognosis and response to immunotherapy and chemotherapy in both species. Conclusion: It remains challenging to recapitulate the heterogeneity and complexity of the bladder cancer tumour microenvironment using in vivo and in vitro models, such as zebrafish and 3D organoids models. Optimization of these techniques to create a more representative translational model has been facilitated through in vitro immune-oncology cocultures, which are considered promising tools to help select the ideal individualized treatment options and predict disease prognosis. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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