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Conditional Reprogramming Modeling of Bladder Cancer for Clinical Translation
The use of advanced preclinical models has become increasingly important in drug development. This is particularly relevant in bladder cancer, where the global burden of disease is quite high based on prevalence and a relatively high rate of lethality. Predictive tools to select patients who will be...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10341071/ https://www.ncbi.nlm.nih.gov/pubmed/37443748 http://dx.doi.org/10.3390/cells12131714 |
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author | Daneshdoust, Danyal Yin, Ming Luo, Mingjue Sundi, Debasish Dang, Yongjun Lee, Cheryl Li, Jenny Liu, Xuefeng |
author_facet | Daneshdoust, Danyal Yin, Ming Luo, Mingjue Sundi, Debasish Dang, Yongjun Lee, Cheryl Li, Jenny Liu, Xuefeng |
author_sort | Daneshdoust, Danyal |
collection | PubMed |
description | The use of advanced preclinical models has become increasingly important in drug development. This is particularly relevant in bladder cancer, where the global burden of disease is quite high based on prevalence and a relatively high rate of lethality. Predictive tools to select patients who will be responsive to invasive or morbid therapies (chemotherapy, radiotherapy, immunotherapy, and/or surgery) are largely absent. Patient-derived and clinically relevant models including patient-derived xenografts (PDX), organoids, and conditional reprogramming (CR) of cell cultures efficiently generate numerous models and are being used in both basic and translational cancer biology. These CR cells (CRCs) can be reprogrammed to maintain a highly proliferative state and reproduce the genomic and histological characteristics of the parental tissue. Therefore, CR technology may be a clinically relevant model to test and predict drug sensitivity, conduct gene profile analysis and xenograft research, and undertake personalized medicine. This review discusses studies that have utilized CR technology to conduct bladder cancer research. |
format | Online Article Text |
id | pubmed-10341071 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-103410712023-07-14 Conditional Reprogramming Modeling of Bladder Cancer for Clinical Translation Daneshdoust, Danyal Yin, Ming Luo, Mingjue Sundi, Debasish Dang, Yongjun Lee, Cheryl Li, Jenny Liu, Xuefeng Cells Review The use of advanced preclinical models has become increasingly important in drug development. This is particularly relevant in bladder cancer, where the global burden of disease is quite high based on prevalence and a relatively high rate of lethality. Predictive tools to select patients who will be responsive to invasive or morbid therapies (chemotherapy, radiotherapy, immunotherapy, and/or surgery) are largely absent. Patient-derived and clinically relevant models including patient-derived xenografts (PDX), organoids, and conditional reprogramming (CR) of cell cultures efficiently generate numerous models and are being used in both basic and translational cancer biology. These CR cells (CRCs) can be reprogrammed to maintain a highly proliferative state and reproduce the genomic and histological characteristics of the parental tissue. Therefore, CR technology may be a clinically relevant model to test and predict drug sensitivity, conduct gene profile analysis and xenograft research, and undertake personalized medicine. This review discusses studies that have utilized CR technology to conduct bladder cancer research. MDPI 2023-06-24 /pmc/articles/PMC10341071/ /pubmed/37443748 http://dx.doi.org/10.3390/cells12131714 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Daneshdoust, Danyal Yin, Ming Luo, Mingjue Sundi, Debasish Dang, Yongjun Lee, Cheryl Li, Jenny Liu, Xuefeng Conditional Reprogramming Modeling of Bladder Cancer for Clinical Translation |
title | Conditional Reprogramming Modeling of Bladder Cancer for Clinical Translation |
title_full | Conditional Reprogramming Modeling of Bladder Cancer for Clinical Translation |
title_fullStr | Conditional Reprogramming Modeling of Bladder Cancer for Clinical Translation |
title_full_unstemmed | Conditional Reprogramming Modeling of Bladder Cancer for Clinical Translation |
title_short | Conditional Reprogramming Modeling of Bladder Cancer for Clinical Translation |
title_sort | conditional reprogramming modeling of bladder cancer for clinical translation |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10341071/ https://www.ncbi.nlm.nih.gov/pubmed/37443748 http://dx.doi.org/10.3390/cells12131714 |
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