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Zebrafish Cancer Avatars: A Translational Platform for Analyzing Tumor Heterogeneity and Predicting Patient Outcomes
The increasing number of available anti-cancer drugs presents a challenge for oncologists, who must choose the most effective treatment for the patient. Precision cancer medicine relies on matching a drug with a tumor’s molecular profile to optimize the therapeutic benefit. However, current precisio...
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/PMC9916713/ https://www.ncbi.nlm.nih.gov/pubmed/36768609 http://dx.doi.org/10.3390/ijms24032288 |
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author | Al-Hamaly, Majd A. Turner, Logan T. Rivera-Martinez, Angelica Rodriguez, Analiz Blackburn, Jessica S. |
author_facet | Al-Hamaly, Majd A. Turner, Logan T. Rivera-Martinez, Angelica Rodriguez, Analiz Blackburn, Jessica S. |
author_sort | Al-Hamaly, Majd A. |
collection | PubMed |
description | The increasing number of available anti-cancer drugs presents a challenge for oncologists, who must choose the most effective treatment for the patient. Precision cancer medicine relies on matching a drug with a tumor’s molecular profile to optimize the therapeutic benefit. However, current precision medicine approaches do not fully account for intra-tumoral heterogeneity. Different mutation profiles and cell behaviors within a single heterogeneous tumor can significantly impact therapy response and patient outcomes. Patient-derived avatar models recapitulate a patient’s tumor in an animal or dish and provide the means to functionally assess heterogeneity’s impact on drug response. Mouse xenograft and organoid avatars are well-established, but the time required to generate these models is not practical for clinical decision-making. Zebrafish are emerging as a time-efficient and cost-effective cancer avatar model. In this review, we highlight recent developments in zebrafish cancer avatar models and discuss the unique features of zebrafish that make them ideal for the interrogation of cancer heterogeneity and as part of precision cancer medicine pipelines. |
format | Online Article Text |
id | pubmed-9916713 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-99167132023-02-11 Zebrafish Cancer Avatars: A Translational Platform for Analyzing Tumor Heterogeneity and Predicting Patient Outcomes Al-Hamaly, Majd A. Turner, Logan T. Rivera-Martinez, Angelica Rodriguez, Analiz Blackburn, Jessica S. Int J Mol Sci Review The increasing number of available anti-cancer drugs presents a challenge for oncologists, who must choose the most effective treatment for the patient. Precision cancer medicine relies on matching a drug with a tumor’s molecular profile to optimize the therapeutic benefit. However, current precision medicine approaches do not fully account for intra-tumoral heterogeneity. Different mutation profiles and cell behaviors within a single heterogeneous tumor can significantly impact therapy response and patient outcomes. Patient-derived avatar models recapitulate a patient’s tumor in an animal or dish and provide the means to functionally assess heterogeneity’s impact on drug response. Mouse xenograft and organoid avatars are well-established, but the time required to generate these models is not practical for clinical decision-making. Zebrafish are emerging as a time-efficient and cost-effective cancer avatar model. In this review, we highlight recent developments in zebrafish cancer avatar models and discuss the unique features of zebrafish that make them ideal for the interrogation of cancer heterogeneity and as part of precision cancer medicine pipelines. MDPI 2023-01-24 /pmc/articles/PMC9916713/ /pubmed/36768609 http://dx.doi.org/10.3390/ijms24032288 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 Al-Hamaly, Majd A. Turner, Logan T. Rivera-Martinez, Angelica Rodriguez, Analiz Blackburn, Jessica S. Zebrafish Cancer Avatars: A Translational Platform for Analyzing Tumor Heterogeneity and Predicting Patient Outcomes |
title | Zebrafish Cancer Avatars: A Translational Platform for Analyzing Tumor Heterogeneity and Predicting Patient Outcomes |
title_full | Zebrafish Cancer Avatars: A Translational Platform for Analyzing Tumor Heterogeneity and Predicting Patient Outcomes |
title_fullStr | Zebrafish Cancer Avatars: A Translational Platform for Analyzing Tumor Heterogeneity and Predicting Patient Outcomes |
title_full_unstemmed | Zebrafish Cancer Avatars: A Translational Platform for Analyzing Tumor Heterogeneity and Predicting Patient Outcomes |
title_short | Zebrafish Cancer Avatars: A Translational Platform for Analyzing Tumor Heterogeneity and Predicting Patient Outcomes |
title_sort | zebrafish cancer avatars: a translational platform for analyzing tumor heterogeneity and predicting patient outcomes |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9916713/ https://www.ncbi.nlm.nih.gov/pubmed/36768609 http://dx.doi.org/10.3390/ijms24032288 |
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