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Protocol to generate a patient derived xenograft model of acquired resistance to immunotherapy in humanized mice

Immunotherapy has revolutionized cancer treatment, but preclinical models are required to understand immunotherapy resistance mechanisms underlying patient relapse. This protocol describes how to generate an acquired resistance humanized in vivo model to immunotherapies in patient-derived xenografts...

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Autores principales: Martínez-Sabadell, Alex, Ovejero Romero, Pablo, Arribas, Joaquín, Arenas, Enrique J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9617204/
https://www.ncbi.nlm.nih.gov/pubmed/36317178
http://dx.doi.org/10.1016/j.xpro.2022.101712
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author Martínez-Sabadell, Alex
Ovejero Romero, Pablo
Arribas, Joaquín
Arenas, Enrique J.
author_facet Martínez-Sabadell, Alex
Ovejero Romero, Pablo
Arribas, Joaquín
Arenas, Enrique J.
author_sort Martínez-Sabadell, Alex
collection PubMed
description Immunotherapy has revolutionized cancer treatment, but preclinical models are required to understand immunotherapy resistance mechanisms underlying patient relapse. This protocol describes how to generate an acquired resistance humanized in vivo model to immunotherapies in patient-derived xenografts (PDX). We detail steps to inject human CD34(+) cells into NSG mice, followed by generation of immunoresistant PDX in humanized mice. This approach recapitulates the human immune system, allowing investigators to generate preclinical resistance models to different immunotherapies for identifying the resistant phenotype. For complete details on the use and execution of this protocol, please refer to Martínez-Sabadell et al., 2022 and Arenas et al. (2021).
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spelling pubmed-96172042022-10-30 Protocol to generate a patient derived xenograft model of acquired resistance to immunotherapy in humanized mice Martínez-Sabadell, Alex Ovejero Romero, Pablo Arribas, Joaquín Arenas, Enrique J. STAR Protoc Protocol Immunotherapy has revolutionized cancer treatment, but preclinical models are required to understand immunotherapy resistance mechanisms underlying patient relapse. This protocol describes how to generate an acquired resistance humanized in vivo model to immunotherapies in patient-derived xenografts (PDX). We detail steps to inject human CD34(+) cells into NSG mice, followed by generation of immunoresistant PDX in humanized mice. This approach recapitulates the human immune system, allowing investigators to generate preclinical resistance models to different immunotherapies for identifying the resistant phenotype. For complete details on the use and execution of this protocol, please refer to Martínez-Sabadell et al., 2022 and Arenas et al. (2021). Elsevier 2022-10-26 /pmc/articles/PMC9617204/ /pubmed/36317178 http://dx.doi.org/10.1016/j.xpro.2022.101712 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Protocol
Martínez-Sabadell, Alex
Ovejero Romero, Pablo
Arribas, Joaquín
Arenas, Enrique J.
Protocol to generate a patient derived xenograft model of acquired resistance to immunotherapy in humanized mice
title Protocol to generate a patient derived xenograft model of acquired resistance to immunotherapy in humanized mice
title_full Protocol to generate a patient derived xenograft model of acquired resistance to immunotherapy in humanized mice
title_fullStr Protocol to generate a patient derived xenograft model of acquired resistance to immunotherapy in humanized mice
title_full_unstemmed Protocol to generate a patient derived xenograft model of acquired resistance to immunotherapy in humanized mice
title_short Protocol to generate a patient derived xenograft model of acquired resistance to immunotherapy in humanized mice
title_sort protocol to generate a patient derived xenograft model of acquired resistance to immunotherapy in humanized mice
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9617204/
https://www.ncbi.nlm.nih.gov/pubmed/36317178
http://dx.doi.org/10.1016/j.xpro.2022.101712
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