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CRISPR-based large-scale modeling of loss-of-function mutations to investigate mechanisms of stress resistance in cancer

Dissecting mechanisms driving subclone expansion in primary cancers has been challenging. Here, we present a protocol to systematically disrupt entire gene networks and assess the functional impact of this perturbation on cancer cell fitness. By combining arrayed CRISPR libraries and high-content mi...

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Detalles Bibliográficos
Autores principales: Simeoni, Fabrizio, Loukas, Ioannis, Wilson, Thomas Stuart, Scaffidi, Paola
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9947008/
https://www.ncbi.nlm.nih.gov/pubmed/36853711
http://dx.doi.org/10.1016/j.xpro.2023.102097
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author Simeoni, Fabrizio
Loukas, Ioannis
Wilson, Thomas Stuart
Scaffidi, Paola
author_facet Simeoni, Fabrizio
Loukas, Ioannis
Wilson, Thomas Stuart
Scaffidi, Paola
author_sort Simeoni, Fabrizio
collection PubMed
description Dissecting mechanisms driving subclone expansion in primary cancers has been challenging. Here, we present a protocol to systematically disrupt entire gene networks and assess the functional impact of this perturbation on cancer cell fitness. By combining arrayed CRISPR libraries and high-content microscopy, we describe steps to identify classes of genes whose inactivation promotes resistance to environmental challenges faced by cancer cells during tumor growth or upon therapy. A proof-of-principle interrogation of the epigenetic regulatory network is described. For complete details on the use and execution of this protocol, please refer to Loukas et al. (2022).(1)
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spelling pubmed-99470082023-02-24 CRISPR-based large-scale modeling of loss-of-function mutations to investigate mechanisms of stress resistance in cancer Simeoni, Fabrizio Loukas, Ioannis Wilson, Thomas Stuart Scaffidi, Paola STAR Protoc Protocol Dissecting mechanisms driving subclone expansion in primary cancers has been challenging. Here, we present a protocol to systematically disrupt entire gene networks and assess the functional impact of this perturbation on cancer cell fitness. By combining arrayed CRISPR libraries and high-content microscopy, we describe steps to identify classes of genes whose inactivation promotes resistance to environmental challenges faced by cancer cells during tumor growth or upon therapy. A proof-of-principle interrogation of the epigenetic regulatory network is described. For complete details on the use and execution of this protocol, please refer to Loukas et al. (2022).(1) Elsevier 2023-02-11 /pmc/articles/PMC9947008/ /pubmed/36853711 http://dx.doi.org/10.1016/j.xpro.2023.102097 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Protocol
Simeoni, Fabrizio
Loukas, Ioannis
Wilson, Thomas Stuart
Scaffidi, Paola
CRISPR-based large-scale modeling of loss-of-function mutations to investigate mechanisms of stress resistance in cancer
title CRISPR-based large-scale modeling of loss-of-function mutations to investigate mechanisms of stress resistance in cancer
title_full CRISPR-based large-scale modeling of loss-of-function mutations to investigate mechanisms of stress resistance in cancer
title_fullStr CRISPR-based large-scale modeling of loss-of-function mutations to investigate mechanisms of stress resistance in cancer
title_full_unstemmed CRISPR-based large-scale modeling of loss-of-function mutations to investigate mechanisms of stress resistance in cancer
title_short CRISPR-based large-scale modeling of loss-of-function mutations to investigate mechanisms of stress resistance in cancer
title_sort crispr-based large-scale modeling of loss-of-function mutations to investigate mechanisms of stress resistance in cancer
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9947008/
https://www.ncbi.nlm.nih.gov/pubmed/36853711
http://dx.doi.org/10.1016/j.xpro.2023.102097
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