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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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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) |
format | Online Article Text |
id | pubmed-9947008 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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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