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Coupling live-cell imaging and in situ isolation of the same single cell to profile the transient states of predicted drug-tolerant cells

Cell response variability is a starting point in cancer drug resistance that has been difficult to analyze because the tolerant cell states are short lived. Here, we present fate-seq, an approach to isolate single cells in their transient states of drug sensitivity or tolerance before profiling. The...

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Autores principales: Bian, Benjamin, Paquet, Agnès, Arguel, Marie-Jeanne, Meyer, Mickael, Peyre, Ludovic, Chalabi, Asma, Péré, Marielle, Lebrigand, Kevin, Waldmann, Rainer, Barbry, Pascal, Hofman, Paul, Roux, Jérémie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9420533/
https://www.ncbi.nlm.nih.gov/pubmed/36042886
http://dx.doi.org/10.1016/j.xpro.2022.101600
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author Bian, Benjamin
Paquet, Agnès
Arguel, Marie-Jeanne
Meyer, Mickael
Peyre, Ludovic
Chalabi, Asma
Péré, Marielle
Lebrigand, Kevin
Waldmann, Rainer
Barbry, Pascal
Hofman, Paul
Roux, Jérémie
author_facet Bian, Benjamin
Paquet, Agnès
Arguel, Marie-Jeanne
Meyer, Mickael
Peyre, Ludovic
Chalabi, Asma
Péré, Marielle
Lebrigand, Kevin
Waldmann, Rainer
Barbry, Pascal
Hofman, Paul
Roux, Jérémie
author_sort Bian, Benjamin
collection PubMed
description Cell response variability is a starting point in cancer drug resistance that has been difficult to analyze because the tolerant cell states are short lived. Here, we present fate-seq, an approach to isolate single cells in their transient states of drug sensitivity or tolerance before profiling. The drug response is predicted in live cells, which are laser-captured by microdissection before any drug-induced change can alter their states. This framework enables the identification of the cell-state signatures causing differential cell decisions upon treatment. For complete details on the use and execution of this protocol, please refer to Meyer et al. (2020).
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spelling pubmed-94205332022-08-29 Coupling live-cell imaging and in situ isolation of the same single cell to profile the transient states of predicted drug-tolerant cells Bian, Benjamin Paquet, Agnès Arguel, Marie-Jeanne Meyer, Mickael Peyre, Ludovic Chalabi, Asma Péré, Marielle Lebrigand, Kevin Waldmann, Rainer Barbry, Pascal Hofman, Paul Roux, Jérémie STAR Protoc Protocol Cell response variability is a starting point in cancer drug resistance that has been difficult to analyze because the tolerant cell states are short lived. Here, we present fate-seq, an approach to isolate single cells in their transient states of drug sensitivity or tolerance before profiling. The drug response is predicted in live cells, which are laser-captured by microdissection before any drug-induced change can alter their states. This framework enables the identification of the cell-state signatures causing differential cell decisions upon treatment. For complete details on the use and execution of this protocol, please refer to Meyer et al. (2020). Elsevier 2022-08-18 /pmc/articles/PMC9420533/ /pubmed/36042886 http://dx.doi.org/10.1016/j.xpro.2022.101600 Text en © 2022 The Author(s) 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
Bian, Benjamin
Paquet, Agnès
Arguel, Marie-Jeanne
Meyer, Mickael
Peyre, Ludovic
Chalabi, Asma
Péré, Marielle
Lebrigand, Kevin
Waldmann, Rainer
Barbry, Pascal
Hofman, Paul
Roux, Jérémie
Coupling live-cell imaging and in situ isolation of the same single cell to profile the transient states of predicted drug-tolerant cells
title Coupling live-cell imaging and in situ isolation of the same single cell to profile the transient states of predicted drug-tolerant cells
title_full Coupling live-cell imaging and in situ isolation of the same single cell to profile the transient states of predicted drug-tolerant cells
title_fullStr Coupling live-cell imaging and in situ isolation of the same single cell to profile the transient states of predicted drug-tolerant cells
title_full_unstemmed Coupling live-cell imaging and in situ isolation of the same single cell to profile the transient states of predicted drug-tolerant cells
title_short Coupling live-cell imaging and in situ isolation of the same single cell to profile the transient states of predicted drug-tolerant cells
title_sort coupling live-cell imaging and in situ isolation of the same single cell to profile the transient states of predicted drug-tolerant cells
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9420533/
https://www.ncbi.nlm.nih.gov/pubmed/36042886
http://dx.doi.org/10.1016/j.xpro.2022.101600
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