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Workflow for high-dimensional flow cytometry analysis of T cells from tumor metastases

We describe a multi-step high-dimensional (HD) flow cytometry workflow for the deep phenotypic characterization of T cells infiltrating metastatic tumor lesions in the liver, particularly derived from colorectal cancer (CRC-LM). First, we applied a novel flow cytometer setting approach based on sing...

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Autores principales: Faccani, Cristina, Rotta, Gianluca, Clemente, Francesca, Fedeli, Maya, Abbati, Danilo, Manfredi, Francesco, Potenza, Alessia, Anselmo, Achille, Pedica, Federica, Fiorentini, Guido, Villa, Chiara, Protti, Maria P, Doglioni, Claudio, Aldrighetti, Luca, Bonini, Chiara, Casorati, Giulia, Dellabona, Paolo, de Lalla, Claudia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Life Science Alliance LLC 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9166301/
https://www.ncbi.nlm.nih.gov/pubmed/35724271
http://dx.doi.org/10.26508/lsa.202101316
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author Faccani, Cristina
Rotta, Gianluca
Clemente, Francesca
Fedeli, Maya
Abbati, Danilo
Manfredi, Francesco
Potenza, Alessia
Anselmo, Achille
Pedica, Federica
Fiorentini, Guido
Villa, Chiara
Protti, Maria P
Doglioni, Claudio
Aldrighetti, Luca
Bonini, Chiara
Casorati, Giulia
Dellabona, Paolo
de Lalla, Claudia
author_facet Faccani, Cristina
Rotta, Gianluca
Clemente, Francesca
Fedeli, Maya
Abbati, Danilo
Manfredi, Francesco
Potenza, Alessia
Anselmo, Achille
Pedica, Federica
Fiorentini, Guido
Villa, Chiara
Protti, Maria P
Doglioni, Claudio
Aldrighetti, Luca
Bonini, Chiara
Casorati, Giulia
Dellabona, Paolo
de Lalla, Claudia
author_sort Faccani, Cristina
collection PubMed
description We describe a multi-step high-dimensional (HD) flow cytometry workflow for the deep phenotypic characterization of T cells infiltrating metastatic tumor lesions in the liver, particularly derived from colorectal cancer (CRC-LM). First, we applied a novel flow cytometer setting approach based on single positive cells rather than fluorescent beads, resulting in optimal sensitivity when compared with previously published protocols. Second, we set up a 26-color based antibody panel designed to assess the functional state of both conventional T-cell subsets and unconventional invariant natural killer T, mucosal associated invariant T, and gamma delta T (γδT)-cell populations, which are abundant in the liver. Third, the dissociation of the CRC-LM samples was accurately tuned to preserve both the viability and antigenic integrity of the stained cells. This combined procedure permitted the optimal capturing of the phenotypic complexity of T cells infiltrating CRC-LM. Hence, this study provides a robust tool for high-dimensional flow cytometry analysis of complex T-cell populations, which could be adapted to characterize other relevant pathological tissues.
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spelling pubmed-91663012022-06-27 Workflow for high-dimensional flow cytometry analysis of T cells from tumor metastases Faccani, Cristina Rotta, Gianluca Clemente, Francesca Fedeli, Maya Abbati, Danilo Manfredi, Francesco Potenza, Alessia Anselmo, Achille Pedica, Federica Fiorentini, Guido Villa, Chiara Protti, Maria P Doglioni, Claudio Aldrighetti, Luca Bonini, Chiara Casorati, Giulia Dellabona, Paolo de Lalla, Claudia Life Sci Alliance Methods We describe a multi-step high-dimensional (HD) flow cytometry workflow for the deep phenotypic characterization of T cells infiltrating metastatic tumor lesions in the liver, particularly derived from colorectal cancer (CRC-LM). First, we applied a novel flow cytometer setting approach based on single positive cells rather than fluorescent beads, resulting in optimal sensitivity when compared with previously published protocols. Second, we set up a 26-color based antibody panel designed to assess the functional state of both conventional T-cell subsets and unconventional invariant natural killer T, mucosal associated invariant T, and gamma delta T (γδT)-cell populations, which are abundant in the liver. Third, the dissociation of the CRC-LM samples was accurately tuned to preserve both the viability and antigenic integrity of the stained cells. This combined procedure permitted the optimal capturing of the phenotypic complexity of T cells infiltrating CRC-LM. Hence, this study provides a robust tool for high-dimensional flow cytometry analysis of complex T-cell populations, which could be adapted to characterize other relevant pathological tissues. Life Science Alliance LLC 2022-06-03 /pmc/articles/PMC9166301/ /pubmed/35724271 http://dx.doi.org/10.26508/lsa.202101316 Text en © 2022 Faccani et al. https://creativecommons.org/licenses/by/4.0/This article is available under a Creative Commons License (Attribution 4.0 International, as described at https://creativecommons.org/licenses/by/4.0/).
spellingShingle Methods
Faccani, Cristina
Rotta, Gianluca
Clemente, Francesca
Fedeli, Maya
Abbati, Danilo
Manfredi, Francesco
Potenza, Alessia
Anselmo, Achille
Pedica, Federica
Fiorentini, Guido
Villa, Chiara
Protti, Maria P
Doglioni, Claudio
Aldrighetti, Luca
Bonini, Chiara
Casorati, Giulia
Dellabona, Paolo
de Lalla, Claudia
Workflow for high-dimensional flow cytometry analysis of T cells from tumor metastases
title Workflow for high-dimensional flow cytometry analysis of T cells from tumor metastases
title_full Workflow for high-dimensional flow cytometry analysis of T cells from tumor metastases
title_fullStr Workflow for high-dimensional flow cytometry analysis of T cells from tumor metastases
title_full_unstemmed Workflow for high-dimensional flow cytometry analysis of T cells from tumor metastases
title_short Workflow for high-dimensional flow cytometry analysis of T cells from tumor metastases
title_sort workflow for high-dimensional flow cytometry analysis of t cells from tumor metastases
topic Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9166301/
https://www.ncbi.nlm.nih.gov/pubmed/35724271
http://dx.doi.org/10.26508/lsa.202101316
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