Isolation and detection of extracellular vesicles from melanoma cells and liquid biopsies using size-exclusion chromatography and nano-flow cytometry

Characterization of extracellular vesicles (EVs) holds great promise for biomarker discovery and understanding of diseases, including melanoma, the deadliest skin cancer type. Here, we describe a size-exclusion chromatography method to isolate and concentrate EVs from patient material including (1)...

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Detalles Bibliográficos
Autores principales: Lattmann, Evelyn, Lapaire, Valérie, Levesque, Mitchell P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Protocol
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10339257/
https://www.ncbi.nlm.nih.gov/pubmed/37421613
http://dx.doi.org/10.1016/j.xpro.2023.102365
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author Lattmann, Evelyn
Lapaire, Valérie
Levesque, Mitchell P.
author_facet Lattmann, Evelyn
Lapaire, Valérie
Levesque, Mitchell P.
author_sort Lattmann, Evelyn
collection PubMed
description Characterization of extracellular vesicles (EVs) holds great promise for biomarker discovery and understanding of diseases, including melanoma, the deadliest skin cancer type. Here, we describe a size-exclusion chromatography method to isolate and concentrate EVs from patient material including (1) patient-derived melanoma cell line supernatants and (2) plasma and serum biopsies. Additionally, we provide a protocol to analyze EVs by nano-flow cytometry. EV suspensions obtained with the presented protocol can be used for several downstream analyses including RNA sequencing and proteomics.
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spelling pubmed-103392572023-07-14 Isolation and detection of extracellular vesicles from melanoma cells and liquid biopsies using size-exclusion chromatography and nano-flow cytometry Lattmann, Evelyn Lapaire, Valérie Levesque, Mitchell P. STAR Protoc Protocol Characterization of extracellular vesicles (EVs) holds great promise for biomarker discovery and understanding of diseases, including melanoma, the deadliest skin cancer type. Here, we describe a size-exclusion chromatography method to isolate and concentrate EVs from patient material including (1) patient-derived melanoma cell line supernatants and (2) plasma and serum biopsies. Additionally, we provide a protocol to analyze EVs by nano-flow cytometry. EV suspensions obtained with the presented protocol can be used for several downstream analyses including RNA sequencing and proteomics. Elsevier 2023-07-07 /pmc/articles/PMC10339257/ /pubmed/37421613 http://dx.doi.org/10.1016/j.xpro.2023.102365 Text en © 2023 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
Lattmann, Evelyn
Lapaire, Valérie
Levesque, Mitchell P.
Isolation and detection of extracellular vesicles from melanoma cells and liquid biopsies using size-exclusion chromatography and nano-flow cytometry
title Isolation and detection of extracellular vesicles from melanoma cells and liquid biopsies using size-exclusion chromatography and nano-flow cytometry
title_full Isolation and detection of extracellular vesicles from melanoma cells and liquid biopsies using size-exclusion chromatography and nano-flow cytometry
title_fullStr Isolation and detection of extracellular vesicles from melanoma cells and liquid biopsies using size-exclusion chromatography and nano-flow cytometry
title_full_unstemmed Isolation and detection of extracellular vesicles from melanoma cells and liquid biopsies using size-exclusion chromatography and nano-flow cytometry
title_short Isolation and detection of extracellular vesicles from melanoma cells and liquid biopsies using size-exclusion chromatography and nano-flow cytometry
title_sort isolation and detection of extracellular vesicles from melanoma cells and liquid biopsies using size-exclusion chromatography and nano-flow cytometry
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10339257/
https://www.ncbi.nlm.nih.gov/pubmed/37421613
http://dx.doi.org/10.1016/j.xpro.2023.102365
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