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Surface enhanced Raman scattering of extracellular vesicles for cancer diagnostics despite isolation dependent lipoprotein contamination
Given the emerging diagnostic utility of extracellular vesicles (EVs), it is important to account for non-EV contaminants. Lipoprotein present in EV-enriched isolates may inflate particle counts and decrease sensitivity to biomarkers of interest, skewing chemical analyses and perpetuating downstream...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society of Chemistry
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8447870/ https://www.ncbi.nlm.nih.gov/pubmed/34473170 http://dx.doi.org/10.1039/d1nr03334d |
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author | Koster, Hanna J. Rojalin, Tatu Powell, Alyssa Pham, Dina Mizenko, Rachel R. Birkeland, Andrew C. Carney, Randy P. |
author_facet | Koster, Hanna J. Rojalin, Tatu Powell, Alyssa Pham, Dina Mizenko, Rachel R. Birkeland, Andrew C. Carney, Randy P. |
author_sort | Koster, Hanna J. |
collection | PubMed |
description | Given the emerging diagnostic utility of extracellular vesicles (EVs), it is important to account for non-EV contaminants. Lipoprotein present in EV-enriched isolates may inflate particle counts and decrease sensitivity to biomarkers of interest, skewing chemical analyses and perpetuating downstream issues in labeling or functional analysis. Using label free surface enhanced Raman scattering (SERS), we confirm that three common EV isolation methods (differential ultracentrifugation, density gradient ultracentrifugation, and size exclusion chromatography) yield variable lipoprotein content. We demonstrate that a dual-isolation method is necessary to isolate EVs from the major classes of lipoprotein. However, combining SERS analysis with machine learning assisted classification, we show that the disease state is the main driver of distinction between EV samples, and largely unaffected by choice of isolation. Ultimately, this study describes a convenient SERS assay to retain accurate diagnostic information from clinical samples by overcoming differences in lipoprotein contamination according to isolation method. |
format | Online Article Text |
id | pubmed-8447870 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Royal Society of Chemistry |
record_format | MEDLINE/PubMed |
spelling | pubmed-84478702021-10-18 Surface enhanced Raman scattering of extracellular vesicles for cancer diagnostics despite isolation dependent lipoprotein contamination Koster, Hanna J. Rojalin, Tatu Powell, Alyssa Pham, Dina Mizenko, Rachel R. Birkeland, Andrew C. Carney, Randy P. Nanoscale Chemistry Given the emerging diagnostic utility of extracellular vesicles (EVs), it is important to account for non-EV contaminants. Lipoprotein present in EV-enriched isolates may inflate particle counts and decrease sensitivity to biomarkers of interest, skewing chemical analyses and perpetuating downstream issues in labeling or functional analysis. Using label free surface enhanced Raman scattering (SERS), we confirm that three common EV isolation methods (differential ultracentrifugation, density gradient ultracentrifugation, and size exclusion chromatography) yield variable lipoprotein content. We demonstrate that a dual-isolation method is necessary to isolate EVs from the major classes of lipoprotein. However, combining SERS analysis with machine learning assisted classification, we show that the disease state is the main driver of distinction between EV samples, and largely unaffected by choice of isolation. Ultimately, this study describes a convenient SERS assay to retain accurate diagnostic information from clinical samples by overcoming differences in lipoprotein contamination according to isolation method. The Royal Society of Chemistry 2021-08-26 /pmc/articles/PMC8447870/ /pubmed/34473170 http://dx.doi.org/10.1039/d1nr03334d Text en This journal is © The Royal Society of Chemistry https://creativecommons.org/licenses/by-nc/3.0/ |
spellingShingle | Chemistry Koster, Hanna J. Rojalin, Tatu Powell, Alyssa Pham, Dina Mizenko, Rachel R. Birkeland, Andrew C. Carney, Randy P. Surface enhanced Raman scattering of extracellular vesicles for cancer diagnostics despite isolation dependent lipoprotein contamination |
title | Surface enhanced Raman scattering of extracellular vesicles for cancer diagnostics despite isolation dependent lipoprotein contamination |
title_full | Surface enhanced Raman scattering of extracellular vesicles for cancer diagnostics despite isolation dependent lipoprotein contamination |
title_fullStr | Surface enhanced Raman scattering of extracellular vesicles for cancer diagnostics despite isolation dependent lipoprotein contamination |
title_full_unstemmed | Surface enhanced Raman scattering of extracellular vesicles for cancer diagnostics despite isolation dependent lipoprotein contamination |
title_short | Surface enhanced Raman scattering of extracellular vesicles for cancer diagnostics despite isolation dependent lipoprotein contamination |
title_sort | surface enhanced raman scattering of extracellular vesicles for cancer diagnostics despite isolation dependent lipoprotein contamination |
topic | Chemistry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8447870/ https://www.ncbi.nlm.nih.gov/pubmed/34473170 http://dx.doi.org/10.1039/d1nr03334d |
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