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Localized fluorescent imaging of multiple proteins on individual extracellular vesicles using rolling circle amplification for cancer diagnosis

Extracellular vesicles (EV) have attracted increasing attention as tumour biomarkers due to their unique biological property. However, conventional methods for EV analysis are mainly based on bulk measurements, which masks the EV‐to‐EV heterogeneity in tumour diagnosis and classification. Herein, a...

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Detalles Bibliográficos
Autores principales: Zhang, Junli, Shi, Jinjin, Zhang, Hongling, Zhu, Yifan, Liu, Wei, Zhang, Kaixiang, Zhang, Zhenzhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7710127/
https://www.ncbi.nlm.nih.gov/pubmed/33304477
http://dx.doi.org/10.1002/jev2.12025
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author Zhang, Junli
Shi, Jinjin
Zhang, Hongling
Zhu, Yifan
Liu, Wei
Zhang, Kaixiang
Zhang, Zhenzhong
author_facet Zhang, Junli
Shi, Jinjin
Zhang, Hongling
Zhu, Yifan
Liu, Wei
Zhang, Kaixiang
Zhang, Zhenzhong
author_sort Zhang, Junli
collection PubMed
description Extracellular vesicles (EV) have attracted increasing attention as tumour biomarkers due to their unique biological property. However, conventional methods for EV analysis are mainly based on bulk measurements, which masks the EV‐to‐EV heterogeneity in tumour diagnosis and classification. Herein, a localized fluorescent imaging method (termed Digital Profiling of Proteins on Individual EV, DPPIE) was developed for analysis of multiple proteins on individual EV. In this assay, an anti‐CD9 antibody engineered biochip was used to capture EV from clinical plasma sample. Then the captured EV was specifically recognized by multiple DNA aptamers (CD63/EpCAM/MUC1), followed by rolling circle amplification to generate localized fluorescent signals. By‐analyzing the heterogeneity of individual EV, we found that the high‐dimensional data collected from each individual EV would provide more precise information than bulk measurement (ELISA) and the percent of CD63/EpCAM/MUC1‐triple‐positive EV in breast cancer patients was significantly higher than that of healthy donors, and this method can achieve an overall accuracy of 91%. Moreover, using DPPIE, we are able to distinguish the EV between lung adenocarcinoma and lung squamous carcinoma patients. This individual EV heterogeneity analysis strategy provides a new way for digging more information on EV to achieve multi‐cancer diagnosis and classification.
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spelling pubmed-77101272020-12-09 Localized fluorescent imaging of multiple proteins on individual extracellular vesicles using rolling circle amplification for cancer diagnosis Zhang, Junli Shi, Jinjin Zhang, Hongling Zhu, Yifan Liu, Wei Zhang, Kaixiang Zhang, Zhenzhong J Extracell Vesicles Research Articles Extracellular vesicles (EV) have attracted increasing attention as tumour biomarkers due to their unique biological property. However, conventional methods for EV analysis are mainly based on bulk measurements, which masks the EV‐to‐EV heterogeneity in tumour diagnosis and classification. Herein, a localized fluorescent imaging method (termed Digital Profiling of Proteins on Individual EV, DPPIE) was developed for analysis of multiple proteins on individual EV. In this assay, an anti‐CD9 antibody engineered biochip was used to capture EV from clinical plasma sample. Then the captured EV was specifically recognized by multiple DNA aptamers (CD63/EpCAM/MUC1), followed by rolling circle amplification to generate localized fluorescent signals. By‐analyzing the heterogeneity of individual EV, we found that the high‐dimensional data collected from each individual EV would provide more precise information than bulk measurement (ELISA) and the percent of CD63/EpCAM/MUC1‐triple‐positive EV in breast cancer patients was significantly higher than that of healthy donors, and this method can achieve an overall accuracy of 91%. Moreover, using DPPIE, we are able to distinguish the EV between lung adenocarcinoma and lung squamous carcinoma patients. This individual EV heterogeneity analysis strategy provides a new way for digging more information on EV to achieve multi‐cancer diagnosis and classification. John Wiley and Sons Inc. 2020-11-11 2020-11 /pmc/articles/PMC7710127/ /pubmed/33304477 http://dx.doi.org/10.1002/jev2.12025 Text en © 2020 The Authors. Journal of Extracellular Vesicles published by Wiley Periodicals LLC on behalf of International Society for Extracellular Vesicles This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Zhang, Junli
Shi, Jinjin
Zhang, Hongling
Zhu, Yifan
Liu, Wei
Zhang, Kaixiang
Zhang, Zhenzhong
Localized fluorescent imaging of multiple proteins on individual extracellular vesicles using rolling circle amplification for cancer diagnosis
title Localized fluorescent imaging of multiple proteins on individual extracellular vesicles using rolling circle amplification for cancer diagnosis
title_full Localized fluorescent imaging of multiple proteins on individual extracellular vesicles using rolling circle amplification for cancer diagnosis
title_fullStr Localized fluorescent imaging of multiple proteins on individual extracellular vesicles using rolling circle amplification for cancer diagnosis
title_full_unstemmed Localized fluorescent imaging of multiple proteins on individual extracellular vesicles using rolling circle amplification for cancer diagnosis
title_short Localized fluorescent imaging of multiple proteins on individual extracellular vesicles using rolling circle amplification for cancer diagnosis
title_sort localized fluorescent imaging of multiple proteins on individual extracellular vesicles using rolling circle amplification for cancer diagnosis
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7710127/
https://www.ncbi.nlm.nih.gov/pubmed/33304477
http://dx.doi.org/10.1002/jev2.12025
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