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使用生物共轭的等离子体金银合金纳米颗粒对癌症进行多重免疫标记。

Multiplexed immunolabelling of cancer using bioconjugated plasmonic gold-silver alloy nanoparticles.

作者信息

Darviot Cécile, Gosselin Bryan, Martin Flavie, Patskovsky Sergiy, Jabin Ivan, Bruylants Gilles, Trudel Dominique, Meunier Michel

机构信息

Polytechnique Montréal Montréal Canada

Centre Hospitalier de l'Université de Montréal Montréal Canada.

出版信息

Nanoscale Adv. 2024 Jul 3;6(17):4385-4393. doi: 10.1039/d4na00052h. eCollection 2024 Aug 20.

DOI:10.1039/d4na00052h
PMID:39170968
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11334976/
Abstract

Reliable protein detection methods are vital for advancing biological research and medical diagnostics. While immunohistochemistry and immunofluorescence are commonly employed, their limitations underscore the necessity for alternative approaches. This study introduces immunoplasmonic labelling, utilizing plasmonic nanoparticles (NPs), specifically designed gold and gold-silver alloy NPs (Au:Ag NPs), for multiplexed and quantitative protein detection. These NPs, when coupled with antibodies targeting proteins of interest, enable accurate counting and evaluation of protein expression levels while overcoming issues such as autofluorescence. In this study, we compare two nanoparticle functionalization strategies-one coating based on thiolated PEG and one coating based on calix[4]arenes-on gold and gold-silver alloy nanoparticles of varying sizes. Overall results tend to demonstrate a greater versatility for the calix[4]arene-based coating. With this coating and using the classical EDC/sulfo-NHS cross-linking procedure, we also demonstrate the successful multiplexed immunolabelling of Her2, CD44, and EpCAM in breast cancer cell lines (SK-BR-3 and MDA-MB-231). Furthermore, we introduce a user-friendly software for automatic NP detection and classification by colour, providing a promising proof-of-concept for the practical application of immunoplasmonic techniques in the quantitative analysis of biopsies in the clinical setting.

摘要

可靠的蛋白质检测方法对于推进生物学研究和医学诊断至关重要。虽然免疫组织化学和免疫荧光是常用方法,但它们的局限性凸显了采用替代方法的必要性。本研究引入了免疫等离子体标记技术,利用等离子体纳米颗粒(NPs),特别是专门设计的金和金银合金纳米颗粒(Au:Ag NPs),用于多重和定量蛋白质检测。这些纳米颗粒与靶向目标蛋白质的抗体结合后,能够准确计数并评估蛋白质表达水平,同时克服诸如自发荧光等问题。在本研究中,我们比较了两种纳米颗粒功能化策略——一种基于硫醇化聚乙二醇的涂层和一种基于杯[4]芳烃的涂层——应用于不同尺寸的金和金银合金纳米颗粒。总体结果倾向于表明基于杯[4]芳烃的涂层具有更大的通用性。使用这种涂层并采用经典的EDC/磺基-NHS交联程序,我们还证明了在乳腺癌细胞系(SK-BR-3和MDA-MB-231)中成功实现了Her2、CD44和EpCAM的多重免疫标记。此外,我们引入了一款用户友好的软件,用于通过颜色自动检测和分类纳米颗粒,为免疫等离子体技术在临床活检定量分析中的实际应用提供了一个有前景的概念验证。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2020/11334976/1bcb0a7c732d/d4na00052h-f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2020/11334976/35d07d50cf79/d4na00052h-s1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2020/11334976/442661819ac8/d4na00052h-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2020/11334976/3c4b190b048d/d4na00052h-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2020/11334976/0b7fc6704bff/d4na00052h-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2020/11334976/d8e294cf5097/d4na00052h-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2020/11334976/d89cbcd3c8c4/d4na00052h-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2020/11334976/6efddbf137d5/d4na00052h-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2020/11334976/731ee5876177/d4na00052h-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2020/11334976/1bcb0a7c732d/d4na00052h-f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2020/11334976/35d07d50cf79/d4na00052h-s1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2020/11334976/442661819ac8/d4na00052h-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2020/11334976/3c4b190b048d/d4na00052h-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2020/11334976/0b7fc6704bff/d4na00052h-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2020/11334976/d8e294cf5097/d4na00052h-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2020/11334976/d89cbcd3c8c4/d4na00052h-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2020/11334976/6efddbf137d5/d4na00052h-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2020/11334976/731ee5876177/d4na00052h-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2020/11334976/1bcb0a7c732d/d4na00052h-f8.jpg

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