Department of Chemistry, Shanghai Stomatological Hospital, School of Pharmacy, Institute of Biomedical Sciences, Fudan University, Shanghai 200438, China.
Department of Laboratory Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
Anal Chem. 2023 Oct 17;95(41):15276-15285. doi: 10.1021/acs.analchem.3c02594. Epub 2023 Oct 2.
Small extracellular vesicles (sEVs) have emerged as noninvasive biomarkers in liquid biopsy due to their significant function in pathology and physiology. However, the phenotypic heterogeneity of sEVs presents a significant challenge to their study and has significant implications for their applications in liquid biopsies. In this study, anodic aluminum oxide films with different pore sizes (AAO nanoarray) were introduced to enable size-based isolation and downstream proteomics profiling of sEV subpopulations. The adjustable pore size and abundant Al on the framework of AAOs allowed size-dependent isolation of sEV subpopulations through nanoconfined effects and Lewis acid-base interaction between AAOs and sEVs. Benefiting from the strong concerted effect, the simple AAO nanoarray enabled specific isolation of three sEV subpopulations, termed "50", "90", and "150 nm" groups, from 10 μL of complex biological samples within 10 min with high capture efficiencies and purities. Moreover, the nanopores of AAOs also acted as nanoreactors for comprehensive proteomic profiling of the captured sEV subpopulations to reveal their heterogeneity. The AAO nanoarray was first investigated on sEVs from a cell culture medium, where sEV subpopulations could be clearly distinguished, and three traditional sEV-specific proteins (CD81, CD9, and FLOT1) could be identified by proteomic analysis. A total of 3946, 3951, and 3940 proteins were identified from 50, 90, and 150 nm sEV subpopulations, respectively, which is almost twice the number compared to those obtained from the conventional approach. The concept was further applied to complex real-case sample analysis from prostate cancer patients. Machine learning and gene ontology (GO) information analysis of the identified proteins indicate that different-sized sEV subpopulations contain unique protein cargos and have distinct cellular components and molecular functions. Further receiver operating characteristic curve (ROC) analysis of the top five differential proteins from the three sEV subpopulations demonstrated the high accuracy of the proposed approach toward prostate cancer diagnosis (AUC > 0.99). More importantly, several proteins involved in focal adhesion and antigen processing and presentation pathways were found to be upregulated in prostate cancer patients, which may serve as potential biomarkers of prostate cancer. These results suggest that the sEV subpopulation-based AAO nanoarray is of great value in facilitating the early diagnosis and prognosis of cancer and opens a new avenue for sEVs in liquid biopsy.
小细胞外囊泡 (sEVs) 因其在病理学和生理学中的重要功能而成为液体活检中的非侵入性生物标志物。然而，sEVs 的表型异质性对其研究提出了重大挑战，并对其在液体活检中的应用具有重要意义。在这项研究中，引入了具有不同孔径的阳极氧化铝膜 (AAO 纳米阵列)，以实现基于大小的 sEV 亚群分离和下游蛋白质组学分析。AAO 的可调孔径和丰富的 Al 框架允许通过纳米受限效应和 AAO 与 sEV 之间的路易斯酸碱相互作用，对 sEV 亚群进行基于大小的分离。得益于强大的协同效应，简单的 AAO 纳米阵列能够在 10 分钟内从 10 μL 复杂生物样品中特异性分离三种 sEV 亚群，分别称为“50nm”、“90nm”和“150nm”组，具有较高的捕获效率和纯度。此外，AAO 的纳米孔还可以作为捕获的 sEV 亚群的综合蛋白质组学分析的纳米反应器，以揭示其异质性。AAO 纳米阵列首先在细胞培养物中的 sEV 上进行了研究，其中可以清楚地区分 sEV 亚群，并通过蛋白质组分析鉴定出三种传统的 sEV 特异性蛋白 (CD81、CD9 和 FLOT1)。分别从 50nm、90nm 和 150nm sEV 亚群中鉴定出 3946、3951 和 3940 种蛋白质，几乎是传统方法获得数量的两倍。该概念进一步应用于来自前列腺癌患者的复杂实际案例样本分析。所鉴定蛋白质的机器学习和基因本体 (GO) 信息分析表明，不同大小的 sEV 亚群包含独特的蛋白质 cargos，并且具有不同的细胞成分和分子功能。进一步对三种 sEV 亚群中前五个差异蛋白的受试者工作特征曲线 (ROC) 分析表明，该方法对前列腺癌诊断具有很高的准确性 (AUC>0.99)。更重要的是，在前列腺癌患者中发现几种参与粘着斑和抗原加工和呈递途径的蛋白质上调，它们可能作为前列腺癌的潜在生物标志物。这些结果表明，基于 sEV 亚群的 AAO 纳米阵列在促进癌症的早期诊断和预后方面具有重要价值，并为液体活检中的 sEVs 开辟了新途径。
