Ultra-Sensitive Automated Profiling of EpCAM Expression on Tumor-Derived Extracellular Vesicles
Ultra-Sensitive Automated Profiling of EpCAM Expression on Tumor-Derived Extracellular Vesicles
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DOI：
10.3389/fgene.2019.01273
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发表时间：
2019-12-17
影响因子：
3.7
通讯作者：
Hu, Tony Y.
中科院分区：
文献类型：
--
作者：
Amrollahi, Pouya;Rodrigues, Meryl;Hu, Tony Y.
细胞外囊泡（EV）在大多数生物流体中是丰富的，并且被认为是有希望的生物标志物候选物，但是EV生物标志物测定的发展部分地受到其对先前EV纯化的要求以及缺乏标准化和可重复的EV分离方法的阻碍。我们现在描述了一种远场纳米等离子体增强散射（FF-nPES）测定法，用于小体积血清（< 5 μ l）中存在的EV的无分离表征。在这种方法中，用癌症选择性抗体捕获EV，与缀合有EV表面蛋白CD 9抗体的金纳米棒杂交，并通过使用全自动暗场显微镜系统分析时散射光的能力进行定量。我们的结果表明，FF-nPES执行类似于EV ELISA，当分析EV表面表达的上皮细胞粘附分子（EpCAM），这具有临床意义的癌症生物标志物。概念验证FF-nPES数据表明，它可以直接分析来自血清样品的EV EpCAM表达，以区分早期胰腺导管腺癌患者与健康受试者，检测自发性胰腺癌小鼠模型中早期肿瘤的发展，并监测胰腺癌患者来源的异种移植小鼠模型中的肿瘤生长。因此，FF-nPES似乎表现出直接分析EV膜生物标志物用于疾病诊断和治疗监测的强大潜力。
Extracellular vesicles (EVs) are abundant in most biological fluids and considered promising biomarker candidates, but the development of EV biomarker assays is hindered, in part, by their requirement for prior EV purification and the lack of standardized and reproducible EV isolation methods. We now describe a far-field nanoplasmon-enhanced scattering (FF-nPES) assay for the isolation-free characterization of EVs present in small volumes of serum (< 5 mu l). In this approach, EVs are captured with a cancer-selective antibody, hybridized with gold nanorods conjugated with an antibody to the EV surface protein CD9, and quantified by their ability to scatter light when analyzed using a fully automated dark-field microscope system. Our results indicate that FF-nPES performs similarly to EV ELISA, when analyzing EV surface expression of epithelial cell adhesion molecule (EpCAM), which has clinical significant as a cancer biomarker. Proof-of-concept FF-nPES data indicate that it can directly analyze EV EpCAM expression from serum samples to distinguish early stage pancreatic ductal adenocarcinoma patients from healthy subjects, detect the development of early stage tumors in a mouse model of spontaneous pancreatic cancer, and monitor tumor growth in patient derived xenograft mouse models of pancreatic cancer. FF-nPES thus appears to exhibit strong potential for the direct analysis of EV membrane biomarkers for disease diagnosis and treatment monitoring.