Pangaea Oncology, Laboratory of Oncology, Quirón Dexeus University Hospital, Sabino Arana 5-19, 08028, Barcelona, Spain.
Department of Biochemistry, Molecular Biology and Biomedicine, Universitat Autónoma de Barcelona (UAB), 08193, Cerdanyola, Spain.
Sci Rep. 2021 Feb 12;11(1):3712. doi: 10.1038/s41598-021-83132-0.
Extracellular vesicles (EVs) are double-layered phospholipid membrane vesicles that are released by most cells and can mediate intercellular communication through their RNA cargo. In this study, we tested if the NanoString nCounter platform can be used for the analysis of EV-mRNA. We developed and optimized a methodology for EV enrichment, EV-RNA extraction and nCounter analysis. Then, we demonstrated the validity of our workflow by analyzing EV-RNA profiles from the plasma of 19 cancer patients and 10 controls and developing a gene signature to differentiate cancer versus control samples. TRI reagent outperformed automated RNA extraction and, although lower plasma input is feasible, 500 μL provided highest total counts and number of transcripts detected. A 10-cycle pre-amplification followed by DNase treatment yielded reproducible mRNA target detection. However, appropriate probe design to prevent genomic DNA binding is preferred. A gene signature, created using a bioinformatic algorithm, was able to distinguish between control and cancer EV-mRNA profiles with an area under the ROC curve of 0.99. Hence, the nCounter platform can be used to detect mRNA targets and develop gene signatures from plasma-derived EVs.
细胞外囊泡（EVs）是双层磷脂膜囊泡，大多数细胞都会释放这种囊泡，通过其 RNA 货物来介导细胞间通讯。在本研究中，我们测试了 NanoString nCounter 平台是否可用于分析 EV-mRNA。我们开发并优化了一种用于 EV 富集、EV-RNA 提取和 nCounter 分析的方法。然后，我们通过分析来自 19 名癌症患者和 10 名对照者的血浆中的 EV-RNA 图谱，并开发一种区分癌症与对照样本的基因特征，证明了我们工作流程的有效性。TRI 试剂优于自动化 RNA 提取，尽管可以降低血浆的上样量，但 500 μL 提供了最高的总计数和检测到的转录本数量。进行 10 个循环的预扩增，然后进行 DNase 处理，可实现可重复的 mRNA 靶标检测。然而，优选设计合适的探针以防止与基因组 DNA 结合。使用生物信息学算法创建的基因特征能够区分对照和癌症 EV-mRNA 图谱，ROC 曲线下面积为 0.99。因此，nCounter 平台可用于从血浆衍生的 EV 中检测 mRNA 靶标并开发基因特征。
