miRNA Profiling of Magnetic Nanopore-Isolated Extracellular Vesicles for the Diagnosis of Pancreatic Cancer
miRNA Profiling of Magnetic Nanopore-Isolated Extracellular Vesicles for the Diagnosis of Pancreatic Cancer
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DOI：
10.1158/0008-5472.can-17-3703
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发表时间：
2018-07-01
期刊：
影响因子：
11.2
通讯作者：
Issadore, David
中科院分区：
文献类型：
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作者：
Ko, Jina;Bhagwat, Neha;Issadore, David
改善胰腺导管腺癌（PDAC）的诊断，以在早期，治愈阶段检测疾病并指导治疗，对于对抗这种疾病的进展至关重要。由于循环生物标志物的稀疏性和可变表型表达，PDAC液体活检的开发已被证明具有挑战性。在这里，我们报告的方法，我们开发的分离特定子集的细胞外囊泡（EV）从血浆中使用一种新的磁性纳米孔捕获技术。此外，我们提出了一个使用RNA测序和机器学习算法识别EV miRNA生物标志物的工作流程，我们将其结合起来对不同的癌症状态进行分类。将这种方法应用于PDAC的小鼠模型，我们鉴定了11种EV miRNA的生物标志物组，其可以在n = 27只小鼠的训练组和n = 57只小鼠的用户盲法验证组中将患有PDAC的小鼠与健康小鼠或具有癌前病变的小鼠区分开（在三向分类中88%的准确度）。这些结果为使用EV miRNA分析和机器学习进行液体biopsization.Significance的可行性提供了强有力的概念验证支持：这些发现提出了一组细胞外囊泡miRNA血液生物标志物，可以在转基因小鼠模型的癌前阶段检测胰腺癌。(C)2018年AACR。
Improved diagnostics for pancreatic ductal adenocarcinoma (PDAC) to detect the disease at earlier, curative stages and to guide treatments is crucial to progress against this disease. The development of a liquid biopsy for PDAC has proven challenging due to the sparsity and variable phenotypic expression of circulating biomarkers. Here we report methods we developed for isolating specific subsets of extracellular vesicles (EV) from plasma using a novel magnetic nanopore capture technique. In addition, we present a workflow for identifying EV miRNA biomarkers using RNA sequencing and machine-learning algorithms, which we used in combination to classify distinct cancer states. Applying this approach to a mouse model of PDAC, we identified a biomarker panel of 11 EV miRNAs that could distinguish mice with PDAC from either healthy mice or those with precancerous lesions in a training set of n = 27 mice and a user-blinded validation set of n = 57 mice (88% accuracy in a three-way classification). These results provide strong proof-of-concept support for the feasibility of using EV miRNA profiling and machine learning for liquid biopsy.Significance: These findings present a panel of extracellular vesicle miRNA blood-based biomarkers that can detect pancreatic cancer at a precancerous stage in a transgenic mousemodel. (C) 2018 AACR.