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Evaluation of Plasma Extracellular Vesicle MicroRNA Signatures for Lung Adenocarcinoma and Granuloma With Monte-Carlo Feature Selection Method

机译:蒙特卡洛特征选择法评估肺腺癌和肉芽肿的血浆细胞外囊泡微RNA特征

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摘要

Extracellular Vesicle (EV) is a compilation of secreted vesicles, including micro vesicles, large oncosomes, and exosomes. It can be used in non-invasive diagnosis. MicroRNAs (miRNAs) processed by exosomes can be detected by liquid biopsy. To objectively evaluate the discriminative ability of miRNAs from whole plasma, EV and EV-free plasma, we analyzed the miRNA expression profiles in whole plasma, EV and EV-free plasma of 10 lung adenocarcinoma and 9 granuloma patients. With Monte-Carlo feature selection method, the top discriminative miRNAs in whole plasma, EV and EV-free plasma were identified, and they were quite different. Using the Repeated Incremental Pruning to Produce Error Reduction (RIPPER) method, we learned the classification rules: in whole plasma, granuloma patients did not express hsa-miR-223-3p while the lung adenocarcinoma patients expressed hsa-miR-223-3p; in EV, the hsa-miR-23b-3p was highly expressed in granuloma patients but not lung adenocarcinoma patients; in EV-free plasma, hsa-miR-376a-3p was expressed in granuloma patients but barely expressed in lung adenocarcinoma patients. For prediction performance, whole plasma had the highest weighted accuracy and EV outperformed EV-free plasma. Our results suggested that EV can be used as lung cancer biomarker. However, since it is less stable and not easy to detect, there are still technological difficulties to overcome.
机译:细胞外囊泡(EV)是分泌的囊泡的汇编,包括微囊泡,大的囊泡和外泌体。它可以用于非侵入性诊断。外泌体处理的MicroRNA(miRNA)可以通过液体活检来检测。为了客观评估全血浆,EV和无EV血浆中miRNA的区分能力,我们分析了10例肺腺癌和9例肉芽肿患者在全血浆,EV和无EV血浆中的miRNA表达谱。使用蒙特卡洛特征选择方法,鉴定了全血浆,EV和无EV血浆中的最高判别性miRNA,它们之间存在很大差异。使用重复增量修剪以减少错误的方法(RIPPER),我们了解了分类规则:在整个血浆中,肉芽肿患者不表达hsa-miR-223-3p,而肺腺癌患者则表达hsa-miR-223-3p。在EV中,hsa-miR-23b-3p在肉芽肿患者中高表达,而在肺腺癌患者中不高。在无EV血浆中,hsa-miR-376a-3p在肉芽肿患者中表达,而在肺腺癌患者中几乎不表达。对于预测性能,整个等离子具有最高的加权精度,并且EV优于无EV的等离子体。我们的结果表明,EV可以用作肺癌的生物标志物。但是,由于它的稳定性较差并且不容易检测,因此仍然需要克服技术难题。

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