肝细胞癌（HCC）是最常见的肝癌类型。小细胞外囊泡 (sEV) 是含有 RNA 的双层脂膜囊泡，作为癌症生物标志物表现出有希望的诊断和预后潜力。从外周血中建立 miRNA 组，用作诊断 HCC 的非侵入性生物标志物。对从血浆中获得的 sEV 进行了分析使用高通量测序。随后使用定量实时聚合酶链反应分析验证了所识别的差异 miRNA 表达模式。随机森林方法识别了 10 种不同的 miRNA，可区分 HCC 血浆与非 HCC 血浆。在验证过程中，miR-140-3p (p = 0.0001) 和 miR-3200-3p (p = 0.0017) 表现出显着的下调。富集分析揭示了这些 miRNA 的靶基因与癌症发展之间的显着相关性。利用逻辑回归，我们开发了一个包含这些经过验证的 miRNA 的诊断模型。受试者工作特征 (ROC) 曲线分析显示曲线下面积 (AUC) 为 0.951，灵敏度为 90.1%，特异性为 87.8%。 sEV 传递的这些异常表达的 miRNA 可能导致 HCC 病理学，并可作为诊断生物标志物适用于 HCC。版权所有 © 2024 罗、焦、郭、陈、王、文、宋、陈、周和宋。

Hepatocellular carcinoma (HCC) is the most common type of liver cancer. Small extracellular vesicles (sEVs) are bilayer lipid membrane vesicles containing RNA that exhibit promising diagnostic and prognostic potential as cancer biomarkers.To establish a miRNA panel from peripheral blood for use as a noninvasive biomarker for the diagnosis of HCC.sEVs obtained from plasma were profiled using high-throughput sequencing. The identified differential miRNA expression patterns were subsequently validated using quantitative real-time polymerase chain reaction analysis.The random forest method identified ten distinct miRNAs distinguishing HCC plasma from non-HCC plasma. During validation, miR-140-3p (p = 0.0001) and miR-3200-3p (p = 0.0017) exhibited significant downregulation. Enrichment analysis uncovered a notable correlation between the target genes of these miRNAs and cancer development. Utilizing logistic regression, we developed a diagnostic model incorporating these validated miRNAs. Receiver operating characteristic (ROC) curve analysis revealed an area under the curve (AUC) of 0.951, with a sensitivity of 90.1% and specificity of 87.8%.These aberrantly expressed miRNAs delivered by sEVs potentially contribute to HCC pathology and may serve as diagnostic biomarkers for HCC.Copyright © 2024 Luo, Jiao, Guo, Chen, Wang, Wen, Song, Chen, Zhou and Song.