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利用小细胞外囊泡传播的miRNA特征构建肝细胞癌诊断模型

Diagnostic model for hepatocellular carcinoma using small extracellular vesicle-propagated miRNA signatures.

作者信息

Luo Xinyi, Jiao Lin, Guo Qin, Chen Yi, Wang Nian, Wen Yang, Song JiaJia, Chen Hao, Zhou Juan, Song Xingbo

机构信息

Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, China.

Department of Laboratory Medicine, the First People's Hospital of Ziyang, Ziyang, China.

出版信息

Front Mol Biosci. 2024 Jun 28;11:1419093. doi: 10.3389/fmolb.2024.1419093. eCollection 2024.

Abstract

BACKGROUND

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.

AIMS

To establish a miRNA panel from peripheral blood for use as a noninvasive biomarker for the diagnosis of HCC.

METHODS

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.

RESULTS

The random forest method identified ten distinct miRNAs distinguishing HCC plasma from non-HCC plasma. During validation, miR-140-3p ( = 0.0001) and miR-3200-3p ( = 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%.

CONCLUSION

These aberrantly expressed miRNAs delivered by sEVs potentially contribute to HCC pathology and may serve as diagnostic biomarkers for HCC.

摘要

背景

肝细胞癌(HCC)是最常见的肝癌类型。小细胞外囊泡(sEVs)是含有RNA的双层脂质膜囊泡,作为癌症生物标志物具有良好的诊断和预后潜力。

目的

从外周血中建立一个miRNA面板,用作HCC诊断的非侵入性生物标志物。

方法

使用高通量测序对从血浆中获得的sEVs进行分析。随后使用定量实时聚合酶链反应分析验证所鉴定的差异miRNA表达模式。

结果

随机森林方法鉴定出10种不同的miRNA,可区分HCC血浆和非HCC血浆。在验证过程中,miR-140-3p(= 0.0001)和miR-3200-3p(= 0.0017)表现出显著下调。富集分析发现这些miRNA的靶基因与癌症发展之间存在显著相关性。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,敏感性为90.1%,特异性为87.8%。

结论

这些由sEVs传递的异常表达的miRNA可能对HCC病理有贡献,并可能作为HCC的诊断生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e3cd/11239443/a47fcf7c081f/fmolb-11-1419093-g001.jpg

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