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

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