Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive lung disease. Lesions in the lung epithelium cause alterations in the microenvironment that promote fibroblast accumulation. Extracellular vesicles (EVs) transport proteins, lipids, and nucleic acids, such as microRNAs (miRNAs). The aim of this study was to characterize the differentially expressed miRNAs in the cargo of EVs obtained from the LL97 and LL29 fibroblast cell lines isolated from IPF lungs versus those derived from the CCD19 fibroblast cell line isolated from a healthy donors. We characterized EVs by ultracentrifugation, Western blotting, and dynamic light scattering. We identified miRNAs by small RNA-seq, a total of 1144 miRNAs, of which 1027 were known miRNAs; interestingly, 117 miRNAs were novel. Differential expression analysis showed that 77 miRNAs were upregulated and 68 were downregulated. In addition, pathway enrichment analyses from the Gene Ontology and Kyoto Encyclopedia of Genomes identified several miRNA target genes in the categories, cell proliferation, regulation of apoptosis, pathways in cancer, and proteoglycans in cancer. Our data reveal that miRNAs contained in EVs cargo could be helpful as biomarkers for fibrogenesis, diagnosis, and therapeutic intervention of IPF.

Hepatocellular carcinoma (HCC) is the most common primary liver cancer, often diagnosed at advanced stages due to insufficient early screening and monitoring. MicroRNAs (miRNAs) are key regulators of gene expression and potential biomarkers for cancer diagnosis. This study investigated the diagnostic potential of miRNAs in Extracellular Vesicles (EVs) from HCC. miRNA expression in EVs was analyzed using HCC cell lines, circulating EVs from a Diethylnitrosamine (DEN)-induced liver tumor rat model, and plasma samples from HCC patients. Receiver Operating Characteristics (ROCs) were applied to evaluate the diagnostic accuracy of circulating EV miRNAs in patients. Five miRNAs (miR-183-5p, miR-19a-3p, miR-148b-3p, miR-34a-5p, and miR-215-5p) were consistently up-regulated in EVs across in vitro and in vivo HCC models. These miRNAs showed statistically significant differences in HCC patients stratified by TNM staging and Edmondson–Steiner grading compared to healthy controls. They also differentiated HCC patients with various etiologies from the control group and distinguished HCC patients, with or without liver cirrhosis, from cirrhotic and healthy individuals. Individually and as a panel, they demonstrated high sensitivity, specificity, and accuracy in identifying HCC patients. Their consistent upregulation across models and clinical samples highlights their robustness as biomarkers for HCC diagnosis, offering the potential for early disease management and prognosis.

Hepatocellular carcinoma (HCC) is the most common liver cancer, often diagnosed at advanced stages due to inadequate early diagnostic methods. MicroRNAs (miRNAs) play crucial roles in gene expression regulation and are possible biomarkers for molecular diagnosis in several diseases, including cancer. This study aimed to investigate the diagnostic potential of miRNAs contained in Extracellular Vesicles (EVs) from HCC. The miRNA expression contained in EVs was analyzed in HCC cell lines, circulating EVs in a Diethylnitrosamine (DEN)-induced HCC rat model, and plasma samples of HCC patients. Receiver Operating Characteristics (ROC) were applied to circulating EV-miRNAs from human patients to evaluate their diagnostic accuracy. The miRNA expression analysis identified five miRNAs (miR-183-5p, miR-19a-3p, miR-148b-3p, miR-34a-5p, and miR-215-5p) consistently up-regulated in EVs from in vitro and in vivo HCC models. These five EVs-derived miRNAs showed statistically significant differences in HCC patients stratified by TNM staging and Edmondson-Steiner grading compared to healthy controls. Individually and in combination, they demonstrated high sensitivity, specificity, and accuracy in distinguishing HCC patients from healthy subjects. The consistent upregulation of the five miRNAs across different experimental models and clinical samples suggests their robustness as biomarkers for HCC diagnosis, and it underscores their clinical potential in early disease management and prognosis.