Potential of extracellular vesicle-derived microRNAs as a platform for biomarker discovery in acute lymphoblastic leukemia - Jeong-An Gim; Kunye Kwak; Yong Park; Byung Soo Kim; Ka-Won Kang (PLoS ONE, 2026)
Background Extracellular vesicle (EV)-derived microRNAs (miRNAs) represent a promising platform for biomarker discovery in acute lymphoblastic leukemia (ALL). This study evaluated the biomarker potential of EV-derived miRNAs isolated from five ALL cell lines. Methods Human ALL cell lines were cultured in EV-depleted fetal bovine serum. These included two parental cell lines, CCL-119 and CRL-3273, and three related cell lines previously characterized as exhibiting chemoresistance-associated phenotypes: CRL-2264 and CRL-2265, derived from CCL-119, and CRL-3274, derived from CRL-3273. EVs were isolated using a commercial size-exclusion chromatography-based method and characterized by nanoparticle tracking analysis, transmission electron microscopy, and immunoblotting for CD9, CD63, and CD81. Small RNA sequencing was subsequently performed. All data processing and visualization were conducted using R statistical software. Results Across all samples, 2,656 EV-derived miRNAs were identified. Among these, three EV-derived miRNAs were prioritized based on consistent directional differences in this exploratory analysis: miR-1226-5p and miR-760 were downregulated, whereas miR-29b-3p was upregulated. To further assess their potential clinical relevance, we evaluated associations between survival and the expression of predicted target genes using the GSE5314 dataset. Higher expression of AHI1 , a gene implicated in leukemogenesis and drug resistance and linked to downregulated miR-760 in our models, was associated with poor survival in patients with ALL. Conclusions This exploratory study identified three EV-derived miRNAs, miR-1226-5p, miR-760, and miR-29b-3p, together with the related gene AHI1 , as candidate biomarker leads in ALL cell line models. Further validation using patient-derived EVs, plasma samples, and subtype-aware clinical cohorts is required before clinical interpretation.