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Non-Coding RNA, Volume 11, Issue 6 (December 2025) – 2 articles

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14 pages, 2853 KB  
Article
The Chromosome 19 microRNA Cluster Facilitates Cancer Stemness in Hepatocellular Carcinoma
by Marian T. Underwood, Varsha Devarapalli, Goodwin G. Jinesh, John H. Lockhart, Marco Napoli, Nino Mtchedlidze, Elsa R. Flores and Andrew S. Brohl
Non-Coding RNA 2025, 11(6), 74; https://doi.org/10.3390/ncrna11060074 - 29 Oct 2025
Abstract
Background/Objectives: Hepatocellular carcinoma (HCC) is one of the world’s deadliest cancers; however, the mechanisms that contribute to its aggressiveness are poorly understood. In the recent literature, overexpression of the Chromosome 19 MicroRNA Cluster (C19MC) has been associated with an aggressive phenotype and unfavorable [...] Read more.
Background/Objectives: Hepatocellular carcinoma (HCC) is one of the world’s deadliest cancers; however, the mechanisms that contribute to its aggressiveness are poorly understood. In the recent literature, overexpression of the Chromosome 19 MicroRNA Cluster (C19MC) has been associated with an aggressive phenotype and unfavorable prognosis in HCC. However, the molecular consequences of C19MC overexpression in HCC remain poorly understood. Methods: Here, we created a constitutive C19MC-overexpressing HCC model and used two different CRISPR-engineered C19MC-overexpressing HCC models to analyze phenotype and transcriptomic changes. Results: We observed that C19MC overexpression induces cancer stem cell (CSC) phenotypic features in vitro and analyzed transcriptomic changes in genes correlating with stemness, such as NFκB and EMT. Conclusions: C19MC induces changes in HCC that are consistent with stemness and aggression, which provides a better understanding of why C19MC could be a biomarker of poor prognosis. Full article
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10 pages, 991 KB  
Perspective
Exploring microRNAs, One Cell at a Time
by Jessica Kreutz, Tijana Mitić and Andrea Caporali
Non-Coding RNA 2025, 11(6), 73; https://doi.org/10.3390/ncrna11060073 - 22 Oct 2025
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Abstract
The emergence of single-cell sequencing and computational analysis has dramatically improved our understanding of cellular diversity and gene expression dynamics. The rapid advancement of high-throughput omics technologies has led to an exponential growth in biological data. However, many gene regulatory processes at the [...] Read more.
The emergence of single-cell sequencing and computational analysis has dramatically improved our understanding of cellular diversity and gene expression dynamics. The rapid advancement of high-throughput omics technologies has led to an exponential growth in biological data. However, many gene regulatory processes at the single-cell level remain underexplored, especially those regulated by post-transcriptional mechanisms involving microRNAs (miRNAs). miRNAs are essential regulators of gene expression, affecting cellular functions in both normal and disease states. Recent innovations, such as single-cell gene expression profiling and bioinformatic analysis, have enabled comprehensive studies that uncover previously hidden miRNA profiles. In this context, we present experimental tools and computational methods for analysing cell-specific miRNA abundance and investigating their mechanisms. These approaches are expected to reveal the complex nature of miRNA biology and, more broadly, enhance our understanding of life sciences and diseases. Full article
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