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Infection with hepatitis B virus (HBV) is a main risk factor for hepatocellular carcinoma (HCC). Extracellular vesicles, such as exosomes, play an important role in tumor development and metastasis, including regulation of HBV-related HCC. In this study, we have characterized exosome microRNA and proteins released in vitro from hepatitis B virus (HBV)-related HCC cell lines SNU-423 and SNU-182 and immortalized normal hepatocyte cell lines (THLE2 and THLE3) using microRNA sequencing and mass spectrometry. Bioinformatics, including functional enrichment and network analysis, combined with survival analysis using data related to HCC in The Cancer Genome Atlas (TCGA) database, were applied to examine the prognostic significance of the results. More than 40 microRNAs and 200 proteins were significantly dysregulated (p < 0.05) in the exosomes released from HCC cells in comparison with the normal liver cells. The functional analysis of the differentially expressed exosomal miRNAs (i.e., mir-483, mir-133a, mir-34a, mir-155, mir-183, mir-182), their predicted targets, and exosomal differentially expressed proteins (i.e., POSTN, STAM, EXOC8, SNX9, COL1A2, IDH1, FN1) showed correlation with pathways associated with HBV, virus activity and invasion, exosome formation and adhesion, and exogenous protein binding. The results from this study may help in our understanding of the role of HBV infection in the development of HCC and in the development of new targets for treatment or non-invasive predictive biomarkers of HCC.
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This content will become publicly available on December 1, 2026
Locus-specific HERV expression associated with hepatocellular carcinoma
Background Human endogenous retroviruses (HERVs) harbor accessory proteins that influence cellular processes and have been linked to a wide variety of diseases, including cancer. This study investigates locus-specific HERV expression and its association with gene dysregulation in hepatocellular carcinoma (HCC), a highly prevalent and deadly form of liver cancer worldwide. Methods We analyzed RNASeq data from 424 HCC samples from The Cancer Genome Atlas (TCGA), which comprised 371 tumor and 50 matched normal tissues from a total of 371 hepatocellular carcinoma participants. We employed Telescope to identify and quantify HERV expression across the total RNA sequencing data. Results The majority of differentially expressed HERVs exhibited reduced expression in tumor tissue (166 downregulated vs. 50 upregulated), suggesting a potential functional role of HERV expression patterns in shaping the pathophysiological landscape of HCC. Specifically, the suppression of HERV-H family members, which are known to regulate cellular differentiation, may contribute to tumor dedifferentiation, increased plasticity, and enhanced metastatic potential. This loss of differentiation control and increased adaptability may play a critical role in driving the progression of liver cancer. Discussion Our study highlights a significant association of HERV expression with HCC, highlighting the differential regulation of specific HERV families in tumor tissue. For example, HERVH and ERVLE families showed consistent downregulation in tumor samples, while HERVE and HERV9 were more commonly upregulated. These shifts may reflect underlying changes in transcriptional regulation or chromatin structure between normal and malignant tissues. Rather than indicating a singular functional role, the observed expression patterns likely reflect a multifaceted relationship between HERVs and tumor biology. Further studies will be needed to determine whether these expression differences contribute to, or result from, tumor progression and to explore their potential as biomarkers or therapeutic targets.
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- Award ID(s):
- 2109688
- PAR ID:
- 10627665
- Publisher / Repository:
- BMC
- Date Published:
- Journal Name:
- Mobile DNA
- Volume:
- 16
- Issue:
- 1
- ISSN:
- 1759-8753
- Subject(s) / Keyword(s):
- Human endogenous retroviruses (HERVs) Hepatocellular carcinoma (HCC) Telescope Locus-specific expression Retrotranscriptomics
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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