Evidence map›Paper›PMID 41845440›Full record

ArticleCell communication and signaling : CCS2026

Decoding the circRNA-miRNA-mRNA regulatory network in hepatitis B virus-driven hepatocellular carcinoma.

Kainat Ahmed, Anwaruddin Mohammad, Nan Chaiyariti, Danya Sankaranarayanan, Pankaj Kumar, Sudhakar Jha

Abstract read
In one paragraph

Article in Cell communication and signaling : CCS, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Kainat AhmedDepartment of Physiological Sciences, College of Veterinary Medicine, Oklahoma State University, Stillwater, OK, USA.
Anwaruddin MohammadBioinformatics Core, University of Virginia School of Medicine, Charlottesville, VA, USA.
Nan ChaiyaritiDepartment of Physiological Sciences, College of Veterinary Medicine, Oklahoma State University, Stillwater, OK, USA.
Danya SankaranarayananDepartment of Physiological Sciences, College of Veterinary Medicine, Oklahoma State University, Stillwater, OK, USA.
Pankaj KumarBioinformatics Core, University of Virginia School of Medicine, Charlottesville, VA, USA. pk7z@virginia.edu.
Sudhakar JhaDepartment of Physiological Sciences, College of Veterinary Medicine, Oklahoma State University, Stillwater, OK, USA. sjha@okstate.edu.

Funding

Women's Oncology Program - WONP30CA044579 · NCI · UNIVERSITY OF VIRGINIA CHARLOTTESVILLE · PI Dina Gould Halme · 1987 to 2026
$72.1M
Pilot Project Grant ProgramP30GM149368 · NIGMS · OKLAHOMA STATE UNIVERSITY STILLWATER · PI LIN LIU · 2023 to 2026
$5.5M
NIGMS NIH HHS P30GM149368NIH HHS P30CA044579
6 · The paper itself

Abstract

backgroundIntegration of the hepatitis B virus (HBV) genome into the host chromosome of infected patients poses a threat to those with HBV-associated hepatocellular carcinoma (HBV-HCC) due to challenges in early diagnosis and poor prognosis. CircRNAs are known for their oncogenic and biomarker potential in various cancers, including HBV-HCC, by sequestering tumor suppressive miRNAs, which, when free, can silence the expression of oncogenic mRNAs. Therefore, we aimed to develop a bioinformatic model to identify the circRNA-miRNA-mRNA axis in HBV-integrated HCC cell lines and to identify prognostic biomarkers specific to HBV-HCC patients.

methodsWe identified dysregulated host circRNAs and mRNAs in HBV-negative and HBV-integrated cells using RNA-seq, followed by differential gene expression analysis with DESeq, and performed pathway analysis using Gene Set Enrichment Analysis (GSEA). Junctional sequences of the circRNAs were validated by Sanger sequencing of the amplified products. RT-qPCR further confirmed the dysregulation of 9 randomly selected circRNAs chosen from those with the highest fold-change and adjusted p-values. The miRNA partners for each circRNA were identified using mirDB. miRNA expression validation was performed using the publicly available Gene Expression Omnibus (GEO) database of the same cells, and Empirical Cumulative Distribution Function (ECDF) plots were generated to assess the fold change of mRNAs in potential binding miRNA partners. The mRNA targets for 10 miRNA ECDF plots were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and hub genes were identified using Search Tool for the Retrieval of Interacting Genes (STRING) Cytohubba protein-protein interaction (PPI) analysis. Survival analysis of hub genes was plotted, and a competitive endogenous RNA (ceRNA) network was constructed using Cytoscape.

resultsWe identified 494 dysregulated circRNAs, 346 dysregulated miRNAs, and 10,419 dysregulated mRNA in HBV-integrated cells through a comprehensive bioinformatic model. circADGRL2 (~ 25-fold) showed the highest upregulation and miR-361-5p acted as a central node of multiple circRNAs: circADGRL2, circPROX1 and circPALS2. BDNF, a target mRNA of miR-361-5p, was identified as the highest risk ratio in HBV-HCC patients, suggesting a possible circADGRL2-miR-361-5p-BDNF axis involved in HBV-HCC. The target mRNAs of miRNAs were predicted to be associated with several cancer pathways, such as MAPK and RAS.

conclusionOur data suggest a potential dysregulated circRNA-miRNA-mRNA axis in HBV-integrated hepatocytes, which may indicate a poor prognosis for HBV-HCC patients.

Indexed as

Carcinoma, HepatocellularGene Regulatory NetworksHepatitis B virusLiver NeoplasmsMicroRNAsRNA, CircularRNA, MessengerCell Line, TumorGene Expression Regulation, NeoplasticHumansMicroRNAsRNA, CircularRNA, MessengercircRNAHepatitis-B VirusHepatocellular CarcinomamiRNA

Identifiers

PMID41845440
PMCPMC13107627

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.