Identification of potential miRNA-mRNA regulatory network contributing to pathogenesis of HBV-related HCC.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:30602391", "kind": "science-record", "revision": 7, "content_hash": "sha256:c0af26a573f0a8b3109b6691b4b2d24414422206d0927ded2ac3edcefa4f4cbb", "created_at": "2026-11-01T15:40:40Z", "updated_at": "2026-11-01T22:00:13Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of potential miRNA-mRNA regulatory network contributing to pathogenesis of HBV-related HCC.", "doi": "10.1186/s12967-018-1761-7", "pmid": "30602391", "authors": ["Weiyang Lou", "Jingxing Liu", "Bisha Ding", "Danni Chen", "Liang Xu", "Jun Ding", "Donghai Jiang", "Lin Zhou", "Shusen Zheng", "Weimin Fan"], "journal": "Journal of translational medicine", "year": 2019, "abstract": "BACKGROUND: Hepatitis B virus (HBV) is one of the major risk factors of hepatocellular carcinoma (HCC). Increasing evidence indicates that microRNA (miRNA)-mRNA axis is involved in HCC. However, a comprehensive miRNA-mRNA regulatory network in HBV-related HCC is still absent. This study aims to identify potential miRNA-mRNA regulatory pathways contributing to pathogenesis of HBV-related HCC.\nMETHODS: Microarray GSE69580 was downloaded from Gene Expression Omnibus (GEO) database. GEO2R and 'R-limma' were used to conduct differential expression analysis. The common miRNAs appeared in the two analytic sets were screened as potential differentially expressed miRNAs (DE-miRNAs). The prognostic roles of screened DE-miRNAs in HCC were further evaluated using Kaplan-Meier plotter database. Target genes of DE-miRNAs were predicted by miRNet. Then, protein-protein interaction (PPI) networks were established for these targets via the STRING database, after which hub genes in the networks were identified by Cytoscape. Functional annotation and pathway enrichment analyses for the target genes were performed through DAVID database. Three enriched pathways related to HBV-related HCC were selected for further analysis and potential target genes commonly appeared in all three pathways were screened. Cytoscape was employed to construct miRNA-hub gene network. The expression and correlation of potential miRNAs and targets were further detected in clinical HBV-related HCC samples by qRT-PCR.\nRESULTS: 7 upregulated and 9 downregulated DE-miRNAs were accessed. 5 of 7 upregulated DE-miRNAs and 5 of 7 downregulated DE-miRNAs indicated significant prognostic roles in HCC. 2312 and 1175 target genes were predicted for the upregulated and downregulated DE-miRNAs, respectively. TP53 was identified as the hub gene in the PPI networks. Pathway enrichment analysis suggested that these predicted targets were linked to hepatitis B, pathways in cancer, microRNAs in cancer and viral carcinogenesis. Further analysis of these pathways screened 20 and 16 target genes for upregulated and downregulated DE-miRNAs, respectively. By detecting the expression of 36 target genes, six candidate target genes were identified. Finally, a potential miRNA-mRNA regulatory network was established based on the results of qRT-PCR and expression correlation analysis.\nCONCLUSIONS: In the study, potential miRNA-mRNA regulatory pathways were identified, exploring the underlying pathogenesis and effective therapy strategy of HBV-related HCC.", "claims": [{"id": "claim-method", "statement": "The differences between two groups were estimated by a two-tailed Student’s t-test. Spearman correlation coefficients were calculated to evaluate the correlations.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:30602391", "locator": "sections[15] \"Statistical analysis\" paragraph 2", "quote": "The differences between two groups were estimated by a two-tailed Student’s t-test. 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Besides, please contact author for data and materials requests.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The microarray data were deposited in the Gene Expression Omnibus (GEO) database (Accession number: GSE69580). 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["hsa-miR-151-3p", "3.38", "5.38", "0.14", "5.57E−04"]], "row_count": 8, "column_count": 5, "numeric_cells": 35, "header_rows": 1, "locator": "section[17]/table-wrap[1]#Tab1"}}, {"id": "asset:table:pmid:30602391:2", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:ae8cab3578fb81993d2e03b22dbdc51cbec796cb45014ebf7ac77b6d3c5feb25", "bytes": 552, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[18]/table-wrap[1]#Tab2", "version": null, "note": "The target number of the upregulated and downregulated DE-miRNAs", "structure": {"pmcid": "PMC6317219", "section_index": 18, "section_title": "Target prediction and analysis of candidate DE-miRNAs", "row_count": 7, "column_count": 4}, "table": {"label": "Table 2", "caption": "The target number of the upregulated and downregulated DE-miRNAs", "rows": [["Upregulated DE-miRNA", "Number", "Downregulated DE-miRNA", "Number"], ["hsa-miR-93-5p", "1220", "hsa-let-7c-5p", "516"], ["hsa-miR-106b-5p", "1091", "hsa-miR-125b-5p", "432"], ["hsa-miR-21-5p", "612", "hsa-miR-99a-5p", "133"], ["hsa-miR-25-3p", "518", "hsa-miR-139-5p", "105"], ["hsa-miR-501-3p", "69", "hsa-miR-486-5p", "67"], ["Total", "2312", "Total", "1175"]], "row_count": 7, "column_count": 4, "numeric_cells": 22, "header_rows": 1, "locator": "section[18]/table-wrap[1]#Tab2"}}, {"id": "asset:table:pmid:30602391:3", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:68b67019fb9ff170c25de4b67fc5d8ba2a528713b523a9e95b9358c5954fd275", "bytes": 583, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[18]/table-wrap[2]#Tab3", "version": null, "note": "Hub genes identified in the PPI networks", "structure": {"pmcid": "PMC6317219", "section_index": 18, "section_title": "Target prediction and analysis of candidate 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METHODS: Microarray GSE69580 was downloaded from Gene Expression", "Oncomine database, which is an online cancer microarray database. P-value < 1E−4, fold change > 2 an"], "order_basis": "paper_text_order:466", "id": "assay:1"}, {"role": "data_generation", "definition_id": "cell_culture", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.85, "evidence": ["e Academy of Sciences (Shanghai, China). 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