DNA hypermethylation of aurora kinase A in hepatitis C virus‑positive hepatocellular carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:31322223", "kind": "science-record", "revision": 8, "content_hash": "sha256:58f7bad64d1c33cb32111f9a88c2666a218efb172ac057fdf0534fbe69404e87", "created_at": "2026-11-01T15:40:47Z", "updated_at": "2026-11-01T22:44:06Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "DNA hypermethylation of aurora kinase A in hepatitis C virus‑positive hepatocellular carcinoma.", "doi": "10.3892/mmr.2019.10487", "pmid": "31322223", "authors": ["Zuohong Ma", "Yefu Liu", "Zhiqiang Hao", "Xiangdong Hua", "Wenxin Li"], "journal": "Molecular medicine reports", "year": 2019, "abstract": "Changes in the methylation levels of tumor suppressor genes or proto‑oncogenes are involved in the pathogenesis of hepatitis C virus (HCV) infection‑induced hepatocellular carcinoma (HCC). The aim of the present study was to identify novel aberrantly methylated differentially expressed genes by integrating mRNA expression profile (GSE19665 and GSE62232) and methylation profile (GSE60753) microarrays downloaded from the Gene Expression Omnibus database. Functional enrichment analysis of screened genes was performed using the DAVID software and BinGO database. Protein‑protein interaction (PPI) networks were constructed using the STRING database, followed by module analysis with MCODE software. The transcriptional and translational expression levels of crucial genes were confirmed using The Cancer Genome Atlas (TCGA) datasets and Human Protein Atlas database (HPA). A total of 122 downregulated/hypermethylated genes and 63 upregulated/hypomethylated genes were identified. These genes were enriched in the Gene Ontology biological processes terms of 'inflammatory response' [Fos proto‑oncogene, AP‑1 transcription factor subunit (FOS)] and 'cell cycle process' [aurora kinase A (AURKA), cyclin dependent kinase inhibitor 3 (CDKN3) and ubiquitin conjugating enzyme E2 C (UBE2C)]. PPI network and module analysis indicated that human oncogenes FOS, AURKA, CDKN3 and UBE2C may be hub genes. mRNA, protein expression and methylation levels of AURKA and FOS were validated by TCGA and HPA data. In conclusion, aberrantly methylated AURKA and FOS may be potential therapeutic targets for HCV‑positive HCC.", "claims": [{"id": "claim-method", "statement": "Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) between HCV-positive HCC and control samples were identified using the Linear Models for Microarray Data method (version 3.34.0; http://bioconductor.org/packages/release/bioc/html/limma.html) (15) in the Bioconductor R package.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:31322223", "locator": "sections[6] \"Differential gene expression and methylation analysis\" paragraph 2", "quote": "Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) between HCV-positive HCC and control samples were identified using the Linear Models for Microarray Data method (version 3.34.0; http://bioconductor.org/packages/release/bioc/html/limma.html) (15) in the Bioconductor R package."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The sequencing datasets GSE19665 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE19665), GSE62232 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE62232) and GSE60753 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60753) were downloaded from the GEO database in NCBI. The mRNA and microRNA sequencing data were obtained from The Cancer Genome Atlas (https://tcga-data.nci.nih.gov).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:31322223", "locator": "sections[19] \"Availability of data and materials\" paragraph 2", "quote": "The sequencing datasets GSE19665 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE19665), GSE62232 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE62232) and GSE60753 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60753) were downloaded from the GEO database in NCBI. The mRNA and microRNA sequencing data were obtained from The Cancer Genome Atlas (https://tcga-data.nci.nih.gov)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:31322223"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE19665"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE19665"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:31322223", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3892/mmr.2019.10487", "sha256": "sha256:22f96d179356c107d1bd6e23efdac103a6a06cb22784edf12c648ce4cb695537", "bytes": 23231, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3892/mmr.2019.10487", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC6691273", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE19665", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE19665", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE19665", "version": null, "note": "The sequencing datasets GSE19665 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE19665), GSE62232 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE62232) and GSE60753 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60753) were downloaded from the GEO database in NCBI. 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