Identification of key genes and pathways in hepatocellular carcinoma: A preliminary bioinformatics analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:30702595", "kind": "science-record", "revision": 6, "content_hash": "sha256:add67c807fbb6cbb579a5067a04bb82bd9dfbc3ab721d7b1b2ab511579401179", "created_at": "2026-11-01T15:40:41Z", "updated_at": "2026-11-01T22:00:19Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of key genes and pathways in hepatocellular carcinoma: A preliminary bioinformatics analysis.", "doi": "10.1097/MD.0000000000014287", "pmid": "30702595", "authors": ["Min Wu", "Zhaobo Liu", "Aiying Zhang", "Ning Li"], "journal": "Medicine", "year": 2019, "abstract": "BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most prevalent cancers worldwide. However, the precise mechanisms of the development and progression of HCC remain unclear. The present study attempted to identify and functionally analyze the differentially expressed genes between HCC and cirrhotic tissues by using comprehensive bioinformatics analyses.\nMETHODS: The GSE63898 gene expression profile was downloaded from the Gene Expression Omnibus (GEO) and analyzed using the online tool GEO2R to identify differentially expressed genes (DEGs). Gene ontology (GO) functional analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the DEGs were performed in DAVID. The STRING database was used to evaluate the interactions of DEGs and to construct a protein-protein interaction (PPI) network using Cytoscape software. Hub genes were selected using the cytoHubba plugin and were validated with the cBioPortal database.\nRESULTS: A total of 301 DEGs were identified between HCC and cirrhotic tissues. The GO analysis results showed that these DEGs were significantly enriched in certain biological processes including negative regulation of growth and cell chemotaxis. Several significant pathways, including the p53 signaling pathway, were identified as being closely associated with these DEGs. The top 12 hub genes were screened and included TTK, NCAPG, TOP2A, CCNB1, CDK1, PRC1, RRM2, UBE2C, ZWINT, CDKN3, AURKA, and RACGAP1. The cBioPortal analysis found that alterations in hub genes could result in significantly reduced disease-free survival in HCC.\nCONCLUSION: The present study identified a series of key genes and pathways that may be involved in the tumorigenicity and progression of HCC, providing a new understanding of the underlying molecular mechanisms of carcinogenesis in HCC.", "claims": [{"id": "claim-method", "statement": "The P values were adjusted to correct for the occurrence of false positive results by using the Benjamini and Hochberg False Discovery Rate method.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:30702595", "locator": "sections[4] \"Identification of differentially expressed genes\" paragraph 2", "quote": "The P values were adjusted to correct for the occurrence of false positive results by using the Benjamini and Hochberg False Discovery Rate method."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The GSE63898 dataset was submitted by Augusto et al and was designed to analyze the genome-wide expression in 228 primary HCC and 168 non-tumor cirrhotic samples from patients treated with surgical resection.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:30702595", "locator": "sections[3] \"Microarray data from HCC and cirrhotic tissues\" paragraph 2", "quote": "The GSE63898 dataset was submitted by Augusto et al and was designed to analyze the genome-wide expression in 228 primary HCC and 168 non-tumor cirrhotic samples from patients treated with surgical resection."}], "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:30702595"], "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:GSE63898"], "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:GSE63898"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:30702595", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1097/MD.0000000000014287", "sha256": 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