Identification of oncogenes and tumor-suppressor genes with hepatocellular carcinoma: A comprehensive analysis based on TCGA and GEO datasets.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36685860", "kind": "science-record", "revision": 4, "content_hash": "sha256:0909c614a4e5c1a433ceec7cf8601cfb65ed5ade8438b09438d6024fcd310d90", "created_at": "2026-11-01T19:01:14Z", "updated_at": "2026-11-01T22:51:05Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of oncogenes and tumor-suppressor genes with hepatocellular carcinoma: A comprehensive analysis based on TCGA and GEO datasets.", "doi": "10.3389/fgene.2022.934883", "pmid": "36685860", "authors": ["Yue Zhu", "Yanfei Wang", "Mengyao Hu", "Xiaoting Lu", "Guoping Sun"], "journal": "Frontiers in genetics", "year": 2022, "abstract": "Aim: Existing targeted therapies for hepatocellular carcinoma (HCC) are resistant and have limitations. It is crucial to find new HCC-related target genes. Methods: RNA-sequencing data of HCC were gathered from The Cancer Genome Atlas and Gene Expression Omnibus datasets. Initially, differentially expressed genes between normal and tumor tissues were identified from four Gene Expression Omnibus datasets, GSE36376, GSE102079, GSE54236, and GSE45267. GO terms and KEGG pathway enrichment analyses were performed to explore the potential biological functions of differentially expressed genes. A PPI network was constructed by using the STRING database, and up-regulated and down-regulated hub genes were defined through 12 topological approaches. Subsequently, the correlation bounded by up-regulated genes and down-regulated genes in the diagnosis, prognosis, and clinicopathological features of HCC was analyzed. Beyond a shadow of doubt, the key oncogene PBK and tumor suppressor gene F9 were screened out, and the specific mechanism was investigated through GSEA enrichment analysis and immune correlation analysis. The role of PBK in HCC was further verified by western blot, CCK8, transwell, and tube formation experiments. Results: CDCA5, CDC20, PBK, PRC1, TOP2A, and NCAPG are good indicators of HCC diagnosis and prognosis. The low expressions of F9, AFM, and C8B indicate malignant progression and poor prognosis of HCC. PBK was found to be closely related to VEGF, VEGFR, and PDGFR pathways. Experiments showed that PBK promotes HCC cell proliferation, migration, invasion, and tube formation in HUVEC cells. F9 was negatively correlated with the degree of immune infiltration, and low expression of F9 suggested a poor response to immunotherapy. Conclusion: The role of HCC-related oncogenes and tumor-suppressor genes in diagnosis and prognosis was identified. In addition, we have found that PBK may promote tumor proliferation through angiogenesis and F9 may be a predictor of tumor immunotherapy response.", "claims": [{"id": "claim-method", "statement": "The limma package of R software was used to identify the DEGs in four datasets.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36685860", "locator": "sections[10] \"Identification of differentially expressed genes\" paragraph 2", "quote": "The limma package of R software was used to identify the DEGs in four datasets."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/Supplementary Material; further inquiries can be directed to the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36685860", "locator": "sections[28] \"Data availability statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/Supplementary Material; further inquiries can be directed to the corresponding author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The analysis identified 104 differentially expressed genes, including 23 up-regulated genes and 81 down-regulated genes, in HCC tissue samples.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36685860", "locator": "sections[20] \"Identification of DEGs\" paragraph 2", "quote": "As presented in Figures 1E, F, we made an attempt to identify 104 DEGs, including 23 up-regulated genes and 81 down-regulated genes in the HCC tissue samples."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The analysis identified 104 differentially expressed genes, including 23 up-regulated genes and 81 down-regulated genes, in HCC tissue samples.", "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:36685860"], "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:GSE102079"], "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:GSE102079"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36685860", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fgene.2022.934883", "sha256": 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