Seven Hub Genes Predict the Prognosis of Hepatocellular Carcinoma and the Corresponding Competitive Endogenous RNA Network.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36276270", "kind": "science-record", "revision": 4, "content_hash": "sha256:34f5f582afbeb87c1075fcfb98e3251f062481b6023c05f5474f92db43786849", "created_at": "2026-11-01T18:15:40Z", "updated_at": "2026-11-01T22:50:26Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Seven Hub Genes Predict the Prognosis of Hepatocellular Carcinoma and the Corresponding Competitive Endogenous RNA Network.", "doi": "10.1155/2022/3379330", "pmid": "36276270", "authors": ["Xueqiong Han", "Jianxun Lu", "Chun Chen", "Yongran Deng", "Mingmei Pan", "Qigeng Li", "Huayun Wu", "Zhenlong Li", "Bingqiang Ni"], "journal": "Journal of oncology", "year": 2022, "abstract": "Purpose: This study was aimed at identifying hub genes and ceRNA regulatory networks linked to prognosis in hepatocellular carcinoma (HCC) and to identify possible therapeutic targets.\nMethods: Differential expression analyses were performed to detect the differentially expressed genes (DEGs) in the four datasets (GSE76427, GSE6764, GSE62232, and TCGA). The intersected DEmRNAs were identified to explore biological significance by enrichment analysis. We built a competitive endogenous RNA (ceRNA) network of lncRNA-miRNA-mRNA. The mRNAs of the ceRNA network were used to perform Cox and Kaplan-Meier analyses to obtain prognosis-related genes, followed by the selection of genes with an area under the curve >0.8 to generate the random survival forest model and obtain feature genes. Furthermore, the feature genes were subjected to least absolute shrinkage and selection operator (LASSO) and univariate Cox analyses were used to identify the hub genes. Finally, the infiltration status of immune cells in the HCC samples was determined.\nResults: A total of 1923 intersected DEmRNAs were identified in four datasets and involved in cell cycle and carbon metabolism. ceRNA network was created using 10 lncRNAs, 67 miRNAs, and 1,923 mRNAs. LASSO regression model was performed to identify seven hub genes, SOCS2, MYOM2, FTCD, ADAMTSL2, TMEM106C, LARS, and KPNA2. Among them, TMEM106C, LARS, and KPNA2 had a poor prognosis. KPNA2 was considered a key gene base on LASSO and Cox analyses and involved in the ceRNA network. T helper 2 cells and T helper cells showed a higher degree of infiltration in HCC.\nConclusion: The findings revealed seven hub genes implicated in HCC prognosis and immune infiltration. A corresponding ceRNA network may help reveal their potential regulatory mechanism.", "claims": [{"id": "claim-method", "statement": "Furthermore, the feature genes were subjected to least absolute shrinkage and selection operator (LASSO) and univariate Cox analyses were used to identify the hub genes.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36276270", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "Furthermore, the feature genes were subjected to least absolute shrinkage and selection operator (LASSO) and univariate Cox analyses were used to identify the hub genes."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets (GSE76427, GSE6764, GSE62232) supporting the conclusions of this article are available in the Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo) and the Cancer Genome Atlas https://portal.gdc.cancer.gov/) database.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36276270", "locator": "sections[23] \"Data Availability\" paragraph 2", "quote": "The datasets (GSE76427, GSE6764, GSE62232) supporting the conclusions of this article are available in the Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo) and the Cancer Genome Atlas https://portal.gdc.cancer.gov/) database."}], "state": "complete"}, {"id": "claim-target-result", "statement": "LASSO regression model was performed to identify seven hub genes, SOCS2, MYOM2, FTCD, ADAMTSL2, TMEM106C, LARS, and KPNA2.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36276270", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "LASSO regression model was performed to identify seven hub genes, SOCS2, MYOM2, FTCD, ADAMTSL2, TMEM106C, LARS, and KPNA2."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "LASSO regression model was performed to identify seven hub genes, SOCS2, MYOM2, FTCD, ADAMTSL2, TMEM106C, LARS, and KPNA2.", "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:36276270"], "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:GSE62232"], "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:GSE62232"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36276270", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2022/3379330", "sha256": 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