A novel seven-gene signature as Prognostic Biomarker in Hepatocellular Carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32913470", "kind": "science-record", "revision": 8, "content_hash": "sha256:cb4621994db9654101f93048a7b7a4c23a497e84ef9fb96a4fd55c4623e19e19", "created_at": "2026-11-01T15:41:10Z", "updated_at": "2026-11-01T22:02:10Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A novel seven-gene signature as Prognostic Biomarker in Hepatocellular Carcinoma.", "doi": "10.7150/jca.44573", "pmid": "32913470", "authors": ["Hui Xie", "Shouping Liu", "Ziying Zhang", "Peng Chen", "Yongguang Tao"], "journal": "Journal of Cancer", "year": 2020, "abstract": "PURPOSE: Our study is designed to develop and certify a promising prognostic signature for hepatocellular carcinoma (HCC). Materials and methods: We retrospectively analyzed mRNA expression profiles and clinicopathological data fetched from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. We formulated a prognostic seven-gene signature composed of differentially expressed mRNAs (DEmRNAs) between HCC and nonneoplastic tissues through univariate Cox regression analysis. The receiver operating characteristic (ROC) curve, survival analysis and multivariate Cox regression analysis as well as nomograms were utilized to assess the prognostic performance of the seven-gene signature. Results: The risk score based on a seven-gene signature categorized HCC subjects into a high- and low-risk group. There was significantly discrepant overall survival (OS) between patients in both groups and the corresponding ROC curve revealed a satisfactory predictive performance in HCC survival in both TCGA and GSE76427 cohort. Multivariate Cox regression analysis demonstrated that a seven-gene signature was an independently prognostic factor for HCC. Nomograms combining this prognostic signature with significant clinical characteristics conferred a crucial reference to predict the 1-,3- and 5 years OS. Conclusions: Our study defined a promising seven-gene signature and nomogram model to forecast the OS of HCC patients, which is instrumental in clinical decision and personalized therapy.", "claims": [{"id": "claim-method", "statement": "To evaluate the survival differences between low- and high-risk HCC patients, we performed survival analysis through Kaplan-Meier curve combined with the log-rank test. The original mRNA expression information was acquired from TCGA and GEO database, respectively.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32913470", "locator": "sections[6] \"Statistical analysis\" paragraph 2", "quote": "To evaluate the survival differences between low- and high-risk HCC patients, we performed survival analysis through Kaplan-Meier curve combined with the log-rank test."}, {"asset": "source:pmid:32913470", "locator": "sections[3] \"Data extraction and manipulation\" paragraph 2", "quote": "The original mRNA expression information was acquired from TCGA and GEO database, respectively."}], "state": "complete"}, {"id": "claim-data-access", "statement": "We retrospectively analyzed mRNA expression profiles and clinicopathological data fetched from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32913470", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "We retrospectively analyzed mRNA expression profiles and clinicopathological data fetched from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets."}], "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:32913470"], "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. 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