A Novel Five-Gene Signature for Prognosis Prediction in Hepatocellular Carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34336648", "kind": "science-record", "revision": 7, "content_hash": "sha256:5c10a0bae7b9eefad913cc39d7c17cee45796cdb8efe3adfd8ec17bb019e1e10", "created_at": "2026-11-01T15:41:46Z", "updated_at": "2026-11-01T22:04:23Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A Novel Five-Gene Signature for Prognosis Prediction in Hepatocellular Carcinoma.", "doi": "10.3389/fonc.2021.642563", "pmid": "34336648", "authors": ["Lisa Su", "Genhao Zhang", "Xiangdong Kong"], "journal": "Frontiers in oncology", "year": 2021, "abstract": "Hepatocellular carcinoma (HCC) has been a global health issue and attracted wide attention due to its high incidence and poor outcomes. In this study, our purpose was to explore an effective prognostic marker for HCC. Five cohort profile datasets from GEO (GSE25097, GSE36376, GSE62232, GSE76427 and GSE101685) were integrated with TCGA-LIHC and GTEx dataset to identify differentially expressed genes (DEGs) between normal and cancer tissues in HCC patients, then 5 upregulated differentially expressed genes and 32 downregulated DEGs were identified as common DEGs in total. Next, we systematically explored the relationship between the expression of 37 common DEGs in tumor tissues and overall survival (OS) rate of HCC patients in TCGA and constructed a novel prognostic model composed of five genes (AURKA, PZP, RACGAP1, ACOT12 and LCAT). Furthermore, the predicted performance of the five-gene signature was verified in ICGC and another independent clinical samples cohort, and the results demonstrated that the signature performed well in predicting the OS rate of patients with HCC. What is more, the signature was an independent hazard factor for HCC patients when considering other clinical factors in the three cohorts. Finally, we found the signature was significantly associated with HCC immune microenvironment. In conclusion, the prognostic five-gene signature identified in our present study could efficiently classify patients with HCC into subgroups with low and high risk of longer overall survival time and help clinicians make decisions for individualized treatment.", "claims": [{"id": "claim-method", "statement": "The association between prognostic risk score and immune, stromal scores were analyzed by Pearson correlation analysis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34336648", "locator": "sections[8] \"Calculation of Immune Status and Immune Infiltrates Analysis\" paragraph 2", "quote": "The association between prognostic risk score and immune, stromal scores were analyzed by Pearson correlation analysis."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material .", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34336648", "locator": "sections[19] \"Data Availability Statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. 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