Identification of a Liver Progenitor Cell-Related Genes Signature Predicting Overall Survival for Hepatocellular Carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34866477", "kind": "science-record", "revision": 5, "content_hash": "sha256:bf613e6cf8525053c6be128dd57ee83950b4c05771bec2bf772d8f7e736bd064", "created_at": "2026-11-01T17:36:34Z", "updated_at": "2026-11-01T22:47:59Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of a Liver Progenitor Cell-Related Genes Signature Predicting Overall Survival for Hepatocellular Carcinoma.", "doi": "10.1177/15330338211041425", "pmid": "34866477", "authors": ["Xiaoyong Li", "Jiaqong Lin", "Yuguo Pan", "Peng Cui", "Jintang Xia"], "journal": "Technology in cancer research & treatment", "year": 2021, "abstract": "Background: Liver progenitor cells (LPCs) play significant roles in the development and progression of hepatocellular carcinoma (HCC). However, no studies on the value of LPC-related genes for evaluating HCC prognosis exist. We developed a gene signature of LPC-related genes for prognostication in HCC. Methods: To identify LPC-related genes, we analyzed mRNA expression arrays from a dataset (GSE57812 & GSE 37071) containing LPCs, mature hepatocytes, and embryonic stem cell samples. HCC RNA-Seq data from The Cancer Genome Atlas (TCGA) were used to explore the differentially expressed genes (DEGs) related to prognosis through DEG analysis and univariate Cox regression analysis. Lasso and multivariate Cox regression analyses were performed to construct the LPC-related gene prognostic model in the TCGA training dataset. This model was validated in the TCGA testing set and an external dataset (International Cancer Genome Consortium [ICGC] dataset). Finally, we investigated the relationship between this prognostic model with tumor-node-metastasis stage, tumor grade, and vascular invasion of HCC. Results: Overall, 1770 genes were identified as LPC-related genes, of which 92 genes were identified as DEGs in HCC tissues compared with normal tissues. Furthermore, we randomly assigned patients from the TCGA dataset to the training and testing cohorts. Twenty-six DEGs correlated with overall survival (OS) in the univariate Cox regression analysis. Lasso and multivariate Cox regression analyses were performed in the TCGA training set, and a 3-gene signature was constructed to stratify patients into 2 risk groups: high-risk and low-risk. Patients in the high-risk group had significantly lower OS than those in the low-risk group. Receiver operating characteristic curve analysis confirmed the signature's predictive capacity. Moreover, the risk score was confirmed to be an independent predictor for patients with HCC. Conclusion: We demonstrated that the LPC-related gene signature can be used for prognostication in HCC. Thus, targeting LPCs may serve as a therapeutic alternative for HCC.", "claims": [{"id": "claim-method", "statement": "Lasso and multivariate Cox regression analyses were performed to construct the LPC-related gene prognostic model in the TCGA training dataset.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34866477", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Lasso and multivariate Cox regression analyses were performed to construct the LPC-related gene prognostic model in the TCGA training dataset."}], "state": "complete"}, {"id": "claim-data-access", "statement": "GSE57812 contains 9 independent samples of second trimester LPCs, 3 independent mature hepatocyte samples, and 6 human embryonic stem cell (ESC) samples while GSE37031 contains 7 normal liver samples.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34866477", "locator": "sections[3] \"Data Collection\" paragraph 2", "quote": "GSE57812 contains 9 independent samples of second trimester LPCs, 3 independent mature hepatocyte samples, and 6 human embryonic stem cell (ESC) samples while GSE37031 contains 7 normal liver samples."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A 3-gene LPC-related prognostic model comprising EZH2, PRKAA2, and SPP1 was constructed using TCGA data and used to stratify HCC patients by prognostic risk.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:34866477", "locator": "sections[9] \"Construction of an LPC-Related Gene Prognostic Model in TCGA Dataset\" paragraph 2", "quote": "Finally, 3 genes, including enhancer of zeste 2 polycomb repressive complex 2 subunit (EZH2), protein kinase AMP-activated catalytic subunit alpha 2 (PRKAA2), and secreted phosphoprotein 1 (SPP1), were identified in the prognostic model."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A 3-gene LPC-related prognostic model comprising EZH2, PRKAA2, and SPP1 was constructed using TCGA data and used to stratify HCC patients by prognostic risk.", "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:34866477"], "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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