A three-gene signature reveals changes in the tumor immune microenvironment in the progression from NAFLD to HCC.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38102321", "kind": "science-record", "revision": 3, "content_hash": "sha256:3d41d2dd734d954bea11216af2796f671a0960b9f9bbcd32ce8af7136d930fc2", "created_at": "2026-11-01T19:03:02Z", "updated_at": "2026-11-01T22:10:53Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A three-gene signature reveals changes in the tumor immune microenvironment in the progression from NAFLD to HCC.", "doi": "10.1038/s41598-023-49358-w", "pmid": "38102321", "authors": ["Lijuan Liu", "Haonan Tang", "Kui Wang", "Jiaying Liu", "Ningbin Luo", "Guanqiao Jin"], "journal": "Scientific reports", "year": 2023, "abstract": "Hepatocellular carcinoma (HCC) is one of the most dangerous malignant tumors. The incidence rates of obesity related NAFLD and NASH are increasing year by year, and they are the main risk factors for HCC at present. Finding the mechanism of malignant transformation of NAFLD and NASH is helpful for early prevention and diagnosis. In this study, we performed differential analysis using NAFLD data, NASH data, and HCC data to identify crossover differential genes. Then, using the clinical data of TCGA, a prognostic risk prediction model of three genes (TEAD4, SOCS2, CIT) was constructed, and survival analysis and receiver operating characteristic curves were drawn. The prognostic model was validated using ICGC, GSE116174 and GSE54236 datasets. In addition, we assessed immune status and function in high- and low-risk populations using a prognostic model. Moreover, we assessed the expression of CIT in clinical samples and HCC cell lines and validated its role in HCC development. Our study elucidates the important role of the tumor immune microenvironment in the development of NAFLD/NASH to HCC, deepens the understanding of the pathogenesis of NAFLD/NASH development to HCC, and is helpful for clinical management and decision-making.", "claims": [{"id": "claim-method", "statement": "The prognostic model (risk score = 0.05957332 * TEAD4 expression − 0.233885624 * SOCS2 expression + 0.38039386 * CIT expression) was constructed based on univariate and multivariate Cox regression analysis of TCGA.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38102321", "locator": "sections[4] \"Genes associated with prognosis and differentially expressed genes\" paragraph 2", "quote": "The prognostic model (risk score = 0.05957332 * TEAD4 expression − 0.233885624 * SOCS2 expression + 0.38039386 * CIT expression) was constructed based on univariate and multivariate Cox regression analysis of TCGA."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data that support the findings of this study are available from the corresponding author upon reasonable request. TCGA-LIHC data are publicly available and extracted from https://portal.gdc.cancer.gov/projects/TCGA-LIHC.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38102321", "locator": "sections[30] \"notes\" paragraph 1", "quote": "The data that support the findings of this study are available from the corresponding author upon reasonable request. TCGA-LIHC data are publicly available and extracted from https://portal.gdc.cancer.gov/projects/TCGA-LIHC."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A three-gene prognostic model comprising TEAD4, SOCS2, and CIT discriminated prognosis in HCC and was externally validated in ICGC, GSE116174, and GSE54236, with reported 1-, 2-, and 3-year ROC AUC values ranging from 0.567 to 0.798 in the external datasets.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38102321", "locator": "sections[15] \"Prognostic model verification\" paragraph 2", "quote": "In the ICGC dataset, the areas under the ROC curve for 1, 2, and 3 years are 0.656, 0.656, and 0.659, respectively; in the GSE116174 dataset, they are 0.604, 0.591, and 0.567; in the GSE54236 dataset, they are 0.791, 0.670, and 0.798, respectively (Fig. 3M–O)."}, {"asset": "source:pmid:38102321", "locator": "sections[15] \"Prognostic model verification\" paragraph 2", "quote": "These data suggest that our model has excellent prognostic value for HCC patients."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A three-gene prognostic model comprising TEAD4, SOCS2, and CIT discriminated prognosis in HCC and was externally validated in ICGC, GSE116174, and GSE54236, with reported 1-, 2-, and 3-year ROC AUC values ranging from 0.567 to 0.798 in the external datasets.", "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:38102321"], "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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