Constructing an immune-related prognostic signature for predicting prognosis and immune response in hepatocellular carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39071637", "kind": "science-record", "revision": 3, "content_hash": "sha256:3eb43179717cf00cc8e7551f18bb1d58abc63458d92973bed988a87b3aba142c", "created_at": "2026-11-01T20:29:08Z", "updated_at": "2026-11-01T22:12:19Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Constructing an immune-related prognostic signature for predicting prognosis and immune response in hepatocellular carcinoma.", "doi": "10.1016/j.heliyon.2024.e34012", "pmid": "39071637", "authors": ["Lichao Cao", "Deliang Huang", "Shenrui Zhang", "Zhiwei Li", "Qingxian Cai", "Fang Chen", "Meilan Zhu", "Ying Ba", "Jun Chen", "Hezi Zhang"], "journal": "Heliyon", "year": 2024, "abstract": "Background: Currently, there are few studies on immune-related prognostic analysis of hepatocellular carcinoma (HCC). Our aim was to establish an immune-correlated prognostic model for HCC.\nMethods: Immune-associated cells were obtained from the scRNA-seq dataset (GSE149614) of HCC. Differentially expressed genes between normal and tumor cells from immune-associated cells and the immune-related genes from the ImmPort database were used to identify immune-related differentially expressed genes (IRDEGs). Subsequently, the risk model was established in the TCGA-LIHC cohort (n = 438) from the Cancer Genome Atlas (TCGA) database by using Kaplan-Meier (K-M) survival curve, univariate/multivariate Cox regression analysis. Subsequently, we further analyzed tumor immune microenvironment characteristics, somatic mutation, immune checkpoint and its ligand expression levels between high- and low-risk groups, as well as drug sensitivity prediction. ICGC cohort was set as the validation cohort. TCGA-LIHC cohort and three independent the Gene Expression Omnibus (GEO) datasets (GSE54236, GSE14520, and GSE64041) was used to verify IRDEGs expression, as well as PCR assays using clinical samples.\nResults: The IRDEGs was composed of 4 genes, namely B2M, SPP1, PPIA, and HRG. The 438 HCC patients were divided into high- and low-risk group. The high-risk group was associated with poor prognosis, including higher T stage, advanced pathological stages, less immune cell infiltration, higher TP53 mutation rate, the high expression of CTLA4 and HAVCR2. Besides, high-risk populations benefit from most chemotherapy drugs. Similarly, the performance of the risk model was validated in the ICGC. All four datasets (TCGA-LIHC cohort, GSE54236, GSE14520, and GSE64041) and clinical q-PCR results demonstrated that, compared with normal samples, the expressions of B2M and HRG were lower in tumor samples, and the expression of SPP1 was higher.\nConclusion: In summary, the immune-related prognostic signature had a good predictive performance on prognosis and immunotherapy for HCC patients.", "claims": [{"id": "claim-method", "statement": "Then, the univariate and multivariate Cox regression models and the survival R package were used to obtain optimal IRDEGs with prognostic ability.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39071637", "locator": "sections[5] \"Generation of the immune-related risk model in HCC\" paragraph 2", "quote": "Then, the univariate and multivariate Cox regression models and the survival R package were used to obtain optimal IRDEGs with prognostic ability."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets used in this study were all from public databases.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39071637", "locator": "sections[18] \"Data availability statement\" paragraph 2", "quote": "The datasets used in this study were all from public databases."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The IRDEGs was composed of 4 genes, namely B2M, SPP1, PPIA, and HRG.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39071637", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "The IRDEGs was composed of 4 genes, namely B2M, SPP1, PPIA, and HRG."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The IRDEGs was composed of 4 genes, namely B2M, SPP1, PPIA, and HRG.", "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:39071637"], "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:GSE14520"], "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:GSE14520"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39071637", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1016/j.heliyon.2024.e34012", "sha256": 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