A programmed cell death-related gene signature to predict prognosis and therapeutic responses in liver hepatocellular carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38466483", "kind": "science-record", "revision": 2, "content_hash": "sha256:342ed295600204d04edbe1196af408fbddf58cf9cd7c867b234e7a1b4c367432", "created_at": "2026-11-01T19:20:24Z", "updated_at": "2026-11-01T21:32:40Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A programmed cell death-related gene signature to predict prognosis and therapeutic responses in liver hepatocellular carcinoma.", "doi": "10.1007/s12672-024-00924-2", "pmid": "38466483", "authors": ["Xinyu Gu", "Jie Pan", "Yanle Li", "Liushun Feng"], "journal": "Discover oncology", "year": 2024, "abstract": "BACKGROUND: Programmed cell death (PCD) functions critically in cancers and PCD-related genes are associated with tumor microenvironment (TME), prognosis and therapeutic responses of cancer patients. This study stratified hepatocellular carcinoma (HCC) patients and develop a prognostic model for predicting prognosis and therapeutic responses.\nMETHODS: Consensus clustering analysis was performed to subtype HCC patients in The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) among the subtypes were filtered and subjected to the least absolute shrinkage and selection operator (LASSO) regression analysis and univariate Cox regression analysis to filter prognostic genes. A PCD-related prognostic gene signature in TCGA was constructed and validated in ICGC-LIRI-JP and GSE14520 datasets. TME was analyzed using CIBERSORT, MCP-counter, TIMER and EPIC algorithms. Drug sensitivity was predicted by oncoPredict package. Spearman analysis was used to detect correlation.\nRESULTS: Four molecular subtypes were categorized based on PCD-related genes. Subtype C1 showed the poorest prognosis, the most infiltration of Fibroblasts, dentritic cell (DC) and cancer-associated fibroblasts (CAFs), and the highest TIDE score. C4 had a better prognosis survival outcome, and lowest immune cell infiltration. The survival outcomes of C2 and C3 were intermediate. Next, a total of 69 co-DEGs were screened among the four subtypes and subsequently we identified five prognostic genes (MCM2, SPP1, S100A9, MSC and EPO) for developing the prognostic model. High-risk patients not only had unfavorable prognosis, higher clinical stage and grade, and more inflammatory pathway enrichment, but also possessed higher possibility of immune escape and were more sensitive to Cisplatin and 5. Fluorouracil. The robustness of the prognostic model was validated in external datasets.\nCONCLUSION: This study provides new insights into clinical subtyping and the PCD-related prognostic signature may serve as a useful tool to predict prognosis and guide treatments for patients with HCC.", "claims": [{"id": "claim-method", "statement": "“ConsensusClusterPlus” R package [20] was used for consensus clustering analysis on 474 PCD-related genes, processing with 500 bootstraps containing 80% TCGA-LIHC samples with pam algorithm and euclidean distance.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38466483", "locator": "sections[5] \"Identification of molecular subtypes based on PCD-related genes\" paragraph 2", "quote": "“ConsensusClusterPlus” R package [20] was used for consensus clustering analysis on 474 PCD-related genes, processing with 500 bootstraps containing 80% TCGA-LIHC samples with pam algorithm and euclidean distance."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets generated and/or analyzed during the current study are available in the [GSE14520] repository, [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE14520].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38466483", "locator": "sections[35] \"notes\" paragraph 1", "quote": "The datasets generated and/or analyzed during the current study are available in the [GSE14520] repository, [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE14520]."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Four molecular subtypes were categorized based on PCD-related genes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38466483", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Four molecular subtypes were categorized based on PCD-related genes."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Four molecular subtypes were categorized based on PCD-related genes.", "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:38466483"], "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:38466483", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1007/s12672-024-00924-2", "sha256": 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