Identification of a novel signature based on macrophage-related marker genes to predict prognosis and immunotherapeutic effects in hepatocellular carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37305578", "kind": "science-record", "revision": 3, "content_hash": "sha256:1da9cb9287cddb0055564fdb7260b931b8656d46ecfd4f14bac0be0d9e2f620b", "created_at": "2026-11-01T19:02:02Z", "updated_at": "2026-11-01T22:09:41Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of a novel signature based on macrophage-related marker genes to predict prognosis and immunotherapeutic effects in hepatocellular carcinoma.", "doi": "10.3389/fonc.2023.1176572", "pmid": "37305578", "authors": ["Yuanshuai Su", "Chen Xue", "Xinyu Gu", "Wankun Wang", "Yu Sun", "Renfang Zhang", "Lanjuan Li"], "journal": "Frontiers in oncology", "year": 2023, "abstract": "Background: Tumor-related macrophages (TAMs) have emerged as an essential part of the immune regulatory network in hepatocellular carcinoma (HCC). Constructing a TAM-related signature is significant for evaluating prognosis and immunotherapeutic response of HCC patients.\nMethods: Informative single-cell RNA sequencing (scRNA-seq) dataset was obtained from the Gene Expression Omnibus (GEO) database, and diverse cell subpopulations were identified by clustering dimension reduction. Moreover, we determined molecular subtypes with the best clustering efficacy by calculating the cumulative distribution function (CDF). The ESTIMATE method, CIBERSORT (cell-type identification by estimating relative subsets of RNA transcripts) algorithm and publicly available tumor immune dysfunction and exclusion (TIDE) tools were used to characterize the immune landscape and tumor immune escape status. A TAM-related gene risk model was constructed through Cox regression and verified in multiple datasets and dimensions. We also performed functional enrichment analysis to detect potential signaling pathways related to TAM marker genes.\nResults: In total, 10 subpopulations and 165 TAM-related marker genes were obtained from the scRNA-seq dataset (GSE149614). After clustering 3 molecular subtypes based on TAM-related marker genes, we found significantly different prognostic survival and immune signatures among the three subtypes. Subsequently, a 9-gene predictive signature (TPP1, FTL, CXCL8, CD68, ATP6V1F, CSTB, YBX1, LGALS3, and APLP2) was identified as an independent prognostic factor for HCC patients. Those patients with high RiskScore had a lower survival rate and benefited less from immunotherapy than those with low RiskScore. Moreover, more samples of the Cluster C subtype were enriched in the high-risk group, with higher tumor immune escape incidence.\nConclusions: We constructed a TAM-related signature with excellent efficacy for predicting prognostic survival and immunotherapeutic responses in HCC patients.", "claims": [{"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37305578", "locator": "sections[25] \"Data availability statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A 9-gene TAM-related signature was identified as an independent prognostic factor for HCC, with high-risk patients having lower survival and benefiting less from immunotherapy.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37305578", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Subsequently, a 9-gene predictive signature (TPP1, FTL, CXCL8, CD68, ATP6V1F, CSTB, YBX1, LGALS3, and APLP2) was identified as an independent prognostic factor for HCC patients."}, {"asset": "source:pmid:37305578", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Those patients with high RiskScore had a lower survival rate and benefited less from immunotherapy than those with low RiskScore."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "A 9-gene TAM-related signature was identified as an independent prognostic factor for HCC, with high-risk patients having lower survival and benefiting less from immunotherapy.", "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:37305578"], "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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Methods: Informative single-cell RNA sequencing (scRNA-seq) dataset was obtained from the Ge", "ods: Informative single-cell RNA sequencing (scRNA-seq) dataset was obtained from the Gene Expressi", "iltration and cluster dimension reduction of scRNA-seq data. (A) Bar chart of cell count statistics", "-related marker genes were obtained from the scRNA-seq dataset (GSE149614). After clustering 3 mole"], "order_basis": "paper_text_order:405", "id": "assay:1"}, {"role": "data_generation", "definition_id": "rna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["C patients. 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