Comprehensive Analysis of the Immunosuppressive Function of Regulatory T Cells in Human Hepatocellular Carcinoma Tissues.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38712609", "kind": "science-record", "revision": 2, "content_hash": "sha256:24a15c0d263498ea4f929695f59b69ce6ff4ff6c7e738def3c7d9195bd4bd69a", "created_at": "2026-11-01T19:20:40Z", "updated_at": "2026-11-01T21:33:04Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Comprehensive Analysis of the Immunosuppressive Function of Regulatory T Cells in Human Hepatocellular Carcinoma Tissues.", "doi": "10.1177/10732748241251580", "pmid": "38712609", "authors": ["Junwei Ge", "Junjun Chen", "Qiong Shen", "Xiao Zheng", "Xuemin Chen", "Liangrong Shi", "Lujun Chen", "Bin Xu"], "journal": "Cancer control : journal of the Moffitt Cancer Center", "year": 2024, "abstract": "BACKGROUND: Immune-based therapies are commonly employed to combat hepatocellular carcinoma (HCC). However, the presence of immune-regulating elements, especially regulatory T cells (Tregs), can dramatically impact the treatment efficacy. A deeper examination of the immune-regulation mechanisms linked to these inhibitory factors and their impact on HCC patient outcomes is warranted.\nMETHODS: We employed multicolor fluorescence immunohistochemistry (mIHC) to stain Foxp3, cytokeratin, and nuclei on an HCC tissue microarray (TMA). Leveraging liver cancer transcriptome data from TCGA, we built a prognostic model focused on Treg-associated gene sets and represented it with a nomogram. We then sourced liver cancer single-cell RNA sequencing data (GSE140228) from the GEO database, selectively focusing on Treg subsets, and conducted further analyses, including cell-to-cell communication and pseudo-time trajectory examination.\nRESULTS: Our mIHC results revealed a more substantial presence of Foxp3+Tregs in HCC samples than in adjacent normal tissue samples (P < .001). An increased presence of Foxp3+Tregs in HCC samples correlated with unfavorable patient outcomes (HR = 1.722, 95% CI:1.023-2.899, P = .041). The multi-factorial prognosis model we built from TCGA liver cancer data highlighted Tregs as a standalone risk determinant for predicting outcomes (HR = 3.84, 95% CI:2.52-5.83, P < .001). Re-analyzing the scRNA-seq dataset (GSE140228) showcased distinctive gene expression patterns in Tregs from varying tissues. Interactions between Tregs and other CD4+T cell types were predominantly governed by the CXCL13/CXCR3 signaling pathway. Communication pathways between Tregs and macrophages primarily involved MIF-CD74/CXCR4, LGALS9/CD45, and PTPRC/MRC1. Additionally, macrophages could influence Tregs via HLA-class II and CD4 interactions.\nCONCLUSION: An elevated presence of Tregs in HCC samples correlated with negative patient outcomes. Elucidating the interplay between Tregs and other immune cells in HCC could provide insights into the modulatory role of Tregs within HCC tissues.", "claims": [{"id": "claim-method", "statement": "Utilizing the R packages “Survival,” “rms,” and “survminer,” we applied the Cox proportional hazard model to the characteristic Treg genes in relation to overall survival (OS).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38712609", "locator": "sections[9] \"Construction of Prognostic Risk Model of Treg Cell Characteristic Genes Based on TCGA LIHC Data\" paragraph 2", "quote": "Utilizing the R packages “Survival,” “rms,” and “survminer,” we applied the Cox proportional hazard model to the characteristic Treg genes in relation to overall survival (OS)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All sequencing data in this study were obtained from publicly available articles, and no additional data were generated in the course of this research.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38712609", "locator": "sections[26] \"Data Availability Statement\" paragraph 2", "quote": "All sequencing data in this study were obtained from publicly available articles, and no additional data were generated in the course of this research."}], "state": "complete"}, {"id": "claim-target-result", "statement": "An increased presence of Foxp3+Tregs in HCC samples correlated with unfavorable patient outcomes (HR = 1.722, 95% CI:1.023-2.899, P = .041).", "kind": "quantitative", "target": {"value": 95.0, "unit": "per cent", "tolerance": null, "source": "An increased presence of Foxp3+Tregs in HCC samples correlated with unfavorable patient outcomes (HR = 1.722, 95% CI:1.023-2.899, P = .041)."}, "evidence": [{"asset": "source:pmid:38712609", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "An increased presence of Foxp3+Tregs in HCC samples correlated with unfavorable patient outcomes (HR = 1.722, 95% CI:1.023-2.899, P = .041)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "An increased presence of Foxp3+Tregs in HCC samples correlated with unfavorable patient outcomes (HR = 1.722, 95% CI:1.023-2.899, P = .041).", "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:38712609"], "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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