T-cell exhaustion signatures characterize the immune landscape and predict HCC prognosis via integrating single-cell RNA-seq and bulk RNA-sequencing.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37006257", "kind": "science-record", "revision": 2, "content_hash": "sha256:25be01a96968565cb04f24c97c29d389657bca98ed6204507cf4177330429ed6", "created_at": "2026-11-01T19:01:39Z", "updated_at": "2026-11-01T21:30:29Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "T-cell exhaustion signatures characterize the immune landscape and predict HCC prognosis via integrating single-cell RNA-seq and bulk RNA-sequencing.", "doi": "10.3389/fimmu.2023.1137025", "pmid": "37006257", "authors": ["Hao Chi", "Songyun Zhao", "Jinyan Yang", "Xinrui Gao", "Gaoge Peng", "Jinhao Zhang", "Xixi Xie", "Guobin Song", "Ke Xu", "Zhijia Xia", "Shi Chen", "Jinqiu Zhao"], "journal": "Frontiers in immunology", "year": 2023, "abstract": "Background: Hepatocellular carcinoma (HCC), the third most prevalent cause of cancer-related death, is a frequent primary liver cancer with a high rate of morbidity and mortality. T-cell depletion (TEX) is a progressive decline in T-cell function due to continuous stimulation of the TCR in the presence of sustained antigen exposure. Numerous studies have shown that TEX plays an essential role in the antitumor immune process and is significantly associated with patient prognosis. Hence, it is important to gain insight into the potential role of T cell depletion in the tumor microenvironment. The purpose of this study was to develop a trustworthy TEX-based signature using single-cell RNA-seq (scRNA-seq) and high-throughput RNA sequencing, opening up new avenues for evaluating the prognosis and immunotherapeutic response of HCC patients.\nMethods: The International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) databases were used to download RNA-seq information for HCC patients. The 10x scRNA-seq. data of HCC were downloaded from GSE166635, and UMAP was used for clustering descending, and subgroup identification. TEX-related genes were identified by gene set variance analysis (GSVA) and weighted gene correlation network analysis (WGCNA). Afterward, we established a prognostic TEX signature using LASSO-Cox analysis. External validation was performed in the ICGC cohort. Immunotherapy response was assessed by the IMvigor210, GSE78220, GSE79671, and GSE91061cohorts. In addition, differences in mutational landscape and chemotherapy sensitivity between different risk groups were investigated. Finally, the differential expression of TEX genes was verified by qRT-PCR.\nResult: 11 TEX genes were thought to be highly predictive of the prognosis of HCC and substantially related to HCC prognosis. Patients in the low-risk group had a greater overall survival rate than those in the high-risk group, according to multivariate analysis, which also revealed that the model was an independent predictor of HCC. The predictive efficacy of columnar maps created from clinical features and risk scores was strong.\nConclusion: TEX signature and column line plots showed good predictive performance, providing a new perspective for assessing pre-immune efficacy, which will be useful for future precision immuno-oncology studies.", "claims": [{"id": "claim-method", "statement": "Afterward, we established a prognostic TEX signature using LASSO-Cox analysis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37006257", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "Afterward, we established a prognostic TEX signature using LASSO-Cox analysis."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material .", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37006257", "locator": "sections[31] \"Data availability statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material ."}], "state": "complete"}, {"id": "claim-target-result", "statement": "An 11-gene TEX signature stratified HCC patients by prognosis, with the low-risk group having a greater overall survival rate than the high-risk group.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37006257", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "11 TEX genes were thought to be highly predictive of the prognosis of HCC and substantially related to HCC prognosis."}, {"asset": "source:pmid:37006257", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Patients in the low-risk group had a greater overall survival rate than those in the high-risk group, according to multivariate analysis, which also revealed that the model was an independent predictor of HCC."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "An 11-gene TEX signature stratified HCC patients by prognosis, with the low-risk group having a greater overall survival rate than the high-risk group.", "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:37006257"], "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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