T cell exhaustion assessment algorism in tumor microenvironment predicted clinical outcomes and immunotherapy effects in glioma.

{"sci_version": "1.0", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36531217", "kind": "science-record", "revision": 2, "content_hash": "sha256:641383d2536d0c707a6c1978bd6c7ae112f63a213d78e99c95d1303903e5400b", "created_at": "2026-11-01T19:01:03Z", "updated_at": "2026-11-01T21:29:42Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "T cell exhaustion assessment algorism in tumor microenvironment predicted clinical outcomes and immunotherapy effects in glioma.", "doi": "10.3389/fgene.2022.1087434", "pmid": "36531217", "authors": ["Lie Chen", "Biao Fu"], "journal": "Frontiers in genetics", "year": 2022, "abstract": "Despite the recent increase in the use of immune checkpoint blockade (ICB), no ICB medications have been approved or are undergoing large-scale clinical trials for glioma. T cells, the main mediators of adaptive immunity, are important components of the tumor immune microenvironment. Depletion of T cells in tumors plays a key role in assessing the sensitivity of patients to immunotherapy. In this study, the bioinformatics approach was applied to construct T cell depletion-related risk assessment to investigate the impact of T cell depletion on prognosis and ICB response in glioma patients. The Cancer Genome Atlas (TCGA) and GSE108474 glioma cohorts and IMvigor210 immunotherapy datasets were collected, including complete mRNA expression profiles and clinical information. We used cell lines to verify the gene expression and the R 3.6.3 tool and GraphPad for bioinformatics analysis and mapping. T cell depletion in glioma patients displayed significant heterogeneity. The T cell depletion-related prognostic model was developed based on seven prognostic genes (HSPB1, HOXD10, HOXA5, SEC61G, H19, ANXA2P2, HOXC10) in glioma. The overall survival of patients with a high TEXScore was significantly lower than that of patients with a low TEXScore. In addition, high TEXScore scores were followed by intense immune responses and a more complex tumor immune microenvironment. The \"hot tumors\" were predominantly enriched in the high-risk group, which patients expressed high levels of suppressive immune checkpoints, such as PD1, PD-L1, and TIM3. However, patients with a low TEXScore had a more significant clinical response to immunotherapy. In addition, HSPB1 expression was higher in the U251 cells than in the normal HEB cells. In conclusion, the TEXScore related to T cell exhaustion combined with other pathological profiles can effectively assess the clinical status of glioma patients. The TEXScore constructed in this study enables the effective assessment of the immunotherapy response of glioma patients and provides therapeutic possibilities.", "claims": [{"id": "claim-method", "statement": "The WGCNA method was used to screen for clinically relevant genes, and a weighted gene co-expression network was constructed using the following parameters: power of β = 4 and scale-free R2 = 0.9.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36531217", "locator": "sections[13] \"Identification of T cell exhausted related genes\" paragraph 2", "quote": "The WGCNA method was used to screen for clinically relevant genes, and a weighted gene co-expression network was constructed using the following parameters: power of β = 4 and scale-free R2 = 0.9."}], "state": "complete"}, {"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:36531217", "locator": "sections[20] \"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": "The T cell depletion-related prognostic model was developed based on seven prognostic genes (HSPB1, HOXD10, HOXA5, SEC61G, H19, ANXA2P2, HOXC10) in glioma.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36531217", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "The T cell depletion-related prognostic model was developed based on seven prognostic genes (HSPB1, HOXD10, HOXA5, SEC61G, H19, ANXA2P2, HOXC10) in glioma."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The T cell depletion-related prognostic model was developed based on seven prognostic genes (HSPB1, HOXD10, HOXA5, SEC61G, H19, ANXA2P2, HOXC10) in glioma.", "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:36531217"], "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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