Identification of an immune-related signature as a prognostic classifier for patients with early-stage head and neck squamous cell carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38617526", "kind": "science-record", "revision": 3, "content_hash": "sha256:f933a68c9b3f8aec64876d712fd615fe544a99923f84a7b911a9fd02436fe02d", "created_at": "2026-11-01T19:20:35Z", "updated_at": "2026-11-01T22:11:41Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of an immune-related signature as a prognostic classifier for patients with early-stage head and neck squamous cell carcinoma.", "doi": "10.21037/tcr-23-1791", "pmid": "38617526", "authors": ["Le Wang", "Yulin Zhang", "Hongmin Li", "Jilin Peng", "Changhui Gao", "Qiuning Yu", "Pei Gao", "Ling Li", "Kuisheng Chen", "Fanglei Ye"], "journal": "Translational cancer research", "year": 2024, "abstract": "Background: Head and neck squamous cell carcinoma (HNSCC) is the most common type and accounts for 90% of all head and neck cancer cases. Despite advances in early diagnosis and treatment strategies-chemotherapy, surgical resection, and radiotherapy-5-year survival remains grim. For patients with early-stage HNSCC, accurately predicting clinical outcomes is challenging. Considering the pivotal role of the immune system in HNSCC, we developed a reliable immune-related gene signature (IRGS) and explored its predictive accuracy in patients with early-stage HNSCC.\nMethods: We examined immune gene expression profiles and clinical information from 230 early-stage HNSCC specimens, including 100 cases from The Cancer Genome Atlas (TCGA), 49 cases from the Gene Expression Omnibus (GEO; GSE65858), and 81 cases from an independent clinical cohort. The prognostic signature was constructed using Kaplan-Meier analysis and the least absolute shrinkage and selection operator (LASSO) Cox algorithm. We also explored the IRGS-related biological pathways and immune landscape using bioinformatics analysis.\nResults: A nine-immune-gene signature was generated to significantly stratify patients into high and low-risk groups. High risk patients exhibited shorter survival time [hazard ratio (HR) =13.795, 95% confidence interval (CI): 3.275-58.109, P<0.001]. The signature demonstrated robust prognostic ability in the training and validation sets and could independently predict overall survival (OS) and relapse-free survival (RFS). Subsequently, the receiver operating characteristic (ROC) curve and C-index confirmed the signature's predictive accuracy compared to clinical parameters. Additionally, cases classified as low risk showed more immune cell infiltration than high-risk cases.\nConclusions: Our novel IRGS is a reliable and robust classifier for accurate patient stratification and prognostic evaluation. Future studies will attempt to affirm the signature's clinical application to early-stage HNSCC.", "claims": [{"id": "claim-method", "statement": "The prognostic signature was constructed using Kaplan-Meier analysis and the least absolute shrinkage and selection operator (LASSO) Cox algorithm.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38617526", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The prognostic signature was constructed using Kaplan-Meier analysis and the least absolute shrinkage and selection operator (LASSO) Cox algorithm."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Data Sharing Statement: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-23-1791/dss", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38617526", "locator": "sections[22] \"fn-group\" paragraph 1", "quote": "Data Sharing Statement: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-23-1791/dss"}], "state": "complete"}, {"id": "claim-target-result", "statement": "High risk patients exhibited shorter survival time [hazard ratio (HR) =13.795, 95% confidence interval (CI): 3.275–58.109, P<0.001].", "kind": "quantitative", "target": {"value": 95.0, "unit": "per cent", "tolerance": null, "source": "High risk patients exhibited shorter survival time [hazard ratio (HR) =13.795, 95% confidence interval (CI): 3.275–58.109, P<0.001]."}, "evidence": [{"asset": "source:pmid:38617526", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "A nine-immune-gene signature was generated to significantly stratify patients into high and low-risk groups."}, {"asset": "source:pmid:38617526", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "High risk patients exhibited shorter survival time [hazard ratio (HR) =13.795, 95% confidence interval (CI): 3.275–58.109, P<0.001]."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "High risk patients exhibited shorter survival time [hazard ratio (HR) =13.795, 95% confidence interval (CI): 3.275–58.109, P<0.001].", "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:38617526"], "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:GSE65858"], "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:GSE65858"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38617526", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.21037/tcr-23-1791", "sha256": 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