Identification and validation of a novel signature based on T cell marker genes to predict prognosis, immunotherapy response and chemotherapy sensitivity in head and neck squamous carcinoma by integrated analysis of single-cell and bulk RNA-sequencing.

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Our study sought to develop a reliable signature incorporating T cell marker genes (TMGs) for predicting the prognosis and therapy responsiveness of head and neck squamous cell carcinoma (HNSCC) patients. We downloaded scRNA-seq data from the GSE181919 to identify TMGs. Subsequently, we devised a 12 TMG signature in the TCGA HNSCC cohort by using LASSO analysis. Patients with high-risk scores were shown to experience unfavorable progression-free survival, disease-specific survival, and overall survival, which was validated in the GSE65858 cohort. Additionally, the nomogram integrated risk score and clinical features are more suitable for clinical application. The enrichment analyses of both pathways and functions showed that high- and low-risk patients had functionally related distinctions. Furthermore, analysis of the immunological landscape confirmed that the low-risk patients had a larger percentage of infiltrating immune cells as well as a higher incidence rate of immune-related events. In the meantime, a greater IPS score and expression of immune checkpoint genes suggested significantly favorable responsiveness to immunotherapy in low-risk patients. On the other hand, the high-risk patients had a greater degree of sensitivity to the chemotherapy agents, which included paclitaxel, gemcitabine, docetaxel, and cisplatin. Our finding revealed that this TMG signature independently functioned as a prognostic marker and guided individualized immunotherapy and chemotherapy selection for patients with HNSCC.", "claims": [{"id": "claim-method", "statement": "To identify the optimal prognostic TMGs for use in the signature's construction in the TCGA-HNSCC cohort, a LASSO regression analysis with 10-fold cross-validation was performed 1000 times by the “glmnet” package.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37954266", "locator": "sections[16] \"T cell marker gene-based prognostic risk model development\" paragraph 2", "quote": "To identify the optimal prognostic TMGs for use in the signature's construction in the TCGA-HNSCC cohort, a LASSO regression analysis with 10-fold cross-validation was performed 1000 times by the “glmnet” package."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Data will be made available on request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37954266", "locator": "sections[24] \"Data availability statement\" paragraph 2", "quote": "Data will be made available on request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The TMG signature independently functioned as a prognostic marker and guided individualized immunotherapy and chemotherapy selection for patients with HNSCC.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37954266", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Our finding revealed that this TMG signature independently functioned as a prognostic marker and guided individualized immunotherapy and chemotherapy selection for patients with HNSCC."}, {"asset": "source:pmid:37954266", "locator": "sections[1] \"Introduction\" paragraph 4", "quote": "Herein, we firstly gathered the scRNA-seq data of HNSCC from the Gene Expression Omnibus (GEO) database to distinguish T cell subclusters and identify TMGs."}, {"asset": "source:pmid:37954266", "locator": "sections[1] \"Introduction\" paragraph 4", "quote": "We aimed to construct the TMG signature linked to the HNSCC prognosis using the least absolute shrinkage and selection operator (LASSO) analysis in the Cancer Genome Atlas (TCGA)-HNSCC cohort and validate in the GSE65858 dataset."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The TMG signature independently functioned as a prognostic marker and guided individualized immunotherapy and chemotherapy selection for patients with HNSCC.", "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:37954266"], "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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