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pmid:39282247

Seven Immune-Related Genes' Prognostic Value and Correlation with Treatment Outcome in Head and Neck Squamous Cell Carcinoma.

Rui Mu · Yuehong Shen · Chuanbin Guo · Xinyun Zhang · Hongyu Yang · Huijun Yang

Mediators of inflammation · 2023 doi:10.1155/2023/8533476

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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title
Seven Immune-Related Genes' Prognostic Value and Correlation with Treatment Outcome in Head and Neck Squamous Cell Carcinoma.
doi
10.1155/2023/8533476
pmid
39282247
authors array · 6 items
[0]
Rui Mu
[1]
Yuehong Shen
[2]
Chuanbin Guo
[3]
Xinyun Zhang
[4]
Hongyu Yang
[5]
Huijun Yang
journal
Mediators of inflammation
year
2023
abstract
Background: Head and neck squamous cell carcinoma (HNSCC) is a growing concern worldwide, due to its poor prognosis, low responsiveness to treatment, and drug resistance. Since immunotherapy effectively improves HNSCC patients' survival status, it is important to continuously explore new immune-related predictive factors to accurately predict the immune landscape and clinical outcomes of individuals suffering from HNSCC. Methods: The HNSCC transcriptome profiling of RNA-sequencing data was retrieved from TCGA database, and the microarray of GSE27020 was obtained from the GEO database for validation. The differentially expressed genes (DEGs) between HNSCC and normal samples were identified by multiple test corrections in TCGA database. The univariate and multivariate Cox analyses were performed to identify proper immune-related genes (IRGs) to construct a risk model. The Cox regression coefficient was employed for calculation of the risk score (RS) of IRG signature. The median value of RS was utilized as a basis to classify individuals with HNSCC into high- and low-risk groups. The Kaplan-Meier (K-M) survival analysis and receiver operating characteristic (ROC) curves were employed for the identification of the prognostic significance and precision of the IRG signature. The signature was also evaluated based on clinical variables, predictive nomogram, mutation analysis, infiltrating immune cells, immune-related pathways, and chemotherapeutic efficacy. The protein-protein interaction (PPI) network and functional enrichment pathway investigations were utilized to explore possible potential molecular mechanisms. Finally, the hub gene's differential mRNA expression levels were evaluated by means of the Gene Expression Profiling Interactive Analysis (GEPIA), and the Human Protein Atlas (HPA) was utilized for the validation of their translational levels. Results: Collectively, 1593 DEGs between HNSCC and normal samples were identified, of which 136 IRGs were differentially expressed. Then, the 136 immune-related DEGs were mostly enriched in the cytokine-related signaling pathways by GO and KEGG analyses. After that, a valuable signature based on seven genes (DKK1, GAST, IGHM, IL12RB2, SLURP1, STC2, and TNFRSF4) was designed. The HNSCC patients into the low-risk group and the high-risk group were divided by using the median RS; the HNSCC patients in the high-risk group had a worse survival than those in the low-risk group. The risk signature was verified to be an independent predictive marker for HNSCC patients. Meanwhile, the RS had the largest contribution to survival of these patients based on the predictive nomogram. In addition, the low-risk HNSCC patients exhibited significantly enriched immune cells, along with an association with high chemosensitivity. Conclusion: The constructed gene signature can independently function as a predictive indicator for the clinical features of HNSCC patients. The low-risk HNSCC subjects might benefit from immunotherapy and chemotherapy.
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The survival curves were estimated by using the K-M survival analysis and log-rank test between different groups. Clinicopathological features were compared by univariate and multivariate Cox regression analyses.
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sections[13] "2.11. Statistical Analysis" paragraph 2
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The survival curves were estimated by using the K-M survival analysis and log-rank test between different groups. Clinicopathological features were compared by univariate and multivariate Cox regression analyses.
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The datasets analyzed during the current study are available in TCGA database (https://portal.gdc.cancer.gov/), ImmPort database (https://immport.niaid.nih.gov/), GEO database (https://www.ncbi.nlm.nih.gov/gds/), TIMER (https://cistrome.shinyapps.io/timer/), STRING biological database (https://string-db.org/), GEPIA database (http://gepia.cancer-pku.cn/), and HPA database (https://www.proteinatlas.org/).
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High-risk HNSCC patients showed worse survival than low-risk patients, and the signature had a 5-year ROC AUC of 0.685.
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HNSCC patients at high risk showed a worse survival in the K-M analysis, in comparison to the patients at low risk (P < 0.001) (Figure 4(a)), with the AUC of 0.685 for the 5-year ROC curve (Figure 4(b)), indicating a certain predictive value of the signature in predicting the survival of individuals with HNSCC.
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sections[16] "3.2. Development and Verification of the IRG-Based Prognostic Signature" paragraph 3
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HNSCC patients at high risk showed a worse survival in the K-M analysis, in comparison to the patients at low risk (P < 0.001) (Figure 4(a)), with the AUC of 0.685 for the 5-year ROC curve (Figure 4(b)), indicating a certain predictive value of the signature in predicting the survival of individuals with HNSCC.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39282247", "kind": "science-record", "revision": 4, "content_hash": "sha256:58015f6deec3abc6be1a8c75a1fcc4a7fac4749346ed8ca0c4f46bc4004dcd3c", "created_at": "2026-11-01T20:29:27Z", "updated_at": "2026-11-01T22:55:11Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Seven Immune-Related Genes' Prognostic Value and Correlation with Treatment Outcome in Head and Neck Squamous Cell Carcinoma.", "doi": "10.1155/2023/8533476", "pmid": "39282247", "authors": ["Rui Mu", "Yuehong Shen", "Chuanbin Guo", "Xinyun Zhang", "Hongyu Yang", "Huijun Yang"], "journal": "Mediators of inflammation", "year": 2023, "abstract": "Background: Head and neck squamous cell carcinoma (HNSCC) is a growing concern worldwide, due to its poor prognosis, low responsiveness to treatment, and drug resistance. Since immunotherapy effectively improves HNSCC patients' survival status, it is important to continuously explore new immune-related predictive factors to accurately predict the immune landscape and clinical outcomes of individuals suffering from HNSCC.\nMethods: The HNSCC transcriptome profiling of RNA-sequencing data was retrieved from TCGA database, and the microarray of GSE27020 was obtained from the GEO database for validation. The differentially expressed genes (DEGs) between HNSCC and normal samples were identified by multiple test corrections in TCGA database. The univariate and multivariate Cox analyses were performed to identify proper immune-related genes (IRGs) to construct a risk model. The Cox regression coefficient was employed for calculation of the risk score (RS) of IRG signature. The median value of RS was utilized as a basis to classify individuals with HNSCC into high- and low-risk groups. The Kaplan-Meier (K-M) survival analysis and receiver operating characteristic (ROC) curves were employed for the identification of the prognostic significance and precision of the IRG signature. The signature was also evaluated based on clinical variables, predictive nomogram, mutation analysis, infiltrating immune cells, immune-related pathways, and chemotherapeutic efficacy. The protein-protein interaction (PPI) network and functional enrichment pathway investigations were utilized to explore possible potential molecular mechanisms. Finally, the hub gene's differential mRNA expression levels were evaluated by means of the Gene Expression Profiling Interactive Analysis (GEPIA), and the Human Protein Atlas (HPA) was utilized for the validation of their translational levels.\nResults: Collectively, 1593 DEGs between HNSCC and normal samples were identified, of which 136 IRGs were differentially expressed. Then, the 136 immune-related DEGs were mostly enriched in the cytokine-related signaling pathways by GO and KEGG analyses. After that, a valuable signature based on seven genes (DKK1, GAST, IGHM, IL12RB2, SLURP1, STC2, and TNFRSF4) was designed. The HNSCC patients into the low-risk group and the high-risk group were divided by using the median RS; the HNSCC patients in the high-risk group had a worse survival than those in the low-risk group. The risk signature was verified to be an independent predictive marker for HNSCC patients. Meanwhile, the RS had the largest contribution to survival of these patients based on the predictive nomogram. In addition, the low-risk HNSCC patients exhibited significantly enriched immune cells, along with an association with high chemosensitivity.\nConclusion: The constructed gene signature can independently function as a predictive indicator for the clinical features of HNSCC patients. The low-risk HNSCC subjects might benefit from immunotherapy and chemotherapy.", "claims": [{"id": "claim-method", "statement": "The survival curves were estimated by using the K-M survival analysis and log-rank test between different groups. Clinicopathological features were compared by univariate and multivariate Cox regression analyses.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39282247", "locator": "sections[13] \"2.11. Statistical Analysis\" paragraph 2", "quote": "The survival curves were estimated by using the K-M survival analysis and log-rank test between different groups. Clinicopathological features were compared by univariate and multivariate Cox regression analyses."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets analyzed during the current study are available in TCGA database (https://portal.gdc.cancer.gov/), ImmPort database (https://immport.niaid.nih.gov/), GEO database (https://www.ncbi.nlm.nih.gov/gds/), TIMER (https://cistrome.shinyapps.io/timer/), STRING biological database (https://string-db.org/), GEPIA database (http://gepia.cancer-pku.cn/), and HPA database (https://www.proteinatlas.org/).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39282247", "locator": "sections[25] \"Data Availability\" paragraph 2", "quote": "The datasets analyzed during the current study are available in TCGA database (https://portal.gdc.cancer.gov/), ImmPort database (https://immport.niaid.nih.gov/), GEO database (https://www.ncbi.nlm.nih.gov/gds/), TIMER (https://cistrome.shinyapps.io/timer/), STRING biological database (https://string-db.org/), GEPIA database (http://gepia.cancer-pku.cn/), and HPA database (https://www.proteinatlas.org/)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "High-risk HNSCC patients showed worse survival than low-risk patients, and the signature had a 5-year ROC AUC of 0.685.", "kind": "quantitative", "target": {"value": 0.685, "unit": "auc", "tolerance": null, "source": "HNSCC patients at high risk showed a worse survival in the K-M analysis, in comparison to the patients at low risk (P < 0.001) (Figure 4(a)), with the AUC of 0.685 for the 5-year ROC curve (Figure 4(b)), indicating a certain predictive value of the signature in predicting the survival of individuals with HNSCC."}, "evidence": [{"asset": "source:pmid:39282247", "locator": "sections[16] \"3.2. Development and Verification of the IRG-Based Prognostic Signature\" paragraph 3", "quote": "HNSCC patients at high risk showed a worse survival in the K-M analysis, in comparison to the patients at low risk (P < 0.001) (Figure 4(a)), with the AUC of 0.685 for the 5-year ROC curve (Figure 4(b)), indicating a certain predictive value of the signature in predicting the survival of individuals with HNSCC."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "High-risk HNSCC patients showed worse survival than low-risk patients, and the signature had a 5-year ROC AUC of 0.685.", "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:39282247"], "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:GSE27020"], "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:GSE27020"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39282247", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2023/8533476", "sha256": "sha256:35c3318235b945cad176abc49751dbb1b929e12c459c9c9bc7a829f4946a87f4", "bytes": 28376, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1155/2023/8533476", "version": null, "note": "Full article fetched from PMC; 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Clinicopathological features were compared by univariate and multivariate Cox regression analyses."}}, {"id": "method-2", "family": "group_comparison", "specific": "wilcoxon", "label": "Group comparison", "dsl_operations": [], "missing_operations": ["group_comparison_wilcoxon"], "expressible": false, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 0.8, "band": "high", "quote": "Wilcoxon"}}, {"id": "method-3", "family": "survival_analysis", "specific": "cox_proportional_hazards", "label": "Survival analysis", "dsl_operations": ["cox_ph"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.7, "band": "medium", "quote": "Cox regression"}}, {"id": "method-4", "family": "survival_analysis", "specific": "log_rank_test", "label": "Survival analysis", "dsl_operations": ["logrank_test"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.8, "band": "high", "quote": "log-rank"}}, {"id": "method-5", "family": "network_analysis", "specific": "ppi_network", "label": "Network / pathway analysis", "dsl_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.7, "band": "medium", "quote": "protein-protein interaction"}}], "targets": [{"id": "target-published-estimate", "claim_id": "claim-target-result", "operation": "build_graph", "expected_value": 0.685, "unit": "auc", "tolerance": null, "state": "complete", "note": "The published estimate as the reader quoted it from the paper. No tolerance is published because the paper states none."}, {"id": "target-published-estimate-p-value", "claim_id": "claim-target-result", "operation": "build_graph", "expected_value": 0.001, "unit": "p-value", "tolerance": null, "state": "complete", "note": "The threshold the paper applied to its own result, as the paper states it. A run that reproduces the effect is judged against this threshold."}], "gaps": ["method.reader_differs_from_extractor"]}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["survival_km"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: kaplan_meier."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE27020"], "resolved_accessions": ["GSE27020"], "statements": ["The datasets analyzed during the current study are available in TCGA database (https://portal.gdc.cancer.gov/), ImmPort database (https://immport.niaid.nih.gov/), GEO database (https://www.ncbi.nlm.nih.gov/gds/), TIMER (https://cistrome.shinyapps.io/timer/), STRING biological database (https://string-db.org/), GEPIA database (http://gepia.cancer-pku.cn/), and HPA database (https://www.proteinatlas.org/)."], "basis": "The paper names GSE27020 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["survival_km"], "assets": ["source:pmid:39282247", "data:geo:GSE27020"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE27020"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T19:31:50Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 8794, "completion_tokens": 2561, "cached_tokens": 264}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:39282247", "type": "paper", "label": "pmid:39282247"}, {"id": "source:pmid:39282247", "type": "manuscript", "label": "PMID 39282247 full text"}, {"id": "data:geo:GSE27020", "type": "dataset", "label": "GEO GSE27020"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:39282247", "type": "paper", "label": "pmid:39282247"}, {"id": "source:pmid:39282247", "type": "manuscript", "label": "PMID 39282247 full text"}, {"id": "data:geo:GSE27020", "type": "dataset", "label": "GEO GSE27020"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-39282247", "type": "extraction", "used": ["source:pmid:39282247"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE27020", "type": "accession_resolution", "used": ["data:geo:GSE27020"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:39282247", "parent_hash": "sha256:407f23b13675506f2f4f04ed94625af2e014ae4ec7c4c14f35b04a321e8ea214", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE27020 licence not read", "asset:data:geo:GSE27020 not downloaded", "execution.not_run", "method.reader_differs_from_extractor", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "rna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["ethods: The HNSCC transcriptome profiling of RNA-sequencing data was retrieved from TCGA database, and t", "als suffering from HNSCC. 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