A Novel Signature of Necroptosis-Associated Genes as a Potential Prognostic Tool for Head and Neck Squamous Cell Carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35754840", "kind": "science-record", "revision": 5, "content_hash": "sha256:55b338ac7ff81ebb6f04501754b726d6543673ae7348f5b9f086e737a497425b", "created_at": "2026-11-01T18:14:47Z", "updated_at": "2026-11-01T22:49:24Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A Novel Signature of Necroptosis-Associated Genes as a Potential Prognostic Tool for Head and Neck Squamous Cell Carcinoma.", "doi": "10.3389/fgene.2022.907985", "pmid": "35754840", "authors": ["Jing Huang", "Hongqi Huo", "Rong Lu"], "journal": "Frontiers in genetics", "year": 2022, "abstract": "Background: Head and neck squamous cell carcinoma (HNSCC) arises from squamous cells in the oral cavity, pharynx and larynx. Although HNSCC is sensitive to radiotherapy, patient prognosis is poor. Necroptosis is a novel programmed form of necrotic cell death. The prognostic value of necroptosis-associated gene expression in HNSCC has not been explored. Material and Methods: We downloaded mRNA expression data of HNSCC patients from TCGA databases and Gene Expression Omnibus (GEO) databases, and compared gene expression between tumor tissues and adjacent normal tissues to identify differentially expressed genes (DEGs) and necroptosis-related prognostic genes. A model with necroptosis-related genes was established to predict patient prognosis via LASSO method and Kaplan-Meier analysis. GSE65858 data set (n = 270) from GEO was used to verify the model's predictive ability. Gene set enrichment analyses, immune microenvironment analysis, principal component analysis, and anti-tumor compound IC50 prediction were also performed. Results: We identified 49 DEGs and found 10 DEGs were associated with patient survival (p < 0.05). A risk model of 6-gene signature was constructed using the TCGA training data set and further validated with the GEO data set. Patients in the low-risk group survived longer than those in the high-risk group (p < 0.05) in the GEO validation sets. Functional analysis showed the two patient groups were associated with distinct immunity conditions and IC50. Conclusion: We constructed a prognostic model with 6 necroptosis-associated genes for HNSCC. The model has potential usage to guide treatment because survival was different between the two groups.", "claims": [{"id": "claim-method", "statement": "Expression of necroptosis-related genes between tumor tissues and adjacent normal tissues was compared to identify DEGs by using the “linear models for microarray data (limma)” R package available from the Bioconductor project (www.bioconductor.org).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35754840", "locator": "sections[4] \"Identification of Different Expression Genes\" paragraph 2", "quote": "Expression of necroptosis-related genes between tumor tissues and adjacent normal tissues was compared to identify DEGs by using the “linear models for microarray data (limma)” R package available from the Bioconductor project (www.bioconductor.org)."}], "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 authors.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35754840", "locator": "sections[18] \"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 authors."}], "state": "complete"}, {"id": "claim-target-result", "statement": "We constructed a prognostic model with 6 necroptosis-associated genes for HNSCC.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35754840", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "We constructed a prognostic model with 6 necroptosis-associated genes for HNSCC."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "We constructed a prognostic model with 6 necroptosis-associated genes for 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:35754840"], "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:35754840", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fgene.2022.907985", "sha256": 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