Identification of potential biomarkers and analysis of prognostic values in head and neck squamous cell carcinoma by bioinformatics analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:28490889", "kind": "science-record", "revision": 9, "content_hash": "sha256:0b0004657be70f4ca61bc81cee9a99f776bd7ef7f7aa2436e0eb0609c4caa41c", "created_at": "2026-11-01T15:40:25Z", "updated_at": "2026-11-01T22:42:59Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of potential biomarkers and analysis of prognostic values in head and neck squamous cell carcinoma by bioinformatics analysis.", "doi": "10.2147/OTT.S135514", "pmid": "28490889", "authors": ["Bo Yang", "Zhifeng Chen", "Yu Huang", "Guoxu Han", "Weizhong Li"], "journal": "OncoTargets and therapy", "year": 2017, "abstract": "The purpose of this study was to find disease-associated genes and potential mechanisms in head and neck squamous cell carcinoma (HNSCC) with deoxyribonucleic acid microarrays. The gene expression profiles of GSE6791 were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were obtained with packages in R language and STRING constructed protein-protein interaction (PPI) network of the DEGs with combined score >0.8. Subsequently, module analysis of the PPI network was performed by Molecular Complex Detection plugin and functions and pathways of the hub gene in subnetwork were studied. Finally, overall survival analysis of hub genes was verified in TCGA HNSCC cohort. A total of 811 DEGs were obtained, which were mainly enriched in the terms related to extracellular matrix (ECM)-receptor interaction, ECM structural constituent, and ECM organization. A PPI network was constructed, consisting of 401 nodes and 1,254 edges and 15 hub genes with high degrees in the network. High expression of 4 genes of the 15 genes was associated with poor OS of patients in HNSCC, including PSMA7, ITGA6, ITGB4, and APP. Two significant modules were detected from the PPI network, and the enriched functions and pathways included proteasome, ECM organization, and ECM-receptor interaction. In conclusion, we propose that PSMA7, ITGA6, ITGB4, and APP may be further explored as potential biomarkers to aid HNSCC diagnosis and treatment.", "claims": [{"id": "claim-method", "statement": "Then, the DEGs between HNSCC samples and normal controls were identified using the empirical Bayes approach in linear models for the microarray data (limma) package.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:28490889", "locator": "sections[4] \"Data preprocessing and identification of DEGs\" paragraph 2", "quote": "Then, the DEGs between HNSCC samples and normal controls were identified using the empirical Bayes approach in linear models for the microarray data (limma) package."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Microarray expression profiles of GSE67917 were downloaded from Gene Expression Omnibus database for identifying DEGs of HNSCC. GSE6791, which was already deposited in GPL570 (Affymetrix Human Genome U133 Plus 2.0 Array, Santa Clara, CA, USA), consisted of 42 HNSCC samples and 14 normal epithelial samples.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:28490889", "locator": "sections[3] \"Microarray data\" paragraph 2", "quote": "Microarray expression profiles of GSE67917 were downloaded from Gene Expression Omnibus database for identifying DEGs of HNSCC. GSE6791, which was already deposited in GPL570 (Affymetrix Human Genome U133 Plus 2.0 Array, Santa Clara, CA, USA), consisted of 42 HNSCC samples and 14 normal epithelial samples."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Using limma on the GSE6791 microarray dataset, the study identified 811 differentially expressed genes between 42 HNSCC samples and 14 normal epithelial samples, including 550 upregulated and 261 downregulated genes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:28490889", "locator": "sections[4] \"Data preprocessing and identification of DEGs\" paragraph 2", "quote": "Then, the DEGs between HNSCC samples and normal controls were identified using the empirical Bayes approach in linear models for the microarray data (limma) package."}, {"asset": "source:pmid:28490889", "locator": "sections[9] \"Identification of DEGs\" paragraph 2", "quote": "The total number of samples analyzed was 42 HNSCC samples, along with 14 normal epithelial samples. After data preprocessing, DEG analysis was performed using the limma software package. A total of 811 genes were identified after the analyses of GSE6791, including 550 upregulated and 261 downregulated genes."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Using limma on the GSE6791 microarray dataset, the study identified 811 differentially expressed genes between 42 HNSCC samples and 14 normal epithelial samples, including 550 upregulated and 261 downregulated genes.", "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:28490889"], "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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