Identification of Hub Genes Associated With Development of Head and Neck Squamous Cell Carcinoma by Integrated Bioinformatics Analysis.

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The aim of this study is to identify significant genes associated with HNSCC and to further analyze its prognostic significance. In our study, the cancer genome atlas (TCGA) HNSCC database and the gene expression profiles of GSE6631 from the Gene Expression Omnibus (GEO) were used to explore the differential co-expression genes in HNSCC compared with normal tissues. A total of 29 differential co-expression genes were screened out by Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis methods. As suggested in functional annotation analysis using the R clusterProfiler package, these genes were mainly enriched in epidermis development and differentiation (biological process), apical plasma membrane and cell-cell junction (cellular component), and enzyme inhibitor activity (molecular function). Furthermore, in a protein-protein interaction (PPI) network containing 21 nodes and 25 edges, the ten hub genes (S100A8, S100A9, IL1RN, CSTA, ANXA1, KRT4, TGM3, SCEL, PPL, and PSCA) were identified using the CytoHubba plugin of Cytoscape. The expression of the ten hub genes were all downregulated in HNSCC tissues compared with normal tissues. Based on survival analysis, the lower expression of CSTA was associated with worse overall survival (OS) in patients with HNSCC. Finally, the protein level of CSTA, which was validated by the Human Protein Atlas (HPA) database, was down-regulated consistently with mRNA levels in head and neck cancer samples. In summary, our study demonstrated that a survival-related gene is highly correlated with head and neck cancer development. Thus, CSTA may play important roles in the progression of head and neck cancer and serve as a potential biomarker for future diagnosis and treatment.", "claims": [{"id": "claim-method", "statement": "In order to find the differentially expressed genes (DEGs) between HNSCC and normal tissues, limma was applied in the TCGA-HNSCC and GSE6631 dataset, respectively, to screen out DEGs.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32528874", "locator": "sections[5] \"Differential Expression Analysis and Interaction With the Modules of Interest\" paragraph 2", "quote": "In order to find the differentially expressed genes (DEGs) between HNSCC and normal tissues, limma was applied in the TCGA-HNSCC and GSE6631 dataset, respectively, to screen out DEGs."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All available data were analyzed in this study. 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