Abstract
Improved insight into the molecular mechanisms of head and neck squamous cell carcinoma (HNSCC) is required to predict prognosis and develop a new therapeutic strategy for targeted genes. 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.
Highlights
Head and neck squamous cell carcinoma (HNSCC) is one of most common types of cancer in the world
In order to find the functional clusters in HNSCC patients, the gene co-expression networks were constructed from the TCGAHNSCC and GSE6631 datasets with the Weighted Gene Co-expression Network Analysis (WGCNA) package
The results of the module-trait relationships are presented in Figure 2B, 3B, revealing that the brown module in the the cancer genome atlas (TCGA)-HNSCC and pink module in the GSE6631 were found to have the highest association with normal tissues
Summary
Head and neck squamous cell carcinoma (HNSCC) is one of most common types of cancer in the world. HNSCC includes several malignancies that originate in the mouth, nasopharynx, oropharynx, hypopharynx, larynx, and neck [1]. HPV is currently the one most wellstudied and frequently used biomarker in HNSCC [4,5,6]. In the past several years, the treatments for managing head and neck cancer included the following: radiation therapy, surgery, and chemotherapy. Appropriate combinations of the three treatment modalities is selected according to the site of the cancer and the stage of the disease [1, 3]. There are diverse treatments for HNSCC, patients have a limited survival advantage
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