Weighted gene co-expression network analysis and prognostic analysis identifies hub genes and the molecular mechanism related to head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a lethal disease with suboptimal survival outcomes. In this study, we aimed to find an independent prognostic factor of head and neck squamous cell carcinoma and investigate its effect on tumor cell proliferation, apoptosis, migration progress and cell cycle phase. Weighted gene co-expression network analysis (WGCNA) is an analysis method for mining module information in chip data through soft threshold. In this article, it was used to divide differential genes into different modules and determined the ten hub genes. Overall survival (OS) and disease-free survival (DFS) analyses as well as univariate and multivariate regression analyses were used to figure out HMGA2 as the independent prognostic factor. RT-qPCR and western blot results revealed the HMGA2 expression levels. Via colony formation, flow cytometry and wound healing assays, we tested the involvement of HMGA2 knockdown in corresponding cancer cell biological behaviors. HMGA2 level was up-regulated in HNSCC tissues and cell lines (SCC-25 and FaDu) in comparison with their normal counterparts. HMGA2 knockdown decreased cancer cell proliferation, promoted cell apoptosis, blocked cell cycle at G0/G1 phase, and inhibited cell migration. We regarded HMGA2 as a potential diagnostic and therapeutic target of HNSCC.