Comprehensive Analysis of the Roles and Prognostic Value of RNA-Binding Proteins in Head and Neck Squamous Cell Carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a malignancy with relatively high incidence and poor prognosis. RNA-binding proteins (RBPs) were reported to be dysregulated in multiple cancers and were closely associated with tumor initiation and progression. However, an integrated analysis of the roles of RBPs in HNSCC has not been conducted. In the present study, we obtained transcriptome data and corresponding clinical information of HNSCC patients from The Cancer Genome Atlas database and screened out differentially expressed RBPs between tumor and normal tissues. Subsequently, we utilized a series of bioinformatics analyses to elucidate the potential functions and prognostic value of these RBPs in HNSCC. As a result, a total of 88 aberrantly expressed RBPs were identified, including 63 downregulated and 25 upregulated RBPs. Functional enrichment analysis suggested that the differentially expressed RBPs mainly participated in mRNA metabolic processes, RNA processing, RNA transport, regulation of RNA stability, RNA degradation, and mRNA surveillance pathway. Three RBP genes (NOVA1,EZH2, andRBM24) were determined as prognosis-related hub genes from whichEZH2andNOVA1were selected to construct a prognostic signature based on LASSO Cox regression algorithm. Further analysis demonstrated that the high-risk patient group stratified by the risk signature has advanced tumor grade and poorer overall survival when compared with low-risk group. Moreover, univariate analysis showed that the risk score, tumor stage, T stage, and N stage were significantly associated with patient overall survival and the multivariate analysis results indicated that the risk score and age were greatly correlated with patient prognosis. Overall, this study provided a comprehensive landscape of RBPs in HNSCC and identified an effective gene signature for predicting the clinical outcomes of HNSCC patient, which may contribute to clinical decision making and individualized cancer treatment.