A Novel Prognostic Model for Oral Squamous Cell Carcinoma: The Functions and Prognostic Values of RNA-Binding Proteins - Lu, Yingjuan; Yan, Yongcong; Li, Bowen; Liu, Mo; Liang, Yancan; Ye, Yushan; Cheng, Weiqi; Li, Jinsong; Jiao, Jiuyang; Chang, Shaohai (Frontiers in Oncology, 2021)
Purpose: The biological roles and clinical significance of RNA-binding proteins (RBPs) in oral squamous cell carcinoma (OSCC) are not fully understood. We investigated the prognostic value of RBPs in OSCC using several bioinformatic strategies. Materials and Methods: OSCC data were obtained from a public online database, the Limma R package was used to identify differentially expressed RBPs, and functional enrichment analysis was performed to elucidate the biological functions of the above RBPs in OSCC. We performed protein-protein interaction (PPI) network and Cox regression analyses to extract prognosis-related hub RBPs. Next, we established and validated a prognostic model based on the hub RBPs using Cox regression and risk score analyses. Results: We found that the differentially expressed RBPs were closely related to the defense response to viruses and multiple RNA processes. We identified ten prognosis-related hub RBPs (ZC3H12D, OAS2, INTS10, ACO1, PCBP4, RNASE3, PTGES3L-AARSD1, RNASE13, DDX4, and PCF11) and effectively predicted the overall survival of OSCC patients. The area under the receiver operating characteristic (ROC) curve (AUC) of the risk score model was 0.781, suggesting that our model exhibited good prognostic performance. Finally, we built a nomogram integrating the ten RBPs. The internal validation cohort results showed a reliable predictive capability of the nomogram for OSCC. Conclusion: We established a novel ten-RBP-based model for OSCC that could enable precise individual treatment and follow-up management strategies in the future.