A novel and independent survival prognostic model for OSCC: the functions and prognostic values of RNA-binding proteins.

BACKGROUND

Oral squamous cell carcinoma (OSCC), exhibiting high morbidity and malignancy, is the most common type of oral cancer. The abnormal expression of RNA-binding proteins (RBPs) plays important roles in the occurrence and progression of cancer. The objective of the present study was to establish a prognostic assessment model of RBPs and to evaluate the prognosis of OSCC patients.

METHODS

Gene expression data in The Cancer Genome Atlas (TCGA) were analyzed by univariate Cox regression analysis model that established a novel nine RBPs, which were used to build a prognostic risk model. A multivariate Cox proportional regression model and the survival analysis were used to evaluate the prognostic risk model. Moreover, the receive operator curve (ROC) analysis was tested further the efficiency of prognostic risk model based on data from TCGA database and Gene Expression Omnibus (GEO).

RESULTS

Nine RBPs' signatures (ACO1, G3BP1, NMD3, RNGTT, ZNF385A, SARS, CARS2, YARS and SMAD6) with prognostic value were identified in OSCC patients. Subsequently, the patients were further categorized into high-risk group and low-risk in the overall survival (OS) and disease-free survival (DFS), and external validation dataset. ROC analysis was significant for both the TCGA and GEO. Moreover, GSEA revealed that patients in the high-risk group significantly enriched in many critical pathways correlated with tumorigenesis than the low, including cell cycle, adheres junctions, oocyte meiosis, spliceosome, ERBB signaling pathway and ubiquitin-mediated proteolysis.

CONCLUSIONS

Collectively, we developed and validated a novel robust nine RBPs for OSCC prognosis prediction. The nine RBPs could serve as an independent and reliable prognostic biomarker and guiding clinical therapy for OSCC patients.