Prognostic value of a microRNA-pair signature in laryngeal squamous cell carcinoma patients.

Abstract

Predicting the prognosis in laryngeal squamous cell carcinoma (LSCC) patients will improve clinical decision-making. Here, we aimed to identify a qualitative signature based on the within-sample relative expression orderings (REOs) of microRNA (miRNA) pairs to predict the overall survival (OS) of LSCC patients. First, we constructed non-repeating miRNA pairs based on differentially expressed miRNAs (DEmiRNAs) between LSCC and normal tissues. Then, we applied a bootstrap-based feature selection method to identify a robust miRNA-pair signature. The bootstrap-based feature selection improved the stability of feature selection by an ensemble based on the data perturbation. Furthermore, a series of bioinformatics analyses were carried out to explore the potential mechanisms of the signature and potential drug targets for LSCC. Based on the REOs of miRNA pairs, we identified a qualitative signature thatconsistedof 12 miRNA pairs. The constructed signature has good performance in predicting the OS of LSCC patients. It is robust against batch effects and more suitable for individual clinical applications.Furthermore, we identified several hub genes that may be potential drug targets for LSCC. Overall, our findings provided a promising signature for predicting theOS of LSCC patients.