小RNA
特征选择
计算生物学
签名(拓扑)
生物信息学
生物
肿瘤科
基因
医学
计算机科学
遗传学
人工智能
数学
几何学
作者
Shu Zhou,Qingchun Meng,Zexuan Wang
标识
DOI:10.1007/s00405-022-07404-9
摘要
PurposePredicting 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.MethodsFirst, 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.ResultsBased on the REOs of miRNA pairs, we identified a qualitative signature that consisted of 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.ConclusionOverall, our findings provided a promising signature for predicting the OS of LSCC patients.
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