Shu Zhou1,2, Qingchun Meng3, Zexuan Wang3. 1. Central Laboratory, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China. shuzhou2007@126.com. 2. Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China. shuzhou2007@126.com. 3. Central Laboratory, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.
Abstract
PURPOSE: 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. METHODS: 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. RESULTS: Based 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. CONCLUSION: Overall, our findings provided a promising signature for predicting the OS of LSCC patients.
PURPOSE: 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. METHODS: 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. RESULTS: Based 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. CONCLUSION: Overall, our findings provided a promising signature for predicting the OS of LSCC patients.
Authors: Eric M Genden; Alfio Ferlito; Carl E Silver; Adam S Jacobson; Jochen A Werner; Carlos Suárez; C René Leemans; Patrick J Bradley; Alessandra Rinaldo Journal: Oral Oncol Date: 2006-11-16 Impact factor: 5.337
Authors: Conor E Steuer; Mark El-Deiry; Jason R Parks; Kristin A Higgins; Nabil F Saba Journal: CA Cancer J Clin Date: 2016-11-29 Impact factor: 508.702
Authors: Elena Fountzilas; Vassiliki Kotoula; Nikolaos Angouridakis; Ilias Karasmanis; Ralph M Wirtz; Anastasia G Eleftheraki; Elke Veltrup; Konstantinos Markou; Angelos Nikolaou; Dimitrios Pectasides; George Fountzilas Journal: PLoS One Date: 2013-08-09 Impact factor: 3.240