@article{TCR24919,
author = {King Wai Lau and Haikang Zeng and Hengrui Liang and Xi Su and Jieling Ma and Shuai Wen and Jin Li},
title = {Bioinformatics-based identification of differentiated expressed microRNA in esophageal squamous cell carcinoma},
journal = {Translational Cancer Research},
volume = {7},
number = {6},
year = {2018},
keywords = {},
abstract = {Background: Although numerous studies have identified and observed altered expression of microRNAs in esophageal squamous cell carcinoma (ESCC), only a limited number of miRNAs were reported up to date, partially due to the limitation of sample size (less than or equal to 100 pair of paired samples). Thus, we performed a comprehensive analysis to improve the ability to detect miRNA expressed differentially in ESCC.
Methods: The study datasets were systematically searched and downloaded from public available databases including European Bioinformatics Institute (EMBL-EBI), ArrayExpress and Gene Expression Omnibus (GEO) database. Only datasets derived from ESCC patients were further screened and quality assessed using R programming language with ArrayExpress package. A total of 4 datasets covering 349 ESCC cases and 326 normal esophageal tissue samples (NE) were included in this study.
Results: The analytic results showed that a total of 108 miRNAs were differentially expressed in esophageal cancer, of which 48 were up-regulated and 60 were down-regulated compared with the adjacent normal esophageal tissues. Moreover, we successfully identified 9 novel differentially expressed miRNAs that have not been discovered to associate with esophageal cancer in the previous studies. We also predicted top 5 potential target genes of these novel miRNAs.
Conclusions: The bioinformatics based analysis summarized the current differential expression of miRNA in ESCC, and exploring unknown miRNA target genes provides guidance for discovering the new biomarkers of ESCC.},
issn = {2219-6803}, url = {https://tcr.amegroups.org/article/view/24919}
}