已发表论文

EIF2B5 mRNA 的高表达及其在肝癌中的预后意义:一项基于 TCGA 和 GEO 数据库的研究

 

Authors Jiao Y, Fu Z, Li Y, Meng L, Liu Y

Received 27 August 2018

Accepted for publication 23 October 2018

Published 20 November 2018 Volume 2018:10 Pages 6003—6014

DOI https://doi.org/10.2147/CMAR.S185459

Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Amy Norman

Peer reviewer comments 2

Editor who approved publication: Dr Antonella D'Anneo

Purpose: Liver cancer is a high mortality disease with no curable treatments. Posttranscriptional modifications play essential roles in the occurrence and the progression of liver cancer. EIF2B5 is a subunit of EIF2B that regulates the initiation and the rate of translation and participates in several diseases including tumors. This study aims to elucidate the prognostic significance of EIF2B5 in liver cancer.
Materials and methods: We used The Cancer Genome Atlas database to analyze the expression of EIF2B5 in liver cancer. Then we used chi-squared and Fisher exact tests to test the correlation between clinical characteristics and EIF2B5 expression. Finally, we assessed the role of EIF2B5 in prognosis by Kaplan–Meier curves and Cox analysis. Gene set enrichment analysis was performed by using The Cancer Genome Atlas data set.
Results: The results showed that EIF2B5 was upregulated in liver cancer, and the expression was related to histologic grade, clinical stage, and vital status. Moreover, Kaplan–Meier curves and Cox analysis implicated that highly expressed EIF2B5 correlated with poor prognosis, and EIF2B5 was an independent risk factor for liver cancer. Gene set enrichment analysis showed that ATR and BRCA pathway, cell cycle pathway, DNA repair, myc signaling pathway, and E2F targets are differentially enriched in EIF2B5 high-expression phenotype.
Conclusion: Our results suggest that EIF2B5 participated in cancer progression and could become a biomarker for the prognosis of patients with liver cancer.
Keywords: liver cancer, EIF2B5, prognosis, diagnosis




Figure 1 The different EIF2B5 expressions in the boxplot.