已发表论文

对与子宫内膜癌转移调控过程相关的 4 种 miRNA 的生物信息学分析

 

Authors Zhu L, Shu Z, Shun X

Received 19 March 2018

Accepted for publication 21 May 2018

Published 1 August 2018 Volume 2018:10 Pages 2337—2346

DOI https://doi.org/10.2147/CMAR.S168594

Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Colin Mak

Peer reviewer comments 3

Editor who approved publication: Professor Kenan Onel

Background: The purpose of this study was to investigate the expression of different miRNAs in nonmetastatic and metastatic endometrial cancer Existing evidence indicates that there are many factors affecting the metastasis of endometrial cancer, and miRNAs play an unique role in many processes of endometiral cancer. 
Materials and methods: miRNA sequences were downloaded from The Cancer Genome Atlas Project database, and Bioinformatics technique was used to deal with those data.
Results: We elucidated the relation between differentially expressed miRNAs and clinical information for a total of 260 tumor tissues and 22 tumor tissues that had metastasized. We used the threshold of P <0.05| log 2 FC | >1.2 to identify potential miRNAs. Four differentially expressed miRNAs were identified in nonmetastatic and metastatic endometrial cancers. Further differential analysis of metastatic tissue revealed that miR-1247 is associated with metastasis of endometrial cancer to the lung, and miR-3200 is associated with the clinical stage of endometrial cancer. A functional enrichment analysis showed that the four miRNAs may be involved in multiple pathways of cancer, including the Wnt, NOTCH, and TGF-β signaling pathways and signaling pathways regulating pluripotency of stem cells. Protein–protein interaction analysis showed that PAK6 SNAP25 MAN1A1 MYB ZBTB4 UST ALDH1A3 , and NRP2  are hub genes of relevant miRNAs in endometrial cancers.
Conclusion: The current study indicates that these four miRNAs may be related to molecular markers of metastasis of endometrial cancer.
Keywords: endometrial cancer, bioinformatics, miR-1247, protein analysis


Figure 2 The target gene prediction and function analysis.