Bioinformatic analysis of four miRNAs relevant to metastasis-regulated processes in endometrial carcinoma

Lingping Zhu,1,2 Zhiqun Shu,3 Xiaoming Sun2,3 1Department of General Practice, Shenzhen Longhua District Central Hospital, Shenzhen, People’s Republic of China; 2Department of General Practice, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China; 3Pudong Institute for Health Development, Shanghai, People’s Republic of China 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 analysi