Literature DB >> 31545079

Analysis of Gene Expression in Bladder Cancer: Possible Involvement of Mitosis and Complement and Coagulation Cascades Signaling Pathway.

Ying Liu1, Shenghua Xiong2, Shiying Liu3, Jie Chen3, Hao Yang4, Gang Liu3, Gengmi Li1,3.   

Abstract

This study focused on identifying bladder cancer (BC)-associated genes, transcription factors (TFs), and microRNAs (miRNAs). Two microarray data sets GSE37815 and GSE40355 were utilized to screen common differentially expressed genes (DEGs) associated with BC. Then, functional enrichment analysis was performed for elucidating the involved functions of DEGs. Subsequently, the protein-protein interaction (PPI) network and submodule of PPI network were analyzed. Finally, the regulation relationships of TF-DEGs and miRNA-DEGs were obtained to construct miRNA-target-TF regulatory network. DEGs were identified across BC and normal bladder tissues samples. Functional enrichment analysis results showed that most upregulated DEGs were closely associated with the Gene Ontology function of "mitotic spindle assembly checkpoint" and pathway of "Cell cycle," whereas most downregulated DEGs were significantly associated with "Complement and coagulation cascades" pathway (e.g., A2M and F13A1) and "Ras signaling pathway" (e.g., GNG11). DEGs such as F13A1 and A2M were highlighted in the PPI network and Submodule 1. In addition, three centromere-associated CENPK, CENPF, and CENPO were enriched in Submodule 2. Moreover, miR-519d had high degree in the regulatory network and CENPO was predicted to be one target of miR-519d. The upregulated CENPK, CENPF, and CENPO, and downregulated A2M, F13A1, and GNG11 might contribute to the progression of BC. In addition, the downregulated miR-519d might lead to the development of BC by upregulating the expression of CENPO. However, future investigation of those findings should be needed.

Entities:  

Keywords:  bladder cancer; differentially expressed genes; protein–protein interaction network; regulatory network

Year:  2019        PMID: 31545079     DOI: 10.1089/cmb.2019.0237

Source DB:  PubMed          Journal:  J Comput Biol        ISSN: 1066-5277            Impact factor:   1.479


  13 in total

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