ABSTRACT
@#【Objective】 The two databases，GEO（gene expression omnibus，GEO）and TCGA（the cancer genome alas ，TCGA），were analyzed using bioinformatics methods to screen differentially expressed genes associated and their related regulatory networks in prostate carcinoma. 【Methods】 The prostate carcinoma gene expression chip data （GSE46602 ，GSE55945） downloaded from the GEO database were integrated into the RNA- seq data of the TCGA database. And the differentially expressed genes analysis was performed using GEO2R and the edgeR package of R software to extract common significant differentially expressed genes. The clusterProfiler package of R software was used to enrich the GO（gene ontology ，GO）function enrichment analysis and KEGG（kyoto encyclopedia of genes and genomes， KEGG）pathway analysis. Differentially expressed genes were further constructed into a protein-protein interaction（PPI） network to screen out key genes for regulatory protein expression in prostate carcinoma. Gene analysis results were combined with TCGA clinical follow-up data to analyze the clinical prognostic value of key node genes. 【Results】A total of 278 significant differentially expressed genes were extracted，of which 178 genes were down- regulated and 100 genes were up-regulated. These genes were closely associated with the function and pathway enrichment such as the regulation of proliferation of epithelial cells，metabolism of benzene- containing compounds，the glutathione metabolism，and focal adhesion. The protein-protein interaction network analysis revealed three key protein expression modules and 12 key node genes. Among these key genes，EDN3（endothelin-3），EDNRB（endothelin receptor B）and AMACR（alpha-methylacyl- coa racemase）were closely related to the survival rate of prostate cancer patients. 【Conclusion】Through bioinformatics analysis of gene chip and RNA-seq data in prostate carcinoma，we found that EDN3，EDNRB and AMACR may play an important role in the occurrence and development of prostate carcinoma.
ABSTRACT
The changes of serum cyclophilin A (CyPA), its receptor CD147 and the downstream signaling pathway during the process of cardiac hypertrophy remain unknown. The present study aims to investigate the relationships between CyPA-CD147-ERK1/2-cyclin D2 signaling pathway and the development of cardiac hypertrophy. Left ventricular hypertrophy was prepared by 2-kidney, 2-clip in Sprague-Dawley rats and observed for 1 week, 4 and 8 weeks. Left ventricular hypertrophy was evaluated by ratio of left ventricular heart weight to body weight (LVW/BW) and cardiomyocyte cross sectional area (CSA). CyPA levels in serum were determined with a rat CyPA ELISA kit. Expressions of CyPA, CD147, phospho-ERK1/2 and cyclin D2 in left ventricular myocytes were determined by Western blot and immunostaining. Compared with sham groups, systolic blood pressure reached hypertensive levels at 4 weeks in 2K2C groups. LVW/BW and CSA in 2K2C groups were significantly increased at 4 and 8 weeks after clipping. ELISA results indicated a prominent increase in serum CyPA level associated with the degree of left ventricular hypertrophy. Western blot revealed that the expressions of CyPA, CD147, phospho-ERK1/2 and cyclin D2 in left ventricular tissues were also remarkably increased as the cardiac hypertrophy developed. The results of the present study demonstrates that serum CyPA and CyPA-CD147-ERK1/2-cyclin D2 signaling pathway in ventricular tissues are time-dependently upregulated and activated with the process of left ventricular hypertrophy. These data suggest that CyPA-CD147 signaling cascade might play a role in the pathogenesis of left ventricular hypertrophy, and CyPA might be a prognosticator of the degree of left ventricular hypertrophy.