ArticleWorld journal of urology2018
Identification of key genes and construction of microRNA-mRNA regulatory networks in bladder smooth muscle cell response to mechanical stimuli using microarray expression profiles and bioinformatics analysis.
Article in World journal of urology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed, 6 citations in OpenAlex.
- Identification of new Wilms tumour predisposition genes: an exome sequencing study.The Lancet. Child & adolescent health · 2019Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
purposeTo identify keys genes and elucidate miRNA-mRNA regulatory networks in Bladder smooth muscle cell (BSMC) response to mechanical stimuli.
methodsHuman BSMCs, seeded on a silicone membrane, were subjected to mechanical stretch or without stretch. Microarray was used to analyze the differential expression of mRNAs and miRNAs between human BSMCs under mechanical stretch and control static control group. Differentially expressed genes(DEGs) and miRNAs (DEMs) in these two groups were identified. Subsequently, differentially expressed DEGs were conducted with functional analysis, and then PPI network was constructed. Finally, miRNA-mRNA regulatory network was visualized using Cytoscape.
results1639 significant DEGs and three DEMs were identified between the stretch group and control static group. The PPI network of DEGs was constructed by STRING, which was composed of 1459 nodes and 1481 edges, including 188 upregulated genes and 255 downregulated genes. Moreover, 36 genes in the PPI network were identified as hub genes in BSMCs response to mechanical stretch, e.g. CCNH, CPSF2, TSNAX, ARPC5 and PSMD3 genes. Subsequently, 39 clusters were selected from PPI network using MCODE, and it was shown that the most significant cluster consisted of 14 nodes and 91 edges. Besides, miR-503HG was the most significantly downregulated miRNA and was predicted to target five upregulated genes, including SMAD7, CCND3, WIPI2, NYNRIN and PVRL1.
conclusionsOur data mining and integration help reveal the mechanotransduction mechanism of BSMCs' response to mechanical stimulation and contribute to the early diagnosis of bladder outlet obstruction (BOO) as well as the improvement of pathogenesis of BOO treatment.
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