A comprehensive evaluation of differentially expressed mRNAs and lncRNAs in cystitis glandularis with gene ontology, KEGG pathway, and ceRNA network analysis

Background

Cystitis glandularis (CG) is a proliferative disorder of the urinary bladder characterized by transitional cells that have undergone glandular metaplasia. The underlying mechanism associated with this transformation is poorly understood.

Methods

The expression of messenger RNA (mRNA) and long non-coding RNA (lncRNA) from normal bladder mucosa and CG were compared using microarray analysis. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was used to describe molecular interactions.

Results

Microarray analysis identified 809 significantly dysregulated mRNAs in CG tissues; 606 were up-regulated and 203 were down-regulated (greater than 2-fold difference in expression from normal tissue, P<0.05). KEGG pathway analysis showed that the mRNAs that co-expressed with lncRNAs were enriched in the cell cycle regulation pathway. Four up-regulated lncRNAs (ENST00000596379, ENST00000463397, NR_001446 and NR_015395) were identified in the coding-non-coding co-expression (CNC) network analysis as being associated with the expression of four mRNAs (SMAD3, ORC1, CCNA2 and CCNB2). NR_015395 was revealed to be a competing endogenous RNA (ceRNA) of miR-133a-3p that targets SMAD3.

Conclusions

This is the first work to measure the expression of dysregulated lncRNA and ceRNA in CG and identify the crosstalk between mRNA and lncRNA expression patterns in the pathogenesis of CG.

Network analysis, and human and animal studies disclose the anticystitis glandularis effects of vitamin C

BACKGROUND

Our present study aimed to unravel the therapeutic biotargets of vitamin C (VC) against cystitis glandularis (CG), and to elucidate the molecular mechanisms for VC treating CG.

METHODS

Network pharmacology was used to predict therapeutic targets of VC against CG, and to identify molecular mechanisms. In addition, further human and animal studies were designed to validate the bioinformatic findings through biochemical tests, computerized tomography scans, and immunostaining assays.

RESULTS

In bioinformatic analyses, pathogenic targets of CG and putative targets of VC were identified, respectively. An interaction network between biological target and functional protein was produced before screening and collecting the key therapeutic targets of VC against CG, biological processes, and signaling pathways. In addition, ingenuity pathway analysis with cloud platform indicated that anti-CG mechanisms of VC were achieved through modulating a cluster of molecular pathways, such as tumor necrosis factor (TNF) pathway. Meanwhile, 18 core targets of VC against CG were identified, and the most important TNF, interleukin-6 (IL6), and Jun biotargets were obtained, respectively. In further validation in human study, cellular TNF-α, IL6, and c-Jun expressions in patient's CG samples were elevated significantly, accompanied with detectable urinary tract infection. Beneficially, VC-dosed CG mice resulted in downregulated expressions of endogenous TNF-α, IL6, and c-Jun in blood and bladder samples.

CONCLUSION

Collectively, these bioinformatic findings and experimentative data uncover the therapeutic targets and biological mechanisms of VC for treating CG, in which the key biomarkers of TNF-α, IL6, and c-Jun may be the potential molecules for treating CG in clinical application.