BackgroundBladder cancer is a malignant tumor in the urinary system with high mortality and recurrence rates. However, the causes and recurrence mechanism of bladder cancer are not fully understood. In this study, we used integrated bioinformatics to screen for key genes associated with the development of bladder cancer and reveal their potential molecular mechanisms.MethodsThe , , and expression profiles were downloaded from the Gene Expression Omnibus database, and these datasets contain 304 tissue samples, including 81 normal bladder tissue samples and 223 bladder cancer samples. The RobustRankAggreg (RRA) method was utilized to integrate and analyze the four datasets to obtain integrated differentially expressed genes (DEGs), and the gene ontology (GO) functional annotation and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis were performed. Protein-protein interaction (PPI) network and module analyses were performed using Cytoscape software. The OncoLnc online tool was utilized to analyze the relationship between the expression of hub genes and the prognosis of bladder cancer.ResultsIn total, 343 DEGs, including 111 upregulated and 232 downregulated genes, were identified from the four datasets. GO analysis showed that the upregulated genes were mainly involved in mitotic nuclear division, the spindle and protein binding. The downregulated genes were mainly involved in cell adhesion, extracellular exosomes and calcium ion binding. The top five enriched pathways obtained in the KEGG pathway analysis were focal adhesion (FA), PI3K-Akt signaling pathway, proteoglycans in cancer, extracellular matrix (ECM)-receptor interaction and vascular smooth muscle contraction. The top 10 hub genes identified from the PPI network were vascular endothelial growth factor A (VEGFA), TOP2A, CCNB1, Cell division cycle 20 (CDC20), aurora kinase B, ACTA2, Aurora kinase A, UBE2C, CEP55 and CCNB2. Survival analysis revealed that the expression levels of ACTA2, CCNB1, CDC20 and VEGFA were related to the prognosis of patients with bladder cancer. In addition, a KEGG pathway analysis of the top 2 modules identified from the PPI network revealed that Module 1 mainly involved the cell cycle and oocyte meiosis, while the analysis in Module 2 mainly involved the complement and coagulation cascades, vascular smooth muscle contraction and FA.ConclusionsThis study identified key genes and pathways in bladder cancer, which will improve our understanding of the molecular mechanisms underlying the development and progression of bladder cancer. These key genes might be potential therapeutic targets and biomarkers for the treatment of bladder cancer.

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Urothelial carcinoma of the bladder (UCB) is one of the commonly diagnosed cancers in the world. The UCB has the highest rate of recurrence of any malignancy. A genome-wide screening of transcriptome dysregulation between cancer and normal tissue would provide insight into the molecular basis of UCB recurrence and is a key step to discovering biomarkers for diagnosis and therapeutic targets. Compared with microarray technology, which is commonly used to identify expression level changes, the recently developed RNA-seq technique has the ability to detect other abnormal regulations in the cancer transcriptome, such as alternative splicing. In this study, we performed high-throughput transcriptome sequencing at ∼50× coverage on a recurrent muscle-invasive cisplatin-resistance UCB tissue and the adjacent non-tumor tissue. The results revealed cancer-specific differentially expressed genes between the tumor and non-tumor tissue enriched in the cell adhesion molecules, focal adhesion and ECM-receptor interaction pathway. Five dysregulated genes, including CDH1, VEGFA, PTPRF, CLDN7, and MMP2 were confirmed by Real time qPCR in the sequencing samples and the additional eleven samples. Our data revealed that more than three hundred genes showed differential splicing patterns between tumor tissue and non-tumor tissue. Among these genes, we filtered 24 cancer-associated alternative splicing genes with differential exon usage. The findings from RNA-Seq were validated by Real time qPCR for CD44, PDGFA, NUMB, and LPHN2. This study provides a comprehensive survey of the UCB transcriptome, which provides better insight into the complexity of regulatory changes during recurrence and metastasis.

Increasing evidence has confirmed that dysregulation of microRNAs (miRNAs) can contribute to the progression and metastasis of human tumors. Previous studied have shown dysregulation of miR-24 in a variety of tumors. However, the roles of miR-24 in human bladder cancer have not been well clarified. Therefore, we investigated the biological functions and molecular mechanisms of miR-24 in human bladder cancer cell lines, evaluating whether it could be a therapeutic biomarker of bladder cancer in the future. In our study, we found that miR-24 is downregulated in human bladder cancer cell lines. Moreover, the low level of miR-24 was associated with increased expression of CARMA3 in bladder cancer cells. Upregulation of miR-24 significantly inhibited proliferation, arrested cell cycle and induced apoptosis in bladder cancer cells. In addition, invasion and epithelial to mesenchymal transition (EMT) of bladder cancer cells was suppressed by overexpressing miR-24. Bioinformatics analysis predicted that the CARMA3 was a potential target gene of miR-24. Further study by luciferase reporter assay demonstrated that miR-24 could directly target CARMA3. Overexpression of CARMA3 in bladder cancer cells transfected with miR-24 mimic partially reversed the inhibitory effect of miR-24. In conclusion, miR-24 inhibited cell proliferation, invasion and EMT in bladder cancer cells by downregulation of CARMA3, and that downregulation of CARMA3 was essential for the miR-24-inhibited cell proliferation, invasion and EMT in bladder cancer cells.