Bioinformatics analysis and functional analysis of bladder cancer gene microarray

QIN Song-lin ZHOU Yang HU Wei LIU Bo-long TANG Zheng

Acta Anatomica Sinica ›› 2019, Vol. 50 ›› Issue (3) : 310-316.

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Acta Anatomica Sinica ›› 2019, Vol. 50 ›› Issue (3) : 310-316. DOI: 10.16098/j.issn.0529-1356.2019.03.008
Cancer Biology

Bioinformatics analysis and functional analysis of bladder cancer gene microarray

  • QIN Song-lin1 ZHOU Yang 2* HU Wei1 LIU Bo-long1 TANG Zheng1
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Abstract

Objective To explore the pathogenesis of bladder cancer from the molecular level and provide new ideas for clinical diagnosis and prognosis evaluation. Methods Human bladder cancer-associated gene chip data GSE31189, including 52 bladder cancer samples and 40 normal bladder samples, was downloaded from a database of gene chips, and then Morpheus (https://software.broadinstitute.org/morpheus/) online tools were used to analyze cancer urothelial tissue and normal urothelial tissue. Differentially expressed genes were then analyzed online using gene-cloud of biotechnology information(GCBI) (https://www.GCBI.com.cn) for enrichment of differentially expressed gene signaling pathways and differential gene interactions. Finally, differential selection genes were selected for cell counting kit-8(CCK-8), invasion and Western blotting assays. Initially verify its function. Results According to the q value, the top 20 genes with the largest difference were selected. Among them, 18 genes were up-regulated and 2 genes were down-regulated in bladder cancer. Gene ontology(GO)analysis revealed that these differentially expressed genes are mainly involved in many biological functions such as inflammatory responses, immune responses, negative regulation of apoptosis, and transcriptional negative control from the RNA polymerase Ⅱ promoter. Pathway analysis showed that these differentially expressed genes are involved in biological processes such as transcriptional dysregulation, metabolic pathways, and nuclear factor kappa beta(NF-κB)signaling pathways in cancer. Gene network analysis found that CXC chemokine receptor 4 (CXCR4) and mitogenactivated protein kinase 10(MAPK10)are the central links in these gene networks. In vitro experiments showed that matrix metalloproteindase-12(MMP-12)downregulation led to the decreased proliferation and invasion of bladder cancer cells and the phoshorylation level of extracellular regulated protein kinases(ERK). Conclusion Multiple bioinformatics analysis can identify the key genes in bladder tumors. CXCR4 and MAPK10 are the key links in the bladder gene network. MMP-12 is highly expressed in bladder cancer cells. Downregulation of MMP-12 can inhibit the proliferation and invasion abilities of bladder cancer cells through ERK pathway.

Key words

Bladder cancer / Gene network / Bioinformatics / On-line analysis / Human

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QIN Song-lin ZHOU Yang HU Wei LIU Bo-long TANG Zheng. Bioinformatics analysis and functional analysis of bladder cancer gene microarray[J]. Acta Anatomica Sinica. 2019, 50(3): 310-316 https://doi.org/10.16098/j.issn.0529-1356.2019.03.008

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