Screening Of Key Genes For Bladder Cancer And Analysis Of Their Correlation With Clinical Characteristics

Objective:Bladder cancer is very common in urological diseases.In recent years,the incidence of bladder cancer in China has increased,although many positive treatment measures were taken,but the survival condition of patients with advanced or metastatic bladder cancer is still poor,at the same time,the prognosis of patients with bladder cancer surveillance is also a difficult problem in disease management,so looking for a reliable molecular markers for early diagnosis and prognosis monitoring become a research hotspot issues.In this study,by comparing the gene expression of bladder cancer and normal tissues in the GEO database,genes that are highly correlated with the occurrence and development of bladder cancer were selected,and the relationship between gene expression level and various clinical data parameters and prognosis was further analyzed,and the molecular mechanism of these genes was explored.It provides a scientific basis for finding potential molecular diagnostic markers and accurate targeted therapy for bladder cancer.Methods:The key word "bladder cancer" was retrieved from GEO database,and the data of bladder cancer gene chip was downloaded.The differentially expressed genes were screened by GEO2 R,the online analysis tool of GEO database.The differentially expressed genes were enriched by GO and KEEG,and their molecular functions and signaling pathways were studied.String online tool was applied to construct protein-protein interaction network,Cytoscape software was downloaded,and MCODEplug-in in the application software was used to analyze key genes in protein interaction network.The relationship between key genes and prognosis was searched in GEPIA website,and the relationship between the expression level of key(Hub)genes and pathological grade,age,gender and TNM stage was analyzed by chi-square test of SPSS25.0 software.Results:Two gene-chip data sets GSE13507 and GSE37815 were obtained from the GEO database.The online analysis tool of GEO2 R screened 214 common differentially expressed genes,including 36 highly expressed genes and 178 low-expressed genes.Functional enrichment of GO and KEGG showed that upregulation genes were mainly concentrated in cell adhesion,exosomes,protein binding,pi3k-akt signaling pathway,complement and coagulation cascade.Down-regulated genes were mainly concentrated in mitotic chromosome condensation,mitotic cell division,ATP binding,cell cycle and P53 signaling pathway.After the PPI network was built by the String online tool,22 core genes that are highly correlated with bladder cancer development and development were screened out by the MCODE plug-in of Cytoscape software: TK1,DCN,COL16A1,STON1,MS4A6 A,APOD,SDPR,CCNB2,KIF2,AURKB,CDC20,TPX2,TTK,PRC1,DTL,CDT1,CENPN,TOP2 A,NUSAP1,NCAPG,SPAG5,GINS2.Among them,STON1,DCN,APOD and SDPR genes were related to the clinical prognosis of bladder cancer,and STON1,DCN and APOD genes were related to the clinical TNM stage and pathological grade(p<0.05).Conclusion:This article proves the bladder cancer can be effectively acquired by the method of bioinformatics and genetic variations in normal tissue adjacent to carcinoma,and through the analysis of the clinical data of database,can draw gene expression level and clinical prognosis,the relationship between clinical stage,pathological level,these genes may asa potential molecular markers of diagnosis of bladder cancer or target for the treatment of bladder cancer.But the real application of these results will require further biological validation and more clinical research.