Identification Of Candidate Biomarkers Correlated With The Diagnosis And Prognosis Of Cervical Cancer Via Integrated Bioinformatics Analysis

Background: Cervical carcinoma is one of the most common malignant gynecological tumors and is associated with high rates of morbidity and mortality.Early diagnosis and early treatment can reduce the mortality rate of cervical cancer.However,there is still no specific biomarkers for the diagnosis and detection of cervical cancer prognosis.Objective: The purpose of this article was to find molecular biomarke rs related to diagnosis and prognosis of cervical cancer via integrated bioi nformatics analysis and public database.Methods:The mRNA expression profile datasets(GSE7803,GSE9750,GSE63514)and micro RNA datasets(GSE30656)were downloaded from the Gene Expression Omnibus database(GEO)in Pub Med.The three mRNAs datasets were integrated to one via integrated bioinformatics.Differentially expressed genes(DEGs)and micro RNAs(DEMs)were obtained by R software.Volcano plot and heatmap of DEGs and DEMs were performed via R codes.the DEGs expression products in cervical cancer were constructed using the STRING database to construct PPI networks.They were further processed using Cytoscape software.The validated mi RNAs and the target genes of DEMs in cervical cancer were identified via HMDD tool and mi RWALK2.0 website,respectively.Subsequently,they were taken intersection with DEMs and DEGs screened from GEO respectively.The expression of DEGs in these cervical tissue samples were validated on GEPIA website.Overall survival analysis(OS)and 5-year survival of patients with cervical cancer were analyzed by Onco Lnc database and HPA dataset,respectively.Immunohistochemical staining was carried out to verify the expression of key genes in cervical cancer tissues.Results:1.Total 83 differentially expressed genes(DEGs,12 upregulated mRNAs and 71 downregulated mRNAs)were identified via R software.Meanwhile,14 differentially expressed mi RNAs(DEMs)were obtained using the limma package,including 3 upregulated mi RNAs and 11 downregulated mi RNAs.2.The HMDD database found 47 mi RNAs that have been validated in cervical cancer.After intersecting with above 14 DEMs,it is found that 3 mi RNAs were closely related to cervical cancer(hsa-mi R-21 and hsa-mi R-16 were upregulated and hsa-mi R-205 was down-regulated);Using mi RWALK2.0 predicted the target genes of the above three mi RNAs,it identified that hsa-mi R-21 had five target genes,hsa-mi R-16 possessed five target genes;hsa-mi R-205 exhibited four target genes.these 14 target genes were intersected with the above 83 DEGs from GEO to obtain 11 target genes.According to the characteristics of the negative correlation between mi RNA and target genes,the genes ESR1,PPP1R3 C,NSG1,TMPRSS11 D,KLF4,GYS2,ENDOU were selected out for further analysis.3.GEPIA analysis indicated that KLF4,ESR1 and PPP1R3 C were reduced in cervical cancer tissues.4.Survival analysis showed low expression of KLF4 was associated with poor overall survival rate(OS),and low expression of ESR1 was closely related to poor 5-year survival rate.5.the expression of KLF4 and ESR1 in cervical cancer tissues was significantly lower than that in normal cervical tissues.Conclusion: This study indicates that KLF4 and ESR1 are downregulated by the upregulated mi R-21 and mi R-16 in cervical cancer,respectively.And the lower expression of KLF4 and ESR1 were closely related to the poor prognosis.They might be of clinical significance for the diagnosis and prognosis of cervical cancer,and provide effective targets for the treatment of cervical cancer.