Bioinformatics Analysis Of Clear Cell Renal Cell Carcinoma And Construction Of CeRNA Regulatory Network

Objective: The aim of this study was to screen the genes and signaling pathways closely related to clear cell renal cell carcinoma(ccRCC)in TCGA database by bioinformatics method and analyze their biological functions.To construct the ceRNA regulatory network based on differentially expressed lncRNAs,miRNAs and mRNAs in ccRCC.To investigate the expression of key genes in the regulatory network and the relationship between them and the clinical prognosis of patients,and to analyze the possible molecular mechanism,providing a theoretical basis for the selection of targeted therapy for ccRCC.Materials and Methods: Transcriptome data of ccRCC and its clinical follow-up information were downloaded from the TCGA database,and the raw data were converted into gene expression profile matrices of lncRNAs,miRNAs,and mRNAs.The differential genes of the three RNAs were extracted separately using the software package with built-in "R" to draw a volcano plot of the differential genes.The protein interaction network of ccRCC differential mRNAs was constructed using STRING 11.0 software,and the top 25 genes with the highest degree of relationship with other nodes were selected to analyze their biological functions.GO analysis and KEGG pathway enrichment analysis were performed on the selected differential mRNAs to explore their biological functions,cellular localization and the biological processes involved.The relationship pairs between lncRNAs and miRNA interactions were downloaded using the LncBase Predicted v.2 database,and the target genes of differential miRNAs were predicted at the miRWalk website.The above data were compared and intersected with differential RNAs to finally obtain the ceRNA regulatory network of ccRCC.The survival analysis of the three RNAs in the ceRNA network and the survival curve were performed using the "Survival" package of the R language,and the gene expression levels of the mRNAs showing significant differences were verified in the GEPIA database.Combined with the clinicopathological information of ccRCC patients in the TCGA database,SPSS 22.0 software was used to analyze the factors affecting the changes in differential mRNA gene expression levels.Cancer tissues and adjacent non-cancerous tissues were collected from 7 ccRCC patients who underwent surgical resection in the Department of Urology of our hospital,and some mRNAs were selected for RT-PCR validation to determine whether there were differences in expression levels.Results: A total of 602 ccRCC transcriptome data(530 tumor samples and 72 normal samples)and 587 miRNA data(516 tumor samples and 71 normal samples)were downloaded from the TCGA database.The resulting mRNAs,lncRNAs,and miRNAs that were differentially expressed in ccRCC were 1937,639,and 200,respectively.The 25 genes represented by PPI network maps KNG1,C3,BDKRB2,PMCH,MCHR1,LPAR5,CASR,NMUR2,C3AR1,F2,CCNA2,CD3 G,CXCR4,GCGR,KIF20 A,TACR1,CCL4,AURKB,BUB1,CCR5,CHRM1,UBE2 C,CD3D,CXCR3,and CXCL10 have the strongest degree and are regarded as the center of the network and can be used as candidate genes to explore the mechanism of ccRCC occurrence and development.GO enrichment analysis showed that the differentially expressed mRNAs were mainly located in the plasma membrane and extracellular region,with transporter activity,signal transduction activity,and molecular transducer activity,which played an important role in the regulation of signal transduction,ion transport,and immune response defense responses.KEGG pathway enrichment analysis results showed that the differentially expressed mRNAs in ccRCC were mainly involved in constituting 30 signaling pathways.Most of which were immune-related signaling pathways,which were: natural killer cell-mediated cytotoxicity pathway,graft-versus-host disease pathway,rheumatoid arthritis pathway,primary immunodeficiency pathway,allograft rejection pathway,autoimmune thyroid disease pathway,antigen processing and presentation pathway,T cell receptor signaling pathway,and chemokine signaling pathway.By performing a comparative intersection of differential mRNAs,lncRNAs,as well as miRNAs,the ceRNA regulatory network of ccRCC was finally successfully constructed,with a total of 14 lncRNA-miRNA-mRNA regulatory pathways in accordance with ceRNA theory.The results of survival analysis in this study showed that a total of 21 differential RNAs showed significant differences in survival prognosis analysis,including 8 mRNAs,12 lncRNAs,and 1 miRNA.Combined with the validation results of partial mRNA gene expression levels by GEPIA database,the correlation analysis was performed between the changes of gene expression levels of TICRR,FMNL1,CLDN10 and FREM1 and the clinicopathological information of patients.The results suggested that the expression levels of TICRR and FMNL1 were up-regulated in ccRCC and positively correlated with the tumor stage of patients,and abnormal platelet levels could affect the expression levels of TICRR;the expression levels of CLDN10 and FREM1 were down-regulated in ccRCC tissues,and their expression levels were negatively correlated with the tumor stage.RT-PCR results suggested that TICRR and FMNL1 expression levels were increased in ccRCC patient cancer tissues compared with those in ccRCC patients,and CLDN10 expression levels were decreased in ccRCC patient cancer tissues.Conclusion: Immune-related signaling pathways play an important role in the occurrence and development of ccRCC,and 14 ceRNA regulatory pathways represented by ENSG00000188242/hsa-miR-16-1-3p/CLDN10 may affect the occurrence and development of ccRCC at different stages,providing a reference basis for the diagnosis,targeted therapy,and prognosis of ccRCC.TICRR and FMNL1 may be highly expressed in ccRCC as oncogenes,and their expression levels are positively correlated with tumor stage;CLDN10 and FREM1 may be lowly expressed in ccRCC as tumor suppressor genes,and their expression levels are negatively correlated with tumor stage.