Bioinformatics Analysis Of Key MRNA-miRNA-lncRNA In Renal Cell Clear Cell Carcinoma Based On GEO Database

Purpose: The global incidence of renal cancer(RC)is increasing every year,accounting for about 3% of all adult malignancies,renal cell clear cell carcinoma(ccRCC)is the highest incidence of renal cancer Subtype,accounting for about 75% of all kidney cancers.The role of mRNA-miRNA-lncRNA regulatory axes in cancer gene expression is currently widely recognized,which has important implications for tumor screening,prevention,and treatment.This study aims to integrate the three data sets in the GEO database by bioinformatics technology to find the mRNA-miRNA-lncRNA regulatory axes in ccRCC and exploring new biomarkers for ccRCC.Methods Screening of differentially expressed genes(DEGs)in the three GEO data(GSE781 GSE6433 GSE11151)of ccRCC and normal kidney tissue by R language.FUNRICH software and KOBAS website are used for Gene Ontology(GO),Kyoto Encyclopedia of Genes and Genomes(KEGG)and PANTHER functional enrichment analysis on selected DEGs.The STRING database was used to construct the functional protein association network corresponding to DEGs,and the central DEGs were calculated by the Cytohubba plug-in in Cytoscape software.The miRTarbase,miRWALK,and starbase databases were used to predict key miRNAs and key lncRNAs upstream of DEGs,and oncolnc and GEPIA sites were used for survival analysis.Results Through enrichment analysis,it was found that Up-regulated genes were enriched in the HIF-1-alpha transcription factor network,Cell Adhesion Molecule(CAM),et.al.Down-regulated genes were enriched in Tyrosine metabolism,MAPK signaling pathway et,al.From the protein-protein interaction network,the top 30up-regulated mRNAs and 30 down-regulated mRNAs were screened according to the DEGREE algorithm,3 significant up-regulated mRNAs(C3?IRFT?T1MP1)and 11 meaningful down-regulated mRNAs(ATP1A1?FABP1?FGF1?GSTMS?PLG?SLC12A1?SLC22A7?SLC22A8?SLC34A1?SLC12A3?UMOD)were obtained by expression and prognosis analysis.Among them,ATP1A1,FABP1,FGF1,SLC12A1,and UMOD genes have been confirmed to be related to the occurrence of kidney cancer.Further,according to the expression and prognosis of miRNA,8 miRNAs(miR-30c-1-3p?miR-30c-2-3p?miR-445-3P ?miR-18a-5p?miR-92b-3p?miR-130b-5p?miR-153-5p?miR-193b-3p)related to the ccRCC survival rate were obtained.Then,four lncRNAs corresponding to miRNAs were selected by differential expression and survival curves: PVTC1,CASO2,PWAR5,and DANCR.Finally,four mRNA-miRNA-lncRNA regulatory axes were obtained:C3-has-miR-455-3p-PVT1,GSTM3-has-miR-92b-3p-PWAR5,ATP1A1-has-miR-193b-3p-DANCR,ATP1A1-has-miR-18a-5p-CASC2.Conclusion In this study,through bioinformatics analysis,four mRNA-miRNA-lncRNA regulatory axes related to ccRCC were obtained.Each of theseRNAs on the regulatory axis can be used as a gene target of ccRCC for scholars to study,which will provide a new direction for further research and experiments on ccRCC.