Comprehensive analysis of differentially expressed profiles and reconstruction of a competing endogenous RNA network in papillary renal cell carcinoma.

Abstract

Long noncoding RNAs (lncRNAs) function as competing endogenous RNAs (ceRNAs). ceRNA networks may serve important roles in various tumors, as demonstrated by an increasing number of studies; however, papillary renal cell carcinoma (PRCC)-associated ceRNA networks mediated by lncRNAs remain unknown. Increased knowledge of ceRNA networks in PRCC may aid the identification of novel targets and biomarkers in the treatment of PRCC. In the present study, a comprehensive investigation of mRNA, lncRNA, and microRNA (miRNA) expression in PRCC was conducted using sequencing data from The Cancer Genome Atlas. Differential expression (DE) profiles of mRNAs, lncRNAs and miRNAs were evaluated, with 1,970 mRNAs, 1,201 lncRNAs and 96 miRNAs identified as genes with significantly different expression between PRCC and control paracancerous tissues. Based on the identified DEmRNAs, a protein-protein interaction network was generated using the STRING database. Furthermore, a ceRNA network for PRCC was determined using a targeted assay combined with the DE of miRNAs, mRNAs and lncRNAs, enabling the identification of important lncRNA-miRNA and miRNA-mRNA pairs. Analysis of the ceRNA network led to the extraction of a subnetwork and the identification of lncRNA maternally expressed 3 (MEG3), lncRNA PWRN1, miRNA (miR)-508, miR-21 and miR519 as important genes. Reverse transcription-quantitative polymerase chain reaction analysis was conducted to validate the results of the bioinformatics analyses; it was revealed that lncRNA MEG3 expression levels were downregulated in PRCC tumor tissues compared with adjacent non-tumor tissues. In addition, survival analysis was conducted to investigate the association between identified genes and the prognosis of patients with PRCC, indicating the potential involvement of 13 mRNAs, 15 lncRNAs and six miRNAs. In conclusion, the present study may improve understanding of the regulatory mechanisms of ceRNA networks in PRCC and provide novel insight for future studies of prognostic biomarkers and potential therapeutic targets.