Abstract

BACKGROUND: A variety of treatment strategies have been developed for clear cell kidney carcinoma (KIRC); however, there is still a need for effective therapeutic targets and prognostic molecular biomarkers. Given that long noncoding RNAs (lncRNAs) has been emerging as an important regulator in tumorigenesis, we explored potential functional lncRNAs in KIRC by comprehensively analyzing the lncRNA–miRNA–mRNA regulatory network with bioinformatics processing tools.

MATERIAL AND METHODS: RNA-seq/miRNA-seq data of KIRC in The Cancer Genome Atlas (TCGA) were obtained and analyzed. The “edgeR” package in R software was used to identify differentially expressed lncRNAs (DElncRNAs, differentially expressed long noncoding RNAs), miRNAs (DEmiRNAs, differentially expressed micro RNAs), and mRNAs (DEmRNAs, differentially expressed messenger RNAs) in KIRC and normal samples. A global triple network was conducted based on the competing endogenous RNA (ceRNA) theory, and survival analysis was conducted by “survival” package in R software.

RESULTS: A total of 4246 DElncRNAs, 179 DEmiRNAs, and 5758 DEmRNAs were identified, among which a subset of them (321 lncRNAs, 26 miRNAs, and 1068 mRNAs) were found to constitute a global ceRNA network in KIRC. Four lncRNAs (ENTPD3-AS1, FGD5-AS1, LIFR-AS1, and UBAC2-AS1) were revealed to be potential therapeutic targets as well as prognostic biomarkers of KIRC by our extensive functional analysis.

CONCLUSIONS: We reported here the identification of functional lncRNAs in KIRC via a TCGA data-based bioinformatics analysis. We believe that this study might contribute to improving the comprehension of the lncRNA-mediated ceRNA regulatory mechanisms in the tumorigenesis of KIRC. Meanwhile, our results suggested that 4 lncRNAs might act as potential therapeutic targets or candidate prognostic biomarkers in KIRC.

Keywords: Carcinoma, Renal Cell