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.