Abstract
BackgroundLong non-coding RNAs (lncRNAs) play crucial roles in the initiation and progression of renal cell carcinoma (RCC) by competing in binding to miRNAs, and related competitive endogenous RNA (ceRNA) networks have been constructed in several cancers. However, the coexpression network has been poorly explored in RCC.MethodsWe collected RCC RNA expression profile data and relevant clinical features from The Cancer Genome Atlas (TCGA). A cluster analysis was explored to show different lncRNA expression patterns. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and gene set enrichment analysis (GSEA) were performed to analyze the functions of the intersecting mRNAs. Targetscan and miRanda bioinformatics algorithms were used to predict potential relationships among RNAs. Univariate Cox proportional hazards regression was conducted to determine the RNA expression levels and survival times.ResultsBioinformatics analysis revealed that the expression profiles of hundreds of aberrantly expressed lncRNAs, miRNAs, and mRNAs were significantly changed between different stages of tumors and non-tumor groups. By combining the data predicted by databases with intersection RNAs, a ceRNA network consisting of 106 lncRNAs, 26 miRNAs and 69 mRNAs was established. Additionally, a protein interaction network revealed the main hub nodes (VEGFA, NTRK2, DLG2, E2F2, MYB and RUNX1). Furthermore, 63 lncRNAs, four miRNAs and 31 mRNAs were significantly associated with overall survival.ConclusionOur results identified cancer-specific lncRNAs and constructed a ceRNA network for RCC. A survival analysis related to the RNAs revealed candidate biomarkers for further study in RCC.
Highlights
Renal cell carcinoma (RCC) is among the ten leading cancer types for estimated new cancer cases in both males and females in the United States (Siegel, Miller & Jemal, 2017)
We constructed the competitive endogenous RNA (ceRNA) network through three steps: (1) we identified intersecting Long non-coding RNAs (lncRNAs), miRNAs, and mRNAs that were differentially expressed in four stages; (2) we predicted lncRNA-miRNA interactions by miRanda and used the Targetscan and miRanda databases to find target genes; and (3) we integrated aberrantly expressed data from the The Cancer Genome Atlas (TCGA) and the predicted miRNA information
Three hundred eighty-five differentially expressed lncRNAs were identified between stage III renal cell carcinoma (RCC) tumor tissues and non-tumor RCC tissues, and 404 differentially expressed lncRNAs were identified between stage IV RCC tumor tissues and non-tumor RCC tissues
Summary
Renal cell carcinoma (RCC) is among the ten leading cancer types for estimated new cancer cases in both males and females in the United States (Siegel, Miller & Jemal, 2017). How to cite this article Xing et al (2018), Integrated analysis of differentially expressed profiles and construction of a competing endogenous long non-coding RNA network in renal cell carcinoma. Increasing numbers of studies on RCC have been conducted to explore tumor initiation and progression, including protein-coding RNAs (mRNAs) and non-coding RNAs (ncRNAs) (Frew & Moch, 2015; Lorenzen & Thum, 2016; Martens-Uzunova et al, 2014; Qin et al, 2014; Schmidt & Linehan, 2016); the tumor-specific mechanisms in the regulation of tumor progression and biological behaviors are not fully understood. Long non-coding RNAs (lncRNAs) play crucial roles in the initiation and progression of renal cell carcinoma (RCC) by competing in binding to miRNAs, and related competitive endogenous RNA (ceRNA) networks have been constructed in several cancers. Bioinformatics analysis revealed that the expression profiles of hundreds of aberrantly expressed lncRNAs, miRNAs, and mRNAs were significantly changed between different stages of tumors and non-tumor groups. A survival analysis related to the RNAs revealed candidate biomarkers for further study in RCC
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