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Updated: Feb 4, 2026

RNA Pull-down Procedure to Identify RNA Targets of a Long Non-coding RNA
Published on: April 10, 2018
Construction and comprehensive analysis of dysregulated long non-coding RNA-associated competing endogenous RNA
Jiawu Wang1, Chengyao Zhang2, Weiyang He1
1Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Objective:
This study aimed to assess the long noncoding RNA (lncRNA)-microRNA (miRNA)-messenger RNA (mRNA) regulatory network in clear cell renal cell carcinoma (ccRCC) by gene expression analyses.
Materials And Methods:
LncRNA, miRNA, and mRNA expression profiles in ccRCC were obtained from The Cancer Genome Atlas. Differentially expressed lncRNAs, mRNAs (cut-off: |log 2 [fold change, FC])| > 2.0 and adjusted P < 0.01) and miRNAs (|log 2FC| > 1.5 and adjusted P < 0.01) were unveiled using R. Cox regression analysis was performed to identify prognostic factors of ccRCC related to overall survival (OS). A protein-protein interaction (PPI) network was constructed for differentially expressed mRNAs (DEmRNAs) by Search Tool for the Retrieval of Interacting Genes (STRING). Key hub genes were screened from top 300 DEmRNAs. LncRNA-miRNA and miRNA-mRNA regulatory network were constructed and combined into the competing endogenous RNA regulatory network. Gene ontology biological terms were screened by STRING; Kyoto Encyclopedia of Genes and Genomes pathways were identified using the "clusterProfiler" package in R.
Results:
A total of 2331, 1517, and 83 DEmRNAs, lncRNAs, and miRNAs were identified, respectively. Eleven lncRNAs (AC016773.1, HOTTIP, LINC00460, NALCN-AS1, PVT1, TRIM36-IT1, WT1-AS, COL18A1-AS1, LINC00443, LINC00472, and TCL6), three miRNAs (hsa-mir-21, hsa-mir-144, and hsa-mir-155), and three mRNAs (COL4A4, NOD2, and GOLGA8B) were associated with OS. Specifically, four lncRNAs (PVT1, LINC00472, TCL6, and WT1-AS1) and one mRNA (Collagen Type IV Alpha 4 Chain) were verified as independent prognostic factors by Gene Expression Profiling Interactive Analysis. Eleven key hub genes were obtained by PPI analysis. "Cell adhesion molecules (CAMs)," "chemical carcinogenesis," and "cytokine-cytokine receptor interaction" were significantly enriched in the network.
Conclusion:
The findings clarify the pathogenesis of ccRCC and might provide potential therapeutic targets.
Insights
Researchers analyzed the regulatory network in clear cell renal cell carcinoma (ccRCC), identifying key long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) linked to patient survival and potential therapeutic targets.
Area of Science:
- Oncology
- Molecular Biology
- Bioinformatics
Background:
- Clear cell renal cell carcinoma (ccRCC) is a significant health concern with complex molecular underpinnings.
- Understanding the regulatory mechanisms involving long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) is crucial for ccRCC research.
Purpose of the Study:
- To elucidate the lncRNA-miRNA-mRNA regulatory network in ccRCC.
- To identify potential prognostic biomarkers and therapeutic targets for ccRCC.
Main Methods:
- Gene expression profiles for lncRNAs, miRNAs, and mRNAs were analyzed from The Cancer Genome Atlas.
- Differentially expressed genes and miRNAs were identified, and Cox regression was used to find prognostic factors.
- Protein-protein interaction networks and competing endogenous RNA (ceRNA) networks were constructed.
Main Results:
- A total of 2331 differentially expressed mRNAs, 1517 lncRNAs, and 83 miRNAs were identified.
- Eleven lncRNAs, three miRNAs, and three mRNAs were significantly associated with overall survival (OS).
- Four lncRNAs and one mRNA were confirmed as independent prognostic factors, and key hub genes were identified.
Conclusions:
- The study clarifies the pathogenesis of ccRCC by detailing its complex regulatory network.
- The identified lncRNAs, miRNAs, and mRNAs represent potential therapeutic targets for ccRCC treatment.
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