4.2 Article

A ceRNA Network Composed of Survival-Related lncRNA miRNAs, and mRNAs in Clear Cell Renal Carcinoma

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HINDAWI LTD
DOI: 10.1155/2022/8504441

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资金

  1. National Natural Science Foundation of China [81871837, 81572117]
  2. Open Project Program of Key Laboratory of Preservation of Human Genetic Resources and Disease Control in China (Harbin Medical University), the Ministry of Education [LPHGRDC2021-007]
  3. Specialized Research Fund for Doctoral Program of Higher Education of China [20132307110007]

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Research identified an RNA regulatory mechanism associated with clear cell renal carcinoma (ccRCC) progression, establishing predictive survival models and a ceRNA network which may offer new avenues and potential biomarkers for clinical prognosis and treatment of ccRCC patients.
Clear cell renal carcinoma (ccRCC) is one of the most common renal carcinomas worldwide, which has worse prognosis compared with other subtypes of tumors. We propose a potential RNA regulatory mechanism associated with ccRCC progression. Accordingly, we screened out clinical factors and the expression of RNAs and miRNAs of ccRCC from the TCGA database. 9 lncRNAs (FGF12-AS2, WT1-AS, TRIM36-IT1, AC009093.1, LINC00443, TCL6, COL18A1-AS1, AC110619.1, HOTTIP), 2 miRNAs (mir-155 and mir-21), and 3 mRNAs (COL4A4, ERMP1, PRELID2) were selected from differential expression RNAs and built predictive survival models. The survival models performed very well in predicting prognosis and were found to be highly correlated with tumor stage. In addition, the survival-related lncRNA-miRNA-mRNA (ceRNA) network was constructed by 18 RNAs including 12 mRNAs, 2 miRNAs, and 4 lncRNAs. It is found that the ECM-receptor interaction, Pathways in cancer, and Chemokine signaling pathway as the main pathways in KEGG pathway analysis. Overall, we established predictive survival model and ceRNA network based on multivariate Cox regression analysis. It may open a new approach and potential biomarkers for clinical prognosis and treatment of ccRCC patients.

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