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Archive > Volume 26 Issue 10 > 2019,26(10):1128-1133. DOI:10.3872/j.issn.1007-385X.2019.10.012 Prev Next
Clinical Research
Screening of colorectal cancer associated lncRNA, miRNA and mRNA based on bioinformatics technology and analysis of their biological functions
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Abstract:
[Abstract] Objective: To screen differentially expressed lncRNA, miRNA and mRNA in colorectal cancer (CRC) in TCGA database,and to explore their relationship with CRC prognosis and related biological functions. Methods: RNA sequencing (RNA-Seq) data and miRNA-Seq data of CRC samples were downloaded from the TCGA database and analyzed, and differentially expressed lncRNA, miRNA and mRNA were screened by R program. The lncRNA-miRNA-mRNA ceRNA network in CRC was constructed by analyzing and integrating the relationships between differentially expressed RNAs through miRcode, TargetScan and miRTarbase databases.Kaplan-Meier method was used to analyze the relationship between the expression of lncRNA, miRNA, mRNA in ceRNA network and the survival prognosis of patients.Finally, the signal pathways involved in the occurrence and development of CRC were analyzed by GSEA functional enrichment analysis software. Results: A total of 614 differentially expressed lncRNAs, 244 differentially expressed miRNAs,and 12 672 differentially expressed mRNAs in CRC were identified; a ceRNA network consisting of 139 lncRNAs, 37 miRNAs and 228 mRNAs was constructed;It was found that 58 lncRNAs, 23 miRNAs, and 150 mRNAs were associated with the prognosis of CRC.The results of GSEA enrichment analysis showed that mRNA was mainly involved in signaling pathways such as Notch, Hedgehog and TGF-β. Conclusion: CRC-related ceRNA network was successfully constructed and lncRNAs, miRNAs and mRNAs associated with CRC prognosis were screened. It provides a valuable preliminary basis for further in-depth clinical research and basic experimental research on CRC.
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Project Supported:
Project supported by the National Natural Science Foundation of China (No. 81560407), and Guizhou Provincial Oncology PostgraduateWorkstation (No. GZZ [2016]06)
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