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CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis
Published on: April 25, 2022
Construction of a Potential Breast Cancer-Related miRNA-mRNA Regulatory Network
Xinhong Liu1,2, Feng Chen3, Fang Tan4
1Chongqing Collaborative Innovation Center for Functional Food, Chongqing Engineering Research Center of Functional Food, Chongqing Engineering Laboratory for Research and Development of Functional Food, Chongqing University of Education, Chongqing 400067, China.
Background:
Breast cancer is a malignant tumor that occurs in the epithelial tissue of the breast gland and has become the most common malignancy in women. The regulation of the expression of related genes by microRNA (miRNA) plays an important role in breast cancer. We constructed a comprehensive breast cancer-miRNA-gene interaction map.
Methods:
Three miRNA microarray datasets (GSE26659, GSE45666, and GSE58210) were obtained from the GEO database. Then, the R software "LIMMA" package was used to identify differential expression analysis. Potential transcription factors and target genes of screened differentially expressed miRNAs (DE-miRNAs) were predicted. The BRCA GE-mRNA datasets (GSE109169 and GSE139038) were downloaded from the GEO database for identifying differentially expressed genes (DE-genes). Next, GO annotation and KEGG pathway enrichment analysis were conducted. A PPI network was then established, and hub genes were identified via Cytoscape software. The expression and prognostic roles of hub genes were further evaluated.
Results:
We found 6 upregulated differentially expressed- (DE-) miRNAs and 18 downregulated DE-miRNAs by analyzing 3 Gene Expression Omnibus databases, and we predicted the upstream transcription factors and downstream target genes for these DE-miRNAs. Then, we used the GEO database to perform differential analysis on breast cancer mRNA and obtained differentially expressed mRNA. We found 10 hub genes of upregulated DE-miRNAs and 10 hub genes of downregulated DE-miRNAs through interaction analysis.
Conclusions:
In this study, we have performed an integrated bioinformatics analysis to construct a more comprehensive BRCA-miRNA-gene network and provide new targets and research directions for the treatment and prognosis of BRCA.
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