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Screening of miRNAs related to prognosis of triple-negative breast cancer and its gene network based on TCGA Database
Yueying SONG,Chao GAO,Wenjun CHEN,Aiyu SHAO,Yichun QIAO,Zhuolin LI
PDF(2406 KB)
PDF(2406 KB)
Screening of miRNAs related to prognosis of triple-negative breast cancer and its gene network based on TCGA Database
),Zhuolin LI2()Objective To identify the key microRNAs （miRNAs） and their target genes associated with the prognosis of triple-negative breast cancer （TNBC） and to discuss their roles in regulatory biological functions and signaling pathways， and to provide the theoretical basis for the selection of prognostic biomarkers for the patients with TNBC. Methods The differentially expressed miRNAs between the TNBC patients and non-TNBC patients were selected based on The Cancer Genome Atlas （TCGA） Database； survival analysis was used to clarify the miRNAs related to the prognosis of the patients；miRDB and miRWalk3.0 online Databases were used to screen for the miRNA target gene； Cytoscape 3.8.2 software was used to elucidate the miRNA-messenger RNA （mRNA） regulatory network；the limma package in R software was used to screen the differentially expressed miRNAs of the TNBC patients and non-TNBC patients； the clusterProfiler package in R software was used to analyze the biological functions and pathways involved by the target genes. Results The survival analysis results showed that miR-9， miR-17， miR-31， miR-146a， miR-188， and miR-190b were associated with the prognosis of the TNBC patients， and low expression levels of these miRNAs were correlated with the poorer prognosis of the patients. A total of 224 target genes regulated by these six miRNAs were identified. The Gene Ontology （GO） functional enrichment analysis results showed that the target genes were primarily involved in the development of mammary alveoli， positive regulation of DNA transcription， and angiogenesis.The Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis results showed that the target genes were mainly enriched in cytokine-cytokine receptor interaction and insulin secretion signaling pathways. The network analysis results identified the key genes in the regulatory network， including solute carrier family 24 member 2 （SLC24A2）， vav guanine nucleotide exchange factor 3 （VAV3）， tripartite motif containing 36 （TRIM36）， synaptotagmin 1 （SYT1）， pleckstrin and Sec7 domain containing 3 （PSD3）， peroxisome proliferator-activated receptor α （PPARA）， RNA polymerase Ⅲ subunit G （POLR3G）， pleomorphic adenoma gene 1 （PLAG1）， ubiquitin associated and SH3 domain containing B （UBASH3B）， and SH3 domain and tetramerization domain containing 2 （SH3TC2）； the interactions of miRNA-mRNA of miR-9-SYT1， miR-9-KIF13B， miR-9-KITLG， miR-17-SLC24A2， miR-31-SLC24A2，miR-146a-SYT1， miR-146a-KIF13B， miR-188-SLC24A2， and miR-188-SLC24A2 were the closest. Conclusion MiR-9， miR-17， miR-31， miR-146a， miR-188， miR-190b and their target genes are involved in physiological processes such as mammary alveolar development and angiogenesis， which are closely associated with the poor prognosis of the patients with TNBC.
Triple negative breast cancer / MicroRNA / Prognosis / Regulatory network / Target gene
R737.9
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