Chongqing 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.
College of Biological and Chemical Engineering, Chongqing University of Education, Chongqing 400067, China.
Biomed Res Int. 2020 Nov 4;2020:6149174. doi: 10.1155/2020/6149174. eCollection 2020.
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.
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.
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.
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.
乳腺癌是一种发生在乳腺腺上皮组织的恶性肿瘤，已成为女性最常见的恶性肿瘤。microRNA（miRNA）对相关基因表达的调控在乳腺癌中起着重要作用。我们构建了一个全面的乳腺癌-miRNA-基因互作图谱。
从 GEO 数据库中获取了三个 miRNA 微阵列数据集（GSE26659、GSE45666 和 GSE58210）。然后，使用 R 软件“LIMMA”包进行差异表达分析。筛选出的差异表达 miRNA（DE-miRNA）的潜在转录因子和靶基因进行预测。从 GEO 数据库中下载 BRCA GE-mRNA 数据集（GSE109169 和 GSE139038），以识别差异表达基因（DE-genes）。接着，进行 GO 注释和 KEGG 通路富集分析。然后构建 PPI 网络，并使用 Cytoscape 软件识别枢纽基因。进一步评估枢纽基因的表达和预后作用。
通过分析 3 个基因表达综合数据库，我们发现了 6 个上调的差异表达 miRNA（DE-miRNA）和 18 个下调的 DE-miRNA，并预测了这些 DE-miRNA 的上游转录因子和下游靶基因。然后，我们使用 GEO 数据库对乳腺癌 mRNA 进行差异分析，获得差异表达的 mRNA。通过相互作用分析，我们找到了 10 个上调的 DE-miRNA 的枢纽基因和 10 个下调的 DE-miRNA 的枢纽基因。
本研究通过综合生物信息学分析，构建了一个更全面的 BRCA-miRNA-基因网络，为 BRCA 的治疗和预后提供了新的靶点和研究方向。
