Identification of breast cancer mechanism based on weighted gene coexpression network analysis.

Our gene expression-profiling analysis aimed to explain the mechanism of breast cancer development by identifying key pathways and constructing networks of related transcription factors (TFs) and microRNAs (miRNAs) in breast cancer tissues. Gene expression profiles of normal and breast cancer tissues were downloaded to identify differentially expressed genes (DEGs). Coexpression modules were explored using weighted gene coexpression network analysis (WGCNA). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were performed to discover the enriched functionally associated gene groups and define pathways in breast cancer, respectively. miRNAs-DEGs and TF-DEG regulatory networks were constructed using Cytoscape. CDK6(cyclin-dependent kinase), miR-124, EGF(epidermal growth factor) and NF-κB(nuclear factor of kappa light polypeptide gene enhancer in B-cells 1) expression was also analyzed using real-time quantitative PCR. Totally, 7713 DEGs were identified for WGCNA. The results revealed that 1388 upregulated DEGs were associated with protein transport, protein localization and organic substance transport, whereas 1819 downregulated DEGs were associated with cancer and Wnt signaling pathways. Five miRNAs (miR-760, miR-1276, miR-124, miR-124-3p and miR-506-3p) with a degree of ⩾15 and one important TF (NF-κB) were identified in miRNA and TF regulatory networks. CDK6 mRNA and miR-124 expression was significantly reduced and EGF mRNA expression was clearly enhanced in cancer tissues compared with those in normal breast tissues. The CDK6 gene could be regulated by miR-124, which is involved in Wnt signaling and cancer pathways. NF-κB might initiate the breast cancer pathway by targeting EGF in human breast cancer tissues. This putative information on regulatory networks in breast cancer will be beneficial for future researches on mechanisms underlying its development.