Identification of potential microRNA diagnostic panels and uncovering regulatory mechanisms in breast cancer pathogenesis

Abstract

Early diagnosis of breast cancer (BC), as the most common cancer among women, increases the survival rate and effectiveness of treatment. MicroRNAs (miRNAs) control various cell behaviors, and their dysregulation is widely involved in pathophysiological processes such as BC development and progress. In this study, we aimed to identify potential miRNA biomarkers for early diagnosis of BC. We also proposed a consensus-based strategy to analyze the miRNA expression data to gain a deeper insight into the regulatory roles of miRNAs in BC initiation. Two microarray datasets (GSE106817 and GSE113486) were analyzed to explore the differentially expressed miRNAs (DEMs) in serum of BC patients and healthy controls. Utilizing multiple bioinformatics tools, six serum-based miRNA biomarkers (miR-92a-3p, miR-23b-3p, miR-191-5p, miR-141-3p, miR-590-5p and miR-190a-5p) were identified for BC diagnosis. We applied our consensus and integration approach to construct a comprehensive BC-specific miRNA-TF co-regulatory network. Using different combination of these miRNA biomarkers, two novel diagnostic models, consisting of miR-92a-3p, miR-23b-3p, miR-191-5p (model 1) and miR-92a-3p, miR-23b-3p, miR-141-3p, and miR-590-5p (model 2), were obtained from bioinformatics analysis. Validation analysis was carried out for the considered models on two microarray datasets (GSE73002 and GSE41922). The model based on similar network topology features, comprising miR-92a-3p, miR-23b-3p and miR-191-5p was the most promising model in the diagnosis of BC patients from healthy controls with 0.89 sensitivity, 0.96 specificity and area under the curve (AUC) of 0.98. These findings elucidate the regulatory mechanisms underlying BC and represent novel biomarkers for early BC diagnosis.