Abstract
Objective Breast cancer (BC) is a heterogeneous type of cancer that occurs as a result of distinct molecular alterations in breast tissue. Although there are many new developments in treatment and targeted therapy for BC in recent years, this cancer type is still the most common one among women with high morbidity and mortality. Therefore, new research is still needed for biomarker detection.
Methods GSE101124 and GSE182471 datasets were obtained from Gene Expression Omnibus (GEO) database to evaluate differentially expressed circular RNAs (circRNAs). The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) databases were used to identify the significantly dysregulated microRNAs (miRNAs) and genes considering the Prediction Analysis of Microarray (PAM50) classification. The circRNA-miRNA-gene relationship was investigated using the Cancer Specific CircRNA (v2.0) (CSCD), miRDB, miRWalk and miRTarBase databases. The circRNA–miRNA–mRNA regulatory network was constructed using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) annotation. The protein-protein interaction network was constructed by the STRING 2021 database and visualized by the Cytoscape tool (v3.9.0). Then, raw miRNA data and genes were filtered using some selection criteria according to a specific expression level in PAM50 subgroups. A bottleneck method was utilized to obtain highly interacted hub genes using cytoHubba Cytoscape plugin. The overall survival (OS) and disease-free survival (DFS) analysis were performed for these hub genes, which are detected within the miRNA and circRNA axis in our study.
Results We identified three circRNAs, three miRNAs, and eighteen candidate target genes that may play an important role in BC. In addition, it has been determined that these molecules can be useful in the classification of BC, especially in determining the basal-like breast cancer (BLBC) subtype.
Conclusions We conclude that hsa_circ_0000515/ miR-486-5p/ SDC1 axis may be an important biomarker candidate in distinguishing patients in the BLBC group, especially according to the PAM50 classification of BC.
Competing Interest Statement
The authors have declared no competing interest.
