An In Silico Approach to Define Potential Biomarkers of miRNA-Associated ceRNAs for Breast Cancer

Abstract

Breast cancer (BC) is the most common type of cancer with the highest incidence in women. Particularly in breast cancer, competing endogenous RNAs (ceRNAs) play crucial roles in a variety of metabolic pathways including proliferation, migration, and apoptosis. The aim of the present study is to identify combinatorial target genes (ceRNAs) by employing in silico research to identify miRNAs specific to BC. The other aim was to determine possible biomarkers for the diagnosis of BC by selecting those containing the Transcribed Ultra Conserved Region (T-UCR). Using the miRWalk database, 40 miRNAs that have been experimentally shown to be clinically linked with BC were found. T-UCR-containing genes with potential ceRNA activity were identified. Genes with statistically significant changes in expression between BC and normal breast tissue were identified using the GEPIA. The relationship of the CLK3 and NFAT5 genes was found using the Spearman correlation test. The Spearman correlation test was used to determine the association between the CLK3 and NFAT5 genes, and the genes were found to be significantly less expressed in BC. The NFAT5 and CLK3 gene pair have been found to be associated with BC (p<0.001; r=0.35), and may function as useful biomarkers for BC.