Identification of differentially expressed miRNAs and mRNAs associated with the regulation of breast cancer via in silico and in vitro methods

Abstract

miRNA expressions are altered during development of breast cancer (BC). The aim of this study is to identify novel cancer-related miRNAs and pathways to understand the mechanisms of BC subtypes. GSE59247 dataset was downloaded from gene expression omnibus (GEO) database and analyzed with GEO2R software. The differential miRNA expressions in BC cells were evaluated by miRNome PCR array. Venn diagram was used to reveal co-differentially expressed miRNAs between GSE59247 dataset and miRNome array. Clinical prognostic significance of selected miRNAs was evaluated via Kaplan Meier curve. KEGG pathway enrichment analysis was performed to find miRNA targets and results were validated by TNM plot analysis and q-RT-PCR. TargetScan database was used to predict the association of miRNAs and 3'-untranslated regions of target genes and their expressions were visualized by human protein atlas database. Venn diagram analysis showed overlap of 11 miRNAs from in silico and in vitro analysis. KEGG analysis revealed `Lysine Degradation Pathway' as the most significantly enriched targeted pathway. q-RT-PCR results confirmed that Lysine degradation pathway related genes SETD7, SETDB2, EHHADH, SETMAR, KMT2A and SUV39H2 were differentially expressed in BC cells. Target prediction analysis identified binding sites between miR-1323-5p and 3'-UTR of SETD7, miR-129-5p and 3'-UTR of EHHADH and miR-628-5p and 3'-UTR of SETDB2 mRNA. Notably, miR-1323-5p, miR-129-5p, and miR-628-5p are differentially expressed in BC and they bind to 3'UTR of critical genes of Lysine degradation pathway, namely SETD7, SETDB2 and EHHADH. These miRNAs might serve as potential diagnostic and prognostic biomarkers for progression.