Expression analysis of selected miR-206 targets from the transforming growth factor-β signaling pathway in breast cancer.
Mahnaz Seifi-AlanAli DianatpourLobat GeranpayehReza MirfakhraieMir D OmraniSeyedeh Morvarid NeishabouriPublished in: Journal of cellular biochemistry (2019)
Breast cancer as a molecularly heterogeneous malignancy is associated with dysregulation of several signaling pathways, including transforming growth factor-β (TGF-β) signaling. On the other hand, several recent studies have demonstrated the role of microRNAs (miRNAs) in breast cancer pathogenesis. In the current study, we performed a computerized search to find miR-206 target genes that are functionally linked to the TGF-β signaling pathway. We selected LEF1, Smad2, and Snail2 genes to assess their expression in 65 breast cancer samples and their adjacent noncancerous tissues (ANCTs) in correlation with expression levels of miR-206 as well as clinicopathological characteristics of patients. miR-206 was significantly downregulated in (Estrogen receptor) ER-positive breast cancer samples compared with their corresponding ANCTs. Association analysis between expression levels of genes and demographic features of patients showed significant association between expressions of SMAD2 and LEF1 genes and body mass index ( P values of 0.03 and 0.02, respectively). miR-206 low-expression levels were associated with TNM stage, mitotic rate, and lymph node involvement ( P values of 0.02, 0.01, and 0.01 respectively). In addition, SMAD2 high-expression levels were associated with HER2 status ( P = 0.02). Consequently, our data highlight the role of TGF-β signaling dysregulation in the pathogenesis of breast cancer and warrant further evaluation of miRNAs and messenger RNA coding genes in this pathway to facilitate detection of cancer biomarkers and therapeutic targets.
Keyphrases
- transforming growth factor
- epithelial mesenchymal transition
- poor prognosis
- signaling pathway
- long non coding rna
- cell proliferation
- genome wide
- end stage renal disease
- estrogen receptor
- body mass index
- lymph node
- long noncoding rna
- ejection fraction
- pi k akt
- positive breast cancer
- prognostic factors
- genome wide identification
- chronic kidney disease
- bioinformatics analysis
- peritoneal dialysis
- gene expression
- patient reported outcomes
- induced apoptosis
- dna methylation
- physical activity
- genome wide analysis
- weight loss
- radiation therapy
- transcription factor
- weight gain
- papillary thyroid
- artificial intelligence
- deep learning
- neoadjuvant chemotherapy