Jeevitha Priya Manoharan - Department of Biotechnology, PSG College of Technology, Coimbatore-۶۴۱۰۰۴, Tamil Nadu, India
Kavinkumar Nirmala Karunakaran - Department of Biotechnology, PSG College of Technology, Coimbatore-۶۴۱۰۰۴, Tamil Nadu, India
Gomathi Dasarathan - Department of Biotechnology, PSG College of Technology, Coimbatore-۶۴۱۰۰۴, Tamil Nadu, India
Subramanian Vidyalakshmi - Department of Biotechnology, PSG College of Technology, Coimbatore-۶۴۱۰۰۴, Tamil Nadu, India

Background: The transcription factor twist-related protein ۱ (TWIST۱) plays a major role in the prognosis of breast cancer. Our present study aimed to identify the network of TWIST۱ with related oncogenes and their associated miRNAs.Method: This in silico study included the differential expression analysis of genes and miRNA associated with breast carcinoma. The breast cancer patients’ data were retrieved from the Gene Expression Omnibus database and the differential expression analysis was done using GEO۲R. Transfac analysis was performed to determine the binding sites of TWIST۱. We predicted the target genes of MicroRNA-۹۶ (miR-۹۶) using miRBase. An integrated network was generated among TWIST۱ and target genes of miR-۹۶ through Gene MANIA. Survival analysis was carried out for TWIST۱ using UALCAN. Experimental methods, including gene expression analysis, were performed in the MDA-MB-۲۳۱ cell line for validating in silico findings.Results: miR-۹۶, the second differentially expressed miRNA among the top ۲۵۰ miRNAs, was found to have eight binding sites for TWIST۱. TWIST۱ was observed to be significantly correlated with patient prognosis. ACTN۴, BCL۲, and FRMD۴A were upregulated and CAMTA۱, DAB۲IP, and E- Cadherin were downregulated in the expression studies carried out in the MDA-MB-۲۳۱ breast cancer cell line.Conclusion: A network between TWIST۱ and target genes of miR-۹۶ was analyzed. Hence, targeting the genes linked with miR-۹۶ could work toward an efficient therapeutic option for breast cancer metastasis.

Twist-related protein ۱, Gene expression, Omnibus datasets, MicroRNA-۹۶, Survival analysis, MDA-MB-۲۳۱ breast cancer cells