Mohammad Mehdi Bordbar - Faculty of Sciences and Advanced Technologies in Biology, University of Science and Culture, Tehran, Iran
Iman Samei Mosleh - Genetic Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran
Shirin Ghadami - Genetic Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran
Amir Amiri Yekta - Department of Genetics, Reproductive Biomedicine Research Center, Royan Institute for Reproductive

Breast cancer is the most common malignancy and the second leading cause of cancer death among women. Genetic factors, along with other factors, playan important role in the development of breast cancer. In this regard, it is important to study the mechanisms of its occurrence and identify diagnostic and prognostic markers, as well as determine appropriate treatment strategies. Using the expression network analysis and pathway approaches in thegenes associated with this disease can provide a deeper understanding of the biological processes associated with it. Therefore, considering the potential of coding genes in prognosis and determining appropriate treatment strategies, in this study, through bioinformatics analysis, mRNAs with thehighest association with breast cancer were selected and their role was investigated. Methods: In this study, based on the raw microarray datareceived from the GEO1 database related to breast tumor tissue in comparison with normal tissue, with access code GSE41970, by using R software and Limma package, differentially expressed genes were obtained. Then after mapping the co-expression network using Cytoscape software, Key coding genes associated with breast cancer were obtained, and important biological pathways for them were identified by the CluGO plugin in Cytoscape software.Results: According to the analyzes, CDK1, PCNA, E2F1, CCNA2, TYMS, CHEK1, MYBL2, TOP2A genes were identified as key mRNAs and were shown to be generally involved in cell cycle checkpoints and histone phosphorylation. Conclusion: according to the mRNAs identified based on bioinformatics analysis and the role of cell cycle checkpoints pathways in Breast cancer, it can be predicted that these coding genes may play a role in Breast cancer, but moreresearch at the laboratory and clinical levels is also necessary in this way

Breast Cancer, Bioinformatics, mRNA, Expression network analysis