Melatonin decreases estrogen receptor binding to estrogen response elements sites on the OCT4 gene in human breast cancer stem cells

Cancer stem cells (CSCs) pose a challenge in cancer treatment, as these cells can drive tumor growth and are resistant to chemotherapy. Melatonin exerts its oncostatic effects through the estrogen receptor (ER) pathway in cancer cells, however its action in CSCs is unclear. Here, we evaluated the effect of melatonin on the regulation of the transcription factor OCT4 (Octamer Binding 4) by estrogen receptor alpha (ERα) in breast cancer stem cells (BCSCs). The cells were grown as a cell suspension or as anchorage independent growth, for the mammospheres growth, representing the CSCs population and treated with 10 nM estrogen (E2) or 10 μM of the environmental estrogen Bisphenol A (BPA) and 1 mM of melatonin. At the end, the cell growth as well as OCT4 and ERα expression and the binding activity of ERα to the OCT4 was assessed. The increase in number and size of mammospheres induced by E2 or BPA was reduced by melatonin treatment. Furthermore, binding of the ERα to OCT4 was reduced, accompanied by a reduction of OCT4 and ERα expression. Thus, melatonin treatment is effective against proliferation of BCSCs in vitro and impacts the ER pathway, demonstrating its potential therapeutic use in breast cancer.

A two-scale mathematical model for DNA transcription

Unlike the earlier description of regulation of DNA transcription as a biological switch which simply turns on and off, scientists now understand that DNA transcription is a much more complex process. It can depend on several transcription factors (proteins) and DNA regulatory elements (transcription factor binding sites). The combination of these two groups of different scaled factors determines the transcription outcome. In this paper, we propose a two-scale mathematical model for the DNA transcription processes, which integrates the characteristics of both transcription factors and DNA cis-regulatory elements. The model was tested on a well designed synthetic system during early development stage of Drosophila embryo. The system involves three transcription factors (two activators and one repressor) and a reporter gene. The predicted results using the model were compared with the real experimental data using both graphical methods and statistical methods. Parameter estimation will also be discussed in the paper.