Estrogen-related receptor alpha (ERRα), an orphan nuclear receptor, participates in metabolism, cell migration, cell invasion, metastasis and progression of breast cancer in a coregulator-dependent manner. My thesis aims to explore the transcription activity of ERRα in breast cancer progression as well as the potential pathological and physiological pathways it may be involved in. To achieve this:

1. We firstly predicted co-regulators for ERRα, using a mathematical algorithm, namely adaptive sparse partial least squares (sPLS) regression algorithm. Our results showed that ZEB1 is the most robust potential co-activator of ERRα. We validated that these two factors co-regulate the expression of eight migration-related targets (8 DEGs), specifically in triple negative breast cancer (TNBC) cells.
2. We then investigated the mechanisms through which these two factors co-regulate gene expression. Our results showed that regulation of the expression of the 8 DEGs by ERRα depends on ZEB1, but not on other transcriptional regulators. ChIP analysis showed that ERRα directly (i.e. in a ZEB1-independent manner) binds to the promoters of the DEGs, whereas ZEB1 requires ERRα to bind to the same promoter elements. This suggests a physical interaction between these factors, that was demonstrated by proximity ligation assays. 
3. We next explored the pathological consequences of these interactions in breast tumors. We observed a correlation between the state of epithelial to mesenchymal transition (EMT) of the tumors and expression of ZEB1 and the 8 DEGs. Since EMT is correlated with breast cancer metastasis, we next investigated the prognosis ability of the 8 DEGS. Our results show that a high joint expression of the 8 DEGs predicts overall survival in TNBC patients.

In conclusion, we identified and experimentally validated a novel co-activator of ERRα involved in breast cancer progression. These two factors act together on the transcription regulation of genes that are highly involved in cancer metastasis and are their expression predicts the clinical outcome of TNBC patients.