Validation of the Estrogen Related Receptor as a therapeutic target in cancer

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Because of their structural similarity to the canonical estrogen receptors (ERalpha and ERβ), it has been considered that the estrogen receptor related (ERR) sub-family of orphan nuclear receptors function as regulators of estrogen responsiveness. It now appears, however, that activities unrelated to ER signaling are an equally important facet of ERR biology. Most notably, it has been shown that ERRalpha is a key regulator of oxidative metabolism, mitochondrial biogenesis and β-oxidation of fatty acids. Outside of the direct realm of metabolism, it has also been shown in several studies that ERRalpha expression correlates with negative prognosis in a variety of cancers. It is not known however, what aspect of ERRalpha activity impacts tumor pathology. Whereas the study of the biology of most nuclear receptors relies on the ability to generate specific, high affinity agonists and antagonists, ERRalpha has proven to be a difficult pharmaceutical target. The atypical ligand-binding pocket of ERRalpha, and the fact that ERRalpha appears to adopt a constitutively active conformation in the absence of an apparent ligand, indicates that the activity of this receptor is regulated primarily by the abundance and activity of coactivators. Interestingly, overexpression of ERRalpha in and of itself does not lead to target gene activation. Rather, our studies reveal that transcriptional activity usually requires that one of its attendant cofactors, PGC-1alpha or PGC-1β, be expressed. Building on this finding, we have been able to develop ¿protein ligands¿ for ERRalpha using combinatorial peptide screens to engineer the NR interacting surfaces of PGC1alpha so that it interacts in a highly selective manner with ERRalpha. The resultant modified coactivator enabled the use of array technology to define the ERRalpha transcriptome and identify several pathways in breast cancer cells in which this receptor is engaged (i.e. HER2 signaling). Using this gene expression data we have developed a robust metagene that enables us to predict ERRalpha activity and have used this to identity cellular models in which to study this receptor. More importantly, when the metagene was used to probe two independent breast tumor array datasets, it revealed that in ERalpha-positive tumors transcriptionally active ERRalpha is associated with a positive disease outcome whereas the same activity is associated with a negative disease outcome in ERalpha-negative breast tumors. We have also shown in breast cancer cells that activated ERRalpha upregulates expression of the mRNAs encoding all of the rate-limiting enzymes of the TCA cycle and the key components of the OXPHOS pathway. Furthermore, analysis of the ¿TCA gene signature¿ in breast tumors revealed that its expression was also associated with a negative outcome in ERalpha-negative breast tumors. Given that tumors are generally thought to rely on glycolytic metabolism, we will explore the mechanisms underlying our paradoxical findings that link ERRalpha, oxidative metabolism and outcomes in breast cancer. In this study we propose to use both cellular and animal models to assess the cause and effect relationship between ERRalpha activity and the pathophysiology of both ERalpha-positive and ERalpha-negative tumors.