Role of Systemic and Cellular Metabolism in Metastasis and Therapy Resistance

One of the aims of Madak-Erdogan lab is to elucidate the crosstalk and interrelationships between ERα and extranuclear initiated and direct nuclear pathways which impinge on gene transcription via chromatin-associated protein kinases. ERα is considered the single most important predictor of breast cancer prognosis and is the target of endocrine therapies, which are generally well tolerated and avoid the morbidity associated with radiation and chemotherapies. Increased activity of protein kinase pathways is one of the major hallmarks of the tumor aggressiveness, acquired endocrine resistance and disease recurrence. It is believed that, in therapy-resistant breast cancers, control of cellular physiology switches from ERα nuclear-initiated pathways to extranuclear-activated protein kinase pathways, which enables these cells to adopt a more aggressive phenotype.The importance of kinases in cancer biology is well known, as increased kinase activity through phosphorylation, mutations or increased expression is often observed in clinical samples and is associated with a poorer prognosis. However, the mechanisms underlying the interplay between ERα and protein kinase pathways in cancer, and the processes by which ERα influences these pathways are poorly understood. As such, identifying new kinases that impact breast cancer physiology is of paramount importance not only to understand the molecular mechanisms underlying cancer progression but also to identify novel pharmacological and druggable targets that would enable increased effectiveness of endocrine therapies by delaying or overcoming the development of resistance. Our ultimate goals are to elucidate how these kinase pathways impact ER actions in the nucleus, to characterize their mode of action in breast cancer, and then to design and test combination therapies so as to enhance the effectiveness of targeted therapies.

Key words: Breast cancer, Estrogen Receptor, Systems biology, Kinase, Obesity, Genomics, Metabolomics