Identifying mechanisms linking stress biology to human breast cancer

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DESCRIPTION (provided by applicant): Understanding human cancer in the context of the social environment is essential for optimizing cancer prevention and care. By identifying stress mechanisms that impact on a patient's neuroendocrine physiology and subsequent tumor biology, we will increase our understanding of tumor biology. The neuroendocrine system links behavior and experience with hormone secretion (e.g. estrogen and cortisol) resulting in hormone-induced gene expression changes within both tumor cells and their microenvironment. However, the cellular and molecular mechanisms underlying the role of chronic stress in breast tumor biology remain poorly understood. Because of the complex genetic and environmental variation found in human populations, identifying the cellular and molecular mechanisms through which stress responses affect cancer biology will require transdisciplinary approaches to traditional models already used for studying cancer. The Conzen and McClintock laboratories have developed such an approach to studying the role of social stress in two complementary rodent models of human breast cancer. We discovered that chronic social isolation leads to a heightened glucocorticoid response to a superimposed stressor; in turn, mammary gland gene expression and morphology suggest an alteration in adipose tissue architecture during gland development. Moreover, social isolation and the ensuing increased stress (glucocorticoid-mediated) reactivity are associated with a significant increase in mammary gland fat metabolism, even prior to invasive cancer development. Based on these data, we propose to study mammary gland fat tissue and its paracrine effects on tumor growth by identifying the gene expression changes as well as the secreted proteins and factors that can contribute to increased tumor growth rates. We predict that completion of these studies will uncover novel stress-induced microenvironment mechanisms affecting mammary tumor growth.