Date

3-29-2012

UMMS Affiliation

Graduate School of Biomedical Sciences, Program in Cancer Biology, MD/PhD Program

Document Type

Dissertation, Doctoral

Subjects

Dissertations, UMMS; Breast Neoplasms; Receptors, Somatomedin; Insulin Receptor Substrate Proteins; Protein Transport; Neoplasm Invasiveness

Disciplines

Cancer Biology | Life Sciences | Medicine and Health Sciences | Neoplasms

Abstract

The insulin-like growth factor-1 receptor (IGF-1R) and many of its downstream signaling components have long been implicated in tumor progression and resistance to therapy. The insulin receptor substrate-1 (IRS-1) and IRS-2 adaptor proteins are two of the major downstream signaling intermediates of the IGF-1R. Despite their considerable homology, previous work in our lab and others has shown that IRS-1 and IRS-2 play divergent roles in breast cancer cells. Signaling through IRS-1 promotes cell proliferation, whereas signaling through IRS-2 promotes cell motility and invasion, as well as glycolysis. Moreover, using a mouse model of mammary tumorigenesis, our lab demonstrated that IRS-2 acts as a positive regulator of metastasis, while IRS-1 cannot compensate for this function.

The focus of my thesis research is to understand how IRS-2, but not IRS-1, promotes breast carcinoma cell invasion and metabolism to support metastasis. In preliminary studies, I have found that IRS-1 and IRS-2 exhibit different expression patterns in both cell lines and human tumors with correlations to patient survival, which provides a potential mechanism for their distinct functions. The localization of IRS-1 and IRS-2 within separate intracellular compartments would determine their access to downstream effectors and substrates, and this would result in unique cellular outcomes. Specifically, I have observed that IRS-2, but not IRS-1, co-localizes with microtubules in breast carcinoma cell lines with implications for signaling through AKT and mTORC2. The goal of this research is to determine how the localization of IRS-2 contributes to its regulation of breast cancer progression and response to therapy and how this information could be used to better predict patient outcomes.