Estrogen receptor alpha (hereafter called ER) is believed to be the main driver of most (>75%) breast cancers in women. Once bound by estrogen, ER works by “turning on” genes that are required for tumor cell growth. Tamoxifen is frequently used to treat ER+ breast cancer because this drug out competes estrogen for ER binding and causes the growth genes to be “turned off” leading to tumor cell death. Unfortunately, many women that receive tamoxifen therapy eventually become resistant to tamoxifen and their tumors begin to grow and spread again. Exactly how tamoxifen resistance occurs remains unclear and this lack of understanding remains a major barrier to developing potentially curative therapies for ER+ breast cancer. One potential reason that these ER+ tumor cells become tamoxifen-resistant is that long-term tamoxifen treatment eventually causes the overproduction of a set of ER-associated proteins called coactivators. These co-activators can then convert tamoxifen from an antagonist to an agonist; meaning that, in the presence of elevated levels of these co-activators, tamoxifen somehow undergoes a switch and begins to turn ER target genes on instead of turning them off. The main goal of this application is to use cutting-edge “big data” technologies to formally test the requirement the PAD2 for estrogen and tamoxifen signaling. Successful completion of our proposed studies will advance our understanding of the precise mechanisms by which estrogen and tamoxifen regulate the expression of ER target genes in breast cancer cells and how the
antagonist-to-agonist “tamoxifen switch” occurs. Additionally, our studies will also help to define new drug candidates for the treatment of tamoxifen sensitive and resistant ER+ breast cancer.  In an adjuvant setting, these new therapies could potentially have curative effects for the treatment of early stage ER+ breast cancer.