Brian D. Lehmann Ph.D., is a Research Associate Professor of Medicine at the Vanderbilt School of Medicine. Dr. Lehmann’s research expertise lies at the intersection of cancer biology and bioinformatics. His unique understanding of both has led to the successful characterization of distinct molecular subgroups for triple negative breast cancer. In that study, he harnessed the power 21 publically available gene expression datasets to molecularly define six subtypes of TNBC. In addition to characterizing this heterogeneous disease, we have identified representative cell culture models that display differential drug sensitivity. He is currently funded by the Susan G. Komen for the Cure Foundation to explore the role of androgen receptor (AR) in breast cancer subtypes. The steroid hormone receptors estrogen receptor (ER), progesterone receptor (PR) and AR are essential for normal epithelial maintenance, however they also contribute to hormone-driven carcinogenesis in breast and prostate cancers. Antiestrogen therapies have dramatically impacted treatment and outcomes of hormone-dependent, ER+ breast cancer. Whereas the role of the estrogen receptor in breast cancer is well established, little is known for the role of androgen signaling in breast tumorigenesis. It is now clear from numerous studies that AR is expressed in 60-70% of breast cancers, independent of ER status. With FDA-approved inhibitors and widespread expression, AR remains a relatively unexplored, but very attractive target for breast cancer. Using a comprehensive integration of genomic and molecular approaches we will determine the biochemical context in which AR signaling drives breast cancer tumorigenesis. Further, based on preliminary data, we hypothesize that targeting AR either alone or in combination with ER antagonists or PI3K pathway inhibitors will represent effective therapeutic strategies for select breast cancers. We will also examine the role of AR in endocrine resistance to ER targeted therapy. Finally, analysis of tumors from clinical trials and cell line models will allow discovery of mechanisms of sensitivity and resistance to AR and PI3K inhibitors, as well as biomarkers that can be used in the development of new treatment regimens and selection of patients for future trials.