Precision medicine seeks to integrate a multitude of available data from a patient's cancer to effectively tailor anti-cancer therapy. Thus far, the development of precision medicine has yielded important clinical successes: for breast cancer, specific targeting of estrogen receptor alpha (ER) and human epidermal growth factor receptor 2 (HER2) with anti-estrogen and anti-HER2 therapeutics, respectively, has confirmed predictive and prognostic value. Despite initial successes, there remain important challenges that limit the full potential of precision medicine. This thesis documents the use of in silico, in vitro, and in vivo approaches to address 3 aspects of precision medicine for breast cancer.

In the first project, we performed a high-throughput screen designed to identify secreted factors from the tumor microenvironment that may contribute to drug resistance in ER+ breast cancer. We discovered fibroblast growth factor 2 (FGF2) as a secreted factor that could cause resistance to ER+ breast cancer drugs, and that targeting FGF2 in combination with anti-estrogen therapy represents a combination therapy opportunity in ER+ breast cancer. In the second project, we identified mixed triple negative breast cancer (TNBC) and ovarian cancer (OVCA) subgroups using gene expression-based clustering analyses, and found that TNBC and OVCA cancers with a "Mesenchymal-like" gene expression signature are sensitive to inhibitors of heat shock protein 90. This work highlights the fact that gene expression data, like gene mutations, can be used as a biomarker to tailor drugs to patients. Finally, the third project involved characterization of the Rac inhibitor EHT1864, which disrupted interactions between Rac and mitogen-activated protein kinases (MAPKs) and p70S6 kinase (p70S6K) and inhibited ER+ PIK3CA-mutant and HER2+ breast cancers. However, EHT1864 had poor pharmacokinetic properties in vivo, warranting additional drug discovery efforts to identify Rac inhibitors with better pharmacologic properties.

Together, these findings show that precision medicine in breast cancer is still in its infancy, and that full incorporation of genomics, proteomics, and other "-omics-scale" approaches is required for a more comprehensive precision medicine paradigm. However, with the acceleration of progress in both basic and clinical cancer research, such a paradigm may not be far from realization.