Increasing awareness of new prognostic and predictive methodologies, and the introduction of next generation sequencing, clearly has established the role of precision medicine in targeted therapy, particularly for cancer patients. Precision medicine includes combinations of diagnostic testing and treatment options that can be offered to patients at presentation, and potentially throughout the course of their disease as new mutations arise and response to treatment diminishes. Precision targeted therapy for breast cancer treatment remains a challenge, because breast cancer is a disease with significant nonbiologic and biologic diversity. The primary clinical goal in breast cancer treatment is to coordinate the most effective local, regional and systemic treatment regimens, including targeted drug regimens, for each patient. The traditional clinical-pathologic paradigm for risk stratification of patients with breast cancer is based on careful considerations of a combination of clinical and histopathologic factors including patient age, menopausal status, tumor size, histologic type, histologic grade, measures of proliferation, lymphovascular invasion, lymph node staging, and evidence of distant metastasis. Differences in histopathologic features of each breast cancer are related directly to the patients underlying tumor biology and risk for metastasis. The use of the biomarkers, estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2), have been invaluable for assessing patient suitability for hormonal or HER2 therapy, thus potentially decreasing a patients risk for recurrence and metastasis; however, the interpretation of these biomarkers is subjective, and the indications for adding chemotherapy are even more challenging. The introduction of multi-gene assays such as Oncotype DX®, and next generation sequencing, has increased our understanding of both tumor biology and clinical behavior, including risks for recurrence and metastasis. These newer technologies offer the possibility for considering more appropriate therapeutic choices, and challenge the relevance of the traditional clinical-pathologic paradigm for selecting the optimal management for a breast cancer patient; however, the cost of these newer technologies is a concern. Several studies have suggested that standard histopathologic variables can provide information similar to that provided by newer technologies, with less of a cost burden to the healthcare system. My work currently focuses on evaluating histologic variables which may provide cost-efficient and cost-effective prognostic and predictive outcome data for breast cancer patients. It has been reported that the tumor microenvironment may affect the Oncotype DX® recurrence score, which has been shown to be both prognostic and predictive of breast cancer recurrence in certain populations of breast cancer patients. In collaboration with Dr. Ed Brown at the University of Rochester (Rochester, NY), Dr. Turner is beginning to explore how components of the tumor microenvironment, such as the extracellular matrix (ECM), may be contributing to breast cancer recurrence and metastasis, and how quantitative analysis of components of the tumor microenvironment such as the ECM can reveal important insights into the process of breast tumor metastasis. In collaboration with Dr. Kate-Rittenhouse-Olson, Dr. Turner is also beginning to explore the value antibodies that potentially target cancer tissue using immunohistochemistry in "in-vivo" models.