Illuminating Actionable Biology in Breast Cancer: Novel Predictive and Prognostic Biomarkers

• Main Author: Bellos, Angela Ogden
• Format: Others
• Published: ScholarWorks @ Georgia State University 2017
• Subjects: Chromosomal instability; proliferation; Ki67; HSET; HER3; EGFR; RARA; racial disparity
• Online Access: http://scholarworks.gsu.edu/biology_diss/185; http://scholarworks.gsu.edu/cgi/viewcontent.cgi?article=1195&context=biology_diss

Assessing hormone receptors (the estrogen and progesterone receptors) and the human epidermal growth factor receptor 2 (HER2) to guide clinical decision making revolutionized treatment for breast cancer patients. However, in the years since these biomarkers were first incorporated into routine clinical care, only a few others have been validated as clinically useful in guiding adjuvant chemotherapy decisions and are recommended by the American Society of Clinical Oncology (ASCO) for patients with hormone-positive breast cancer. For patients with triple-negative breast cancer (TNBC), which lacks hormone and HER2 receptors, not any of these biomarkers are recommended by ASCO due to insufficient evidence that they meaningfully improve clinical outcomes. Breast cancer is the second-leading cause of cancer-related death among women in the US, indicating an unmet need to improve treatments, which can be accomplished in part by identifying and validating novel predictive and prognostic biomarkers that yield actionable information about the clinical course of breast cancers, especially TNBCs. A major obstacle to improving outcomes for breast cancer patients is intratumor heterogeneity (ITH), which can be extensive in breast cancer and drives treatment resistance and relapse. I envision that assaying drivers of ITH can inform clinicians about which breast tumors may be intrinsically more aggressive and carry a greater risk of breast cancer-related morbidity and mortality. My research, presented here, primarily focuses on testing the impact of drivers of ITH (namely, centrosome amplification [CA], the clustering protein KIFC1, and mitotic propensity and its drivers) on clinical outcomes in breast cancer in multivariable models as well as the correlates of in vitro efficacy of centrosome declustering drugs (which can selectively eliminate cancer cells with CA). Collectively, these studies reveal gene signatures and immunohistochemical biomarkers that are independent predictors of aggressive breast cancer course and rational strategies to optimize targeted therapy to combat cancer cells exhibiting CA, thereby contributing to the literature on the development of precision medicine for breast cancer patients, including TNBC patients.