Breast cancer is a highly prevalent and deadly disease. Globally, it is the most diagnosed cancer in women and is responsible for the most cancer-related deaths among women. Breast cancer is also a remarkably heterogeneous disease, with clear variability in clinical parameters including histological presentation, receptor status, and gene expression patterns that differ between patients. A significant amount of effort has been spent characterizing breast cancer into subtypes, with the main goal of improving patient outcomes by: 1) designing targeted therapies, and 2) improving our ability to determine patient prognosis. While scientists have made significant strides in meeting these goals, we still lack targeted therapies for some subtypes of breast cancer, and current therapies often fail to provide a lasting cure. Thus, additional research is needed to improve patient care. One promising area in breast cancer research is cancer metabolism. Using metabolism as a therapeutic target is rapidly gaining traction, as it is now widely appreciated that cancer cells exhibit significant differences in metabolism compared to normal cells. The primary goal of this dissertation is to study the metabolism of distinct subtypes of breast cancer and identify metabolic vulnerabilities that can be used to effectively treat each subtype.This thesis will begin with a review of current classification strategies for breast cancer subtypes and knowledge regarding subtype-specific metabolism. It will also consider modern techniques for targeting breast cancer metabolism for therapeutic benefit. Breast cancer heterogeneity and metabolism are investigated using cell lines and tumors derived from the MMTV-Myc mouse model, which mimics the complexity observed in human disease. Cell lines derived from two histologically defined subtypes, epithelial-mesenchymal transition (EMT) and papillary, are used to establish clear metabolic profiles for each subtype. Metabolic vulnerabilities are identified in glutathione biosynthesis and the tricarboxylic acid cycle in the EMT subtype and nucleotide biosynthesis is determined to be a metabolic weakness in the papillary subtype. It is further shown that pharmacologically targeting each of these metabolic pathways has the greatest effect on reducing proliferation when used against the vulnerable subtype. These in vitro findings are then expanded upon by integrating genomic and metabolomic data acquired from in vivo tumors. In vivo experiments reveal that the EMT and papillary tumors prefer parallel pathways to generate nucleotides, with the EMT subtype preferring to salvage nucleotides while the papillary subtype prefers to produce nucleotides de novo. CRISPR/Cas9 gene editing is used to functionally characterize the metabolic effects of targeting nucleotide salvage and de novo biosynthesis in the EMT and papillary subtypes, and determine that targeting the preferred pathway of each subtype is most effective at slowing tumor growth.Overall, this work demonstrates the power of using metabolism as a therapeutic target of breast cancer, and further shows that metabolic vulnerabilities specific to individual subtypes can be used effectively to guide personalized medicine.
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