Estrogenic hormones play a significant role in breast cancer development and progression. Anti-estrogenic therapies including the Selective Estrogen Receptor Modulator (SERM) tamoxifen, and the 3rd generation aromatase inhibitors (AI) including anastrozole, letrozole, and exemestane have clearly played a substantial role in decreasing breast cancer mortality rates, especially when used in the adjuvant setting. Tamoxifen has also been shown to prevent breast cancer. Approximately 60-70% of all newly diagnosed breast cancers are estrogen receptor (ER)-positive, but only 60% of these will respond to endocrine therapy. It is not currently possible to identify which patients with ER-positive cancers will benefit from endocrine therapy nor is it possible to determine whether a particular treatment approach (tamoxifen vs AI) will work best for an individual patient. We hypothesize inherited germline Single Nucleotide Polymorphisms (SNPs) in genes that account for drug disposition, drug targets, and drug's actions significantly contribute to the interpatient differences in benefit from anti-estrogen therapy. The goal of this proposal is to identify variants in genes involved in drug and steroid metabolizing enzymes, and the estrogen signaling pathway and determine whether they can predict benefit and/or side effects of two of the most widely used anti-estogens tamoxifen and anastrozole. To achieve this goal, we will conduct a comprehensive genotype analysis of patients who participated to one the seminal prospective randomized clinical trials that established the role AIs for the treatment of breast cancer: The Arimidex, Tamoxifen, Alone or in Combination (ATAC) trial. The ATAC trial compared the efficacy and toxicity of upfront tamoxifen versus anastrozole for 5 years. We hypothesize that a genetic approach can identify specific subsets of patients form whom one form of endocrine therapy (tamoxifen vs anastrozole) is better than the other.
The promise of personalized medicine lies in the ability to choose the optimal treatment for each patient. Nowhere can this be better utilized than the field of cancer pharmacology, particularly in breast cancer. We believe that by better understanding the exact genes involved in drug action and their underlying genetics, we will be able to better predict response to anti-estrogen therapy and better anticipate side effects that may significantly alter quality of life. In these studies, we will develop genetic predictors of response to and side effects of two of the most commonly used drug in the treatment of breast cancer, tamoxifen and anastrozole. Our results will allow clinicians to better anticipate the risks versus benefit for individual patients.
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