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.

Public Health Relevance

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.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM099143-03
Application #
8441623
Study Section
Cancer Biomarkers Study Section (CBSS)
Program Officer
Okita, Richard T
Project Start
2011-06-15
Project End
2016-03-31
Budget Start
2013-04-01
Budget End
2014-03-31
Support Year
3
Fiscal Year
2013
Total Cost
$296,774
Indirect Cost
$83,102
Name
University of Michigan Ann Arbor
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
Hertz, Daniel L; Speth, Kelly A; Kidwell, Kelley M et al. (2017) Variable aromatase inhibitor plasma concentrations do not correlate with circulating estrogen concentrations in post-menopausal breast cancer patients. Breast Cancer Res Treat 165:659-668
Ahern, Thomas P; Hertz, Daniel L; Damkier, Per et al. (2017) Cytochrome P-450 2D6 (CYP2D6) Genotype and Breast Cancer Recurrence in Tamoxifen-Treated Patients: Evaluating the Importance of Loss of Heterozygosity. Am J Epidemiol 185:75-85
Capper, C P; Liu, J; McIntosh, L R et al. (2017) Functional characterization of the G162R and D216H genetic variants of human CYP17A1. J Steroid Biochem Mol Biol :
Hertz, D L; Kidwell, K M; Seewald, N J et al. (2017) Polymorphisms in drug-metabolizing enzymes and steady-state exemestane concentration in postmenopausal patients with breast cancer. Pharmacogenomics J 17:521-527
Hertz, Daniel L; Caram, Megan V; Kidwell, Kelley M et al. (2016) Evidence for association of SNPs in ABCB1 and CBR3, but not RAC2, NCF4, SLC28A3 or TOP2B, with chronic cardiotoxicity in a cohort of breast cancer patients treated with anthracyclines. Pharmacogenomics 17:231-40
Santa-Maria, Cesar A; Blackford, Amanda; Nguyen, Anne T et al. (2016) Association of Variants in Candidate Genes with Lipid Profiles in Women with Early Breast Cancer on Adjuvant Aromatase Inhibitor Therapy. Clin Cancer Res 22:1395-402
Paoletti, Costanza; Larios, Jose M; Muñiz, Maria C et al. (2016) Heterogeneous estrogen receptor expression in circulating tumor cells suggests diverse mechanisms of fulvestrant resistance. Mol Oncol 10:1078-85
Hertz, Daniel L; Rae, James M (2016) Individualized Tamoxifen Dose Escalation: Confirmation of Feasibility, Question of Utility. Clin Cancer Res 22:3121-3
Capper, Cameron P; Rae, James M; Auchus, Richard J (2016) The Metabolism, Analysis, and Targeting of Steroid Hormones in Breast and Prostate Cancer. Horm Cancer 7:149-64
Kadakia, Kunal C; Snyder, Claire F; Kidwell, Kelley M et al. (2016) Patient-Reported Outcomes and Early Discontinuation in Aromatase Inhibitor-Treated Postmenopausal Women With Early Stage Breast Cancer. Oncologist 21:539-46

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