Estrogens, enzyme variants, and breast cancer: A risk model

Philip S. Crooke, Marylyn Deriggi Ritchie, David L. Hachey, Sheila Dawling, Nady Roodi, Fritz F. Parl

Research output: Contribution to journalArticle

27 Citations (Scopus)

Abstract

Oxidative metabolites of estrogens have been implicated in the development of breast cancer, yet relatively little is known about the metabolism of estrogens in the normal breast. We developed a mathematical model of mammary estrogen metabolism based on the conversion of 17β-estradiol (E 2) by the enzymes cytochrome P450 (CYP) 1A1 and CYP1B1, catechol-O-methyltransferase (COMT), and glutathione S-transferase P1 into eight metabolites [i.e., two catechol estrogens, 2-hydroxyestradiol (2-OHE 2) and 4-hydroxyestradiol (4-OHE2); three methoxyestrogens, 2-methoxyestradiol, 2-hydroxy-3-methoxyestradiol, and 4-methoxyestradiol; and three glutathione (SG)-estrogen conjugates, 2-OHE 2-1-SG, 2-OHE2-4-SG, and 4-OHE2-2-SG]. When used with experimentally determined rate constants with purified enzymes, the model provides for a kinetic analysis of the entire metabolic pathway. The predicted concentration of each metabolite during a 30-minute reaction agreed well with the experimentally derived results. The model also enables simulation for the transient quinones, E2-2,3-quinone (E2-2,3-Q) and E2-3,4-quinone (E2-3,4-Q), which are not amenable to direct quantitation. Using experimentally derived rate constants for genetic variants of CYP1A1, CYP1B1, and COMT, we used the model to simulate the kinetic effect of enzyme polymorphisms on the pathway and identified those haplotypes generating the largest amounts of catechols and quinones. Application of the model to a breast cancer case-control population identified a subset of women with an increased risk of breast cancer based on their enzyme haplotypes and consequent E2-3,4-Q production. This in silica model integrates both kinetic and genomic data to yield a comprehensive view of estrogen metabolomics in the breast. The model offers the opportunity to combine metabolic, genetic, and lifetime exposure data in assessing estrogens as a breast cancer risk factor.

Original languageEnglish (US)
Pages (from-to)1620-1629
Number of pages10
JournalCancer Epidemiology Biomarkers and Prevention
Volume15
Issue number9
DOIs
StatePublished - Sep 1 2006

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Estrogens
Breast Neoplasms
Enzymes
Catechol O-Methyltransferase
Quinones
Breast
Haplotypes
Catechol Estrogens
Catechols
Cytochrome P-450 CYP1A1
Metabolomics
Metabolic Networks and Pathways
Glutathione Transferase
Silicon Dioxide
Glutathione
Estradiol
Theoretical Models
Population
estradiol-3,4-quinone
benzoquinone

All Science Journal Classification (ASJC) codes

  • Epidemiology
  • Oncology

Cite this

Crooke, P. S., Ritchie, M. D., Hachey, D. L., Dawling, S., Roodi, N., & Parl, F. F. (2006). Estrogens, enzyme variants, and breast cancer: A risk model. Cancer Epidemiology Biomarkers and Prevention, 15(9), 1620-1629. https://doi.org/10.1158/1055-9965.EPI-06-0198
Crooke, Philip S. ; Ritchie, Marylyn Deriggi ; Hachey, David L. ; Dawling, Sheila ; Roodi, Nady ; Parl, Fritz F. / Estrogens, enzyme variants, and breast cancer : A risk model. In: Cancer Epidemiology Biomarkers and Prevention. 2006 ; Vol. 15, No. 9. pp. 1620-1629.
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Crooke, PS, Ritchie, MD, Hachey, DL, Dawling, S, Roodi, N & Parl, FF 2006, 'Estrogens, enzyme variants, and breast cancer: A risk model', Cancer Epidemiology Biomarkers and Prevention, vol. 15, no. 9, pp. 1620-1629. https://doi.org/10.1158/1055-9965.EPI-06-0198

Estrogens, enzyme variants, and breast cancer : A risk model. / Crooke, Philip S.; Ritchie, Marylyn Deriggi; Hachey, David L.; Dawling, Sheila; Roodi, Nady; Parl, Fritz F.

In: Cancer Epidemiology Biomarkers and Prevention, Vol. 15, No. 9, 01.09.2006, p. 1620-1629.

Research output: Contribution to journalArticle

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AU - Crooke, Philip S.

AU - Ritchie, Marylyn Deriggi

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AU - Parl, Fritz F.

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