Breast Cancer Research and Treatment

, Volume 108, Issue 1, pp 137–149

Breast cancer: a candidate gene approach across the estrogen metabolic pathway

  • Christina Justenhoven
  • Ute Hamann
  • Falk Schubert
  • Marc Zapatka
  • Christiane B. Pierl
  • Sylvia Rabstein
  • Silvia Selinski
  • Tina Mueller
  • Katja Ickstadt
  • Michael Gilbert
  • Yon-Dschun Ko
  • Christian Baisch
  • Beate Pesch
  • Volker Harth
  • Hermann M. Bolt
  • Caren Vollmert
  • Thomas Illig
  • Roland Eils
  • Jürgen Dippon
  • Hiltrud Brauch
Epidemiology

DOI: 10.1007/s10549-007-9586-8

Cite this article as:
Justenhoven, C., Hamann, U., Schubert, F. et al. Breast Cancer Res Treat (2008) 108: 137. doi:10.1007/s10549-007-9586-8

Abstract

Polymorphisms within the estrogen metabolic pathway are prime candidates for a possible association with breast cancer risk. We investigated 11 genes encoding key proteins of this pathway for their potential contribution to breast cancer risk. Of these CYP17A1, CYP19A1, EPHX1, HSD17B1, SRD5A2, and PPARG2 participate in biosynthesis, CYP1A1, CYP1B1, COMT, GSTP1, and SOD2 in catabolism and detoxification. We performed a population-based case-control study with 688 incident breast cancer cases and 724 controls from Germany and genotyped 18 polymorphisms by matrix assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), PCR based RFLP (restriction fragment length polymorphism), and TaqMan® allelic discrimination. Genotype frequencies were compared between cases and controls and odds ratios were calculated by conditional logistic regression. Further statistical analyses were based on cluster analysis, multifactor dimensionality reduction, logic regression, and global testing. Single factor analyses pointed to CYP1B1_1294_GG as a possible breast cancer risk modulator (OR = 2.57; 95% CI: 1.34–4.93) and two way stratification suggested associations between BMI ≥ 30 kg/m2 and COMT_472_GG (P = 0.0076 and P = 0.0026), BMI < 20 kg/m2 and HSD17B1_937_GG (P = 0.0082) as well as CYP17A1_-34_CC and HRT use ≥10 years (P = 0.0063). Following correction for multiple testing none of these associations remained significant. No significant association between breast cancer risk and genetic polymorphisms was observed in multifactor analyses. The tested polymorphisms of the estrogen metabolic pathway may not play a direct role in breast cancer risk. Therefore, future association studies should be extended to other polymorphisms and other regulatory pathways.

Keywords

Breast cancer Susceptibility Estrogen metabolism Polymorphisms Association analyses Multivariate analyses 

Supplementary material

10549_2007_9586_MOESM1_ESM.doc (171 kb)
ESM1 (DOC 197 kb)

Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • Christina Justenhoven
    • 1
    • 10
  • Ute Hamann
    • 2
  • Falk Schubert
    • 3
  • Marc Zapatka
    • 3
  • Christiane B. Pierl
    • 4
  • Sylvia Rabstein
    • 4
  • Silvia Selinski
    • 5
    • 6
  • Tina Mueller
    • 5
  • Katja Ickstadt
    • 5
  • Michael Gilbert
    • 2
  • Yon-Dschun Ko
    • 7
  • Christian Baisch
    • 7
  • Beate Pesch
    • 4
  • Volker Harth
    • 7
  • Hermann M. Bolt
    • 6
  • Caren Vollmert
    • 8
  • Thomas Illig
    • 8
  • Roland Eils
    • 3
  • Jürgen Dippon
    • 9
  • Hiltrud Brauch
    • 1
    • 10
  1. 1.Molecular Mechanisms of Origin and Treatment of Breast CancerDr. Margarete Fischer-Bosch-Institute of Clinical PharmacologyStuttgartGermany
  2. 2.Molecular Genetics of Breast CancerDeutsches Krebsforschungszentrum (DKFZ)HeidelbergGermany
  3. 3.Department of Theoretical BioinformaticsDeutsches Krebsforschungszentrum (DKFZ)HeidelbergGermany
  4. 4.Berufsgenossenschaftliches Forschungsinstitut für Arbeitsmedizin (BGFA)Ruhr University BochumBochumGermany
  5. 5.Department of StatisticsUniversität DortmundDortmundGermany
  6. 6.Institut für Arbeitsphysiologie an der Universität DortmundDortmundGermany
  7. 7.Department of Internal MedicineEvangelische Kliniken Bonn gGmbH, Johanniter KrankenhausBonnGermany
  8. 8.Institute of EpidemiologyGSF-National Research Center for Environment and HealthNeuherbergGermany
  9. 9.Department of MathematicsUniversität StuttgartStuttgartGermany
  10. 10.University TuebingenTuebingenGermany

Personalised recommendations