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Genetic variation in estrogen and progesterone pathway genes and breast cancer risk: an exploration of tumor subtype-specific effects

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Abstract

Purpose

To determine whether associations between estrogen pathway-related single nucleotide polymorphisms (SNPs) and breast cancer risk differ by molecular subtype, we evaluated associations between SNPs in cytochrome P450 family 19 subfamily A polypeptide 1 (CYP19A1), estrogen receptor (ESR1), 3-beta hydroxysteroid dehydrogenase type I (HSD3B1), 17-beta hydroxysteroid dehydrogenase type II (HSD17B2), progesterone receptor (PGR), and sex hormone-binding globulin (SHBG) and breast cancer risk in a case–control study in North Carolina.

Methods

Cases (n = 1,972) were women 20–74 years old and diagnosed with breast cancer between 1993 and 2001. Population-based controls (n = 1,776) were frequency matched to cases by age and race. A total of 195 SNPs were genotyped, and linkage disequilibrium was evaluated using the r 2 statistic. Odds ratios (ORs) and 95 % confidence intervals (CIs) for associations with breast cancer overall and by molecular subtype were estimated using logistic regression. Monte Carlo methods were used to control for multiple comparisons; two-sided p values <3.3 × 10−4 were statistically significant. Heterogeneity tests comparing the two most common subtypes, luminal A (n = 679) and basal-like (n = 200), were based on the Wald statistic.

Results

ESR1 rs6914211 (AA vs. AT+TT, OR 2.24, 95 % CI 1.51–3.33), ESR1 rs985191 (CC vs. AA, OR 2.11, 95 % CI 1.43–3.13), and PGR rs1824128 (TT+GT vs. GG, OR 1.33, 95 % CI 1.14–1.55) were associated with risk after accounting for multiple comparisons. Rs6914211 and rs985191 were in strong linkage disequilibrium among controls (African-Americans r 2 = 0.70; whites r 2 = 0.95). There was no evidence of heterogeneity between luminal A and basal-like subtypes, and the three SNPs were also associated with elevated risk of the less common luminal B, HER2+/ER−, and unclassified subtypes.

Conclusions

ESR1 and PGR SNPs were associated with risk, but lack of heterogeneity between subtypes suggests variants in hormone-related genes may play similar roles in the etiology of breast cancer molecular subtypes.

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Acknowledgments

This work was supported by funding from the National Institutes of Health [P50-CA58223, P30-CA16086, R25-CA57726 to S.J.N., P30ES10126 to M. D. G. and R. C. M.]. The authors wish to thank Patricia Basta of the University of North Carolina at Chapel Hill Epidemiology Department, and Michael Andre and Amanda Beaty of the University of North Carolina Lineberger Comprehensive Cancer Center for their work preparing the DNA samples and conducting the genotyping. The authors also thank Jessica Tse of the University of North Carolina at Chapel Hill Epidemiology Department for advice and statistical support.

Conflict of interest

Sarah J. Nyante is currently a postdoctoral fellow at the National Institutes of Health, which funded the research undertaken at the University of North Carolina at Chapel Hill. There are no other conflicts of interest to declare.

Author information

Authors and Affiliations

  1. Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA

    Sarah J. Nyante

  2. Epidemiology Department, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Marilie D. Gammon, Jeannette T. Bensen & Robert C. Millikan

  3. Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Marilie D. Gammon, Jeannette T. Bensen, Dan Yu Lin, Jingchun Luo & Robert C. Millikan

  4. Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, QC, Canada

    Jay S. Kaufman

  5. Biostatistics Department, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Dan Yu Lin & Yijuan Hu

  6. Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, OH, USA

    Jill S. Barnholtz-Sloan

  7. Fred Hutchinson Cancer Research Center, Seattle, WA, USA

    Qianchuan He

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  1. Sarah J. Nyante
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Correspondence to Sarah J. Nyante.

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Robert C. Millikan: Deceased.

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Nyante, S.J., Gammon, M.D., Kaufman, J.S. et al. Genetic variation in estrogen and progesterone pathway genes and breast cancer risk: an exploration of tumor subtype-specific effects. Cancer Causes Control 26, 121–131 (2015). https://doi.org/10.1007/s10552-014-0491-2

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