Breast cancer subtypes and previously established genetic risk factors: a bayesian approach

Abstract

Background: Gene expression analyses indicate that breast cancer is a heterogeneous disease with at least five immunohistologic subtypes. Despite growing evidence that these subtypes are etiologically and prognostically distinct, few studies have investigated whether they have divergent genetic risk factors. To help fill in this gap in our understanding, we examined associations between breast cancer subtypes and previously established susceptibility loci among white and African-American women in the Carolina Breast Cancer Study.

Methods: We used Bayesian polytomous logistic regression to estimate ORs and 95% posterior intervals for the association between each of 78 single nucleotide polymorphisms (SNP) and five breast cancer subtypes. Subtypes were defined using five immunohistochemical markers: estrogen receptors (ER), progesterone receptors (PR), human epidermal growth factor receptors 1 and 2 (HER1/2), and cytokeratin (CK) 5/6.

Results: Several SNPs in TNRC9/TOX3 were associated with luminal A (ER/PR+, HER2-) or basal-like breast cancer (ER-, PR-, HER2-, HER1, or CK 5/6+), and one SNP (rs3104746) was associated with both. SNPs in FGFR2 were associated with luminal A, luminal B (ER/PR+, HER2+), or HER2+/ER- disease, but none were associated with basal-like disease. We also observed subtype differences in the effects of SNPs in 2q35, 4p, TLR1, MAP3K1, ESR1, CDKN2A/B, ANKRD16, and ZM1Z1.

Conclusion and impact: We found evidence that genetic risk factors for breast cancer vary by subtype and further clarified the role of several key susceptibility genes. .

Figure 1

Odds ratios and 95% posterior intervals for previous GWAS–identified SNPs: All CBCS participants

Figure 2

Odds ratios and 95% posterior intervals for previous GWAS–identified SNPs for CBCS whites (left) and African–Americans (right)