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    Keywords: CANCER ; MODELS ; POPULATION ; RISK ; VARIANTS ; BREAST ; BREAST-CANCER ; OVARIAN-CANCER ; PHENOTYPE ; PREVALENCE ; ESTROGEN-RECEPTOR ; GENETIC SUSCEPTIBILITY ; LOCI ; GENOME-WIDE ASSOCIATION ; CONFER SUSCEPTIBILITY ; Risk prediction
    Abstract: ABSTRACT: INTRODUCTION: Previous studies have demonstrated that common breast cancer susceptibility alleles are differentially associated with breast cancer risk for BRCA1 and/or BRCA2 mutation carriers. It is currently unknown how these alleles are associated with different breast cancer subtypes in BRCA1 and BRCA2 mutation carriers defined by estrogen (ER) or progesterone receptor (PR) status of the tumor. METHODS: We used genotype data on up to 11,421 BRCA1 and 7,080 BRCA2 carriers, of whom 4,310 had been affected with breast cancer and had information on either ER or PR status of the tumor, to assess the associations of twelve loci with breast cancer tumor characteristics. Associations were evaluated using a retrospective cohort approach. RESULTS: The results suggested stronger associations with ER-positive breast cancer than ER-negative for eleven loci in both BRCA1 and BRCA2 carriers. Among BRCA1 carriers, SNP rs2981582 (FGFR2) exhibited the biggest difference based on ER status (per-allele HR for ER-positive=1.35, 95%CI:1.17-1.56 vs HR=0.91, 95%CI:0.85-0.98 for ER-negative, P-heterogeneity=6.5e-6). In contrast, SNP rs2046210 at 6q25.1 near ESR1 was primarily associated with ER-negative breast cancer risk for both BRCA1 and BRCA2 carriers. In BRCA2 carriers, SNPs in FGFR2, TOX3, LSP1, SLC4A7/NEK10, 5p12, 2q35, and1p11.2 were significantly associated with ER-positive but not ER-negative disease. Similar results were observed when differentiating breast cancer cases by PR status. CONCLUSIONS: The associations of the twelve SNPs with risk for BRCA1 and BRCA2 carriers differ by ER-positive or ER-negative breast cancer status. The apparent differences in SNP associations between BRCA1 and BRCA2 carriers, and non-carriers, may be explicable by differences in the prevalence of tumor subtypes. As more risk modifying variants are identified, incorporating these associations into breast cancer subtype-specific risk models may improve clinical management for mutation carriers.
    Type of Publication: Journal article published
    PubMed ID: 22053997
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