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  • 1
    Keywords: CANCER ; GROWTH ; POPULATION ; RISK ; TUMORS ; COMPLEX ; RISK-FACTORS ; BRCA1 ; ovarian cancer ; GENOME-WIDE ASSOCIATION ; CONSORTIUM ; CONFER SUSCEPTIBILITY ; COMMON VARIANTS ; TUMOR SUBTYPES ; 14Q24.1 RAD51L1
    Abstract: The 19p13.1 breast cancer susceptibility locus is a modifier of breast cancer risk in BRCA1 mutation carriers and is also associated with risk of ovarian cancer. Here we investigated 19p13.1 variation and risk of breast cancer subtypes, defined by estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2) status, using 48,869 breast cancer cases and 49,787 controls from the Breast Cancer Association Consortium (BCAC). Variants from 19p13.1 were not associated with breast cancer overall or with ER-positive breast cancer but were significantly associated with ER-negative breast cancer risk [rs8170 Odds Ratio (OR)=1.10, 95% Confidence Interval (CI) 1.05 - 1.15, p=3.49 x 10-5] and triple negative (TN) (ER, PR and HER2 negative) breast cancer [rs8170 OR=1.22, 95% CI 1.13 - 1.31, p=2.22 x 10-7]. However, rs8170 was no longer associated with ER-negative breast cancer risk when TN cases were excluded [OR=0.98, 95% CI 0.89 - 1.07, p=0.62]. In addition, a combined analysis of TN cases from BCAC and the Triple Negative Breast Cancer Consortium (TNBCC) (n=3,566) identified a genome-wide significant association between rs8170 and TN breast cancer risk [OR=1.25, 95% CI 1.18 - 1.33, p=3.31 x 10-13]. Thus, 19p13.1 is the first triple negative-specific breast cancer risk locus and the first locus specific to a histological subtype defined by ER, PR, and HER2 to be identified. These findings provide convincing evidence that genetic susceptibility to breast cancer varies by tumor subtype and that triple negative tumors and other subtypes likely arise through distinct etiologic pathways.
    Type of Publication: Journal article published
    PubMed ID: 22331459
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  • 2
    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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