Interactions Between Genetic Variants and Breast Cancer Risk Factors in the Breast and Prostate Cancer Cohort Consortium

Genomic Epidemiology Group, German Cancer Research Center (Deutsches Krebsforschungszentrum
Journal of the National Cancer Institute (Impact Factor: 12.58). 08/2011; 103(16):1252-63. DOI: 10.1093/jnci/djr265
Source: PubMed


Recently, several genome-wide association studies have identified various genetic susceptibility loci for breast cancer. Relatively little is known about the possible interactions between these loci and the established risk factors for breast cancer.
To assess interactions between single-nucleotide polymorphisms (SNPs) and established risk factors, we prospectively collected DNA samples and questionnaire data from 8576 breast cancer case subjects and 11 892 control subjects nested within the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium (BPC3). We genotyped 17 germline SNPs (FGFR2-rs2981582, FGFR2-rs3750817, TNRC9-rs3803662, 2q35-rs13387042, MAP3K1-rs889312, 8q24-rs13281615, CASP8-rs1045485, LSP1-rs3817198, COL1A1-rs2075555, COX11-rs6504950, RNF146-rs2180341, 6q25-rs2046210, SLC4A7-rs4973768, NOTCH2-rs11249433, 5p12-rs4415084, 5p12-rs10941679, RAD51L1-rs999737), and odds ratios were estimated by logistic regression to confirm previously reported associations with breast cancer risk. We performed likelihood ratio test to assess interactions between 17 SNPs and nine established risk factors (age at menarche, parity, age at menopause, use of hormone replacement therapy, family history, height, body mass index, smoking status, and alcohol consumption), and a correction for multiple testing of 153 tests (adjusted P value threshold = .05/153 = 3 × 10(-4)) was done. Case-case comparisons were performed for possible differential associations of polymorphisms by subgroups of tumor stage, estrogen and progesterone receptor status, and age at diagnosis. All statistical tests were two-sided.
We confirmed the association of 14 SNPs with breast cancer risk (P(trend) = 2.57 × 10(-3) -3.96 × 10(-19)). Three SNPs (LSP1-rs3817198, COL1A1-rs2075555, and RNF146-rs2180341) did not show association with breast cancer risk. After accounting for multiple testing, no statistically significant interactions were detected between the 17 SNPs and the nine risk factors. We also confirmed that SNPs in FGFR2 and TNRC9 were associated with greater risk of estrogen receptor-positive than estrogen receptor-negative breast cancer (P(heterogeneity) = .0016 for FGFR2-rs2981582 and P(heterogeneity) = .0053 for TNRC9-rs3803662). SNP 5p12-rs10941679 was statistically significantly associated with greater risk of progesterone receptor-positive than progesterone receptor-negative breast cancer (P(heterogeneity) = .0028).
This study does not support the hypothesis that known common breast cancer susceptibility loci strongly modify the associations between established risk factors and breast cancer.

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Available from: Maria-Jose Sanchez
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    • "This study investigated 12 SNPs, 9 of them overlapping with those included in the study by Travis et al (2010) and (Milne et al, 2010). An investigation in 8576 breast cancer cases and 11 892 controls nested within the Breast and Prostate Cancer Cohort Consortium (BPC3) also found no evidence for gene–environment interactions between 17 common susceptibility loci and 9 environmental factors investigated (Campa et al, 2011). The second gene–environment interaction study within BCAC (Nickels et al, 2013) assessed 11 additional newly identified susceptibility SNPs (23 SNPs in total) using a larger sample size than before, including up to 34 793 breast cancers and 41 099 controls. "
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    ABSTRACT: Hereditary, genetic factors as well as lifestyle and environmental factors, for example, parity and body mass index, predict breast cancer development. Gene-environment interaction studies may help to identify subgroups of women at high-risk of breast cancer and can be leveraged to discover new genetic risk factors. A few interesting results in studies including over 30 000 breast cancer cases and healthy controls indicate that such interactions exist. Explorative gene-environment interaction studies aiming to identify new genetic or environmental factors are scarce and still underpowered. Gene-environment interactions might be stronger for rare genetic variants, but data are lacking. Ongoing initiatives to genotype larger sample sets in combination with comprehensive epidemiologic databases will provide further opportunities to study gene-environment interactions in breast cancer. However, based on the available evidence, we conclude that associations between the common genetic variants known today and breast cancer risk are only weakly modified by environmental factors, if at all.British Journal of Cancer advance online publication, 12 January 2016; doi:10.1038/bjc.2015.439
    Preview · Article · Jan 2016 · British Journal of Cancer
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    • "Several studies have assessed the impact of these newly discovered SNPs and found that the inclusion of SNP testing alongside family history and other classic markers of breast cancer risk enhances the accuracy of risk assessment (Brentnall et al. 2014; Campa et al. 2011; Heald et al. 2012; Mealiffe et al. 2010). One study described family history and personal genome screening as " complementary tools for cancer risk assessment " (Heald et al. 2012, p 547), while another discussed the improvement in classification of breast cancer risks when SNP risk factors were combined with clinical risk factors (Mealiffe et al. 2010). "
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    ABSTRACT: Single nucleotide polymorphisms (SNPs) have the potential to improve personalized medicine in breast cancer care. As new SNPs are discovered, further enhancing risk classification, SNP testing may serve to complement family history and phenotypic risk factors when assessed in a clinical setting. SNP analysis is particularly relevant to high-risk women who may seek out such information to guide their decision-making around risk-reduction. However, little is known about how high-risk women may respond to SNP testing with regard to clinical decision-making. We examined high-risk women's interest in SNP testing for breast cancer risk through an online survey of hypothetical testing scenarios. Women stated their preferences for sharing test results and selected the most likely follow-up action they would pursue in each of the test result scenarios (above average and below average risk for breast cancer). Four hundred seventy-eight women participated. Most women (89 %) did not know what a SNP was prior to the study. Once SNP testing was described, 75 % were interested in SNP testing. Participants stated an interest in lifestyle interventions for risk-reduction and wanted to discuss their testing results with their doctor or a genetic counselor. Women are interested in SNP testing and are prepared to make lifestyle changes based on testing results. Women's preference for discussing testing results with a healthcare provider aligns with the current trend towards SNP testing in a clinical setting.
    Full-text · Article · Dec 2014 · Journal of Genetic Counseling
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    • "Stratification of tumors by ER status indicated that the two SNPs (rs4415084 and rs10941679) on 5p12 confer risk, preferentially for ER-positive tumors, with no risk for ER-negative BC. Results from subgroup analyses on ER status of tumors were in agreement with previous reports [5], [25]. Findings from previous studies suggested that several SNPs are predominantly associated with ER-positive BC: 2q35-rs13387042 [22], TNRC9-rs3803662 [25], [37], 8q24-rs13281615 [38], FGFR2-rs2981582 [39]. The present findings support the notion that ER-positive and ER-negative tumors have different genetic components to their risks. "
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    ABSTRACT: The association between polymorphisms on 5p12 and breast cancer (BC) has been widely evaluated since it was first identified through genome-wide association approach; however, the studies have yielded contradictory results. We sought to investigate this inconsistency by performing a comprehensive meta-analysis on two wildly studied polymorphisms (rs10941679 and rs4415084) on 5p12. Databases including Pubmed, EMBASE, Web of Science, EBSCO, and Cochrane Library databases were searched to find relevant studies. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the strength of association. The random-effects model was applied, addressing heterogeneity and publication bias. A total of 19 articles involving 100,083 cases and 163,894 controls were included. An overall random-effects per-allele OR of 1.09 (95% CI: 1.06-1.12; P = 4.5×10(-8)) and 1.09 (95% CI: 1.05-1.12; P = 4.2×10(-7)) was found for the rs10941679 and rs4415084 polymorphism respectively. Significant results were found in Asians and Caucasians when stratified by ethnicity; whereas no significant associations were found among Africans/African-Americans. Similar results were also observed using dominant or recessive genetic models. In addition, we find both rs4415084 and rs10941679 conferred significantly greater risks of ER-positive breast cancer than of ER-negative tumors. Our findings demonstrated that rs10941679-G allele and rs4415084-T allele might be risk-conferring factors for the development of breast cancer, especially in Caucasians and East-Asians.
    Full-text · Article · Sep 2013 · PLoS ONE
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