A comprehensive evaluation of interaction between genetic variants and use of menopausal hormone therapy on mammographic density.

INTRODUCTION: Mammographic density is an established breast cancer risk factor with a strong genetic component and can be increased in women using menopausal hormone therapy (MHT). Here, we aimed to identify genetic variants that may modify the association between MHT use and mammographic density. METHODS: The study comprised 6,298 postmenopausal women from the Mayo Mammography Health Study and nine studies included in the Breast Cancer Association Consortium. We selected for evaluation 1327 single nucleotide polymorphisms (SNPs) showing the lowest P-values for interaction (P int) in a meta-analysis of genome-wide gene-environment interaction studies with MHT use on risk of breast cancer, 2541 SNPs in candidate genes (AKR1C4, CYP1A1-CYP1A2, CYP1B1, ESR2, PPARG, PRL, SULT1A1-SULT1A2 and TNF) and ten SNPs (AREG-rs10034692, PRDM6-rs186749, ESR1-rs12665607, ZNF365-rs10995190, 8p11.23-rs7816345, LSP1-rs3817198, IGF1-rs703556, 12q24-rs1265507, TMEM184B-rs7289126, and SGSM3-rs17001868) associated with mammographic density in genome-wide studies. We used multiple linear regression models adjusted for potential confounders to evaluate interactions between SNPs and current use of MHT on mammographic density. RESULTS: No significant interactions were identified after adjustment for multiple testing. The strongest SNP-MHT interaction (unadjusted P int <0.0004) was observed with rs9358531 6.5kb 5' of PRL. Furthermore, three SNPs in PLCG2 that had previously been shown to modify the association of MHT use with breast cancer risk were found to modify also the association of MHT use with mammographic density (unadjusted P int <0.002), but solely among cases (unadjusted P int SNP×MHT×case-status <0.02). CONCLUSIONS: The study identified potential interactions on mammographic density between current use of MHT and SNPs near PRL and in PLCG2, which require confirmation. Given the moderate size of the interactions observed, larger studies are needed to identify genetic modifiers of the association of MHT use with mammographic density.This is the final version of the article. It first appeared from BioMed Central via http://dx.doi.org/10.1186/s13058-015-0625-

Assessment of variation in immunosuppressive pathway genes reveals TGFBR2 to be associated with prognosis of estrogen receptor-negative breast cancer after chemotherapy

Introduction: Tumor lymphocyte infiltration is associated with clinical response to chemotherapy in estrogen receptor (ER) negative breast cancer. To identify variants in immunosuppressive pathway genes associated with prognosis after adjuvant chemotherapy for ER-negative patients, we studied stage I-III invasive breast cancer patients of European ancestry, including 9,334 ER-positive (3,151 treated with chemotherapy) and 2,334 ER-negative patients (1,499 treated with chemotherapy). Methods: We pooled data from sixteen studies from the Breast Cancer Association Consortium (BCAC), and employed two independent studies for replications. Overall 3,610 single nucleotide polymorphisms (SNPs) in 133 genes were genotyped as part of the Collaborative Oncological Gene-environment Study, in which phenotype and clinical data were collected and harmonized. Multivariable Cox proportional hazard regression was used to assess genetic associations with overall survival (OS) and breast

Assessing interactions between the associations of common genetic susceptibility variants, reproductive history and body mass index with breast cancer risk in the breast cancer association consortium: a combined case-control study.

INTRODUCTION: Several common breast cancer genetic susceptibility variants have recently been identified. We aimed to determine how these variants combine with a subset of other known risk factors to influence breast cancer risk in white women of European ancestry using case-control studies participating in the Breast Cancer Association Consortium. METHODS: We evaluated two-way interactions between each of age at menarche, ever having had a live birth, number of live births, age at first birth and body mass index (BMI) and each of 12 single nucleotide polymorphisms (SNPs) (10q26-rs2981582 (FGFR2), 8q24-rs13281615, 11p15-rs3817198 (LSP1), 5q11-rs889312 (MAP3K1), 16q12-rs3803662 (TOX3), 2q35-rs13387042, 5p12-rs10941679 (MRPS30), 17q23-rs6504950 (COX11), 3p24-rs4973768 (SLC4A7), CASP8-rs17468277, TGFB1-rs1982073 and ESR1-rs3020314). Interactions were tested for by fitting logistic regression models including per-allele and linear trend main effects for SNPs and risk factors, respectively, and single-parameter interaction terms for linear departure from independent multiplicative effects. RESULTS: These analyses were applied to data for up to 26,349 invasive breast cancer cases and up to 32,208 controls from 21 case-control studies. No statistical evidence of interaction was observed beyond that expected by chance. Analyses were repeated using data from 11 population-based studies, and results were very similar. CONCLUSIONS: The relative risks for breast cancer associated with the common susceptibility variants identified to date do not appear to vary across women with different reproductive histories or body mass index (BMI). The assumption of multiplicative combined effects for these established genetic and other risk factors in risk prediction models appears justified.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Evidence that breast cancer risk at the 2q35 locus is mediated through IGFBP5 regulation.

GWAS have identified a breast cancer susceptibility locus on 2q35. Here we report the fine mapping of this locus using data from 101,943 subjects from 50 case-control studies. We genotype 276 SNPs using the 'iCOGS' genotyping array and impute genotypes for a further 1,284 using 1000 Genomes Project data. All but two, strongly correlated SNPs (rs4442975 G/T and rs6721996 G/A) are excluded as candidate causal variants at odds against >100:1. The best functional candidate, rs4442975, is associated with oestrogen receptor positive (ER+) disease with an odds ratio (OR) in Europeans of 0.85 (95% confidence interval=0.84-0.87; P=1.7 × 10(-43)) per t-allele. This SNP flanks a transcriptional enhancer that physically interacts with the promoter of IGFBP5 (encoding insulin-like growth factor-binding protein 5) and displays allele-specific gene expression, FOXA1 binding and chromatin looping. Evidence suggests that the g-allele confers increased breast cancer susceptibility through relative downregulation of IGFBP5, a gene with known roles in breast cell biology

Genome-wide association study of germline variants and breast cancer-specific mortality.

BackgroundWe examined the associations between germline variants and breast cancer mortality using a large meta-analysis of women of European ancestry.MethodsMeta-analyses included summary estimates based on Cox models of twelve datasets using ~10.4 million variants for 96,661 women with breast cancer and 7697 events (breast cancer-specific deaths). Oestrogen receptor (ER)-specific analyses were based on 64,171 ER-positive (4116) and 16,172 ER-negative (2125) patients. We evaluated the probability of a signal to be a true positive using the Bayesian false discovery probability (BFDP).ResultsWe did not find any variant associated with breast cancer-specific mortality at P &lt; 5 × 10-8. For ER-positive disease, the most significantly associated variant was chr7:rs4717568 (BFDP = 7%, P = 1.28 × 10-7, hazard ratio [HR] = 0.88, 95% confidence interval [CI] = 0.84-0.92); the closest gene is AUTS2. For ER-negative disease, the most significant variant was chr7:rs67918676 (BFDP = 11%, P = 1.38 × 10-7, HR = 1.27, 95% CI = 1.16-1.39); located within a long intergenic non-coding RNA gene (AC004009.3), close to the HOXA gene cluster.ConclusionsWe uncovered germline variants on chromosome 7 at BFDP &lt; 15% close to genes for which there is biological evidence related to breast cancer outcome. However, the paucity of variants associated with mortality at genome-wide significance underpins the challenge in providing genetic-based individualised prognostic information for breast cancer patients

Ki67, chemotherapy response, and prognosis in breast cancer patients receiving neoadjuvant treatment

<p>Abstract</p> <p>Background</p> <p>The pathological complete response (pCR) after neoadjuvant chemotherapy is a surrogate marker for a favorable prognosis in breast cancer patients. Factors capable of predicting a pCR, such as the proliferation marker Ki67, may therefore help improve our understanding of the drug response and its effect on the prognosis. This study investigated the predictive and prognostic value of Ki67 in patients with invasive breast cancer receiving neoadjuvant treatment for breast cancer.</p> <p>Methods</p> <p>Ki67 was stained routinely from core biopsies in 552 patients directly after the fixation and embedding process. HER2/neu, estrogen and progesterone receptors, and grading were also assessed before treatment. These data were used to construct univariate and multivariate models for predicting pCR and prognosis. The tumors were also classified by molecular phenotype to identify subgroups in which predicting pCR and prognosis with Ki67 might be feasible.</p> <p>Results</p> <p>Using a cut-off value of > 13% positively stained cancer cells, Ki67 was found to be an independent predictor for pCR (OR 3.5; 95% CI, 1.4, 10.1) and for overall survival (HR 8.1; 95% CI, 3.3 to 20.4) and distant disease-free survival (HR 3.2; 95% CI, 1.8 to 5.9). The mean Ki67 value was 50.6 ± 23.4% in patients with pCR. Patients without a pCR had an average of 26.7 ± 22.9% positively stained cancer cells.</p> <p>Conclusions</p> <p>Ki67 has predictive and prognostic value and is a feasible marker for clinical practice. It independently improved the prediction of treatment response and prognosis in a group of breast cancer patients receiving neoadjuvant treatment. As mean Ki67 values in patients with a pCR were very high, cut-off values in a high range above which the prognosis may be better than in patients with lower Ki67 values may be hypothesized. Larger studies will be needed in order to investigate these findings further.</p

2q36.3 is associated with prognosis for oestrogen receptor-negative breast cancer patients treated with chemotherapy

Large population-based registry studies have shown that breast cancer prognosis is inherited. Here we analyse single-nucleotide polymorphisms (SNPs) of genes implicated in human immunology and inflammation as candidates for prognostic markers of breast cancer survival involving 1,804 oestrogen receptor (ER)-negative patients treated with chemotherapy (279 events) from 14 European studies in a prior large-scale genotyping experiment, which is part of the Collaborative Oncological Gene-environment Study (COGS) initiative. We carry out replication using Asian COGS samples (n=522, 53 events) and the Prospective Study of Outcomes in Sporadic versus Hereditary breast cancer (POSH) study (n=315, 108 events). Rs4458204-A near CCL20 (2q36.3) is found to be associated with breast cancer-specific death at a genome-wide significant level (n=2,641, 440 events, combined allelic hazard ratio (HR)=1.81 (1.49-2.19); P for trend=1.90 × 10 â ̂'9). Such survival-associated variants can represent ideal targets for tailored therapeutics, and may also enhance our current prognostic prediction capabilities

Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer.

Genome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ∼14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising 15,748 breast cancer cases and 18,084 controls together with 46,785 cases and 42,892 controls from 41 studies genotyped on a 211,155-marker custom array (iCOGS). Analyses were restricted to women of European ancestry. We generated genotypes for more than 11 million SNPs by imputation using the 1000 Genomes Project reference panel, and we identified 15 new loci associated with breast cancer at P < 5 × 10(-8). Combining association analysis with ChIP-seq chromatin binding data in mammary cell lines and ChIA-PET chromatin interaction data from ENCODE, we identified likely target genes in two regions: SETBP1 at 18q12.3 and RNF115 and PDZK1 at 1q21.1. One association appears to be driven by an amino acid substitution encoded in EXO1.BCAC is funded by Cancer Research UK (C1287/A10118, C1287/A12014) and by the European Community's Seventh Framework Programme under grant agreement 223175 (HEALTH-F2-2009-223175) (COGS). Meetings of the BCAC have been funded by the European Union COST programme (BM0606). Genotyping on the iCOGS array was funded by the European Union (HEALTH-F2-2009-223175), Cancer Research UK (C1287/A10710, C8197/A16565), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer program and the Ministry of Economic Development, Innovation and Export Trade of Quebec, grant PSR-SIIRI-701. Combination of the GWAS data was supported in part by the US National Institutes of Health (NIH) Cancer Post-Cancer GWAS initiative, grant 1 U19 CA148065-01 (DRIVE, part of the GAME-ON initiative). For a full description of funding and acknowledgments, see the Supplementary Note.This is the author accepted manuscript. The final version is available from NPG via http://dx.doi.org/10.1038/ng.324

Interactions Between Genetic and Epidemiological Factors Influencing Mammographic Density

Studies have identified genetic and epidemiological factors associated with mammographic density (MD) phenotypes. However, MD-associated genetic variants only account for a small proportion of the total estimated heritability. Interrogating interactions between genetic and epidemiological factors could potentially identify additional MD-associated loci, expand our understanding of the genetic basis of MD phenotypes, and clarify how epidemiological factors modulate relationships between genetic variants and MD. We conducted six separate genome-wide, gene-environment (GxE) interaction analyses, applying 2 degrees of freedom (df) and 1df interaction tests, for each of three MD phenotypes (percent density (PD), dense area (DA), and non-dense area (NDA)). The six epidemiological factors considered were height, ever parous, parity, ever menopausal hormone therapy (MHT), ever breastfeeding, and months of breastfeeding. We included European ancestry participants from multiple studies within the Markers of Density (MODE) consortium and the Breast Cancer Association Consortium (BCAC) (n = 4,895 - 16,218 depending on specific analyses). We identified 11 loci with genome-wide significant (P &lt; 5 × 10-8) interaction tests including two novel common genetic signals interacting with parity (8p21.2) and ever breastfeeding (19p13.2) for NDA. Our results suggest that epidemiological risk factors might influence relationships between common genetic variants and MD phenotypes at particular genomic loci.</p

Age- and Tumor Subtype-Specific Breast Cancer Risk Estimates for CHEK2*1100delC Carriers.

PURPOSE: CHEK2*1100delC is a well-established breast cancer risk variant that is most prevalent in European populations; however, there are limited data on risk of breast cancer by age and tumor subtype, which limits its usefulness in breast cancer risk prediction. We aimed to generate tumor subtype- and age-specific risk estimates by using data from the Breast Cancer Association Consortium, including 44,777 patients with breast cancer and 42,997 controls from 33 studies genotyped for CHEK2*1100delC. PATIENTS AND METHODS: CHEK2*1100delC genotyping was mostly done by a custom Taqman assay. Breast cancer odds ratios (ORs) for CHEK2*1100delC carriers versus noncarriers were estimated by using logistic regression and adjusted for study (categorical) and age. Main analyses included patients with invasive breast cancer from population- and hospital-based studies. RESULTS: Proportions of heterozygous CHEK2*1100delC carriers in controls, in patients with breast cancer from population- and hospital-based studies, and in patients with breast cancer from familial- and clinical genetics center-based studies were 0.5%, 1.3%, and 3.0%, respectively. The estimated OR for invasive breast cancer was 2.26 (95%CI, 1.90 to 2.69; P = 2.3 × 10(-20)). The OR was higher for estrogen receptor (ER)-positive disease (2.55 [95%CI, 2.10 to 3.10; P = 4.9 × 10(-21)]) than it was for ER-negative disease (1.32 [95%CI, 0.93 to 1.88; P = .12]; P interaction = 9.9 × 10(-4)). The OR significantly declined with attained age for breast cancer overall (P = .001) and for ER-positive tumors (P = .001). Estimated cumulative risks for development of ER-positive and ER-negative tumors by age 80 in CHEK2*1100delC carriers were 20% and 3%, respectively, compared with 9% and 2%, respectively, in the general population of the United Kingdom. CONCLUSION: These CHEK2*1100delC breast cancer risk estimates provide a basis for incorporating CHEK2*1100delC into breast cancer risk prediction models and into guidelines for intensified screening and follow-up.NIH