Mammographic density adjusted for age and body mass index (BMI) is a heritable marker of breast cancer susceptibility. Little is known about the biological mechanisms underlying the association between mammographic density and breast cancer risk. We examined whether common low-penetrance breast cancer susceptibility variants contribute to inter-individual differences in mammographic density measures.
We established an international consortium (DENSNP) of 19 studies from 10 countries, comprising 16,895 Caucasian women, to conduct a pooled cross-sectional analysis of common breast cancer susceptibility variants in 14 independent loci and mammographic density measures. Dense and non-dense areas, and percent density, were measured using interactive-thresholding techniques. Mixed linear models were used to assess the association between genetic variants and the square roots of mammographic density measures adjusted for study, age, case status, body mass index (BMI) and menopausal status.
Consistent with their breast cancer associations, the C-allele of rs3817198 in LSP1 was positively associated with both adjusted dense area (p=0.00005) and adjusted percent density (p=0.001) whereas the A-allele of rs10483813 in RAD51L1 was inversely associated with adjusted percent density (p=0.003), but not with adjusted dense area (p=0.07).
We identified two common breast cancer susceptibility variants associated with mammographic measures of radio-dense tissue in the breast gland.
We examined the association of 14 established breast cancer susceptibility loci with mammographic density phenotypes within a large genetic consortium and identified two breast cancer susceptibility variants, LSP1-rs3817198 and RAD51L1-rs10483813, associated with mammographic measures and in the same direction as the breast cancer association.
breast density; breast cancer; genetics; biomarkers; mammography
E-cadherin is involved in cell-cell adhesion and epithelial-to-mesenchymal transitions (EMT). In cancers, loss or inactivation of E-cadherin is associated with epithelial cell proliferation and invasion. Here, we sought to determine if risk associations for 18 breast cancer susceptibility single nucleotide polymorphisms (SNPs) differed by E-cadherin tumor tissue expression in the Polish Breast Cancer Study (PBCS), using data on 1,347 invasive breast cancer cases and 2,366 controls. E-cadherin expression (low/high) was assessed using immunohistochemical staining of tumor tissue microarrays. Replication data on 2,006 cases and 6,714 controls from the Study of Epidemiology and Risk Factors in Cancer Heredity (SEARCH) was used to follow-up promising findings from PBCS. In PBCS, we found the rs11249433 SNP at the 1p11.2 locus to be more strongly associated with risk of E-cadherin low tumors (OR = 1.30, 95% CI 1.08 – 1.56) than with E-cadherin high tumors (OR = 1.06, 95% CI 0.95 – 1.18; case-only p-heterogeneity (p-het) = 0.05). Findings in PBCS for rs11249433 were replicated in SEARCH. Combined analyses of the two datasets for SNP rs11249433 revealed significant heterogeneity by E-cadherin expression (combined case-only p-het = 0.004). Further, among carriers of rs11249433, the highest risk was seen for E-cadherin low tumors that were ER-positive and of lobular histology. Our results in two independent data sets suggest that rs11249433, which is located between the NOTCH2 and FCGR1B genes within the 1p11.2 locus, is more strongly associated with risk of breast tumors with low or absent E-cadherin expression, and suggest that evaluation of E-cadherin tumor tissue expression may be useful in clarifying breast cancer risk factor associations.
Developing improved methods for breast cancer risk prediction could facilitate the targeting of interventions to women at highest risk, thereby reducing mortality, while sparing low-risk women the costs and inconvenience of unnecessary testing and procedures. However, currently available risk assessment tools fall short of achieving accurate individual risk prediction, precluding implementation of this approach. Improving these tools will require the identification of new methods of assessing risk and increasing the accuracy of existing risk indicators. We review four emerging topics that may have importance for breast cancer risk assessment: etiological heterogeneity, genetic susceptibility, mammographic breast density and assessment of breast involution.
Breast Cancer; Risk; Genetics; Mammographic Density; Involution; Etiology; Epidemiology
Women using menopausal hormone therapy (MHT) are at increased risk to develop breast cancer (BC). To detect genetic modifiers of the association between current use of MHT and BC risk, we conducted a meta-analysis of four genome-wide case-only studies followed by replication in eleven case-control studies. We used a case-only design to assess interactions between single nucleotide polymorphisms (SNPs) and current MHT use on risk of overall and lobular BC. The discovery stage included 2,920 cases (541 lobular) from four genome-wide association studies. The top 1,391 SNPs showing P-values for interaction (Pint) <3.0×10−03 were selected for replication using pooled case-control data from eleven studies of the Breast Cancer Association Consortium, including 7,689 cases (676 lobular) and 9,266 controls. Fixed effects meta-analysis was used to derive combined Pint. No SNP reached genome-wide significance in either the discovery or combined stage. We observed effect modification of current MHT use on overall BC risk by two SNPs on chr13 near POMP (combined Pint≤8.9×10−06), two SNPs in SLC25A21 (combined Pint≤4.8×10−05), and three SNPs in PLCG2 (combined Pint≤4.5×10−05). The association between lobular BC risk was potentially modified by one SNP in TMEFF2 (combined Pint≤2.7×10−05), one SNP in CD80 (combined Pint≤8.2×10−06), three SNPs on chr17 near TMEM132E (combined Pint≤2.2×10−06), and two SNPs on chr18 near SLC25A52 (combined Pint≤4.6×10−05). In conclusion, polymorphisms in genes related to solute transportation in mitochondria, transmembrane signaling and immune cell activation are potentially modifying BC risk associated with current use of MHT. These findings warrant replication in independent studies.
breast cancer; genetic variation; menopausal hormone therapy; genome-wide
Individual differences in breast size are a conspicuous feature of variation in human females and have been associated with fecundity and advantage in selection of mates. To identify common variants that are associated with breast size, we conducted a large-scale genotyping association meta-analysis in 7,169 women of European descent across 3 independent sample collections with digital or screen film mammograms.
The samples consisted of the Swedish KARMA, LIBRO-1 and SASBAC studies genotyped on iCOGS, a custom illumina iSelect genotyping array comprising of 211,155 single nucleotide polymorphisms (SNPs) designed for replication and fine mapping of common and rare variants with relevance to breast, ovary and prostate cancer. Breast size of each subject was ascertained by measuring total breast area (mm2) on a mammogram.
We confirm genome-wide significant associations at 8p11.23 (rs10086016, P = 1.3 × 10−14) and report a new locus at 22q13 (rs5995871, P = 3.2 × 10−8). The latter region contains the MKL1 gene, which has been shown to impact endogenous estrogen-receptor α transcriptional activity and is recruited on estradiol-sensitive genes. We also replicated previous GWAS findings for breast size at four other loci.
A new locus at 22q13 may be associated with female breast size.
Genome-wide association studies; population genetics; meta-analysis; breast size
Previous studies of breast tissue gene expression have demonstrated that the extratumoral microenvironment has substantial variability across individuals, some of which can be attributed to epidemiologic factors. To evaluate how mammographic density (MD) and breast tissue composition relate to extratumoral microenvironment gene expression, we used data on 121 breast cancer patients from the population-based Polish Women's Breast Cancer Study.
Breast cancer cases were classified based on a previously reported, biologically-defined extratumoral gene expression signature with two subtypes: an Active subtype, which is associated with high expression of genes related to fibrosis and wound response, and an Inactive subtype, which has high expression of cellular adhesion genes. MD of the contralateral breast was assessed using pre-treatment mammograms and a quantitative, reliable computer-assisted thresholding method. Breast tissue composition was evaluated based on digital image analysis of tissue sections.
The Inactive extratumoral subtype was associated with significantly higher percentage mammographic density (PD) and dense area (DA) in univariate analysis (PD: p=0.001; DA: p=0.049) and in multivariable analyses adjusted for age and body mass index (PD: p=0.004; DA: p=0.049). Inactive/higher MD tissue was characterized by a significantly higher percentage of stroma and a significantly lower percentage of adipose tissue, with no significant change in epithelial content. Analysis of published gene expression signatures suggested that Inactive/higher MD tissue expressed increased estrogen response and decreased TGF-β signaling.
By linking novel molecular phenotypes with MD, our results indicate that MD reflects broad transcriptional changes, including changes in both epithelia- and stroma-derived signaling.
mammographic density; breast microenvironment; gene expression
The single nucleotide polymorphism 5p12-rs10941679has been found to be associated with risk of breast cancer, particularly estrogen receptor (ER)-positive disease. We aimed to further explore this association overall, and by tumor histopathology, in the Breast Cancer Association Consortium.
Data were combined from 37 studies, including 40,972 invasive cases, 1,398 cases of ductal carcinoma in situ (DCIS) and 46,334 controls, all of white European ancestry, as well as 3,007 invasive cases and 2,337 controls of Asian ancestry. Associations overall and by tumor invasiveness and histopathology were assessed using logistic regression.
For white Europeans, the per-allele odds ratio (OR) associated with 5p12-rs10941679 was 1.11 (95% confidence interval [CI] =1.08–1.14, P=7×10−18) for invasive breast cancer and 1.10 (95%CI=1.01–1.21, P=0.03) for DCIS. For Asian women, the estimated OR for invasive disease was similar (OR=1.07, 95%CI=0.99–1.15, P=0.09). Further analyses suggested that the association in white Europeans was largely limited to progesterone receptor (PR)-positive disease (per-allele OR=1.16, 95%CI=1.12–1.20, P=1×10−18 versus OR=1.03, 95%CI=0.99–1.07, P=0.2 for PR-negative disease; P-heterogeneity=2×10−7); heterogeneity by estrogen receptor status was not observed (P=0.2) once PR status was accounted for. The association was also stronger for lower-grade tumors (per-allele OR [95%CI]=1.20 [1.14–1.25], 1.13 [1.09–1.16] and 1.04 [0.99–1.08] for grade 1, 2 and 3/4, respectively; P–trend=5×10−7).
5p12 is a breast cancer susceptibility locus for PR-positive, lower gradebreast cancer.
Multi-centre fine-mapping studies of this region are needed as a first step to identifying the causal variant or variants.
Breast cancer; SNP; susceptibility; disease subtypes
The transforming growth factor beta (TGF-β) pathway can play either a tumor-suppressing or a tumor-promoting role in human breast carcinogenesis. In order to determine whether expression of TGF-β signaling factors varies by age at onset and breast tumor characteristics that have prognostic significance, we undertook a study of 623 women with invasive breast carcinoma enrolled in a population-based case–control study conducted in Poland from 2000 to 2003. TGF-β signaling factors were analyzed by immunohistochemistry in tumor tissue microarrays. We found that most tumors expressed extracellular-TGF-β1 (78%), TGF-β2 (91%), TGF-β3 (93%), TGF-βR2 (72%), and phospho-SMAD2 (61%), whereas intracellular-TGF-β1 was expressed in 32% of tumors. Expression of TGF-β ligands (β1, β2, and β3) was associated with prognostically favorable pathological features including small size, and low grade, and these associations were similar for ER-positive and negative tumors. On the contrary, expression of the receptor TGF-βR2 was primarily associated with small tumor size among ER-negative tumors, while expression of the transcription factor phospho-SMAD2 was associated with positive nodal status among ER-negative tumors. The greater frequency of expression of phospho-SMAD2 in cancers associated with lymph node metastases is consistent with a pro-progression role for TGF-β. In addition, expression of extracellular-TGF-β1 (P = 0.005), TGF-βR2 (P = 8.2E-11), and phospho-SMAD2 (P = 1.3E-8) was strongly associated with earlier age at onset, independent of ER status. Our data provide evidence that TGF-β signaling patterns vary by age and pathologic features of prognostic significance including ER expression. These results warrant analysis in studies of clinical outcomes accounting for age, ER status and treatment.
Transforming growth factor beta; Breast cancer; Estrogen receptor
In the National Cancer Institute Cancer Genetic Markers of Susceptibility (CGEMS) genome-wide association study of breast cancer, a single nucleotide polymorphism (SNP) marker, rs999737, in the 14q24.1 interval, was associated with breast cancer risk. In order to fine map this region, we imputed a 3.93MB region flanking rs999737 for Stages 1 and 2 of the CGEMS study (5,692 cases, 5,576 controls) using the combined reference panels of the HapMap 3 and the 1000 Genomes Project. Single-marker association testing and variable-sized sliding-window haplotype analysis were performed, and for both analyses the initial tagging SNP rs999737 retained the strongest association with breast cancer risk. Investigation of contiguous regions did not reveal evidence for an additional independent signal. Therefore, we conclude that rs999737 is an optimal tag SNP for common variants in the 14q24.1 region and thus narrow the candidate variants that should be investigated in follow-up laboratory evaluation.
RAD51L1; breast cancer; genome-wide association study; fine-mapping; imputation
“Molecular histology” of the breast may be conceptualized as encompassing the normative ranges of histological structure and marker expression in normal breast tissues in relation to a woman’s age and life experiences. Studies of molecular histology can aid our understanding of early events in breast carcinogenesis and provide data for comparison with diseased breast tissues. Until recently, lack of epidemiologically annotated, optimally prepared normal breast tissues obtained from healthy women presented a barrier to breast cancer research. The Komen Tissue Bank at Indiana University is a unique biorepository that was developed to overcome this limitation. The Bank enrolls healthy donors who provide questionnaire data, blood, and up to four breast biopsies, which are prepared as both formalin fixed paraffin embedded and frozen tissues. The resource is accessible to researchers worldwide through a proposal submission, review, and approval process. As of November 2010, the Bank had collected specimens and information from 1,174 donors. In this review, we discuss the importance of studying normal breast tissues, assess the strengths and limitations of studying normal tissues obtained from different sources, and summarize the features of the Komen Tissue Bank. As research projects are completed, results will be posted on the Bank’s website.
Normal breast; Biorepository; Cancer; Biomarkers; Molecular histology
Elevated levels of circulating estrogens and androgens are linked to higher breast cancer risk among postmenopausal women; however, little is known about hormone levels within the breast. Hormone concentrations within the breast may not be reflected in the blood and are likely important contributors to breast carcinogenesis. We used a previously validated method to measure levels of estrone, estradiol, androstenedione and testosterone in adipose tissue removed as part of breast excisions performed for cancer in 100 postmenopausal women (69 ER/PR +/+ and 31 ER/PR −/−) participating in a breast cancer case-control study. We also measured the same steroid hormones, as well as estrone sulfate, and SHBG in serum from these patients and 100 controls matched on ages at blood collection and on menopause.
Overall, concentrations of serum hormones did not vary significantly between controls and cases. However, women with ER−/PR− breast cancers had lower circulating levels of all measured sex steroid hormones and higher SHBG levels than women with ER+/PR+ breast cancers and controls. Similarly, hormone concentrations in breast adipose tissue were higher among women with ER+/PR+ compared to ER−/PR− breast cancer, although differences were only significant for testosterone.
These data demonstrate that high sex steroid concentrations in both serum and adipose tissues are more strongly related to ER+/PR+ than ER−/PR− breast cancers. Measurement of sex hormones in serum and in the microenvironment may help in understanding the hormonal etiology of breast cancer, suggest methods for prevention, and have value in gauging treatment response and prognosis.
sex steroid hormone; breast adipose; breast cancer; intratissue; hormone receptor
Molecular and morphological alterations related to carcinogenesis have been found in terminal duct lobular units (TDLUs), the microscopic structures from which most breast cancer precursors and cancers develop, and therefore, analysis of these structures may reveal early changes in breast carcinogenesis and etiologic heterogeneity. Accordingly, we evaluated relationships of breast cancer risk factors and tumor pathology to estrogen receptor (ER) and progesterone receptor (PR) expression in TDLUs surrounding breast cancers.
We analyzed 270 breast cancer cases included in a population-based breast cancer case-control study conducted in Poland. TDLUs were mapped in relation to breast cancer: within the same block as the tumor (TDLU-T), proximal to tumor (TDLU-PT), or distant from (TDLU-DT). ER/PR was quantitated using image analysis of immunohistochemically stained TDLUs prepared as tissue microarrays.
In surgical specimens containing ER-positive breast cancers, ER and PR levels were significantly higher in breast cancer cells than in normal TDLUs, and higher in TDLU-T than in TDLU-DT or TDLU-PT, which showed similar results. Analyses combining DT-/PT TDLUs within subjects demonstrated that ER levels were significantly lower in premenopausal women vs. postmenopausal women (odds ratio [OR]=0.38, 95% confidence interval [CI]=0.19, 0.76, P=0.0064) and among recent or current menopausal hormone therapy users compared with never users (OR=0.14, 95% CI=0.046–0.43, Ptrend=0.0006). Compared with premenopausal women, TDLUs of postmenopausal women showed lower levels of PR (OR=0.90, 95% CI=0.83–0.97, Ptrend=0.007). ER and PR expression in TDLUs was associated with epidermal growth factor receptor (EGFR) expression in invasive tumors (P=0.019 for ER and P=0.03 for PR), but not with other tumor features.
Our data suggest that TDLUs near breast cancers reflect field effects, whereas those at a distance demonstrate influences of breast cancer risk factors on at-risk breast tissue. Analyses of mapped TDLUs may provide information about the sequence of molecular changes occurring in breast carcinogenesis.
terminal duct lobular units (TDLUs); estrogen receptor; progesterone receptor; breast cancer; risk factors; tumor characteristics
We aim to develop a protein microarray platform capable of presenting both natural and denatured forms of proteins for antibody biomarker discovery. We will further optimize plasma screening protocols to improve detection.
We developed a new covalent capture protein microarray chemistry using HaloTag fusion proteins and ligand. To enhance protein yield, we used HeLa cell lysate as an in vitro transcription translation system (IVTT). E. coli lysates were added to the plasma blocking buffer to reduce non-specific background. These protein microarrays were probed with plasma samples and autoantibody responses were quantified and compared with or without denaturing buffer treatment.
We demonstrated that protein microarrays using the covalent attachment chemistry endured denaturing conditions. Blocking with E. coli lysates greatly reduced the background signals and expression with IVTT based on HeLa cell lysates significantly improved the antibody signals on protein microarrays probed with plasma samples. Plasma samples probed on denatured protein arrays produced autoantibody profiles distinct from those probed on natively displayed proteins.
Conclusions and clinical relevance
This versatile protein microarray platform allows the display of both natural and denatured proteins, offers a new dimension to search for disease-specific antibodies, broadens the repertoire of potential biomarkers, and will potentially yield clinical diagnostics with greater performance.
Antibody; Autoantibody; Biomarker; Protein microarray; Denaturation
We evaluated whether 13 single nucleotide polymorphisms (SNPs) identified in genome-wide association studies interact with one another and with reproductive and menstrual risk factors in association with breast cancer risk. DNA samples and information on parity, breastfeeding, age at menarche, age at first birth, and age at menopause were collected through structured interviews from 1484 breast cancer cases and 1307 controls who participated in a population-based case-control study conducted in three U.S. states. A polygenic score was created as the sum of risk allele copies multiplied by the corresponding log odds estimate. Logistic regression was used to test associations between SNPs, the score, reproductive and menstrual factors and breast cancer risk. Nonlinearity of the score was assessed by the inclusion of a quadratic term for polygenic score. Interactions between the aforementioned variables were tested by including a cross-product term in models. We confirmed associations between rs13387042 (2q35), rs4973768 (SLC4A7), rs10941679 (5p12), rs2981582 (FGFR2), rs3817198 (LSP1), rs3803662 (TOX3) and rs6504950 (STXBP4) with breast cancer. Women in the score’s highest quintile had 2.2-fold increased risk when compared to women in the lowest quintile (95% confidence interval:1.67–2.88). The quadratic polygenic score term was not significant in the model (p=0.85), suggesting established breast cancer loci are not associated with increased risk more than the sum of risk alleles. Modifications of menstrual and reproductive risk factors associations with breast cancer risk by polygenic score were not observed. Our results suggest interactions between breast cancer susceptibility loci and reproductive factors are not strong contributors to breast cancer risk.
Epidemiology; reproductive and menstrual factors; breast cancer; breast cancer susceptibility loci
Candidate variant association studies have been largely unsuccessful in identifying common breast cancer susceptibility variants, although most studies have been underpowered to detect associations of a realistic magnitude. We assessed 41 common non-synonymous single-nucleotide polymorphisms (nsSNPs) for which evidence of association with breast cancer risk had been previously reported. Case-control data were combined from 38 studies of white European women (46 450 cases and 42 600 controls) and analyzed using unconditional logistic regression. Strong evidence of association was observed for three nsSNPs: ATXN7-K264R at 3p21 [rs1053338, per allele OR = 1.07, 95% confidence interval (CI) = 1.04–1.10, P = 2.9 × 10−6], AKAP9-M463I at 7q21 (rs6964587, OR = 1.05, 95% CI = 1.03–1.07, P = 1.7 × 10−6) and NEK10-L513S at 3p24 (rs10510592, OR = 1.10, 95% CI = 1.07–1.12, P = 5.1 × 10−17). The first two associations reached genome-wide statistical significance in a combined analysis of available data, including independent data from nine genome-wide association studies (GWASs): for ATXN7-K264R, OR = 1.07 (95% CI = 1.05–1.10, P = 1.0 × 10−8); for AKAP9-M463I, OR = 1.05 (95% CI = 1.04–1.07, P = 2.0 × 10−10). Further analysis of other common variants in these two regions suggested that intronic SNPs nearby are more strongly associated with disease risk. We have thus identified a novel susceptibility locus at 3p21, and confirmed previous suggestive evidence that rs6964587 at 7q21 is associated with risk. The third locus, rs10510592, is located in an established breast cancer susceptibility region; the association was substantially attenuated after adjustment for the known GWAS hit. Thus, each of the associated nsSNPs is likely to be a marker for another, non-coding, variant causally related to breast cancer risk. Further fine-mapping and functional studies are required to identify the underlying risk-modifying variants and the genes through which they act.
Dietary and circulating carotenoids have been inversely associated with breast cancer risk, but observed associations may be due to confounding. Single nucleotide polymorphisms (SNPs) in β-carotene 15,15′-monooxygenase 1 (BCMO1), a gene encoding the enzyme involved in the first step of synthesizing vitamin A from dietary carotenoids, have been associated with circulating carotenoid concentrations and may serve as unconfounded surrogates for those biomarkers. We determined associations between variants in BCMO1 and breast cancer risk in a large cohort consortium.
We used unconditional logistic regression to test four SNPs in BCMO1 for associations with breast cancer risk in 9,226 cases and 10,420 controls from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3). We also tested weighted multi-SNP scores composed of the two SNPs with strong, confirmed associations with circulating carotenoid concentrations.
Neither the individual SNPs nor the weighted multi-SNP scores were associated with breast cancer risk (odds ratio (95% confidence interval) comparing extreme quintiles of weighted multi-SNP scores =1.04 (0.94–1.16) for β-carotene, 1.08 (0.98–1.20) for α-carotene, 1.04 (0.94–1.16) for β-cryptoxanthin, 0.95 (0.87–1.05) for lutein/zeaxanthin, and 0.92 (0.83–1.02) for retinol). Furthermore, no associations were observed when stratifying by estrogen receptor status, but power was limited.
Our results do not support an association between SNPs associated with circulating carotenoid concentrations and breast cancer risk.
Future studies will need additional genetic surrogates and/or sample sizes at least three times larger to contribute evidence of a causal link between carotenoids and breast cancer.
breast cancer; BCMO1; β-carotene 15,15′-monooxygenase 1; carotenoids; single nucleotide polymorphism
Genes that alter disease risk only in combination with certain
environmental exposures may not be detected in genetic association analysis. By
using methods accounting for gene-environment (G × E) interaction, we
aimed to identify novel genetic loci associated with breast cancer risk. Up to
34,475 cases and 34,786 controls of European ancestry from up to 23 studies in
the Breast Cancer Association Consortium were included. Overall, 71,527 single
nucleotide polymorphisms (SNPs), enriched for association with breast cancer,
were tested for interaction with 10 environmental risk factors using three
recently proposed hybrid methods and a joint test of association and
interaction. Analyses were adjusted for age, study, population stratification,
and confounding factors as applicable. Three SNPs in two independent loci showed
statistically significant association: SNPs rs10483028 and rs2242714 in perfect
linkage disequilibrium on chromosome 21 and rs12197388 in ARID1B on chromosome
6. While rs12197388 was identified using the joint test with parity and with age
at menarche (P-values = 3 × 10−07),
the variants on chromosome 21 q22.12, which showed interaction with adult body
mass index (BMI) in 8,891 postmenopausal women, were identified by all methods
applied. SNP rs10483028 was associated with breast cancer in women with a BMI
below 25 kg/m2 (OR = 1.26, 95% CI 1.15–1.38) but not in women
with a BMI of 30 kg/m2 or higher (OR = 0.89, 95% CI 0.72–1.11,
P for interaction = 3.2 × 10−05).
Our findings confirm comparable power of the recent methods for detecting G
× E interaction and the utility of using G × E interaction
analyses to identify new susceptibility loci.
breast cancer risk; gene-environment interaction; polymorphisms; body mass index; case-control study
Bladder cancer results from the combined effects of environmental and genetic factors, smoking being the strongest risk factor. Evaluating absolute risks resulting from the joint effects of smoking and genetic factors is critical to evaluate the public health relevance of genetic information. Analyses included up to 3,942 cases and 5,680 controls of European background in seven studies. We tested for multiplicative and additive interactions between smoking and 12 susceptibility loci, individually and combined as a polygenic risk score (PRS). Thirty-year absolute risks and risk differences by levels of the PRS were estimated for US-males aged 50-years. Six out of 12 variants showed significant additive gene-environment interactions, most notably NAT2 (P=7×10-4) and UGT1A6 (P=8×10-4). The 30-year absolute risk of bladder cancer in US males was 6.2% for all current smokers. This risk ranged from 2.9% for current smokers in the lowest quartile of the PRS to 9.9% for current smokers in the upper quartile. Risk difference estimates indicated that 8,200 cases would be prevented if elimination of smoking occurred in 100,000 men in the upper PRS quartile, compared to 2,000 cases prevented by a similar effort in the lowest PRS quartile (P-additive =1×10-4). The impact of eliminating smoking the on number of bladder cancer cases prevented is larger for individuals at higher than lower genetic risk. Our findings could have implications for targeted prevention strategies. However, other smoking-related diseases, as well as practical and ethical considerations, need to be considered before any recommendations could be made.
Estrogen receptor (ER)-negative tumors represent 20–30% of all breast cancers, with a higher proportion occurring in younger women and women of African ancestry1. The etiology2 and clinical behavior3 of ER-negative tumors are different from those of tumors expressing ER (ER positive), including differences in genetic predisposition4. To identify susceptibility loci specific to ER-negative disease, we combined in a meta-analysis 3 genome-wide association studies of 4,193 ER-negative breast cancer cases and 35,194 controls with a series of 40 follow-up studies (6,514 cases and 41,455 controls), genotyped using a custom Illumina array, iCOGS, developed by the Collaborative Oncological Gene-environment Study (COGS). SNPs at four loci, 1q32.1 (MDM4, P = 2.1 × 10−12 and LGR6, P = 1.4 × 10−8), 2p24.1 (P = 4.6 × 10−8) and 16q12.2 (FTO, P = 4.0 × 10−8), were associated with ER-negative but not ER-positive breast cancer (P > 0.05). These findings provide further evidence for distinct etiological pathways associated with invasive ER-positive and ER-negative breast cancers.
A few epidemiologic studies have found that use of nonsteroidal anti-inflammatory drugs (NSAIDs) is associated with reduced risk of bladder cancer. However, the effects of specific NSAID use and individual variability in risk have not been well studied. We examined the association between NSAIDs use and bladder cancer risk, and its modification by 39 candidate genes related to NSAID metabolism. A population-based case–control study was conducted in northern New England, enrolling 1,171 newly diagnosed cases and 1,418 controls. Regular use of nonaspirin, nonselective NSAIDs was associated with reduced bladder cancer risk, with a statistically significant inverse trend in risk with duration of use (ORs of 1.0, 0.8, 0.6 and 0.6 for <5, 5–9, 10–19 and 201 years, respectively; ptrend = 0.015). This association was driven mainly by ibuprofen; significant inverse trends in risk with increasing duration and dose of ibuprofen were observed (ptrend = 0.009 and 0.054, respectively). The reduced risk from ibuprofen use was limited to individuals carrying the T allele of a single nucleotide polymorphism (rs4646450) compared to those who did not use ibuprofen and did not carry the T allele in the CYP3A locus, providing new evidence that this association might be modified by polymorphisms in genes that metabolize ibuprofen. Significant positive trends in risk with increasing duration and cumulative dose of selective cyclooxygenase (COX-2) inhibitors were observed. Our results are consistent with those from previous studies linking use of NSAIDs, particularly ibuprofen, with reduced risk. We observed a previously unrecognized risk associated with use of COX-2 inhibitors, which merits further evaluation.
bladder cancer; nonsteroidal anti-inflammatory drugs; gene–drug interaction; CYP3A
Genome-wide association studies have consistently found variants in FGFR2 to be associated with breast cancer. Recent reports suggest that postmenopausal hormone therapy use may modify the association between single nucleotide polymorphisms in FGFR2 and breast cancer risk. We assessed the hypothesis that the association between rs1219648 (FGFR2) single nucleotide polymorphism and breast cancer risk is modified by postmenopausal hormone therapy use in a population-based case-control study.
We evaluated rs1219648 single nucleotide polymorphism for an association with breast cancer risk using data obtained from 869 postmenopausal breast cancer cases diagnosed between the years of 1995-2000 and 808 postmenopausal community controls who participated in a study conducted in three U.S. states. Detailed postmenopausal hormone therapy information was collected through a structured telephone interview and DNA samples were collected through the mail using an established mouthwash protocol. Odds ratios (OR) and 95% confidence intervals (CI) were calculated using logistic regression models adjusted for age and state of residence.
We observed a significant association with the rs1219648 and breast cancer risk (per-allele OR=1.22, 95%CI: 1.06-1.41; p-value=0.007), which did not vary significantly by ever use of estrogen plus progestogen therapy (interaction p-value=0.48). There was stronger evidence of an interaction between ever use of estrogen-only hormone therapy and increasing number of rs1219648 risk alleles to increase breast cancer risk (interaction p-value=0.08).
Our results are consistent with a risk association for FGFR2 but provide limited support for interaction with hormone therapy use. The study raises the possibility that the FGFR2 rs1219648 variant is more strongly associated with risk in estrogen-only hormone users, though this observation needs to be examined in larger studies.
breast cancer; genetics; hormone therapy; gene-environment interaction; epidemiology
The length of female reproductive lifespan is associated with multiple adverse outcomes, including breast cancer, cardiovascular disease and infertility. The biological processes that govern the timing of the beginning and end of reproductive life are not well understood. Genetic variants are known to contribute to ∼50% of the variation in both age at menarche and menopause, but to date the known genes explain <15% of the genetic component. We have used genome-wide association in a bivariate meta-analysis of both traits to identify genes involved in determining reproductive lifespan. We observed significant genetic correlation between the two traits using genome-wide complex trait analysis. However, we found no robust statistical evidence for individual variants with an effect on both traits. A novel association with age at menopause was detected for a variant rs1800932 in the mismatch repair gene MSH6 (P = 1.9 × 10−9), which was also associated with altered expression levels of MSH6 mRNA in multiple tissues. This study contributes to the growing evidence that DNA repair processes play a key role in ovarian ageing and could be an important therapeutic target for infertility.
Genome-wide association studies (GWAS) of breast cancer defined by hormone receptor status have revealed loci contributing to susceptibility of estrogen receptor (ER)-negative subtypes. To identify additional genetic variants for ER-negative breast cancer, we conducted the largest meta-analysis of ER-negative disease to date, comprising 4754 ER-negative cases and 31 663 controls from three GWAS: NCI Breast and Prostate Cancer Cohort Consortium (BPC3) (2188 ER-negative cases; 25 519 controls of European ancestry), Triple Negative Breast Cancer Consortium (TNBCC) (1562 triple negative cases; 3399 controls of European ancestry) and African American Breast Cancer Consortium (AABC) (1004 ER-negative cases; 2745 controls). We performed in silico replication of 86 SNPs at P ≤ 1 × 10-5 in an additional 11 209 breast cancer cases (946 with ER-negative disease) and 16 057 controls of Japanese, Latino and European ancestry. We identified two novel loci for breast cancer at 20q11 and 6q14. SNP rs2284378 at 20q11 was associated with ER-negative breast cancer (combined two-stage OR = 1.16; P = 1.1 × 10−8) but showed a weaker association with overall breast cancer (OR = 1.08, P = 1.3 × 10–6) based on 17 869 cases and 43 745 controls and no association with ER-positive disease (OR = 1.01, P = 0.67) based on 9965 cases and 22 902 controls. Similarly, rs17530068 at 6q14 was associated with breast cancer (OR = 1.12; P = 1.1 × 10−9), and with both ER-positive (OR = 1.09; P = 1.5 × 10−5) and ER-negative (OR = 1.16, P = 2.5 × 10−7) disease. We also confirmed three known loci associated with ER-negative (19p13) and both ER-negative and ER-positive breast cancer (6q25 and 12p11). Our results highlight the value of large-scale collaborative studies to identify novel breast cancer risk loci.
There has been a long-standing controversy in epidemiology with regard to an appropriate risk scale for testing interactions between genes (G) and environmental exposure (E ). Although interaction tests based on the logistic model—which approximates the multiplicative risk for rare diseases—have been more widely applied because of its convenience in statistical modeling, interactions under additive risk models have been regarded as closer to true biologic interactions and more useful in intervention-related decision-making processes in public health. It has been well known that exploiting a natural assumption of G-E independence for the underlying population can dramatically increase statistical power for detecting multiplicative interactions in case-control studies. However, the implication of the independence assumption for tests for additive interaction has not been previously investigated. In this article, the authors develop a likelihood ratio test for detecting additive interactions for case-control studies that incorporates the G-E independence assumption. Numerical investigation of power suggests that incorporation of the independence assumption can enhance the efficiency of the test for additive interaction by 2- to 2.5-fold. The authors illustrate their method by applying it to data from a bladder cancer study.
additive risk model; case-control studies; gene-environment independence; gene-environment interaction; multiplicative risk model