Endometrial cancer is the most common malignancy of the female genital tract in developed countries. To identify genetic variants associated with endometrial cancer risk, we undertook a genome-wide association study involving 1,265 endometrial cancer cases from Australia and the UK and 5,190 controls from the Wellcome Trust Case Control Consortium. Genotype frequencies in cases and controls were compared for 519,655 SNPs. Forty-seven SNPs that showed evidence of association with endometrial cancer in stage 1 were genotyped in 3,957 additional cases and 6,886 controls. We identified an endometrial cancer susceptibility locus close to HNF1B on chromosome 17q (SNP rs4430796: P=7.1×10−10), that is also associated with risk of prostate cancer and is inversely associated with type 2 diabetes.
Recent genome-wide association studies identified 11 single nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk. We investigated these and 62 other SNPs for their prognostic relevance. Confirmed BC risk SNPs rs17468277 (CASP8), rs1982073 (TGFB1), rs2981582 (FGFR2), rs13281615 (8q24), rs3817198 (LSP1), rs889312 (MAP3K1), rs3803662 (TOX3), rs13387042 (2q35), rs4973768 (SLC4A7), rs6504950 (COX11) and rs10941679 (5p12) were genotyped for 25 853 BC patients with the available follow-up; 62 other SNPs, which have been suggested as BC risk SNPs by a GWAS or as candidate SNPs from individual studies, were genotyped for replication purposes in subsets of these patients. Cox proportional hazard models were used to test the association of these SNPs with overall survival (OS) and BC-specific survival (BCS). For the confirmed loci, we performed an accessory analysis of publicly available gene expression data and the prognosis in a different patient group. One of the 11 SNPs, rs3803662 (TOX3) and none of the 62 candidate/GWAS SNPs were associated with OS and/or BCS at P<0.01. The genotypic-specific survival for rs3803662 suggested a recessive mode of action [hazard ratio (HR) of rare homozygous carriers=1.21; 95% CI: 1.09–1.35, P=0.0002 and HR=1.29; 95% CI: 1.12–1.47, P=0.0003 for OS and BCS, respectively]. This association was seen similarly in all analyzed tumor subgroups defined by nodal status, tumor size, grade and estrogen receptor. Breast tumor expression of these genes was not associated with prognosis. With the exception of rs3803662 (TOX3), there was no evidence that any of the SNPs associated with BC susceptibility were associated with the BC survival. Survival may be influenced by a distinct set of germline variants from those influencing susceptibility.
Percent mammographic density adjusted for age and body mass index (BMI) is one of the strongest risk factors for breast cancer and has a heritable component that remains largely unidentified. We performed a three-stage genome-wide association study (GWAS) of percent mammographic density to identify novel genetic loci associated with this trait. In stage 1, we combined three GWASs of percent density comprised of 1241 women from studies at the Mayo Clinic and identified the top 48 loci (99 single nucleotide polymorphisms). We attempted replication of these loci in 7018 women from seven additional studies (stage 2). The meta-analysis of stage 1 and 2 data identified a novel locus, rs1265507 on 12q24, associated with percent density, adjusting for age and BMI (P = 4.43 × 10−8). We refined the 12q24 locus with 459 additional variants (stage 3) in a combined analysis of all three stages (n = 10 377) and confirmed that rs1265507 has the strongest association in the 12q24 region (P = 1.03 × 10−8). Rs1265507 is located between the genes TBX5 and TBX3, which are members of the phylogenetically conserved T-box gene family and encode transcription factors involved in developmental regulation. Understanding the mechanism underlying this association will provide insight into the genetics of breast tissue composition.
Validation of an association between the UGT1A6_19_T>G (rs6759892) polymorphism and overall breast cancer risk. A pilot study included two population-based case-control studies from Germany (MARIE-GENICA). An independent validation study comprised four independent breast cancer case-control studies from Finland (KBCP, OBCS), Germany (BBCC), and Sweden (SASBAC). The pooled analysis included 7418 cases and 8720 controls from all six studies. Participants were of European descent. Genotyping was done by MALDI-TOF MS and statistical analysis was performed by logistic regression adjusted for age and study. The increased overall breast cancer risk for women with the UGT1A6_19_GG genotype which was observed in the pilot study was confirmed in the set of four independent study collections (OR 1.13, 95% CI 1.05–1.22; p = 0.001). The pooled study showed a similar effect (OR 1.09, 95% CI 1.04–1.14; p = 0.001). The risk effect on the basis of allele frequencies was highly significant, the pooled analysis showed an OR of 1.11 (95% CI 1.06–1.16; p = 5.8 × 10−6). We confirmed the association of UGT1A6_19_GG with increased overall breast cancer risk and conclude that our result from a well powered multi-stage study adds a novel candidate to the panel of validated breast cancer susceptibility loci.
UGT1A6; polymorphism; breast cancer risk; validation; metabolism
Breast cancer is the most common cancer among women. To date, 22 common breast cancer susceptibility loci have been identified accounting for ~ 8% of the heritability of the disease. We followed up 72 promising associations from two independent Genome Wide Association Studies (GWAS) in ~70,000 cases and ~68,000 controls from 41 case-control studies and nine breast cancer GWAS. We identified three new breast cancer risk loci on 12p11 (rs10771399; P=2.7 × 10−35), 12q24 (rs1292011; P=4.3×10−19) and 21q21 (rs2823093; P=1.1×10−12). SNP rs10771399 was associated with similar relative risks for both estrogen receptor (ER)-negative and ER-positive breast cancer, whereas the other two loci were associated only with ER-positive disease. Two of the loci lie in regions that contain strong plausible candidate genes: PTHLH (12p11) plays a crucial role in mammary gland development and the establishment of bone metastasis in breast cancer, while NRIP1 (21q21) encodes an ER co-factor and has a role in the regulation of breast cancer cell growth.
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
Research has found that patients treated for cancer generally have an increased risk for cognitive problems. However, many studies have focused on cognitive performance of cancer patients under the age of 65 who received chemotherapy treatment. Less studied is the extent to which cancer diagnosis may be associated with cognitive impairment as a late effect for older adults.
In this retrospective, co-twin design study, twin pairs 65 years of age and older discordant for cancer were identified from the Swedish Twin Registry. A pair was included if both twins participated in cognitive screening, and the twin with the cancer history was screened at least 3 years after cancer diagnosis and treatment.
Female, but not male, survivors of cancer were significantly (odds ratio = 2.42, 95% confidence interval = 1.23–4.74) more likely to exhibit cognitive impairment 3 or more years after cancer diagnosis and treatment as their co-twin without a history of cancer. In particular, risk was higher among survivors of gynecologic cancers (odds ratio = 10.00, 95% confidence interval = 1.28–78.11) and those who had treatments directly or potentially affecting ovarian functioning (odds ratio = 13.00, 95% confidence interval = 1.70–99.36) compared with their respective co-twins.
These findings suggest that localized treatments and other cancer-related factors should be explored as determinants that underlie the association between cancer diagnosis and long-term cognitive impairment.
Cancer treatment; Long-term effects; Cognitive impairment; Twin analysis
Recent large--scale association studies, both of genome-wide and candidate gene design, have revealed several single-nucleotide polymorphisms (SNPs) which are significantly associated with risk of developing breast cancer. As both breast and endometrial cancers are considered to be hormonally driven and share multiple risk factors, we investigated whether breast cancer risk alleles are also associated with endometrial cancer risk. We genotyped nine breast cancer risk SNPs in up to 4188 endometrial cases and 11 928 controls, from between three and seven Caucasian populations. None of the tested SNPs showed significant evidence of association with risk of endometrial cancer.
During the recent years, rapid development of sequencing technologies and a competitive market has enabled researchers to perform massive sequencing projects at a reasonable cost. As the price for the actual sequencing reactions drops, enabling more samples to be sequenced, the relative price for preparing libraries gets larger and the practical laboratory work becomes complex and tedious. We present a cost-effective strategy for simplified library preparation compatible with both whole genome- and targeted sequencing experiments. An optimized enzyme composition and reaction buffer reduces the number of required clean-up steps and allows for usage of bulk enzymes which makes the whole process cheap, efficient and simple. We also present a two-tagging strategy, which allows for multiplex sequencing of targeted regions. To prove our concept, we have prepared libraries for low-pass sequencing from 100 ng DNA, performed 2-, 4- and 8-plex exome capture and a 96-plex capture of a 500 kb region. In all samples we see a high concordance (>99.4%) of SNP calls when comparing to commercially available SNP-chip platforms.
Background: Although high doses of ionizing radiation have long been linked to circulatory disease, evidence for an association at lower exposures remains controversial. However, recent analyses suggest excess relative risks at occupational exposure levels.
Objectives: We performed a systematic review and meta-analysis to summarize information on circulatory disease risks associated with moderate- and low-level whole-body ionizing radiation exposures.
Methods: We conducted PubMed/ISI Thomson searches of peer-reviewed papers published since 1990 using the terms “radiation” AND “heart” AND “disease,” OR “radiation” AND “stroke,” OR “radiation” AND “circulatory” AND “disease.” Radiation exposures had to be whole-body, with a cumulative mean dose of < 0.5 Sv, or at a low dose rate (< 10 mSv/day). We estimated population risks of circulatory disease from low-level radiation exposure using excess relative risk estimates from this meta-analysis and current mortality rates for nine major developed countries.
Results: Estimated excess population risks for all circulatory diseases combined ranged from 2.5%/Sv [95% confidence interval (CI): 0.8, 4.2] for France to 8.5%/Sv (95% CI: 4.0, 13.0) for Russia.
Conclusions: Our review supports an association between circulatory disease mortality and low and moderate doses of ionizing radiation. Our analysis was limited by heterogeneity among studies (particularly for noncardiac end points), the possibility of uncontrolled confounding in some occupational groups by lifestyle factors, and higher dose groups (> 0.5 Sv) generally driving the observed trends. If confirmed, our findings suggest that overall radiation-related mortality is about twice that currently estimated based on estimates for cancer end points alone (which range from 4.2% to 5.6%/Sv for these populations).
cancer; circulatory disease; heart disease; radiation; stroke
It is unclear whether estrogen receptor (ER)-status of first primary breast cancer is associated with risk of metachronous (non-simultaneous) contralateral breast cancer (CBC), and to what extent endocrine therapy affects this association.
We studied the effect of ER-status of the first cancer on the risk of CBC overall, and for different ER-subtypes of CBC, using a large, population-based cohort. The cohort consisted of all women diagnosed with breast cancer in the Stockholm region 1976–2005; 25715 patients, of whom 940 suffered CBC. The relative risk was analyzed mainly using standardized incidence ratios (SIR).
Women with breast cancer had a doubled risk of CBC compared to the risk of breast cancer in the general female population (SIR: 2.22 [2.08–2.36]), for women with a previous ER-positive cancer: SIR = 2.30 (95% CI:2.11–2.50) and for women with a previous ER-negative cancer: SIR = 2.17 (95% CI:1.82–2.55). The relative risk of ER-positive and ER-negative CBC was very similar for women with ER-positive first cancer (SIR = 2.02 [95%CI: 1.80–2.27] and SIR = 1.89 [95%CI: 1.46–2.41] respectively) while for patients with ER-negative first cancer the relative risk was significantly different (SIR = 1.27 [95% CI:0.94–1.68] for ER-positive CBC and SIR = 4.96 [95%CI:3.67–6.56] for ER-negative CBC). Patients with ER-positive first cancer who received hormone therapy still had a significantly higher risk of CBC than the risk of breast cancer for the general female population (SIR = 1.74 [95% CI:1.47–2.03]).
The risk of CBC for a breast cancer patient is increased to about two-fold, compared to the risk of breast cancer in the general female population. This excess risk decreases, but does not disappear, with adjuvant endocrine therapy. Patients with ER-positive first cancers have an increased risk for CBC of both ER subtypes, while patients with ER-negative first cancer have a specifically increased risk of ER-negative CBC.
Percent mammographic breast density (PMD) is a strong heritable risk factor for breast cancer. However, the pathways through which this risk is mediated are still unclear. To explore whether PMD and breast cancer have a shared genetic basis, we identified genetic variants most strongly associated with PMD in a published meta-analysis of five genome-wide association studies (GWAS) and used these to construct risk scores for 3628 breast cancer cases and 5190 controls from the UK2 GWAS of breast cancer. The signed per-allele effect estimates of SNPs were multiplied with the respective allele counts in the individual and summed over all SNPs to derive the risk score for an individual. These scores were included as the exposure variable in a logistic regression model with breast cancer case-control status as the outcome. This analysis was repeated using ten different cut-offs for the most significant density SNPs (1-10% representing 5,222-50,899 SNPs). Permutation analysis was also performed across all 10 cut-offs. The association between risk score and breast cancer was significant for all cut-offs from 3-10% of top density SNPs, being most significant for the 6% (2-sided P=0.002) to 10% (P=0.001) cut-offs (overall permutation P=0.003). Women in the top 10% of the risk score distribution had a 31% increased risk of breast cancer [OR= 1.31 (95%CI 1.08-1.59)] compared to women in the bottom 10%. Together, our results demonstrate that PMD and breast cancer have a shared genetic basis that is mediated through a large number of common variants.
breast cancer; mammographic density; SNPs; polygenic; Mendelian Randomisation
Given that the transcriptional regulatory activity of estrogen receptor (ER) is modulated by its biochemical cofactors, genetic variation within the ER cofactor genes may alter cellular response to estrogen exposure and consequently modify the risk for endometrial cancer. We genotyped 685 tagging SNPs within 60 ER cofactor genes in 564 endometrial cancer cases and 1,510 controls from Sweden, and tested their associations with the risk of endometrial cancer. We investigated the associations of individual SNPs by using a trend test as well as multiple SNPs within a gene or gene complex by using multi-variant association analysis. No significant association was observed for any individual SNPs or genes, but a marginal association of the cumulative genetic variation of the NCOA2 complex as a whole (NCOA2, CARM1, CREBBP, PRMT1 and EP300) with endometrial cancer risk was observed (Padjusted = 0.033). However, the association failed to be replicated in an independent European dataset of 1265 cases and 5190 controls (P = 0.71). The results indicate that common genetic variants within ER cofactor genes are unlikely to play a significant role in endometrial cancer risk in European population.
Mammographic density (MD) is a strong, independent risk factor for breast cancer, but measuring MD is time consuming and reader dependent. Objective MD measurement in a high-throughput fashion would enable its wider use as a biomarker for breast cancer. We use a public domain image-processing software for the fully automated analysis of MD and penalized regression to construct a measure that mimics a well-established semiautomated measure (Cumulus). We also describe measures that incorporate additional features of mammographic images for improving the risk associations of MD and breast cancer risk.
We randomly partitioned our dataset into a training set for model building (733 cases, 748 controls) and a test set for model assessment (765 cases, 747 controls). The Pearson product-moment correlation coefficient (r) was used to compare the MD measurements by Cumulus and our automated measure, which mimics Cumulus. The likelihood ratio test was used to validate the performance of logistic regression models for breast cancer risk, which included our measure capturing additional information in mammographic images.
We observed a high correlation between the Cumulus measure and our measure mimicking Cumulus (r = 0.884; 95% CI, 0.872 to 0.894) in an external test set. Adding a variable, which includes extra information to percentage density, significantly improved the fit of the logistic regression model of breast cancer risk (P = 0.0002).
Our results demonstrate the potential to facilitate the integration of mammographic density measurements into large-scale research studies and subsequently into clinical practice.
Relative survival is commonly used for studying survival of cancer patients as it captures both the direct and indirect contribution of a cancer diagnosis on mortality by comparing the observed survival of the patients to the expected survival in a comparable cancer-free population. However, existing methods do not allow estimation of the impact of isolated conditions (e.g., excess cardiovascular mortality) on the total excess mortality. For this purpose we extend flexible parametric survival models for relative survival, which use restricted cubic splines for the baseline cumulative excess hazard and for any time-dependent effects.
In the extended model we partition the excess mortality associated with a diagnosis of cancer through estimating a separate baseline excess hazard function for the outcomes under investigation. This is done by incorporating mutually exclusive background mortality rates, stratified by the underlying causes of death reported in the Swedish population, and by introducing cause of death as a time-dependent effect in the extended model. This approach thereby enables modeling of temporal trends in e.g., excess cardiovascular mortality and remaining cancer excess mortality simultaneously. Furthermore, we illustrate how the results from the proposed model can be used to derive crude probabilities of death due to the component parts, i.e., probabilities estimated in the presence of competing causes of death.
The method is illustrated with examples where the total excess mortality experienced by patients diagnosed with breast cancer is partitioned into excess cardiovascular mortality and remaining cancer excess mortality.
The proposed method can be used to simultaneously study disease patterns and temporal trends for various causes of cancer-consequent deaths. Such information should be of interest for patients and clinicians as one way of improving prognosis after cancer is through adapting treatment strategies and follow-up of patients towards reducing the excess mortality caused by side effects of the treatment.
Survival analysis; Cancer; Relative survival; Regression models; Competing risks
Using the Breast Cancer Association Consortium, the authors previously reported that the single nucleotide polymorphism 7q21-rs6964587 (AKAP9-M463I) is associated with breast cancer risk. The authors have now assessed this association more comprehensively using 16 independent case–control studies.
The authors genotyped 14 843 invasive case patients and 19 852 control subjects with white European ancestry and 2595 invasive case patients and 2192 control subjects with Asian ancestry. ORs were estimated by logistic regression, adjusted for study. Heterogeneity in ORs was assessed by fitting interaction terms or by subclassifying case patients and applying polytomous logistic regression.
For white European women, the minor T allele of 7q21-rs6964587 was associated with breast cancer risk under a recessive model (OR 1.07, 95% CI 1.00 to 1.13, p = 0.04). Results were inconclusive for Asian women. From a combined analysis of 24 154 case patients and 33 376 control subjects of white European ancestry from the present and previous series, the best-fitting model was recessive, with an estimated OR of 1.08 (95% CI 1.03 to 1.13, p = 0.001). The OR was greater at younger ages (p trend = 0.01).
This may be the first common susceptibility allele for breast cancer to be identified with a recessive mode of inheritance.
Prolonged excessive estrogen exposure unopposed by progesterone is widely accepted to be a risk factor for endometrial cancer development. The physiological function of progesterone is dependent upon the presence of its receptor [progesterone receptor (PGR)] and several studies have reported single nucleotide polymorphisms (SNPs) in the PGR gene to be associated with endometrial cancer risk. We sought to confirm the associations with endometrial cancer risk previously reported for four different PGR polymorphisms. A maximum of 2888 endometrial cancer cases and 4483 female control subjects from up to three studies were genotyped for four PGR polymorphisms (rs1042838, rs10895068, rs11224561 and rs471767). Logistic regression with adjustment for age, study, ethnicity and body mass index was performed to calculate odds ratios (ORs) and associated 95% confidence intervals (CIs) and P-values. Of the four SNPs investigated, only rs11224561 in the 3′ region of the PGR gene was found to be significantly associated with endometrial cancer risk. The A allele of the rs11224561 SNP was associated with increased risk of endometrial cancer (OR per allele 1.31; 95% CI 1.12–1.53, P = 0.001, adjusted for age and study), an effect of the same magnitude and direction as reported previously. We have validated the endometrial cancer risk association with a tagSNP in the 3′ untranslated region of PGR previously reported in an Asian population. Replication studies will be required to refine the risk estimate and to establish if this, or a correlated SNP, is the underlying causative variant.
The dyslexia candidate gene, DYX1C1, shown to regulate and interact with estrogen receptors and involved in the regulation of neuronal migration, has recently been proposed as a putative cancer biomarker. This study was undertaken to assess the prognostic value and therapy-predictive potential of DYX1C1 mRNA and protein expression in breast cancer.
DYX1C1 mRNA expression was assessed at the mRNA level in three independent population-derived patient cohorts. An association to estrogen/progesterone receptor status, Elston grade, gene expression subtype and lymph node status was analyzed within these cohorts. DYX1C1 protein expression was examined using immunohistochemistry in cancer and normal breast tissue. The statistical analyses were performed using the non-parametric Wilcoxon rank-sum test, ANOVA, Fisher's exact test and a multivariate proportional hazard (Cox) model.
DYX1C1 mRNA is significantly more highly expressed in tumors that have been classified as estrogen receptor α and progesterone receptor-positive. The expression of DYX1C1 among the molecular subtypes shows the lowest median expression within the basal type tumors, which are considered to have the worst prognosis. The expression of DYX1C1 is significantly lower in tumors graded as Elston grade 3 compared with grades 1 and 2. DYX1C1 protein is expressed in 88% of tumors and in all 10 normal breast tissues examined. Positive protein expression was significantly correlated to overall survival (Hazard ratio 3.44 [CI 1.84-6.42]) of the patients but not to any of the variables linked with mRNA expression.
We show that the expression of DYX1C1 in breast cancer is associated with several clinicopathological parameters and that loss of DYX1C1 correlates with a more aggressive disease, in turn indicating that DYX1C1 is a potential prognostic biomarker in breast cancer.
DYX1C1; Breast cancer; Estrogen receptor; Dyslexia
Over the last decade several breast cancer risk alleles have been identified which has led to an increased interest in individualised risk prediction for clinical purposes.
We investigate the performance of an up-to-date 18 breast cancer risk single-nucleotide polymorphisms (SNPs), together with mammographic percentage density (PD), body mass index (BMI) and clinical risk factors in predicting absolute risk of breast cancer, empirically, in a well characterised Swedish case-control study of postmenopausal women. We examined the efficiency of various prediction models at a population level for individualised screening by extending a recently proposed analytical approach for estimating number of cases captured.
The performance of a risk prediction model based on an initial set of seven breast cancer risk SNPs is improved by additionally including eleven more recently established breast cancer risk SNPs (P = 4.69 × 10-4). Adding mammographic PD, BMI and all 18 SNPs to a Swedish Gail model improved the discriminatory accuracy (the AUC statistic) from 55% to 62%. The net reclassification improvement was used to assess improvement in classification of women into low, intermediate, and high categories of 5-year risk (P = 8.93 × 10-9). For scenarios we considered, we estimated that an individualised screening strategy based on risk models incorporating clinical risk factors, mammographic density and SNPs, captures 10% more cases than a screening strategy using the same resources, based on age alone. Estimates of numbers of cases captured by screening stratified by age provide insight into how individualised screening programs might appear in practice.
Taken together, genetic risk factors and mammographic density offer moderate improvements to clinical risk factor models for predicting breast cancer.
Previous studies have suggested that breast cancer risk factors are associated with estrogen receptor (ER) and progesterone receptor (PR) expression status of the tumors.
We pooled tumor marker and epidemiological risk factor data from 35 568 invasive breast cancer case patients from 34 studies participating in the Breast Cancer Association Consortium. Logistic regression models were used in case–case analyses to estimate associations between epidemiological risk factors and tumor subtypes, and case–control analyses to estimate associations between epidemiological risk factors and the risk of developing specific tumor subtypes in 12 population-based studies. All statistical tests were two-sided.
In case–case analyses, of the epidemiological risk factors examined, early age at menarche (≤12 years) was less frequent in case patients with PR− than PR+ tumors (P = .001). Nulliparity (P = 3 × 10−6) and increasing age at first birth (P = 2 × 10−9) were less frequent in ER− than in ER+ tumors. Obesity (body mass index [BMI] ≥ 30 kg/m2) in younger women (≤50 years) was more frequent in ER−/PR− than in ER+/PR+ tumors (P = 1 × 10−7), whereas obesity in older women (>50 years) was less frequent in PR− than in PR+ tumors (P = 6 × 10−4). The triple-negative (ER−/PR−/HER2−) or core basal phenotype (CBP; triple-negative and cytokeratins [CK]5/6+ and/or epidermal growth factor receptor [EGFR]+) accounted for much of the heterogeneity in parity-related variables and BMI in younger women. Case–control analyses showed that nulliparity, increasing age at first birth, and obesity in younger women showed the expected associations with the risk of ER+ or PR+ tumors but not triple-negative (nulliparity vs parity, odds ratio [OR] = 0.94, 95% confidence interval [CI] = 0.75 to 1.19, P = .61; 5-year increase in age at first full-term birth, OR = 0.95, 95% CI = 0.86 to 1.05, P = .34; obesity in younger women, OR = 1.36, 95% CI = 0.95 to 1.94, P = .09) or CBP tumors.
This study shows that reproductive factors and BMI are most clearly associated with hormone receptor–positive tumors and suggest that triple-negative or CBP tumors may have distinct etiology.
Increased mammographic breast density is one of the strongest risk factors for breast cancer. While two-thirds of the variation in mammographic density appears to be genetically influenced, few variants have been identified. We examined the association of inherited variation in genes from pathways that mediate cell division with percent mammographic density (PMD) adjusted for age, body mass index (BMI) and postmenopausal hormones, in two studies of healthy postmenopausal women.
We investigated 2,058 single nucleotide polymorphisms (SNPs) in 378 genes involved in regulation of mitosis for associations with adjusted PMD among 484 unaffected postmenopausal controls (without breast cancer) from the Mayo Clinic Breast Cancer Study (MCBCS) and replicated the findings in postmenopausal controls (n = 726) from the Singapore and Sweden Breast Cancer Study (SASBAC) study. PMD was assessed in both studies by a computer-thresholding method (Cumulus) and linear regression approaches were used to assess the association of SNPs and PMD, adjusted for age, BMI and postmenopausal hormones. A P-value threshold of 4.2 × 10-5 based on a Bonferroni correction of effective number of independent tests was used for statistical significance. Further, a pathway-level analysis was conducted of all 378 genes using the self-contained gene-set analysis method GLOSSI.
A variant in PRPF4, rs10733604, was significantly associated with adjusted PMD in the MCBCS (P = 2.7 × 10-7), otherwise, no single SNP was associated with PMD. Additionally, the pathway analysis provided no evidence of enrichment in the number of associations observed between SNPs in the mitotic genes and PMD (P = 0.60). We evaluated rs10733604 (PRPF4), and 73 other SNPs at P < 0.05 from 51 genes in the SASBAC study. There was no evidence of an association of rs10733604 (PRPF4) with adjusted PMD in SASBAC (P = 0.23). There were, however, consistent associations (P < 0.05) of variants at the putative locus, LOC375190, Aurora B kinase (AURKB), and Mini-chromosome maintenance complex component 3 (MCM3) with adjusted PMD, although these were not statistically significant.
Our findings do not support a role of inherited variation in genes involved in regulation of cell division and adjusted percent mammographic density in postmenopausal women.
Incidence of breast cancer is increasing around the world and it is still the leading cause of cancer mortality in low- and middle-income countries. We utilized Swedish nationwide registers to study breast cancer incidence and case fatality to disentangle the effect of socioeconomic position (SEP) and immigration from the trends in native Swedes.
A nation-wide cohort of women in Sweden was followed between 1961 and 2007 and incidence rate ratio (IRR) and hazard ratio (HR) with 95% confidence intervals (CIs) were estimated using Poisson and Cox proportional regression models, respectively.
Incidence continued to increase; however, it remained lower among immigrants (IRR = 0.88, 95% CI = 0.86 to 0.90) but not among immigrants' daughters (IRR = 0.97, 95% CI = 0.94 to 1.01) compared to native Swedes. Case fatality decreased over the last decades and was similar in native Swedes and immigrants. However, case fatality was significantly 14% higher if cancer was diagnosed after age 50 and 20% higher if cancer was diagnosed in the most recent years among immigrants compared with native Swedes. Women with the highest SEP had significantly 20% to 30% higher incidence but had 30% to 40% lower case fatality compared with women with the lowest SEP irrespective of country of birth. Age at immigration and duration of residence significantly modified the incidence and case fatality.
Disparities found in case fatality among immigrants by age, duration of residence, age at immigration and country of birth emphasize the importance of targeting interventions on women that are not likely to attend screenings or are not likely to adhere to the therapy suggested by physicians. The lower risk of breast cancer among immigrant women calls for more knowledge about how the lifestyle factors in these women differ from those with high risk, so that preventative measures may be implemented.
A cost-efficient way to increase power in a genetic association study is to pool controls from different sources. The genotyping effort can then be directed to large case series. The Nordic Control database, NordicDB, has been set up as a unique resource in the Nordic area and the data are available for authorized users through the web portal (http://www.nordicdb.org). The current version of NordicDB pools together high-density genome-wide SNP information from ∼5000 controls originating from Finnish, Swedish and Danish studies and shows country-specific allele frequencies for SNP markers. The genetic homogeneity of the samples was investigated using multidimensional scaling (MDS) analysis and pairwise allele frequency differences between the studies. The plot of the first two MDS components showed excellent resemblance to the geographical placement of the samples, with a clear NW–SE gradient. We advise researchers to assess the impact of population structure when incorporating NordicDB controls in association studies. This harmonized Nordic database presents a unique genome-wide resource for future genetic association studies in the Nordic countries.
common controls; genome-wide data; Nordic Control Database; population stratification
High percent mammographic density adjusted for age and body mass index (BMI) is one of the strongest risk factors for breast cancer. We conducted a meta-analysis of five genome-wide association studies of percent mammographic density and report an association with rs10995190 in ZNF365 (combined P=9×6·10−10). This finding might partly explain the underlying biology of the recently discovered association between common variants in ZNF365 and breast cancer risk.