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Breast tissue enhances on contrast MRI and is called background parenchymal enhancement (BPE). Having high BPE has been associated with an increased risk of breast cancer. We examined the relationship between BPE and the amount of fibroglandular tissue on MRI (MRI-FGT) and breast cancer risk factors. This was a cross-sectional study of 415 women without breast cancer undergoing contrast-enhanced breast MRI at Memorial Sloan Kettering Cancer Center. All women completed a questionnaire assessing exposures at the time of MRI. Prevalence ratios (PR) and 95% confidence intervals (CI) describing the relationship between breast cancer risk factors and BPE and MRI-FGT were generated using modified Poisson regression. In multivariable-adjusted models a positive association between body mass index (BMI) and BPE was observed, with a 5-unit increase in BMI associated with a 14% and 44% increase in prevalence of high BPE in pre- and post-menopausal women, respectively. Conversely, a strong inverse relationship between BMI and MRI-FGT was observed in both pre- (PR = 0.66, 95% CI 0.57, 0.76) and post-menopausal (PR = 0.66, 95% CI 0.56, 0.78) women. Use of preventive medication (e.g., tamoxifen) was associated with having low BPE, while no association was observed for MRI-FGT. BPE is an imaging marker available from standard contrast-enhanced MRI, that is influenced by endogenous and exogenous hormonal exposures in both pre- and post-menopausal women.

BACKGROUND: Background parenchymal enhancement (BPE) on breast magnetic resonance imaging (MRI) may be associated with breast cancer risk, but previous studies of the association are equivocal and limited by incomplete blinding of BPE assessment. In this study, we evaluated the association between BPE and breast cancer based on fully blinded assessments of BPE in the unaffected breast. METHODS: The Imaging and Epidemiology (IMAGINE) study is a multicenter breast cancer case-control study of women receiving diagnostic, screening, or follow-up breast MRI, recruited from three comprehensive cancer centers in the USA. Cases had a first diagnosis of unilateral breast cancer and controls had no history of or current breast cancer. A single board-certified breast radiologist with 12 years experience, blinded to case-control status and clinical information, assessed the unaffected breast for BPE without view of the affected breast of cases (or the corresponding breast laterality of controls). The association between BPE and breast cancer was estimated by multivariable logistic regression separately for premenopausal and postmenopausal women. RESULTS: The analytic dataset included 835 cases and 963 controls. Adjusting for fibroglandular tissue (breast density), age, race/ethnicity, BMI, parity, family history of breast cancer, BRCA1/BRCA2 mutations, and other confounders, moderate/marked BPE (vs minimal/mild BPE) was associated with breast cancer among premenopausal women [odds ratio (OR) 1.49, 95% CI 1.05-2.11; p = 0.02]. Among postmenopausal women, mild/moderate/marked vs minimal BPE had a similar, but statistically non-significant, association with breast cancer (OR 1.45, 95% CI 0.92-2.27; p = 0.1). CONCLUSIONS: BPE is associated with breast cancer in premenopausal women, and possibly postmenopausal women, after adjustment for breast density and confounders. Our results suggest that BPE should be evaluated alongside breast density for inclusion in models predicting breast cancer risk.

Glioma incidence is highest in non-Hispanic Whites, and to date, glioma genome-wide association studies (GWAS) to date have only included European ancestry (EA) populations. African Americans and Hispanics in the US have varying proportions of EA, African (AA) and Native American ancestries (NAA). It is unknown if identified GWAS loci or increased EA is associated with increased glioma risk. We assessed whether EA was associated with glioma in African Americans and Hispanics. Data were obtained for 832 cases and 675 controls from the Glioma International Case-Control Study and GliomaSE Case-Control Study previously estimated to have

Glioblastoma (GBM) is the most common malignant brain tumor in the United States. Incidence of GBM increases with age, and younger age-at-diagnosis is significantly associated with improved prognosis. While the relationship between candidate GBM risk SNPs and age-at-diagnosis has been explored, genome-wide association studies (GWAS) have not previously been stratified by age. Potential age-specific genetic effects were assessed in autosomal SNPs for GBM patients using data from four previous GWAS. Using age distribution tertiles (18-53, 54-64, 65+) datasets were analyzed using age-stratified logistic regression to generate p values, odds ratios (OR), and 95% confidence intervals (95%CI), and then combined using meta-analysis. There were 4,512 total GBM cases, and 10,582 controls used for analysis. Significant associations were detected at two previously identified SNPs in 7p11.2 (rs723527 [p54-63 = 1.50x10-9 , OR54-63 = 1.28, 95%CI54-63 = 1.18-1.39; p64+ = 2.14x10-11 , OR64+ = 1.32, 95%CI64+ = 1.21-1.43] and rs11979158 [p54-63 = 6.13x10-8 , OR54-63 = 1.35, 95%CI54-63 = 1.21-1.50; p64+ = 2.18x10-10 , OR64+ = 1.42, 95%CI64+ = 1.27-1.58]) but only in persons >54. There was also a significant association at the previously identified lower grade glioma (LGG) risk locus at 8q24.21 (rs55705857) in persons ages 18-53 (p18-53 = 9.30 × 10-11 , OR18-53 = 1.76, 95%CI18-53 = 1.49-2.10). Within The Cancer Genome Atlas (TCGA) there was higher prevalence of 'LGG'-like tumor characteristics in GBM samples in those 18-53, with IDH1/2 mutation frequency of 15%, as compared to 2.1% [54-63] and 0.8% [64+] (p = 0.0005). Age-specific differences in cancer susceptibility can provide important clues to etiology. The association of a SNP known to confer risk for IDH1/2 mutant glioma and higher prevalence of IDH1/2 mutation within younger individuals 18-53 suggests that more younger individuals may present initially with 'secondary glioblastoma.'

Background parenchymal enhancement (BPE) is the degree to which normal breast tissue enhances on contrast-enhanced magnetic resonance imaging (MRI). MRI-density is a volumetric measure of breast density that is highly correlated with mammographic density, an established breast cancer risk factor. Endogenous estrogen concentrations are positively associated with postmenopausal breast cancer risk and BPE has been shown to be sensitive to hormonal exposures. The objective of our study was to examine the relationship between BPE and MRI-density and serum hormone concentrations in postmenopausal women. This was a study of cancer-free postmenopausal women undergoing contrast-enhanced breast MRI (N = 118). At the time of MRI all women completed a self-administered questionnaire and blood samples were collected for hormone analyses. Serum concentrations of estrone (E1), estradiol (E2) and bioavailable E2 were examined by category of BPE and MRI-density. Compared to women with minimal BPE, those who had marked BPE had significantly higher serum concentrations of E1, E2 and bioavailable E2 (90% increase, ptrend across all categories = 0.001; 150% increase, ptrend  = 0.001; and 158% increase, ptrend  = 0.001, respectively). These associations were only affected to a minor extent by adjustment for BMI and other variables. After adjustment for BMI, no significant associations between MRI-density and serum E1, E2 and bioavailable E2 were observed. Serum estrogen concentrations were significantly positively associated with BPE. Our study provides further evidence of the hormone-sensitive nature of BPE, indicating a potential role for BPE as an imaging marker of endogenous and exogenous hormonal exposures in the breast.

Incidence of glioma is approximately 50% higher in males. Previous analyses have examined exposures related to sex hormones in women as potential protective factors for these tumors, with inconsistent results. Previous glioma genome-wide association studies (GWAS) have not stratified by sex. Potential sex-specific genetic effects were assessed in autosomal SNPs and sex chromosome variants for all glioma, GBM and non-GBM patients using data from four previous glioma GWAS. Datasets were analyzed using sex-stratified logistic regression models and combined using meta-analysis. There were 4,831 male cases, 5,216 male controls, 3,206 female cases and 5,470 female controls. A significant association was detected at rs11979158 (7p11.2) in males only. Association at rs55705857 (8q24.21) was stronger in females than in males. A large region on 3p21.31 was identified with significant association in females only. The identified differences in effect of risk variants do not fully explain the observed incidence difference in glioma by sex.

To examine for a causal relationship between vitamin D and glioma risk we performed an analysis of genetic variants associated with serum 25-hydroxyvitamin D (25(OH)D) levels using Mendelian randomisation (MR), an approach unaffected by biases from confounding. Two-sample MR was undertaken using genome-wide association study data. Single nucleotide polymorphisms (SNPs) associated with 25(OH)D levels were used as instrumental variables (IVs). We calculated MR estimates for the odds ratio (OR) for 25(OH)D levels with glioma using SNP-glioma estimates from 12,488 cases and 18,169 controls, using inverse-variance weighted (IVW) and maximum likelihood estimation (MLE) methods. A non-significant association between 25(OH)D levels and glioma risk was shown using both the IVW (OR = 1.21, 95% confidence interval [CI] = 0.90-1.62, P = 0.201) and MLE (OR = 1.20, 95% CI = 0.98-1.48, P = 0.083) methods. In an exploratory analysis of tumour subtype, an inverse relationship between 25(OH)D levels and glioblastoma (GBM) risk was identified using the MLE method (OR = 0.62, 95% CI = 0.43-0.89, P = 0.010), but not the IVW method (OR = 0.62, 95% CI = 0.37-1.04, P = 0.070). No statistically significant association was shown between 25(OH)D levels and non-GBM glioma. Our results do not provide evidence for a causal relationship between 25(OH)D levels and all forms of glioma risk. More evidence is required to explore the relationship between 25(OH)D levels and risk of GBM.

Genome-wide association studies (GWAS) have transformed our understanding of glioma susceptibility, but individual studies have had limited power to identify risk loci. We performed a meta-analysis of existing GWAS and two new GWAS, which totaled 12,496 cases and 18,190 controls. We identified five new loci for glioblastoma (GBM) at 1p31.3 (rs12752552; P = 2.04 × 10-9, odds ratio (OR) = 1.22), 11q14.1 (rs11233250; P = 9.95 × 10-10, OR = 1.24), 16p13.3 (rs2562152; P = 1.93 × 10-8, OR = 1.21), 16q12.1 (rs10852606; P = 1.29 × 10-11, OR = 1.18) and 22q13.1 (rs2235573; P = 1.76 × 10-10, OR = 1.15), as well as eight loci for non-GBM tumors at 1q32.1 (rs4252707; P = 3.34 × 10-9, OR = 1.19), 1q44 (rs12076373; P = 2.63 × 10-10, OR = 1.23), 2q33.3 (rs7572263; P = 2.18 × 10-10, OR = 1.20), 3p14.1 (rs11706832; P = 7.66 × 10-9, OR = 1.15), 10q24.33 (rs11598018; P = 3.39 × 10-8, OR = 1.14), 11q21 (rs7107785; P = 3.87 × 10-10, OR = 1.16), 14q12 (rs10131032; P = 5.07 × 10-11, OR = 1.33) and 16p13.3 (rs3751667; P = 2.61 × 10-9, OR = 1.18). These data substantiate that genetic susceptibility to GBM and non-GBM tumors are highly distinct, which likely reflects different etiology.

Decades of research have established only a few etiological factors for glioma, which is a rare and highly fatal brain cancer. Common methodological challenges among glioma studies include small sample sizes, heterogeneity of tumor subtypes, and retrospective exposure assessment. Here, we briefly describe the Glioma International Case-Control (GICC) Study (recruitment, 2010-2013), a study being conducted by the Genetic Epidemiology of Glioma International Consortium that integrates data from multiple data collection sites, uses a common protocol and questionnaire, and includes biospecimen collection. To our knowledge, the GICC Study is the largest glioma study to date that includes collection of blood samples, which will allow for genetic analysis and interrogation of gene-environment interactions.

BackgroundWhile certain inherited syndromes (e.g. Neurofibromatosis or Li-Fraumeni) are associated with an increased risk of glioma, most familial gliomas are non-syndromic. This study describes the demographic and clinical characteristics of the largest series of non-syndromic glioma families ascertained from 14 centres in the United States (US), Europe and Israel as part of the Gliogene Consortium.MethodsFamilies with 2 or more verified gliomas were recruited between January 2007 and February 2011. Distributions of demographic characteristics and clinical variables of gliomas in the families were described based on information derived from personal questionnaires.FindingsThe study population comprised 841 glioma patients identified in 376 families (9797 individuals). There were more cases of glioma among males, with a male to female ratio of 1.25. In most families (83%), 2 gliomas were reported, with 3 and 4 gliomas in 13% and 3% of the families, respectively. For families with 2 gliomas, 57% were among 1st-degree relatives, and 31.5% among 2nd-degree relatives. Overall, the mean (±standard deviation [SD]) diagnosis age was 49.4 (±18.7) years. In 48% of families with 2 gliomas, at least one was diagnosed at

BackgroundWe propose a 2-step model-based approach, with correction for ascertainment, to linkage analysis of a binary trait with variable age of onset and apply it to a set of multiplex pedigrees segregating for adult glioma.MethodsFirst, we fit segregation models by formulating the likelihood for a person to have a bivariate phenotype, affection status and age of onset, along with other covariates, and from these we estimate population trait allele frequencies and penetrance parameters as a function of age (N = 281 multiplex glioma pedigrees). Second, the best fitting models are used as trait models in multipoint linkage analysis (N = 74 informative multiplex glioma pedigrees). To correct for ascertainment, a prevalence constraint is used in the likelihood of the segregation models for all 281 pedigrees. Then the trait allele frequencies are reestimated for the pedigree founders of the subset of 74 pedigrees chosen for linkage analysis.ResultsUsing the best-fitting segregation models in model-based multipoint linkage analysis, we identified 2 separate peaks on chromosome 17; the first agreed with a region identified by Shete and colleagues who used model-free affected-only linkage analysis, but with a narrowed peak: and the second agreed with a second region they found but had a larger maximum log of the odds (LOD).ConclusionsOur approach was able to narrow the linkage peak previously published for glioma.ImpactWe provide a practical solution to model-based linkage analysis for disease affection status with variable age of onset for the kinds of pedigree data often collected for linkage analysis.

The risk of glioma has consistently been shown to be increased twofold in relatives of patients with primary brain tumors (PBT). A recent genome-wide linkage study of glioma families provided evidence for a disease locus on 17q12-21.32, with the possibility of four additional risk loci at 6p22.3, 12p13.33-12.1, 17q22-23.2, and 18q23. To identify the underlying genetic variants responsible for the linkage signals, we compared the genotype frequencies of 5,122 SNPs mapping to these five regions in 88 glioma cases with and 1,100 cases without a family history of PBT (discovery study). An additional series of 84 familial and 903 non-familial cases were used to replicate associations. In the discovery study, 12 SNPs showed significant associations with family history of PBT (P < 0.001). In the replication study, two of the 12 SNPs were confirmed: 12p13.33-12.1 PRMT8 rs17780102 (P = 0.031) and 17q12-21.32 SPOP rs650461 (P = 0.025). In the combined analysis of discovery and replication studies, the strongest associations were attained at four SNPs: 12p13.33-12.1 PRMT8 rs17780102 (P = 0.0001), SOX5 rs7305773 (P = 0.0001) and STKY1 rs2418087 (P = 0.0003), and 17q12-21.32 SPOP rs6504618 (P = 0.0006). Further, a significant gene-dosage effect was found for increased risk of family history of PBT with these four SNPs in the combined data set (P(trend)

Given the greatly elevated risks of contralateral breast cancer (CBC) observed in breast cancer patients who carry mutations in BRCA1 and BRCA2, it is critical to determine the effectiveness of standard adjuvant therapies in preventing CBC in mutation carriers. The WECARE study is a matched, case-control study of 708 women with CBC as cases and 1,399 women with unilateral breast cancer (UBC) as controls, including 181 BRCA1/BRCA2 mutation carriers. Interviews and medical record reviews provided detailed information on risk factors and breast cancer therapy. All study participants were screened for BRCA1 and BRCA2 mutations using denaturing high-performance liquid chromatography (DHPLC) to detect genetic variants in the coding and flanking regions of the genes. Conditional logistic regression was used to compare the risk of CBC associated with chemotherapy and tamoxifen in BRCA1/BRCA2 mutation carriers and non-carriers. Chemotherapy was associated with lower CBC risk both in non-carriers (RR = 0.6 [95% CI: 0.5-0.7]) and carriers (RR = 0.5 [95% CI: 0.2-1.0]; P value = 0.04). Tamoxifen was associated with a reduced CBC risk in non-carriers (RR = 0.7 [95% CI: 0.6-1.0]; P value = 0.03). We observed a similar but non-significant reduction associated with tamoxifen in mutation carriers (RR = 0.7 [95% CI: 0.3-1.8]). The tests of heterogeneity comparing carriers to non-carriers did not provide evidence for a difference in the associations with chemotherapy (P value = 0.51) nor with tamoxifen (P value = 0.15). Overall, we did not observe a difference in the relative risk reduction associated with adjuvant treatment between BRCA1/BRCA2 mutation carriers and non-carriers. However, given the higher absolute CBC risk in mutation carriers, the potentially greater impact of adjuvant therapy in reducing CBC risk among mutation carriers should be considered when developing treatment plans for these patients.

ObjectiveReproductive factors, such as early age at menarche, late age at menopause, and nulliparity are known risk factors for breast cancer. Previously, we reported these factors to be associated with risk of developing contralateral breast cancer (CBC). In this study, we evaluated the association between these factors and CBC risk among BRCA1 and BRCA2 (BRCA1/2) mutation carriers and non-carriers.MethodsThe WECARE Study is a population-based multi-center case-control study of 705 women with CBC (cases) and 1,397 women with unilateral breast cancer (controls). All participants were screened for BRCA1/2 mutations and 181 carriers were identified. Conditional logistic regression models were used to evaluate associations between reproductive factors and CBC for mutation carriers and non-carriers.ResultsNone of the associations between reproductive factors and CBC risk differed between mutation carriers and non-carriers. The increase in risk with younger age at menarche and decrease in risk in women with more than two full-term pregnancies seen in non-carriers were not significantly different in carriers (adjusted RRs = 1.31, 95% CI 0.65-2.65 and 0.53, 95% CI 0.19-1.51, respectively). No significant associations between the other reproductive factors and CBC risk were observed in mutation carriers or non-carriers.ConclusionFor two reproductive factors previously shown to be associated with CBC risk, we observed similar associations for BRCA1/2 carriers. This suggests that reproductive variables that affect CBC risk may have similar effects in mutation carriers and non-carriers.

BackgroundIonizing radiation is a known mutagen and an established breast carcinogen. The ATM gene is a key regulator of cellular responses to the DNA damage induced by ionizing radiation. We investigated whether genetic variants in ATM play a clinically significant role in radiation-induced contralateral breast cancer in women.MethodsThe Women's Environmental, Cancer, and Radiation Epidemiology Study is an international population-based case-control study nested within a cohort of 52,536 survivors of unilateral breast cancer diagnosed between 1985 and 2000. The 708 case subjects were women with contralateral breast cancer, and the 1397 control subjects were women with unilateral breast cancer matched to the case subjects on age, follow-up time, registry reporting region, and race and/or ethnicity. All women were interviewed and underwent full mutation screening of the entire ATM gene. Complete medical treatment history information was collected, and for all women who received radiotherapy, the radiation dose to the contralateral breast was reconstructed using radiotherapy records and radiation measurements. Rate ratios (RRs) and corresponding 95% confidence intervals (CIs) were estimated by using multivariable conditional logistic regression. All P values are two-sided.ResultsAmong women who carried a rare ATM missense variant (ie, one carried by or =1.0 Gy: RR = 3.3, 95% CI = 1.4 to 8.0) or compared with unexposed women who carried the same predicted deleterious missense variant (0.01-0.99 Gy: RR = 5.3, 95% CI = 1.6 to 17.3; > or =1.0 Gy: RR = 5.8, 95% CI = 1.8 to 19.0; P(trend) = .044).ConclusionsWomen who carry rare deleterious ATM missense variants and who are treated with radiation may have an elevated risk of developing contralateral breast cancer. However, the rarity of these deleterious missense variants in human populations implies that ATM mutations could account for only a small portion of second primary breast cancers.

PurposeTo quantify the risk of second primary breast cancer in the contralateral breast (CB) after radiotherapy (RT) for first breast cancer.Methods and materialsThe study population included participants in the Women's Environmental, Cancer, and Radiation Epidemiology study: 708 cases (women with asynchronous bilateral breast cancer) and 1399 controls (women with unilateral breast cancer) counter-matched on radiation treatment. Participants were 1.0 Gy of absorbed dose to the specific quadrant of the CB had a 2.5-fold greater risk for CB cancer than unexposed women (RR = 2.5, 95% CI 1.4-4.5). No excess risk was observed in women >40 years of age. Women 5 years had a RR of 3.0 (95% CI 1.1-8.1), and the dose response was significant (excess RR per Gy of 1.0, 95% CI 0.1-3.0).ConclusionsWomen 1.0 Gy to the CB had an elevated, long-term risk of developing a second primary CB cancer. The risk is inversely related to age at exposure and is dose dependent.

BackgroundResults from randomized trials indicate that treatment with tamoxifen or chemotherapy for primary breast cancer reduces the risk for contralateral breast cancer. However, less is known about how long the risk is reduced and the impact of factors such as age and menopausal status.MethodsThe study included 634 women with contralateral breast cancer (case patients) and 1158 women with unilateral breast cancer (control subjects) from the Women's Environment, Cancer and Radiation Epidemiology Study. The women were younger than age 55 when they were first diagnosed with breast cancer during 1985-1999. Rate ratios (RRs) and 95% confidence intervals (CIs) for contralateral breast cancer after treatment with chemotherapy or tamoxifen were assessed by multivariable adjusted conditional logistic regression analyses.ResultsChemotherapy was associated with a lower risk for contralateral breast cancer (RR = 0.57, 95% CI = 0.42 to 0.75) than no chemotherapy. A statistically significant association between chemotherapy and reduced risk for contralateral breast cancer persisted up to 10 years after the first breast cancer diagnosis and was stronger among women who became postmenopausal within 1 year of the first breast cancer diagnosis (RR = 0.28, 95% CI = 0.11 to 0.76). Tamoxifen use was also associated with reduced risk for contralateral breast cancer (RR = 0.66, 95% CI = 0.50 to 0.88) compared with no use, and the association was statistically significant for 5 years after the first diagnosis.ConclusionThe associations between chemotherapy and tamoxifen treatment and reduced risk for contralateral breast cancer appear to continue for 10 and 5 years, respectively, after the initial breast cancer is diagnosed. Ovarian suppression may have a role in the association between chemotherapy and reduced risk for contralateral breast cancer.

IntroductionDeficiencies in cellular responses to DNA damage can predispose to cancer. Ionizing radiation can cause cluster damage and double-strand breaks (DSBs) that pose problems for cellular repair processes. Three genes (ATM, BRCA1, and BRCA2) encode products that are essential for the normal cellular response to DSBs, but predispose to breast cancer when mutated.DesignTo examine the joint roles of radiation exposure and genetic susceptibility in the etiology of breast cancer, we designed a case-control study nested within five population-based cancer registries. We hypothesized that a woman carrying a mutant allele in one of these genes is more susceptible to radiation-induced breast cancer than is a non-carrier. In our study, 700 women with asynchronous bilateral breast cancer were individually matched to 1400 controls with unilateral breast cancer on date and age at diagnosis of the first breast cancer, race, and registry region, and counter-matched on radiation therapy. Each triplet comprised two women who received radiation therapy and one woman who did not. Radiation absorbed dose to the contralateral breast after initial treatment was estimated with a comprehensive dose reconstruction approach that included experimental measurements in anthropomorphic and water phantoms applying patient treatment parameters. Blood samples were collected from all participants for genetic analyses.ConclusionsOur study design improves the potential for detecting gene-environment interactions for diseases when both gene mutations and the environmental exposures of interest are rare in the general population. This is particularly applicable to the study of bilateral breast cancer because both radiation dose and genetic susceptibility have important etiologic roles, possibly by interactive mechanisms. By using counter-matching, we optimized the informativeness of the collected dosimetry data by increasing the variability of radiation dose within the case-control sets and enhanced our ability to detect radiation-genotype interactions.