Breast cancer risk is influenced by rare coding variants in susceptibility genes such as BRCA1 and many common, mainly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. We report results from a genome-wide association study (GWAS) of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry1. We identified 65 new loci associated with overall breast cancer at p<5x10-8. The majority of credible risk SNPs in the new loci fall in distal regulatory elements, and by integrating in-silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all SNPs in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the utility of genetic risk scores for individualized screening and prevention.

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57–1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628–0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.

Most common breast cancer susceptibility variants have been identified through genome-wide association studies (GWAS) of predominantly estrogen receptor (ER)-positive disease1. We conducted a GWAS using 21,468 ER-negative cases and 100,594 controls combined with 18,908 BRCA1 mutation carriers (9,414 with breast cancer), all of European origin. We identified independent associations at P < 5 × 10−8 with ten variants at nine new loci. At P < 0.05, we replicated associations with 10 of 11 variants previously reported in ER-negative disease or BRCA1 mutation carrier GWAS and observed consistent associations with ER-negative disease for 105 susceptibility variants identified by other studies. These 125 variants explain approximately 14% of the familial risk of this breast cancer subtype. There was high genetic correlation (0.72) between risk of ER-negative breast cancer and breast cancer risk for BRCA1 mutation carriers. These findings may lead to improved risk prediction and inform further fine-mapping and functional work to better understand the biological basis of ER-negative breast cancer.

The prevalence and spectrum of germline mutations in BRCA1 and BRCA2 have been reported in single populations, with the majority of reports focused on White in Europe and North America. The Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) has assembled data on 18,435 families with BRCA1 mutations and 11,351 families with BRCA2 mutations ascertained from 69 centers in 49 countries on six continents. This study comprehensively describes the characteristics of the 1,650 unique BRCA1 and 1,731 unique BRCA2 deleterious (disease‐associated) mutations identified in the CIMBA database. We observed substantial variation in mutation type and frequency by geographical region and race/ethnicity. In addition to known founder mutations, mutations of relatively high frequency were identified in specific racial/ethnic or geographic groups that may reflect founder mutations and which could be used in targeted (panel) first pass genotyping for specific populations. Knowledge of the population‐specific mutational spectrum in BRCA1 and BRCA2 could inform efficient strategies for genetic testing and may justify a more broad‐based oncogenetic testing in some populations.

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

PurposeUnderstanding of the etiology and pathogenesis of pancreatic cancer (PaCa) is still insufficient. This study evaluated the associations between concentrations of selenium (Se) and copper (Cu) in the serum of PaCa patients.Materials and MethodsThe study included 100 PaCa patients and 100 control subjects from the same geographical region in Poland. To determine the average concentration of Se, Cu, and ratio Cu:Se in the Polish population, assay for Se and Cu was performed in 480 healthy individuals. Serum levels of Se and Cu were measured using inductively coupled plasma mass spectrometry.ResultsIn the control group, the average Se level was 76 µg/L and Cu 1,098 µg/L. The average Se level among PaCa patients was 60 µg/L and the mean Cu level was 1,432 µg/L. The threshold point at which any decrease in Se concentration was associated with PaCa was 67.45 µg/L. The threshold point of Cu level above which there was an increase in the prevalence of PaCa was 1,214.58 µg/L. In addition, a positive relationship was observed between increasing survival time and Se plasma level.ConclusionThis retrospective study suggests that low levels of Se and high levels of Cu might influence development of PaCa and that higher levels of Se are associated with longer survival in patients with PaCa. The results suggest that determining the level of Se and Cu could be incorporated into a risk stratification scheme for the selection and surveillance control examination to complement existing screening and diagnostic procedures.

Background: BRCA1/2 mutations confer high lifetime risk of breast cancer, although other factors may modify this risk. Whether height or body mass index (BMI) modifies breast cancer risk in BRCA1/2 mutation carriers remains unclear. Methods: We used Mendelian randomization approaches to evaluate the association of height and BMI on breast cancer risk, using data from the Consortium of Investigators of Modifiers of BRCA1/2 with 14 676 BRCA1 and 7912 BRCA2 mutation carriers, including 11 451 cases of breast cancer. We created a height genetic score using 586 height-associated variants and a BMI genetic score using 93 BMI-associated variants. We examined both observed and genetically determined height and BMI with breast cancer risk using weighted Cox models. All statistical tests were two-sided. Results: Observed height was positively associated with breast cancer risk (HR ¼ 1.09 per 10 cm increase, 95% confidence interval [CI] ¼ 1.0 to 1.17; P ¼ 1.17). Height genetic score was positively associated with breast cancer, although this was not statistically significant (per 10 cm increase in genetically predicted height, HR ¼ 1.04, 95% CI ¼ 0.93 to 1.17; P ¼ .47). Observed BMI was inversely associated with breast cancer risk (per 5 kg/m 2 increase, HR ¼ 0.94, 95% CI ¼ 0.90 to 0.98; P ¼ .007). BMI genetic score was also inversely associated with breast cancer risk (per 5 kg/m 2 increase in genetically predicted BMI, HR ¼ 0.87, 95% CI ¼ 0.76 to 0.98; P ¼ .02). BMI was primarily associated with premenopausal breast cancer. Conclusion: Height is associated with overall breast cancer and BMI is associated with premenopausal breast cancer in BRCA1/2 mutation carriers. Incorporating height and BMI, particularly genetic score, into risk assessment may improve cancer management.

BackgroundLung cancer is a leading cause of cancer-related mortality globally. Folate helps to maintain DNA integrity and to regulate gene expression. Serum folate levels may affect the risk of several cancers, including lung cancer. In this study we evaluated the association between serum folate concentration and variations in genes involved in folate metabolism with lung cancer incidence in Poland.MethodsThe study included 366 lung cancer patients and 366 control subjects. We measured serum folate concentration and genotyped six variants in MTHFR, MTR and MTRR genes. The odds ratios of being diagnosed with lung cancer were calculated using conditional univariable and multivariable logistic regression with respect to folate level and genotypes.ResultsThe mean serum folate level was lower in lung cancer cases than in control group (20.07 nmol/l vs. 22.52 nmol/l, p = 0.002). The odds ratio for lung cancer declined with increasing serum content of the folate. The folate concentration of >25.71 nmol/l (IVth quartile) in comparison to <15.92 nmol/l (Ist quartile) was associated with an odds ratio of 0.61 (95%CI 0.40–0.95, p = 0.03). The analysis of variations in MTHFR, MTR and MTRR genes did not reveal any significant difference between lung cancer cases and controls in univariable and multivariable analyses.ConclusionIn this case-control study, lower serum folate concentrations were associated with a higher risk of lung cancer diagnosis. Although previous findings have been somewhat mixed, our results add to the evidence that circulating folate levels may be an indicator of lung cancer risk.