Association analysis identifies 65 new breast cancer risk loci, predicts target genes for known risk loci and demonstrates a strong overlap with somatic driver genes in breast tumours. Genome-wide association studies for breast cancer have identified common genetic variation that influences susceptibility to this disease, but much of the genetic risk remains unexplained. Doug Easton and colleagues report a genome-wide association study for breast cancer in more than 122,000 cases and 105,000 controls. The authors genotyped a subset of these cases using OncoArray, a new, custom genome-wide single-nucleotide polymorphism (SNP) array for cancer genomics. Overall, they identify 65 loci newly associated with breast cancer susceptibility, and estimate that, together with 107 previously identified breast cancer susceptibility loci, these explain about 18 per cent of the familial relative risk of breast cancer. Polygenic risk scores may be used in risk prediction models and may improve early detection and targeted prevention of the disease. Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study 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 that are associated with overall breast cancer risk at P < 5 × 10−8. The majority of credible risk single-nucleotide polymorphisms in these 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 single-nucleotide polymorphisms 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 use 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.

Doug Easton and colleagues report the results of a large-scale genome-wide association study of breast cancer. They discover 15 new susceptibility loci and highlight likely target genes in several of the newly associated regions. Genome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ∼14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising 15,748 breast cancer cases and 18,084 controls together with 46,785 cases and 42,892 controls from 41 studies genotyped on a 211,155-marker custom array (iCOGS). Analyses were restricted to women of European ancestry. We generated genotypes for more than 11 million SNPs by imputation using the 1000 Genomes Project reference panel, and we identified 15 new loci associated with breast cancer at P < 5 × 10−8. Combining association analysis with ChIP-seq chromatin binding data in mammary cell lines and ChIA-PET chromatin interaction data from ENCODE, we identified likely target genes in two regions: SETBP1 at 18q12.3 and RNF115 and PDZK1 at 1q21.1. One association appears to be driven by an amino acid substitution encoded in EXO1.

Local cancer relapse risk after breast conservation surgery followed by radiotherapy has fallen sharply in many countries, and is influenced by patient age and clinicopathological factors. We hypothesise that partial-breast radiotherapy restricted to the vicinity of the original tumour in women at lower than average risk of local relapse will improve the balance of beneficial versus adverse effects compared with whole-breast radiotherapy. IMPORT LOW is a multicentre, randomised, controlled, phase 3, non-inferiority trial done in 30 radiotherapy centres in the UK. Women aged 50 years or older who had undergone breast-conserving surgery for unifocal invasive ductal adenocarcinoma of grade 1-3, with a tumour size of 3 cm or less (pT1-2), none to three positive axillary nodes (pN0-1), and minimum microscopic margins of non-cancerous tissue of 2 mm or more, were recruited. Patients were randomly assigned (1:1:1) to receive 40 Gy whole-breast radiotherapy (control), 36 Gy whole-breast radiotherapy and 40 Gy to the partial breast (reduced-dose group), or 40 Gy to the partial breast only (partial-breast group) in 15 daily treatment fractions. Computer-generated random permuted blocks (mixed sizes of six and nine) were used to assign patients to groups, stratifying patients by radiotherapy treatment centre. Patients and clinicians were not masked to treatment allocation. Field-in-field intensity-modulated radiotherapy was delivered using standard tangential beams that were simply reduced in length for the partial-breast group. The primary endpoint was ipsilateral local relapse (80% power to exclude a 2·5% increase [non-inferiority margin] at 5 years for each experimental group; non-inferiority was shown if the upper limit of the two-sided 95% CI for the local relapse hazard ratio [HR] was less than 2·03), analysed by intention to treat. Safety analyses were done in all patients for whom data was available (ie, a modified intention-to-treat population). This study is registered in the ISRCTN registry, number ISRCTN12852634. Between May 3, 2007, and Oct 5, 2010, 2018 women were recruited. Two women withdrew consent for use of their data in the analysis. 674 patients were analysed in the whole-breast radiotherapy (control) group, 673 in the reduced-dose group, and 669 in the partial-breast group. Median follow-up was 72·2 months (IQR 61·7-83·2), and 5-year estimates of local relapse cumulative incidence were 1·1% (95% CI 0·5-2·3) of patients in the control group, 0·2% (0·02-1·2) in the reduced-dose group, and 0·5% (0·2-1·4) in the partial-breast group. Estimated 5-year absolute differences in local relapse compared with the control group were -0·73% (-0·99 to 0·22) for the reduced-dose and -0·38% (-0·84 to 0·90) for the partial-breast groups. Non-inferiority can be claimed for both reduced-dose and partial-breast radiotherapy, and was confirmed by the test against the critical HR being more than 2·03 (p=0·003 for the reduced-dose group and p=0·016 for the partial-breast group, compared with the whole-breast radiotherapy group). Photographic, patient, and clinical assessments recorded similar adverse effects after reduced-dose or partial-breast radiotherapy, including two patient domains achieving statistically significantly lower adverse effects (change in breast appearance [p=0·007 for partial-breast] and breast harder or firmer [p=0·002 for reduced-dose and p<0·0001 for partial-breast]) compared with whole-breast radiotherapy. We showed non-inferiority of partial-breast and reduced-dose radiotherapy compared with the standard whole-breast radiotherapy in terms of local relapse in a cohort of patients with early breast cancer, and equivalent or fewer late normal-tissue adverse effects were seen. This simple radiotherapy technique is implementable in radiotherapy centres worldwide. Cancer Research UK.

Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking. We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates. There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer. The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report.

Roger Milne and colleagues conduct a genome-wide association study for estrogen receptor (ER)-negative breast cancer combined with BRCA1 mutation carriers in a large cohort. They identify ten new risk variants and find high genetic correlation between breast cancer risk for BRCA1 mutation carriers and risk of ER-negative breast cancer in the general population. 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 16% 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.