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.

Breast cancer is the most common cancer in women, with at least 1.7 million cases diagnosed and 0.5 million deaths per annum worldwide.¹ Early diagnosis from mammography screening reduces breast cancer mortality by 20% to 40% in the general population.^2,3 In women at an elevated risk of breast cancer, selective estrogen receptor modulator therapy for 5 years reduces the risk of breast cancer by about 40%, and the effect persists for at least 20 years.⁴ Risk-based breast cancer screening is not commonly adopted in the United States or elsewhere, but it has the potential to increase the benefits and decrease the harms of screening and increase the number of women eligible for preventive therapy. A prerequisite for the implementation of risk-adapted screening intervals and use of preventive therapies in precision medicine is accurate risk assessment.

Integrin αvβ6 promotes migration, invasion, and survival of cancer cells; however, the relevance and role of αvβ6 has yet to be elucidated in breast cancer. Protein expression of integrin subunit beta6 (β6) was measured in breast cancers by immunohistochemistry (n > 2000) and ITGB6 mRNA expression measured in the Molecular Taxonomy of Breast Cancer International Consortium dataset. Overall survival was assessed using Kaplan Meier curves, and bioinformatics statistical analyses were performed (Cox proportional hazards model, Wald test, and Chi-square test of association). Using antibody (264RAD) blockade and siRNA knockdown of β6 in breast cell lines, the role of αvβ6 in Human Epidermal Growth Factor Receptor 2 (HER2) biology (expression, proliferation, invasion, growth in vivo) was assessed by flow cytometry, MTT, Transwell invasion, proximity ligation assay, and xenografts (n ≥ 3), respectively. A student’s t-test was used for two variables; three-plus variables used one-way analysis of variance with Bonferroni’s Multiple Comparison Test. Xenograft growth was analyzed using linear mixed model analysis, followed by Wald testing and survival, analyzed using the Log-Rank test. All statistical tests were two sided. High expression of either the mRNA or protein for the integrin subunit β6 was associated with very poor survival (HR = 1.60, 95% CI = 1.19 to 2.15, P = .002) and increased metastases to distant sites. Co-expression of β6 and HER2 was associated with worse prognosis (HR = 1.97, 95% CI = 1.16 to 3.35, P = .01). Monotherapy with 264RAD or trastuzumab slowed growth of MCF-7/HER2-18 and BT-474 xenografts similarly (P < .001), but combining 264RAD with trastuzumab effectively stopped tumor growth, even in trastuzumab-resistant MCF-7/HER2-18 xenografts. Targeting αvβ6 with 264RAD alone or in combination with trastuzumab may provide a novel therapy for treating high-risk and trastuzumab-resistant breast cancer patients.

The concordance index is often used to measure how well a biomarker predicts the time to an event. Estimators of the concordance index for predictors of right-censored data are reviewed, including those based on censored pairs, inverse probability weighting and a proportional-hazards model. Predictive and prognostic biomarkers often lose strength with time, and in this case the aforementioned statistics depend on the length of follow up. A semi-parametric estimator of the concordance index is developed that accommodates converging hazards through a single parameter in a Pareto model. Concordance index estimators are assessed through simulations, which demonstrate substantial bias of classical censored-pairs and proportional-hazards model estimators. Prognostic biomarkers in a cohort of women diagnosed with breast cancer are evaluated using new and classical estimators of the concordance index.

Breast cancer is the most commonly diagnosed cancer among women worldwide. Approximately half of all breast cancers in women with a family history of the disease are explained by a known genetic component.^1,2 Pathogenic variants in BRCA1/BRCA2 and single-nucleotide polymorphisms (SNPs) explain a large proportion of the risk in women with a strong family history. SNPs also contribute to the development of nonfamilial breast cancer in women, accounting for about 16% of genetic risk.² On a population basis, the polygenic risk conferred by these susceptibility SNPs is greater than the risk from single pathogenic variants in a single high- or moderate-risk gene,¹ especially for women without any family history of breast cancer.^3,4 Dependent on genotyping of susceptibility SNPs (ie, 0 risk alleles, 1 risk allele, or 2 risk alleles), a risk estimate can be derived, which may be used for risk prediction by combining the risk estimates for each SNP in a polygenic risk score.

Mammography is less effective in detecting cancer in dense than in fatty breasts. We undertook a systematic search in PubMed to identify studies on women with dense breasts who underwent screening with mammography supplemented with ultrasound. A meta-analysis was undertaken on the proportion of cancers detected only by ultrasound, out of all screen-detected cancers, and the proportion of women with negative mammography who were referred for assessment following ultrasound screening. Twenty-nine studies satisfied our inclusion criteria. The proportion of total cancers detected only by ultrasound was 0.29 (95% CI: 0.27-0.31), consistent with an approximately 40% increase in the detection of cancers compared to mammography. In the studied populations, this translated into an additional 3.8 (95% CI: 3.4-4.2) screen-detected cases per 1000 mammography-negative women. About 13% (32/248) of cancers were in situ from 17 studies with information on this subgroup. Ultrasound approximately doubled the referral for assessment in three studies with these data. Studies have consistently shown an increased detection of breast cancer by supplementary ultrasound screening. An inclusion of supplementary ultrasound into routine screening will need to consider the availability of ultrasound and diagnostic assessment capacities.