BACKGROUNDGenetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking. METHODSWe used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,461 controls. In separate analyses for protein-truncating variants and rare missense variants in these genes, we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluated missense-variant associations according to domain and classification of pathogenicity. RESULTSProtein-truncating variants in 5 genes (ATM, BRCA1, BRCA2, CHEK2, and PALB2) were associated with a risk of breast cancer overall with a P value of less than 0.0001. Protein-truncating variants in 4 other genes (BARD1, RAD51C, RAD51D, and TP53) were associated with a risk of breast cancer overall with a P value of less than 0.05 and a Bayesian false-discovery probability of less than 0.05. For protein-truncating variants in 19 of the remaining 25 genes, the upper limit of the 95% confidence interval of the odds ratio for breast cancer overall was less than 2.0. For protein-truncating variants in ATM and CHEK2, odds ratios were higher for estrogen receptor (ER)-positive disease than for ER-negative disease; for protein-truncating variants in BARD1, BRCA1, BRCA2, PALB2, RAD51C, and RAD51D, odds ratios were higher for ER-negative disease than for ER-positive disease. Rare missense variants (in aggregate) in ATM, CHEK2, and TP53 were associated with a risk of breast cancer overall with a P value of less than 0.001. For BRCA1, BRCA2, and TP53, missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a risk of breast cancer overall, with the risk being similar to that of protein-truncating variants. CONCLUSIONSThe results of this study define the genes that are most clinically useful for inclusion on panels for the prediction of breast cancer risk, as well as provide estimates of the risks associated with protein-truncating variants, to guide genetic counseling. (Funded by European Union Horizon 2020 programs and others.

BackgroundThe multifactorial Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) breast cancer risk prediction model has been recently extended to consider all established breast cancer risk factors. We assessed the clinical validity of the model in a large independent prospective cohort.MethodsWe validated BOADICEA (V.6) in the Swedish KARolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA) cohort including 66 415 women of European ancestry (median age 54 years, IQR 45–63; 816 incident breast cancers) without previous cancer diagnosis. We calculated 5-year risks on the basis of questionnaire-based risk factors, pedigree-structured first-degree family history, mammographic density (BI-RADS), a validated breast cancer polygenic risk score (PRS) based on 313-SNPs, and pathogenic variant status in 8 breast cancer susceptibility genes: BRCA1, BRCA2, PALB2, CHEK2, ATM, RAD51C, RAD51D and BARD1. Calibration was assessed by comparing observed and expected risks in deciles of predicted risk and the calibration slope. The discriminatory ability was assessed using the area under the curve (AUC).ResultsAmong the individual model components, the PRS contributed most to breast cancer risk stratification. BOADICEA was well calibrated in predicting the risks for low-risk and high-risk women when all, or subsets of risk factors are included in the risk prediction. Discrimination was maximised when all risk factors are considered (AUC=0.70, 95% CI: 0.66 to 0.73; expected-to-observed ratio=0.88, 95% CI: 0.75 to 1.04; calibration slope=0.97, 95% CI: 0.95 to 0.99). The full multifactorial model classified 3.6% women as high risk (5-year risk ≥3%) and 11.1% as very low risk (5-year risk <0.33%).ConclusionThe multifactorial BOADICEA model provides valid breast cancer risk predictions and a basis for personalised decision-making on disease prevention and screening.

Key Points Question What breast tumor characteristics are associated with rare pathogenic protein truncating or missense variants in breast cancer susceptibility genes? Findings In this case-control study involving 46 387 control participants and 42 680 women with a diagnosis of breast cancer, pathology features (eg, tumor subtype, morphology, size, TNM stage, and lymph node involvement) associated with rare germline (likely) pathogenic variants in 9 different breast cancer susceptibility genes were studied. Substantial differences in tumor subtype distribution by gene were found. Meaning The results of this study suggest that tumor subtypes differ by gene; these findings can potentially inform guidelines for gene panel testing, risk prediction in unaffected individuals, variant classification, and understanding of breast cancer etiology.

Hereditary breast and/or ovarian cancer is a highly heterogeneous disease with more than 10 known disease-associated genes. In the framework of the BRIDGES project (Breast Cancer Risk after Diagnostic Gene Sequencing), the RAD51C gene has been sequenced in 60,466 breast cancer patients and 53,461 controls. We aimed at functionally characterizing all the identified genetic variants that are predicted to disrupt the splicing process. Forty RAD51C variants of the intron-exon boundaries were bioinformatically analyzed, 20 of which were selected for splicing functional assays. To test them, a splicing reporter minigene with exons 2 to 8 was designed and constructed. This minigene generated a full-length transcript of the expected size (1062 nucleotides), sequence, and structure (Vector exon V1- RAD51C exons_2-8- Vector exon V2). The 20 candidate variants were genetically engineered into the wild type minigene and functionally assayed in MCF-7 cells. Nineteen variants (95%) impaired splicing, while 18 of them produced severe splicing anomalies. At least 35 transcripts were generated by the mutant minigenes: 16 protein-truncating, 6 in-frame, and 13 minor uncharacterized isoforms. According to ACMG/AMP-based standards, 15 variants could be classified as pathogenic or likely pathogenic variants: c.404G > A, c.405-6T > A, c.571 + 4A > G, c.571 + 5G > A, c.572-1G > T, c.705G > T, c.706-2A > C, c.706-2A > G, c.837 + 2T > C, c.905-3C > G, c.905-2A > C, c.905-2_905-1del, c.965 + 5G > A, c.1026 + 5_1026 + 7del, and c.1026 + 5G > T.

Ki-67 is a nuclear protein and a proliferation marker frequently used in establishing the prognosis for breast cancer patients. To investigate the prognostic value of the Ki-67 proliferation index in female cats with mammary carcinoma, a prospective study was conducted with 96 animals. The Ki-67 index of primary tumors (n ¼ 96) was initially determined, and whenever possible, the Ki-67 index of regional lymph node metastasis (n ¼ 38) and distant metastasis (n ¼ 16) was also estimated. The optimal cutoff value for the Ki-67 index was determined by univariate and multivariate analysis. Ki-67 indices 14% were detected in 72.9% (70 of 96) of the tumors. Tumors with a Ki-67 index 14% were significantly associated with large size (P ¼ .022), poor differentiation (P ¼ .009), presence of necrotic areas (P ¼ .008), estrogen receptor-negative status (P < .0001), fHER2-negative status (P ¼ .003), and shorter overall survival (P ¼ .012). Moreover, Ki-67 expression in the primary tumor was strongly and positively correlated with both regional metastasis (P < .0001; r ¼ 0.83) and distant metastasis (P < .0001; r ¼ 0.83), and was significantly higher in distant metastases when compared with the primary tumor (P ¼ .0009). A similar correlation was also observed between regional and distant metastasis (P < .0001; r ¼ 0.75). On the basis of the above results, the authors propose the adoption of the 14% value as the optimal cutoff for Ki-67 to identify tumors with high risk of disease progression.Keywords feline mammary carcinoma, Ki-67 proliferation index, prognostic factor, cutoff value Feline mammary carcinomas (FMCs) are among the most prevalent tumors in cats, with an incidence that can reach 40% of all tumor cases in this species. 23,39,42 Contrary to those of humans and dogs, 85% to 93% of feline mammary tumors are considered malignant, and the most common histotypes are the tubular, papillary, solid, and cribriform carcinomas. 39 Feline mammary tumors may metastasize to the regional lymph nodes, lungs, and liver, as well as other organs. Although some studies correlate age, tumor size, presence of regional metastasis, and malignancy grade with overall survival (OS), 19,37,43 still scarce information is available regarding the proliferation index of FMC. Based on this scenario, additional prognostic and predictive factors may provide useful insights into tumor biology to achieve a more efficient therapy and a better follow-up of the affected female cats.Ki-67 is a protein found only in growing, dividing cells. It is expressed in all cell cycle phases, except in the resting phase (G0). With an intranuclear localization, the expression levels of Ki-67 are low during the G1 and S phases, rapidly increase during the G2 phase, and reach a peak in mitosis. This well-defined expression pattern makes the Ki-67 antigen a good proliferation marker, very useful and reliable in the prognosis of human breast cancer. 9,45 Several studies of women demonstrated that high Ki-67 expression is a poor prognostic indicator of 5-year rec...