Changes in breast cancer risk associated with benign breast disease from 1967 to 2013.

Background: Benign breast disease (BBD) increases breast cancer (BC) risk progressively for women diagnosed with nonproliferative change, proliferative disease without atypia (PDWA), and atypical hyperplasia (AH). Leveraging data from 18 704 women in the Mayo BBD Cohort (1967-2013), we evaluated temporal trends in BBD diagnoses and how they have influenced associated BC risk over 4 decades.

Methods: BC risk trends associated with BBD were evaluated using standardized incidence ratios (SIRs) and age-period-cohort modeling across 4 eras-premammogram (1967-1981), precore needle biopsy (CNB) (1982-1992), transition to CNB (1993-2001), and CNB era (2002-2013).

Investigating the added value of incorporatingmammographic density to an integrated breastcancer risk model with questionnaire-based riskfactors and polygenic risk score.

Introduction: Incorporation of mammographic density to breast cancer risk models could improve risk stratification to tailor screening and prevention strategies according to risk. Robust evaluation of the value of adding mammographic density to models with comprehensive information on questionnaire-based risk factors and polygenic risk score is needed to determine its effectiveness in improving risk stratification of such models.

Methods: We used the Individualized Coherent Absolute Risk Estimator (iCARE) tool for risk model building and validation to incorporate density to a previously validated literature-based model with questionnaire-based risk factors and a 313-variant polygenic risk score (PRS).

Polygenic score distribution differences across European ancestry populations: implications for breast cancer risk prediction.

Background: The 313-variant polygenic risk score (PRS) provides a promising tool for clinical breast cancer risk prediction. However, evaluation of the PRS across different European populations which could influence risk estimation has not been performed.

Methods: We explored the distribution of PRS across European populations using genotype data from 94,072 females without breast cancer diagnosis, of European-ancestry from 21 countries participating in the Breast Cancer Association Consortium (BCAC) and 223,316 females without breast cancer diagnosis from the UK Biobank.

Volumetric Breast Density Estimation From Three-Dimensional Reconstructed Digital Breast Tomosynthesis Images Using Deep Learning.

Purpose: Breast density is a widely established independent breast cancer risk factor. With the increasing utilization of digital breast tomosynthesis (DBT) in breast cancer screening, there is an opportunity to estimate volumetric breast density (VBD) routinely. However, current available methods extrapolate VBD from two-dimensional (2D) images acquired using DBT and/or depend on the existence of raw DBT data, which is rarely archived by clinical centers because of storage constraints.

Plasma prolactin and postmenopausal breast cancer risk: a pooled analysis of four prospective cohort studies.

Background: Prolactin, a hormone produced by the pituitary gland, regulates breast development and may contribute to breast cancer etiology. However, most epidemiologic studies of prolactin and breast cancer have been restricted to single, often small, study samples with limited exploration of effect modification.

Methods: The Biomarkers in Breast Cancer Risk Prediction consortium includes 8,279 postmenopausal women sampled from four prospective cohort studies, of whom 3,441 were diagnosed with invasive breast cancer after enrollment.

Pathogenic Variants in Cancer Susceptibility Genes Predispose to Ductal Carcinoma In Situ of the Breast.

Purpose: To determine the relationship between germline pathogenic variants (PV) in cancer predisposition genes and the risk of ductal carcinoma in situ (DCIS).

Experimental Design: Germline PV frequencies in breast cancer predisposition genes (ATM, BARD1, BRCA1, BRCA2, CDH1, CHEK2, PALB2, RAD51C, and RAD51D) were compared between DCIS cases and unaffected controls and between DCIS and invasive ductal breast cancer (IDC) cases from a clinical testing cohort (n = 9,887), a population-based cohort (n = 3,876), and the UK Biobank (n = 2,421). The risk of contralateral breast cancer (CBC) for DCIS cases with PV was estimated in the population-based cohort.

Comparison of progression risk of monoclonal gammopathy of undetermined significance by method of detection.

Monoclonal gammopathy of undetermined significance (MGUS) is an asymptomatic premalignant disorder. The current standard of care is not to screen for MGUS, so it is often incidentally diagnosed in the clinic. It is unknown whether the outcomes of screened vs clinically detected MGUS differ.

Polygenic risk scores stratify breast cancer risk among women with benign breast disease.

Purpose: Most breast biopsies are diagnosed as benign breast disease (BBD), with 1.5- to fourfold increased breast cancer (BC) risk. Apart from pathologic diagnoses of atypical hyperplasia, few factors aid in BC risk assessment of these patients.

Functional variant rs9344 at 11q13.3 regulates CCND1 expression in multiple myeloma with t(11;14).

Multiple myeloma (MM) is a plasma cell (PC) malignancy characterized by cytogenetic abnormalities, such as t(11;14)(q13;q32), resulting in CCND1 overexpression. The rs9344 G allele within CCND1 is the most significant susceptibility allele for t(11;14). Sequencing data from 2 independent cohorts, CoMMpass (n = 698) and Mayo Clinic (n = 661), confirm the positive association between the G allele and t(11;14).

Risk of Incident Melanoma Among Individuals With Low-Count Monoclonal B-Cell Lymphocytosis.

Purpose: Chronic lymphocytic leukemia (CLL)-phenotype monoclonal B-cell lymphocytosis (MBL) is a premalignant condition that is roughly 500-fold more common than CLL. It is unknown whether the two-fold increased risk of developing melanoma associated with CLL extends to individuals with MBL.

Methods: Using the Mayo Clinic Biobank, we identified participants who were 40 years or older with no previous hematological malignancies, who resided in the 27 counties around Mayo Clinic, and who had available biospecimens for screening.

Association of early menarche with breast tumor molecular features and recurrence.

Background: Early menarche is an established risk factor for breast cancer but its molecular contribution to tumor biology and prognosis remains unclear.

Methods: We profiled transcriptome-wide gene expression in breast tumors (N = 846) and tumor-adjacent normal tissues (N = 666) from women in the Nurses' Health Studies (NHS) to investigate whether early menarche (age < 12) is associated with tumor molecular and prognostic features in women with breast cancer. Multivariable linear regression and pathway analyses using competitive gene set enrichment analysis were conducted in both tumor and adjacent-normal tissue and externally validated in TCGA (N = 116).

Multivariate testing and effect size measures for batch effect evaluation in radiomic features.

While precision medicine applications of radiomics analysis are promising, differences in image acquisition can cause "batch effects" that reduce reproducibility and affect downstream predictive analyses. Harmonization methods such as ComBat have been developed to correct these effects, but evaluation methods for quantifying batch effects are inconsistent. In this study, we propose the use of the multivariate statistical test PERMANOVA and the Robust Effect Size Index (RESI) to better quantify and characterize batch effects in radiomics data.

Placement of an artificial urethral sphincter in 8 male dogs with urethral diverticulum.

Background: Urethral diverticulum (UD) is a poorly defined anomaly consisting of an outpouching of the urethra. Management without surgical resection is not previously reported in dogs.

Hypothesis/objectives: Report the outcome of male dogs presented for urinary incontinence with UD treated with an artificial urethral sphincter (AUS).

Disentangling the relationships of body mass index and circulating sex hormone concentrations in mammographic density using Mendelian randomization.

Purpose: Mammographic density phenotypes, adjusted for age and body mass index (BMI), are strong predictors of breast cancer risk. BMI is associated with mammographic density measures, but the role of circulating sex hormone concentrations is less clear. We investigated the relationship between BMI, circulating sex hormone concentrations, and mammographic density phenotypes using Mendelian randomization (MR).