Denison, Lori A.

Abstract 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). Results With a median follow-up of 15.8 years, 9.9% of women were diagnosed with BC (invasive and/or DCIS). From the premammogram era to the CNB era, we observed a significant increase in BC risk, rising from an SIR of 1.61 to 1.99. The proportion of proliferative BBD diagnoses (PDWA or AH) increased markedly over time (28.1%-49.7%), as did the proportion of DCIS events (11%-28%; χ2 P < .001). Within specific BBD categories, the risk of invasive BC increased modestly. Conclusions Absolute risk of BC within BBD categories remained stable, but the relative risk of BC after BBD increased over time due to notable increases in higher risk BBD lesions, specifically PDWA and AH. These findings illustrate how evolving screening practices have changed the risk profile of BBD and should inform management strategies for patients with BBD in modern clinical settings.

Abstract Background: Benign breast disease (BBD) is a risk factor for breast cancer (BC); however, little is known about the genetic alterations present at the time of BBD diagnosis, and how these relate to risk of incident BC. Methods: A subset of a long-term BBD cohort was selected to examine DNA variation across three BBD groups (42 future estrogen receptor-positive (ER+) BC, 36 future estrogen receptor-negative (ER-) BC and 42 controls cancer-free for at least 16 years post-BBD). DNA extracted from archival formalin fixed, paraffin-embedded (FFPE) tissue blocks was tested and analyzed for presence of DNA alterations using a targeted panel of 93 BC-associated genes. To address artifacts frequently observed in FFPE tissues (e.g., C>T changes), we applied three filtering strategies based on alternative allele frequencies and nucleotide substitution context. Gene-level associations were performed using two burden tests, SKAT-O and logistic regression, and adjusted for clinical and technical covariates including epithelial percentage, histologic impression, patient age and year of BBD biopsy. Results: After filtering, the variant frequency of SNPs in our samples was highly consistent with population allele frequencies reported in 1KG/ExAC (0.986, p <1e-16). Ten genes were found to be associated with later cancer status by four of 12 association methods, with nominal p-values <0.05: MED12, MSH2, BRIP1, PMS1, GATA3, MUC16, FAM175A, EXT2, MLH1 and TGFB1. Additionally, analysis revealed 11 and 19 gene-level associations with p-values <0.05 and OR<1 for all cancer cases and ER- cases, respectively. Comparing between the three case groups, BBD ER+ cases were closer to controls in mutation profile, while BBD ER- cases were distinct. Notably, the variant burden was significantly higher in controls than in either ER+ or ER- cases. CD45 expression was associated with mutational burden (p=0.003).Conclusions: Somatic mutations were more frequent in benign breast tissue from women who did not develop cancer, opening questions of clonal diversity or immune-mediated restraint on future cancer development. CD45 expression was positively associated with mutational burden, most strongly in controls. Further studies in both normal and premalignant tissues are needed to better understand the role of somatic gene mutations and their contribution to future cancer development.

Abstract Background: Biopsy diagnosis of benign breast disease (BBD) based on the most severe lesion in a sample predicts future breast cancer risk and has implications for screening and management. Lobules are the functional unit of the breast and the structures from which BBD arises. We developed and preliminarily validated an automated computational pathology algorithm to discriminate normal from BBD breast lobules as a step toward automated comprehensive characterization of benign biopsies. Methods: 152 BBD biopsies (27 training, 125 validation) from the Mayo Clinic were examined using scanned digital images of H&E stained sections. For each image, a pathologist annotated up to 10 representative lobules as normal or BBD using standard pathology criteria. A deep learning algorithm to quantify lobular features was developed using 129 lobules from 27 subjects. Nine features were identified that discriminate normal vs BBD lobules, expressing lobule size, acini size and number, acinar lumen size, proportion of lobular stroma, and capillaries. Here, we validate their performance to discriminate normal vs BBD lobules in a set of 1250 lobules from 125 subjects using area under the ROC curve (AUC) analysis. Random forest analysis was used for multivariable modeling; model performance was assessed with a tenfold cross-validation approach. Results: Median subject age was 52 years. Among the 125 validation subjects, BBD findings were nonproliferative in 39%, proliferative in 45%, and atypical hyperplasia in 16%. Sections included 552 (44%) normal lobules and 698 BBD (56%) lobules, with representation of both lobule types on each section. In univariate analyses, four individual features showed good discrimination between normal vs. BBD lobules, yielding the following AUCs: lobule size= 0.74, mean acini size= 0.75, epithelial area= 0.75, and number of acini with large lumens= 0.76. Lobule size and epithelial area were highly correlated (Spearman rank correlation r = 0.95), but both of these features showed lower correlation with mean acini size and number of acini with large lumens (each r &lt; 0.5). With random forest modeling, number of acini with large lumens was the strongest discriminating feature, followed by mean acini size, lobule size, and epithelial area. With ten-fold cross validation of the multivariable random forest model, the overall AUC was 0.82 (95% CI: 0.79-0.85). Conclusion: Our validation showed that automated quantitative computational pathology assessment of breast lobules can discriminate normal versus BBD on a per lobule basis. This finding supports the feasibility of developing automated algorithms to classify every lesion in breast biopsies, expanding beyond visual assessment. Further studies using deep learning may reveal novel pathology features for classifying BBD biopsies with the potential to strengthen estimation of breast cancer risk. Citation Format: Amy C. Degnim, Thomas de Bel, Mark E. Sherman, Derek C. Radisky, Stacey J. Winham, Tanya L. Hoskin, Melody L. Stallings Mann, Marlene Frost, Robert A. Vierkant, Brendan T. Broderick, Ethan P. Heinzen, Rushin Brahmbhatt, Muhammad Arshad, Celine M. Vachon, Jodi M. Carter, Lori A. Denison, Daniel W. Visscher, Jeroen van der Laak. Discrimination of benign breast disease from normal lobules using an automated computational pathology algorithm [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2113.

Abstract Over one million women in the United States receive biopsy diagnoses of benign breast disease (BBD) each year, which confer a 1.5–4.0-fold increase in breast cancer risk. Studies in the general population suggest that nonsteroidal anti-inflammatory agents (NSAID) lower breast cancer risk; however, associations among women with BBD are unknown. We assessed whether NSAID use among women diagnosed with BBD is associated with lower breast cancer risk. Participants included 3,080 women (mean age = 50.3 ± 13.5 years) in the Mayo BBD surgical biopsy cohort diagnosed between January 1, 1992 and December 31, 2001 who completed breast cancer risk factor questionnaires that assessed NSAID use, and whose biopsies underwent detailed pathology review, masked to outcome. Women were followed from date of BBD biopsy to breast cancer diagnosis (main outcome) or censoring (death, prophylactic mastectomy, reduction mammoplasty, lobular carcinoma in situ or last contact). Median follow-up time was 16.4 ± 6.0 years. Incident breast cancer was diagnosed among 312 women over a median follow-up of 9.9 years. Regular non-aspirin NSAID use was associated with lower breast cancer risk [HR = 0.63; 95% confidence interval (CI) = 0.46–0.85; P = 0.002] with trends of lower risk (highest tertiles of use vs. nonuse) for greater number of years used [HR = 0.55; 95% CI = 0.31–0.97; Ptrend = 0.003), days used per month (HR = 0.51; 95% CI = 0.33–0.80; Ptrend = 0.001) and lifetime number of doses taken (HR = 0.53; 95% CI = 0.31–0.89; Ptrend = 0.003). We conclude that nonaspirin NSAID use is associated with statistically significant lower breast cancer risk after a BBD biopsy, including a dose–response effect, suggesting a potential role for NSAIDs in breast cancer prevention among patients with BBD.

Purpose Women with atypical hyperplasia (AH) on breast biopsy have an aggregate increased risk of breast cancer (BC), but existing risk prediction models do not provide accurate individualized estimates of risk in this subset of high-risk women. Here, we used the Mayo benign breast disease cohort to develop and validate a model of BC risk prediction that is specifically for women with AH, which we have designated as AH-BC. Patients and Methods Retrospective cohorts of women age 18 to 85 years with pathologically confirmed benign AH from Rochester, MN, and Nashville, TN, were used for model development and external validation, respectively. Clinical risk factors and histologic features of the tissue biopsy were selected using L1-penalized Cox proportional hazards regression. Identified features were included in a Fine and Gray regression model to estimate BC risk, with death as a competing risk. Model discrimination and calibration were assessed in the model-building set and an external validation set. Results The model-building set consisted of 699 women with AH, 142 of whom developed BC (median follow-up, 8.1 years), and the external validation set consisted of 461 women with 114 later BC events (median follow-up, 11.4 years). The final AH-BC model included three covariates: age at biopsy, age at biopsy squared, and number of foci of AH. At 10 years, the AH-BC model demonstrated good discrimination (0.63 [95% CI, 0.57 to 0.70]) and calibration (0.87 [95% CI, 0.66 to 1.24]). In the external validation set, the model showed acceptable discrimination (0.59 [95% CI, 0.51 to 0.67]) and calibration (0.91 [95% CI, 0.65 to 1.42]). Conclusion We have created a new model with which to refine BC risk prediction for women with AH. The AH-BC model demonstrates good discrimination and calibration, and it validates in an external data set.

2 Background: Women with atypical hyperplasia (AH) on breast biopsy have an aggregate increased risk of breast cancer (BC), but accurate personalized risk prediction is desirable to facilitate individual clinical management decisions. Currently used models provide poor BC risk prediction for women with AH. Our goal was to develop and validate an improved risk prediction model for women with AH. Methods: From a cohort of 13,538 women with benign breast disease from 1967-2001, pathology review confirmed 699 with AH. Clinical risk factors and histologic features of the tissue biopsy were recorded, and BC events were ascertained from study questionnaires, tumor registry, and review of medical records. Using a lasso approach, 23 variables were assessed for model inclusion. Lasso-identified features were then fit in a Cox regression model to estimate BC risk. Model discrimination was assessed with C-statistics in the model-building set and in a separate external validation set. Calibration was assessed by comparing observed to predicted breast cancer counts. Results: The model-building set comprised 699 women with 142 BC events (median follow-up 8.1 years), and the external validation set comprised 461 women with 114 BC events (median follow-up 11.4 years). The final model included three covariates: age at biopsy, age squared, and number of foci of AH. Model performance was good, with a C-statistic of 0.622 (SE = 0.027) in the model-building set and 0.594 (SE = 0.029) in the external validation set. The model is well-calibrated, with observed to expected numbers of BCs nearly equal across all post-biopsy follow-up years. Conclusions: We propose a new model for predicting BC risk in women with AH based on age at biopsy and number of foci of atypia. This model provides absolute risk estimates for women with AH, has good discriminatory ability, is well-calibrated, and validates in an external cohort.

Abstract Purpose: Little is known about the role of the immune system in the earliest stages of breast carcinogenesis. We studied quantitative differences in immune cell types between breast tissues from normal donors and those from women with benign breast disease (BBD). Experimental Design: A breast tissue matched case–control study was created from donors to the Susan G. Komen for the Cure Tissue Bank (KTB) and from women diagnosed with BBD at Mayo Clinic (Rochester, MN) who either subsequently developed cancer (BBD cases) or remained cancer-free (BBD controls). Serial tissue sections underwent immunostaining and digital quantification of cell number per mm2 for CD4+ T cells, CD8+ T cells, CD20+ B cells, and CD68+ macrophages and quantification of positive pixel measure for CD11c (dendritic cells). Results: In 94 age-matched triplets, BBD lobules showed greater densities of CD8+ T cells, CD11c+ dendritic cells, CD20+ B cells, and CD68+ macrophages compared with KTB normals. Relative to BBD controls, BBD cases had lower CD20+ cell density (P = 0.04). Nearly 42% of BBD cases had no CD20+ B cells in evaluated lobules compared with 28% of BBD controls (P = 0.02). The absence of CD20+ cells versus the presence in all lobules showed an adjusted OR of 5.7 (95% confidence interval, 1.4–23.1) for subsequent breast cancer risk. Conclusions: Elevated infiltration of both innate and adaptive immune effectors in BBD tissues suggests an immunogenic microenvironment. The reduced B-cell infiltration in women with later breast cancer suggests a role for B cells in preventing disease progression and as a possible biomarker for breast cancer risk. Clin Cancer Res; 23(14); 3945–52. ©2017 AACR.

Abstract Background: Age-related lobular involution (LI) is a physiological process in which the terminal duct lobular units of the breast regress as a woman ages. Analyses of breast biopsies from women with benign breast disease (BBD) have found that extent of LI is negatively associated with subsequent breast cancer development. Here we assess the natural course of LI within individual women, and the impact of progressive LI on breast cancer risk. Methods: The Mayo Clinic BBD cohort consists of 13,455 women with BBD from 1967-2001. The BBD cohort includes 1115 women who had multiple benign biopsies, 106 of whom had developed breast cancer. Within this multiple biopsy cohort, the progression of the LI process was examined by age at initial biopsy and time between biopsies. The relationship between LI progression and breast cancer risk was assessed using standardized incidence ratios (SIRs) and by Cox proportional hazards analysis. Results: Women who had multiple biopsies were younger age and had a slightly higher family history of breast cancer as compared with the overall BBD cohort. Extent of LI at subsequent biopsy was greater with increasing time between biopsies and for women age 55+ at initial biopsy. Among women with multiple biopsies, there was a significant association of higher breast cancer risk among those with involution stasis (lack of progression, HR 1.63) as compared with those with involution progression, p = 0.036. Conclusions: The multiple biopsy BBD cohort allows for a longitudinal study of the natural progression of LI. The majority of women in the multiple biopsy cohort showed progression of LI status between benign biopsies, and extent of progression was highest for women who were in the perimenopausal age range at initial biopsy. Progression of LI status between initial and subsequent biopsy was associated with decreased breast cancer risk. Citation Format: Derek Radisky, Daniel W. Visscher, Ryan Frank, Robert A. Vierkant, Stacey J. Winham, Melody L. Stallings-Mann, Tanya L. Hoskin, Aziza Nassar, Celine M. Vachon, Lori A. Denison, Lynn C. Hartmann, Marlene H. Frost, Amy C. Degnim. Natural history of age-related lobular involution and impact on breast cancer risk. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr LB-364.

BACKGROUNDWomen with atypical hyperplasia (AH) on breast biopsy have a substantially increased risk of breast cancer (BC). Here the BC risk for the extent and subtype of AH is reported for 2 separate cohorts.METHODSAll samples containing AH were included from 2 cohorts of women with benign breast disease (Mayo Clinic and Nashville). Histology review quantified the number of foci of atypical ductal hyperplasia (ADH) and atypical lobular hyperplasia (ALH). The BC risk was stratified for the number of AH foci within AH subtypes.RESULTSThe study included 708 Mayo AH subjects and 466 Nashville AH subjects. In the Mayo cohort, an increasing number of foci of AH was associated with a significant increase in the risk of BC both for ADH (relative risks of 2.61, 5.21, and 6.36 for 1, 2, and ≥3 foci, respectively; P for linear trend = .006) and for ALH (relative risks of 2.56, 3.50, and 6.79 for 1, 2, and ≥3 foci, respectively; P for linear trend = .001). In the Nashville cohort, the relative risks of BC for ADH were 2.70, 5.17, and 15.06 for 1, 2, and ≥3 foci, respectively (P for linear trend < .001); for ALH, the relative risks also increased but not significantly (2.61, 3.48, and 4.02, respectively; P = .148). When the Mayo and Nashville samples were combined, the risk increased significantly for 1, 2, and ≥3 foci: the relative risks were 2.65, 5.19, and 8.94, respectively, for ADH (P < .001) and 2.58, 3.49, and 4.97, respectively, for ALH (P = .001).CONCLUSIONSIn 2 independent cohort studies of benign breast disease, the extent of atypia stratified the long‐term BC risk for ADH and ALH. Cancer 2016;122:2971‐2978. © 2016 American Cancer Society.