Frost, Marlene H.

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 BackgroundFormalin-fixed, paraffin-embedded (FFPE) tissues have many advantages for identification of risk biomarkers, including wide availability and potential for extended follow-up endpoints. However, RNA derived from archival FFPE samples has limited quality. Here we identified parameters that determine which FFPE samples have the potential for successful RNA extraction, library preparation, and generation of usable RNAseq data.MethodsWe optimized library preparation protocols designed for use with FFPE samples using seven FFPE and Fresh Frozen replicate pairs, and tested optimized protocols using a study set of 130 FFPE biopsies from women with benign breast disease. Metrics from RNA extraction and preparation procedures were collected and compared with bioinformatics sequencing summary statistics. Finally, a decision tree model was built to learn the relationship between pre-sequencing lab metrics and qc pass/fail status as determined by bioinformatics metrics.ResultsSamples that failed bioinformatics qc tended to have low median sample-wise correlation within the cohort (Spearman correlation < 0.75), low number of reads mapped to gene regions (< 25 million), or low number of detectable genes (11,400 # of detected genes with CPM > 2). The median RNA concentration and pre-capture library Qubit values for qc failed samples were 18.7 ng/ul and 1.68 ng/ul respectively, which were significantly lower than those of qc pass samples (40.8 ng/ul and 5.58 ng/ul). We built a decision tree model based on input RNA concentration, input library qubit values, and achieved an F score of 0.803 in predicting QC status (pass/fail) of FFPE samples. ConclusionsWe provide a bioinformatics quality control recommendation for FFPE samples from breast tissue by evaluating bioinformatic and sample metrics. Our results suggest a minimum concentration of 25 ng/ul FFPE-extracted RNA for library preparation and 1.8 ng/ul pre-capture library output to achieve adequate RNA-seq data for downstream bioinformatics analysis.

Background In clinical trials and clinical practice, patient-reported outcomes are almost always assessed using multiple patient-reported outcome measures at the same time. This raises concerns about whether patient responses are affected by the order in which the patient-reported outcome measures are administered. Methods This questionnaire-based study of order effects included adult cancer patients from five cancer centers. Patients were randomly assigned to complete questionnaires via paper booklets, interactive voice response system, or tablet web survey. Linear Analogue Self-Assessment, Patient-Reported Outcomes Version of the Common Terminology Criteria for Adverse Events, and Patient-Reported Outcomes Measurement Information System assessment tools were each used to measure general health, physical function, social function, emotional distress/anxiety, emotional distress/depression, fatigue, sleep, and pain. The order in which the three tools, and domains within tools, were presented to patients was randomized. Rates of missing data, scale scores, and Cronbach’s alpha coefficients were compared by the order in which they were assessed. Analyses included Cochran–Armitage trend tests and mixed models adjusted for performance score, age, sex, cancer type, and curative intent. Results A total of 1830 patients provided baseline patient-reported outcome assessments. There were no significant trends in rates of missing values by whether a scale was assessed earlier or later. The largest order effect for scale scores was due to a large mean score at one assessment time point. The largest difference in Cronbach’s alpha between the versions for the Patient-Reported Outcomes Measurement Information System scales was 0.106. Conclusion The well-being of a cancer patient has many different aspects such as pain, fatigue, depression, and anxiety. These are assessed using a variety of surveys often collected at the same time. This study shows that the order in which the different aspects are collected from the patient is not important.

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: Women with benign breast disease (BBD) are at increased risk of breast cancer (BC). Classic studies based on film-based mammographic screening and pathology diagnosis of surgical biopsies conducted in the 1980s established a hierarchy of increasing BC risk: non-proliferative (NP) BBD, proliferative BBD without atypia (PDWA) and atypical hyperplasia (AH). Given changes in epidemiological BC risk factors and introduction of percutaneous core needle biopsy (CNB) in mid-1990s, and later, digital mammography, we hypothesized that the patient characteristics and relative frequency of BBD diagnoses have changed over time. Accordingly, we performed a longitudinal analysis of the frequency of patient characteristics and BBD diagnoses in the Mayo BBD cohort. Methods: Utilizing the Mayo Clinic Surgical and Pathology Indices, women ages 18 to 85 who had a BBD biopsy between 1/1/67 and 12/31/13 were identified. Breast pathologists reviewed biopsies masked to diagnoses of incident BC diagnosed in follow-up. Demographic characteristics and BC events were obtained by query of institutional data sources and participant surveys. Trends were evaluated for the following eras: 1: pre-mammogram (1967-1981), 2: pre-CNB (1982-1992), 3: CNB Transition (1993-2001), and 4: CNB (2002-2013). Demographics were formally compared across eras using chi-square tests for categorical variables and analyses of variance (ANOVAs) for continuous variables. Results: From 1967-2013, the cohort includes 19,582 unique women with BBD. The frequency of CNB increased from eras 1-4: 0.04%, 0.6%, 51.3 %, and 88.9%, respectively. Mean age at BBD diagnosis was younger in era 1 (48.0 years) vs eras 2-4 (53.2, 52.0, and 51.8, respectively, p&lt;0.001). The percentage of biopsies diagnosed as PDWA increased from era 1-4 (25.7%, 34.3%, 35.2%, 46.2%, p&lt;0.001), as did the percentage with AH (2.4%, 5.1%, 8.6%, 12.3%, p&lt;0.001). Over eras 1-4, the percentages of women with a strong family history of BC increased (9.9%, 12.7%, 17.1%, and 29.0%, p&lt;0.001) as did mean BMI (24.8, 26.4, 27.4, and 28.6, p&lt;0.001). With a median follow-up of 10.9 years, 1,719 breast cancers have developed, with increasing proportion of noninvasive (DCIS-only) disease across eras 1-4: 15.0%, 21.1%, 21.2%, and 33.2%, p&lt; 0.001. Conclusions: Analysis of this large, single institution BBD cohort for the 46 year period 1967-2013 demonstrates that BC risk factors among BBD patients has changed over time, with subjects demonstrating increasing age, BMI, and family history, and that the percentages of BBD classified as PDWA and AH have increased. Impact on BC risk will be further investigated. Citation Format: Amy Degnim, Karthik Ghosh, Jodi M Carter, Robert A Vierkant, Matthew R Jensen, Stacey J Winham, Tanya L Hoskin, Marlene Frost, Teresa M Allers, Denise L Gehling, Mindy J Kern, Laura M Pacheco-Spann, Celine M Vachon, Derek C Radisky, Daniel W Visscher, Mark E Sherman. Benign breast disease: Temporal trends from 1967 to 2013 [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS7-11.

Abstract Background: Women with benign breast disease (BBD) experience an increased risk of breast cancer (BC). Histologic classification of BBD, as non-proliferative disease (NP), proliferative disease without atypia (PDWA) or atypical hyperplasia (AH), stratifies groups of patients into progressively higher categories of BC risk. However, this classification does not comprehensively assess the proliferative state of the epithelium throughout the biopsy. In addition, while AH is considered the most high-risk class of BBD, it is not always a highly proliferative lesion; atypical ductal lesions may reflect focal cytologic and architectural changes. We evaluated the association of an alternative classification of BBD severity and BC risk based on subjective grading of: 1) the maximal degree of epithelial proliferation and 2) multifocality of epithelial proliferation. Methods: Pathologists reviewed biopsies from participants aged 18 to 85 years in the Mayo BBD cohort (2002-2013), masked to BC outcomes, ascertained via questionnaires, tumor registry data and medical record review. Biopsies were classified as NP, PDWA or AH and semi-quantitatively scored for: 1) maximal degree of epithelial proliferation within a focus (DP) (0-3; none to severe) and 2) multifocality of proliferation (MP) (0-3; none to multiple foci). DP and MP scores were also summed to give a DP+MP score (0-6). Associations of DP and MP with BC risk were examined using Cox proportional hazards regression analyses, adjusting for age at BBD biopsy. Women were followed from date of initial biopsy to date of BC, death or last follow-up. Results: Of the 1529 assessable biopsies, 544 (35.6%) were classified as NP, 708 (46.3%) as PDWA and 277 (18.1%) as AH. Both DP and MP scores had significant positive correlation with increasing BBD severity (DP: r=0.51, p&lt; 0.001; MP: r=0.52, p&lt; 0.001). Mean (SD) DP scores were 0.6 (0.6) for NP, 1.6 (0.9) for PDWA, and 1.8 (0.7) for AH (ANOVA p&lt;0.001). Mean (SD) for MP scores were 0.6 (0.6) for NP, 1.4 (0.8) for PDWA, and 1.8 (0.8) for AH (ANOVA p&lt;0.001). Mean (SD) for DP+MP scores were 1.2 (1.2) for NP, 2.9 (1.5) for PDWA, and 3.6 (1.2) for AH (ANOVA p&lt;0.001). With median follow-up of 8.8 years for controls and 5.3 years for cases, 10.6% of the women in the cohort developed BC. Compared to those with DP scores of 0, women with DP scores of 3 had significantly increased BC risk (HR 1.42, 95% CI: 1.16, 1.74, p=0.003). MP was associated with a non-significant increase in BC risk for scores of 3 versus 0 (HR: 1.20, 95% CI: 0.97,1.49, p=0.11). DP+MP scores of 6 conferred the highest BC risk (HR (score 6 vs. 0): 1.62, 95% CI 1.18,2.21, p=0.02). Results did not substantively differ after adjusting for BBD severity as NP, PDWA or AH. Conclusions: In this preliminary analysis within the Mayo BBD cohort, both proliferative degree (DP) and multifocality (MP) scores were correlated with histologic severity of BBD. DP and DP+MP scores were each associated with increased BC risk. We conclude that improved characterization of epithelial proliferation in BBD biopsies may enable refined prediction of individual BC risk. Citation Format: Jodi M Carter, Matthew R Jensen, Robert A Vierkant, Stacey J Winham, Tanya L Hoskin, Marlene Frost, Karthik Ghosh, Derek C Radisky, Amy C Degnim, Mark E Sherman. Epithelial proliferation score as an independent breast cancer risk predictor in benign breast disease [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD10-10.

Abstract Background: Parity reduces risk of late onset breast cancer (BC), but childbirth is associated with a transient rise in BC risk. In a prior analysis of normal breast tissues donated for research to the Komen Tissue Bank (KTB), we reported that numbers of lobules (the primary structures from which BCs arise) are increased among parous versus nulliparous women. To further define the histological features that may be related to the transient rise in post-partum BC risk, we performed an expanded histologic review of 757 breast tissues donated to the KTB by women ≤45 years of age and compared lobule number, acinar count per lobule, and abundance of immune cells, and specifically plasma cells, between nulliparous and parous women. Methods: We assessed digital scans of H&E stained tissue sections of KTB tissues for total number of lobules, and evaluated acini / lobule (ordinal categories) and lobule span (um) for ≤10 lobules per section. Masked to epidemiologic data, we subjectively assessed images including ≥5 lobules for the presence of benign breast disease (BBD), ≥3 plasma cells per section and increased immune cells in lobules. We compared parous women according to time since last birth (≤5 years or &gt;5 years) to nulliparas (referent) using age-adjusted regression models appropriate for data type (count, continuous, ordinal, or categorical). Results: Compared to nulliparous women, parous women ≤5 years of a birth had a 1.83-fold increase in lobule counts (95% confidence interval [CI]: 1.47-2.28, P&lt;0.001), increased plasma cells in lobules (OR=1.86; 95% CI: 1.08-3.18, P&lt;0.025), and subjectively, increased immune cells in lobules (OR=2.46, 95% CI: 1.39-4.36, P&lt;0.002). Comparisons of parous women ≥5 years post-partum to nulliparas revealed a 1.83-fold increase in numbers of lobules (95% CI: 1.42-2.36, P&lt;0.001); however, lobule span in parous women was 0.89 times that of nulliparous women (95% CI: 0.80-0.99, P=0.037) and other features assessed did not show statistically significant differences. Conclusion: Histologically, normal breast tissues reveal persistently increased lobule counts and increased plasma cells and inflammation for ≤5 years post-partum compared with nulliparous women, although other lobular features decrease between ≤5 and &gt;5 years after a birth. Future molecular studies will define how these changes in the epithelium and microenvironment during the post-partum period may inform mechanisms that mediate the transient increase in BC risk after childbirth and the reduction in BC risk that occurs later in life. Citation Format: Joshua Ogony, DereK C. Radisky, Amy C. Degnim, Marlene Frost, Tanya L. Hoskin, Michael G. Heckman, Launia J. White, Mark E. Sherman. Analysis of post-partum breast tissue to understand early onset breast cancer [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 4635.

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.

1061 Background: Benign breast disease (BBD) is a significant risk factor for breast cancer (BC); however little is known about the aggressiveness of the BCs these patients develop. Shared features between select atypias and low-grade DCIS have led some to speculate that a history of BBD portends the development of well-differentiated BCs. Methods: The Mayo BBD cohort includes 9,376 women who had benign breast biopsies from 1967–1991. Data on BC events were obtained from medical records and questionnaires. Tissue from the BCs was reviewed by a single breast pathologist (DWV). Results: Our cohort included 6,244 patients with nonproliferative disease (NP), 2,801 women with proliferative disease without atypia (PDWA), and 331 with atypical hyperplasias (AH). With a median of 18 years of follow-up, 799 patients with BBD have developed breast cancer, 416 initially had NP, 313 had PDWA, and 70 AH. BC tissue was available for 703 of the women. The cancers were invasive ductal in 76.1% (n = 535), invasive lobular in 9.4% (n = 66), and DCIS alone in 14.5% (n = 102) patients. Grade is currently available for 500 women, and is well differentiated in 29.4% (n = 150), moderately differentiated in 42.7% (n = 218) and poorly differentiated in 27.8% (n = 142). In 537 cases the malignant tissue had a concurrent benign component consisting of NP in 24% (n = 129), PDWA in 25.1% (n = 135), and AH in 50.8% (n = 273). In regards to tumor size, 69.6% had T1 tumors, 24.9% T2 tumors, and 5.5% T3 disease. Metastasis to lymph nodes occurred in 25% of patients. Median time to BC was 12.3 years and did not differ across the different benign entities. Breast cancer developed within 5 years from the initial BBD in 163 women (20%). In this group, tumor size was greater (p = 0.02), and there were more poorly differentiated tumors (p = 0.006) than in those who later developed BC. Conclusions: In the BCs that have developed in our BBD cohort, we do not see a preponderance of well-differentiated, good-risk BCs. Patients diagnosed within 5 years of BBD appear to have BCs with more aggressive features. No significant financial relationships to disclose.