Stallings‐Mann, Melody

Abstract Breast cancer (BC) remains a leading health concern worldwide and is often undetected until the cancer metastasizes. Early detection can limit the need for aggressive treatments and improve prognosis. We analyzed early immune and molecular markers in benign breast disease (BBD) biopsies prior to BC development to identify women at elevated risk of developing node-positive invasive BC, which might direct surveillance and prevention efforts aimed at reducing incidence of this disease. Utilizing the Mayo Clinic BBD cohort, we compared women who developed node-positive BC following their BBD biopsy (cases; n=42) with those who remained cancer-free (controls; n=37), matched on patient age and biopsy date. We used NanoString nCounter system to identify differentially expressed genes (DEGs) between cases and controls. We also developed a multiplex immunofluorescence (mIF) approach using Opal system by Akoya Biosciences for comprehensive marker detection in FFPE tissue, enabling correlation of cells expressing DEGs with innate and adaptive immune cells. Digitized images were segmented, and cell phenotyping, and spatial relationships were compared between cases and controls. Our findings revealed significantly increased expression levels of IRF8 (interferon regulatory factor 8, a factor involved in immune cell differentiation) in controls as compared to cases and found that increased IRF8 expression in cases is correlated with delayed cancer onset. Additionally, controls exhibited higher frequencies of CD4+, CD8+, CD68+, CD20+ and CD11c+ immune cells, and lower frequency of Ki67+ staining, with a notable increase of CD11c+/CD68+ cells, a marker for M1 type macrophages, indicating a pro-inflammatory, antitumorigenic immune microenvironment polarization. Furthermore, our mIF analyses offer new insights into spatial biomarker localization, enhancing prognostic accuracy. Our findings suggest that decreased numbers of immune cells in BBD biopsies may be associated with increased risk of developing axillary node-positive BC. This research underscores the importance of dissecting molecular and immune interactions in BBD for assessing the risk of this disease. Our results have the potential to improve individualized risk assessment, leading to more targeted surveillance and informed screening, potentially reducing BC incidence and mortality through early intervention. This study not only contributes to our understanding of BC pathogenesis but also opens avenues for developing novel preventive strategies. Citation Format: Matilde Rossi, Nicole Cruz-Reyes, Melody L. Stallings Mann, Bryan M. McCauley, Tanya L. Hoskin, Robert A. Vierkant, Stacey J. Winham, Amy C. Degnim, Mark E. Sherman, Derek C. Radisky. Interferon regulatory factor 8 (IRF8) as a biomarker for early detection and prevention of axillary lymph node-positive breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4773.

Abstract Purpose Breast cancer risk is elevated in pathogenic germline BRCA 1/2 mutation carriers due to compromised DNA quality control and elevated mutagenic load. We hypothesized that if immunosurveillance promotes tumor suppression, then normal breast lobules from BRCA carriers may demonstrate higher immune cell densities. Methods We assessed immune cell composition in normal breast lobules from age-matched women with progressively increased breast cancer risk, including 1) 19 women who donated normal breast tissue to the Komen Tissue Bank (KTB) at Indiana University Simon Cancer Center, 2) 15 women with biopsy-identified benign breast disease (BBD), and 3) 19 prophylactic mastectomies from women with germline mutations in BRCA1/2 genes. We performed immunohistochemical stains and analysis to quantitate immune cell densities from digital images in up to 10 representative lobules per sample. Median cell counts per mm2 were compared between groups using Wilcoxon rank-sum tests. Results Compared to BBD tissues, normal breast lobules from BRCA carriers had significantly higher densities of CD8 + cells (median 354.4 vs 200.0 cells/mm2, p = 0.01). Compared to KTB normal donor breast tissues, normal breast lobules from BRCA carriers also had significantly higher densities of CD4+ (median 116.3 vs 17.7 cells/mm2), CD8+ (354.4 vs 150.9 cells/mm2), CD11c+ (3.5% vs 0.4% pixels positive), and CD68+ (237.5 vs 57.8 cells/mm2) immune cells (each p < 0.001). Conclusions These preliminary analyses show that normal/benign breast lobules of BRCA mutation carriers contain increased immune cells compared with BBD and normal donated tissues. Future studies will be helpful to define relationships of mutations and immune responses.

Abstract Introduction: The immune microenvironment of the breast is critical in the development and progression of breast cancer. By analyzing the immune components of breast tissues from patients at varying degrees of breast cancer risk, we may gain enhanced understanding of breast cancer risk and mechanisms of carcinogenesis. Methods: We compared the immune cell composition in breast lobules of age-matched patients with normal and benign breast disease (BBD) at progressively lower breast cancer risk: 1) 18 women with germline mutations in (BRCA1/2); 2) women at intermediate risk (BBD), and 3) women at normal risk (Komen Tissue Bank- (KTB)). We performed immunohistochemical stains for T lymphocytes (CD4, CD8); dendritic cells (CD11c); B lymphocytes (CD20) and macrophages (CD68) and quantitated immune cell densities in up to 10 representative lobules per sample. Results: The median age of all groups was 43.8 years (range: 34-67). BRCA carriers and BBD patients had a higher percentage of fibrocystic lobules (50% fibrocystic) compared to KTB samples (15% fibrocystic), p&lt;0.001. BRCA carriers had significantly higher densities of CD4, CD8, CD11c, and CD68 positive immune cells compared to KTB donor breast tissues, see Table. Compared with BBD patients, mutation carriers had higher densities of CD8+ cells and suggestively higher CD4+ cells, with similar results for other markers assessed. Conclusions: Preliminarily, these data showed that benign prophylactic breast tissues from BRCA mutation carriers contain increased numbers of several immune cell types versus tissues from patients at lower breast cancer risk, including BBD patients and research tissue donors. Further investigation is needed to confirm and expand these findings in relation to breast cancer risk. Table: Pairwise Wilcoxon rank-sum p-values comparing immune cell densities in breast lobules from women with BRCA germline mutations, vs BBD and KTB groups. All Lobules BRCA BBD KTB BRCA vs BBD BRCA vs KTB Median Median Median p-value p-value (IQR) (IQR) (IQR) CD4+, cells/mm2 116.3 63.8 17.7 0.08 &lt;0.001 (46.4-183.6) (25.0-121.1) (13.3-40.6) CD8+, cells/mm2 354.4 200 150.9 0.01 &lt;0.001 (285.5-473.2) (118.9-385) (110.1-225.0) CD11c+, % pp 3.5 3.4 0.4 0.66 &lt;0.001 (1.9-6.8) (1.6-4.7) (0-0.6) CD20+, cells/mm2 6.2 16.7 0 0.16 0.65 (0-25.4) (0-58.3) (0-20.8) CD68, cells/mm2 237.5 219 57.8 0.99 &lt;0.001 (122.9-281.8) (75.0-459.4) (29.2-100.0) IQR - Interquartile Range pp - pixel positive Citation Format: Joshua W. Ogony, Tanya L. Hoskin, Melody L. Stallings Mann, Stacey J. Winham, Rushin Brahmbhatt, Muhammad Asad Arshad, Alvaro Pena Jimenez, Teresa M. Allers, Mark E. Sherrman, Daniel W. Visscher, Derek C. Radisky, Amy C. Degnim. Immune biomarkers in breast tissues of patients with BRCA1/2 mutations, benign breast disease, and normal tissue donors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5947.

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.

Abstract Background:Breast terminal duct lobular units (TDLUs), the source of most breast cancer (BC) precursors, are shaped by age-related involution, a gradual process, and postpartum involution (PPI), a dramatic inflammatory process that restores baseline microanatomy after weaning. Dysregulated PPI is implicated in the pathogenesis of postpartum BCs. We propose that assessment of TDLUs in the postpartum period may have value in risk estimation, but characteristics of these tissues in relation to epidemiological factors are incompletely described.Methods: Using validated Artificial Intelligence and morphometric methods, we analyzed digitized images of tissue sections of normal breast tissues stained with hematoxylin and eosin from donors <45 years from the Komen Tissue Bank (180 parous and 545 nulliparous). Metrics assessed by AI, included: TDLU count; adipose tissue fraction; mean acini count/TDLU; mean dilated acini; mean average acini area; mean “capillary” area; mean epithelial area; mean ratio of epithelial area versus intralobular stroma; mean mononuclear cell count (surrogate of immune cells); mean fat area proximate to TDLUs and TDLU area. We compared epidemiologic characteristics collected via questionnaire by parity status and race, using a Wilcoxon rank sum test or Fisher’s exact test. Histologic features were compared between nulliparous and parous women (overall and by time between last birth and donation [ recent birth: ≤5 years versus remote birth: >5 years]) using multivariable regression models.Results:Normal breast tissues of parous women contained significantly higher TDLU counts and acini counts, more frequent dilated acini, higher mononuclear cell counts in TDLUs and smaller acini area per TDLU than nulliparas (all multivariable analyses p<0.001). Differences in TDLU counts and average acini size persisted for >5 years postpartum whereas increases in immune cells were most marked <5 years of a birth. Relationships were suggestively modified by several other factors, including demographic and reproductive characteristics, ethanol consumption and breastfeeding duration. Conclusions:Our study identified sustained expansion of TDLU numbers and reduced average acini area among parous versus nulliparous women and notable increases in immune responses within five years following childbirth. Further, we show that quantitative characteristics of normal breast samples vary with demographic features and BC risk factors.

Abstract Benign breast disease (BBD) is an established risk factor for development of breast cancer (BC). However, little is known about the prevalence of somatic genetic alterations at the time of BBD diagnosis and relationship to subsequent BC. To characterize DNA variants in BBD and investigate association with BC risk, we isolated DNA from formalin-fixed paraffin-embedded (FFPE) BBD biopsies and assessed mutations using a panel of 93 breast cancer predisposition genes (Qiagen GeneRead). The study set consisted of 120 BBD patients from three age-matched groups defined based on 16 years of BC follow-up: BBD-controls (cancer-free after 16 years), BBD-ER+, or BBD-ER- breast cancer (within 16 years). Bioinformatics quality checks included comparisons of paired fresh-frozen and FFPE replicates to reduce false variant calls induced by FFPE artifacts. Gene-level variant burden differences among study groups were assessed using 12 statistical approaches, adjusted for patient age, year of biopsy, and histology. To investigate possible immune implications of increased variant burden, extent of leukocytes in the BBD biopsies was assessed using CD45 immunohistochemistry. To assess variant profile changes during the progression from BBD to BC, we also performed targeted sequencing of 12 BBD-matched subsequent tumor samples (six ER+ and six ER-) developed within 5 years of BBD diagnosis. Gene-level association results showed consistently skewed distributions suggesting a higher variant burden in BBD controls: among the top 10 genes associated with case-status (p&lt;0.05), all had BC-risk odds ratio estimates less than 1.0. Immune infiltrates, assessed by CD45 H-scores, were positively associated with overall variant burden (r=0.42, p=0.0031), and noticeably higher in cancer-free controls (r=0.50, p=0.005). Comparison of mutation variants in 12 BBD cases that developed cancer within 5 years of diagnosis and their subsequent tumors revealed that more than half of the non-SNP variants were shared between the BBD and the subsequent tumor (54.6%), whereas less than one quarter were unique to the tumor (20.6%) or unique to the BBD (24.9%). Through BBD-BC paired variant analysis, three subjects were found with newly emergent clones uniquely appearing in the tumors and four subjects had loss of clones in the tumor that were present in the BBD. These results show that somatic variant burden is lower in patients with BBD that progress to BC, mutation profiles of BC progression are heterogeneous, and BBD tissues with reduced variant burden also show reduced immune infiltrate. This implicates a potential protective role for immune activation in BBD. Future directions will define the characteristics of the potentially protective immune response and its role in variant heterogeneity in a larger sample set, integrated with paired RNA sequencing to better understand the pathways involved and the relationship to immune infiltration. Citation Format: Stacey J. Winham, Julie M. Cunningham, Yuanhang Liu, Aditya V. Bhagwate, Ethan P. Heinzen, Samantha J. McDonough, Melody L. Stallings-Mann, Robert A. Vierkant, Jodi M. Carter, Mark E. Sherman, Derek C. Radisky, Amy C. Degnim, Chen Wang. Somatic variant burdenin benign breast disease and association with risk of subsequent breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2274.

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 Background: Archived formalin fixed paraffin embedded (FFPE) samples are valuable clinical resources to examine clinically relevant morphology features and also to study genetic changes. However, DNA quality and quantity of FFPE samples are sub-optimal, and resulting NGS-based genetics variant detections are prone to false positives. Evaluations of wet-lab and bioinformatics approaches are needed to optimize variant detection from FFPE samples. Results: As a pilot study, we designed within-subject triplicate samples of DNA derived from paired FFPE and fresh frozen breast tissues to highlight FFPE-specific artifacts. For FFPE samples, we tested two FFPE DNA extraction methods to determine impact of wet-lab procedures on variant calling: QIAGEN QIAamp DNA Mini Kit ("QA"), and QIAGEN GeneRead DNA FFPE Kit ("QGR"). We also used negative-control (NA12891) and positive control samples (Horizon Discovery Reference Standard FFPE). All DNA sample libraries were prepared for NGS according to the QIAseq Human Breast Cancer Targeted DNA Panel protocol and sequenced on the HiSeq 4000. Variant calling and filtering were performed using QIAGEN Gene Globe Data Portal. Detailed variant concordance comparisons and mutational signature analysis were performed to investigate effects of FFPE samples compared to paired fresh frozen samples, along with different DNA extraction methods. In this study, we found that five times or more variants were called with FFPE samples, compared to their paired fresh-frozen tissue samples even after applying molecular barcoding error-correction and default bioinformatics filtering recommended by the vendor. We also found that QGR as an optimized FFPE-DNA extraction approach leads to much fewer discordant variants between paired fresh frozen and FFPE samples. Approximately 92 % of the uniquely called FFPE variants were of low allelic frequency range (<5%), and collectively shared a “C>T|G>A” mutational signature known to be representative of FFPE artifacts resulting from cytosine deamination. Based on control samples and FFPE-frozen replicates, we derived an effective filtering strategy with associated empirical false-discovery estimates. Conclusions: Through this study, we demonstrated feasibility of calling and filtering genetic variants from FFPE tissue samples using a combined strategy with molecular barcodes, optimized DNA extraction, and bioinformatics methods incorporating genomics context such as mutational signature and variant allelic frequency.