Winham, Stacey J.

Abstract Background: Biopsy diagnoses of benign breast disease (BBD) confer a 1.5- to 4-fold increased risk of developing breast cancer (BC) compared with women without BBD. Previously, we reported that decreased numbers of specific immune cell types in lobules of BBD biopsies predicted increased BC risk, suggesting the promise of future tissue biomarker studies to define BC risk markers among BBD patients. Thus, we applied protein-based GeoMx® Digital Spatial Profiling (DSP) to BBD biopsies preceding BC (cases) and to BBD biopsies from cancer-free patients (controls) to identify possible BC risk markers, which we then evaluated in subsequent BC tissues and in surrounding normal lobules of cases. Methods: Archived pathology slides of BBD biopsies were reviewed and used to guide preparation of TMAs containing 1.0-mm diameter FFPE cores of lobules from an age- and cohort-period-matched set of 91 cases and 88 controls from the Mayo Clinic BBD Cohort. For patients who later developed BC, we prepared TMAs of BC tissue and surrounding mapped normal lobules. We applied GeoMx® DSP (immune and canonical signaling proteins) to both sets of TMAs. Following QC and data normalization, associations of case status with log-transformed biomarker expression in lobules of BBD biopsies were carried out using linear mixed modeling approaches, accounting for multiple ROIs per individual. Biomarkers significantly associated with case status (p<0.05) were further examined in BCs and adjacent normal lobules, using similar approaches. Results: The mean age at BBD biopsy was 52 years, and at BC diagnosis of cases, 61.4 years (mean time from BBD to BC was 10.2 years). A family history of BC was more frequent among cases (70% versus 43%; chi-square p=0.002). Of 72 biomarkers tested, 46 (64.4%) were evaluable after QC and normalization and 5 were associated with BC risk after adjustment for family history of BC: BCL2 (p=0.005), STING (p=0.006), CD44 (p=0.02), S100 protein (p=0.03) and pan-AKT (p=0.05); each showed higher levels in lobules of BBD biopsies of controls than cases. Three unique patterns appeared when examining these biomarkers across tissue type within cases: for BCL2 (p=5 x 10-9) and STING (p=2 x 10-19), levels were high in both BC and lobules surrounding BC but low in preceding BBD; for GAPDH (p=4 x 10-53) and pan-AKT (p=2 x 10-33), levels were high in BC, low in preceding BBD, and moderate in lobules surrounding BC; and for CD44 (p=2 x 10-6) and S100B (p=2 x 10-49), levels were low in BC, high in lobules surrounding BC and moderate in preceding BBD. Conclusions: Using a novel TMA of lobules in combination with DSP, we preliminarily identified immune-based and PI3 kinase-related protein biomarkers in BBD biopsies associated with BC risk. In case-only analyses, these markers demonstrated complex differences between lobules in BBD biopsies, subsequent BCs and adjacent normal lobules. Citation Format: Robert Alan Vierkant, Jodi M. Carter, Stacey J. Winham, Chen Wang, Jennifer M. Kachergus, Ji Shi, Raymond M. Moore, Bryan M. McCauley, Laura M. Pacheco-Spann, E A. Thompson, Derek C. Radisky, Amy C. Degnim, Mark E. Sherman. Towards prediction of breast cancer risk in benign biopsies with high-plex GeoMx spatial protein profiling [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 2203.

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<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 <0.001 (46.4-183.6) (25.0-121.1) (13.3-40.6) CD8+, cells/mm2 354.4 200 150.9 0.01 <0.001 (285.5-473.2) (118.9-385) (110.1-225.0) CD11c+, % pp 3.5 3.4 0.4 0.66 <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 <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.

Objective: Studies on low-grade serous ovarian cancer (LGSC) are limited by a low number of cases. The aim of this study was to define the prognostic significance of age, stage, and CA-125 levels on survival in a multi-institutional cohort of women with pathologically confirmed LGSC. Methods: Women with LGSC were identified from the collaborative Ovarian Cancer Association Consortium (OCAC). Cases of newly diagnosed primary LGSC were included if peri-operative CA-125 levels were available. Age at diagnosis, FIGO stage, pre- and post-treatment CA-125 levels, residual disease, adjuvant chemotherapy, disease recurrence, and vital status were collected by the participating institutions. Progression-free (PFS) and overall survival (OS) were calculated. Multivariable (MVA) Cox proportional hazard models were used and hazard ratios (HR) calculated. Results: A total of 176 women with LGSC were included in this study; 82% had stage III/IV disease. The median PFS was 2.3 years and the median OS was 6.4 years. Age at diagnosis was not significantly associated with worse PFS (p = 0.23) or OS (p = 0.3) (HR per year: 0.99; 95%CI, 0.96–1.01 and 0.98; 95%CI 0.95–1.01). FIGO stage III/IV was independently associated with PFS (HR 4.26, 95%CI 1.43–12.73) and OS (HR 1.69, 95%CI 0.56–5.05). Elevated CA-125 (≥35 U/mL) at diagnosis was not significantly associated with worse PFS (p = 0.87) or OS (p = 0.78) in MVA. Elevated CA-125 (≥35 U/mL) after completion of primary treatment was independently associated with worse PFS (HR 2.81, 95%CI 1.36–5.81) and OS (HR 6.62, 95%CI 2.45–17.92). In the MVA, residual disease was independently associated with PFS (0.022), but not OS (0.85). Conclusion: Advanced LGSC was associated with poor long-term prognosis. FIGO stage and abnormal post-treatment CA-125 level are key prognostic factors inversely associated with PFS and OS. Highlights: 1. Through a multi-center collaborative effort, data from 176 women with low-grade serous ovarian cancer were analyzed. 2. Although low-grade serous ovarian cancer is often considered indolent, the progression-free and overall survival are poor. 3. Elevated post-treatment CA-125 levels are independently associated with poor survival.

Genome-wide association studies (GWAS) have identified more than 200 susceptibility loci for breast cancer, but these variants explain less than a fifth of the disease risk. Although gene–environment interactions have been proposed to account for some of the remaining heritability, few studies have empirically assessed this. We obtained genotype and risk factor data from 46,060 cases and 47,929 controls of European ancestry from population-based studies within the Breast Cancer Association Consortium (BCAC). We built gene expression prediction models for 4,864 genes with a significant (P < 0.01) heritable component using the transcriptome and genotype data from the Genotype-Tissue Expression (GTEx) project. We leveraged predicted gene expression information to investigate the interactions between gene-centric genetic variation and 14 established risk factors in association with breast cancer risk, using a mixed-effects score test. After adjusting for number of tests using Bonferroni correction, no interaction remained statistically significant. The strongest interaction observed was between the predicted expression of the C13orf45 gene and age at first full-term pregnancy (PGXE = 4.44 × 10−6). In this transcriptome-informed genome-wide gene–environment interaction study of breast cancer, we found no strong support for the role of gene expression in modifying the associations between established risk factors and breast cancer risk. Our study suggests a limited role of gene–environment interactions in breast cancer risk.

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.

Digital mammography has seen an explosion in the number of radiomic features used for risk-assessment modeling. However, having more features is not necessarily beneficial, as some features may be overly sensitive to imaging physics (contrast, noise, and image sharpness). To measure the effects of imaging physics, we analyzed the feature variation across imaging acquisition settings (kV, mAs) using an anthropomorphic phantom. We also analyzed the intra-woman variation (IWV), a measure of how much a feature varies between breasts with similar parenchymal patterns—a woman’s left and right breasts. From 341 features, we identified “robust” features that minimized the effects of imaging physics and IWV. We also investigated whether robust features offered better case-control classification in an independent data set of 575 images, all with an overall BI-RADS® assessment of 1 (negative) or 2 (benign); 115 images (cases) were of women who developed cancer at least one year after that screening image, matched to 460 controls. We modeled cancer occurrence via logistic regression, using cross-validated area under the receiver-operating-characteristic curve (AUC) to measure model performance. Models using features from the most-robust quartile of features yielded an AUC = 0.59, versus 0.54 for the least-robust, with p < 0.005 for the difference among the quartiles.

Abstract Background: Ovarian clear cell carcinoma (OCCC) is a rare ovarian cancer histotype that tends to be resistant to standard platinum-based chemotherapeutics. We sought to better understand the role of DNA methylation in clinical and biological subclassification of OCCC. Methods: We interrogated genome-wide methylation using DNA from fresh frozen tumors from 271 cases, applied nonsmooth nonnegative matrix factorization (nsNMF) clustering, and evaluated clinical associations and biological pathways. Results: Two approximately equally sized clusters that associated with several clinical features were identified. Compared with Cluster 2 (N = 137), Cluster 1 cases (N = 134) presented at a more advanced stage, were less likely to be of Asian ancestry, and tended to have poorer outcomes including macroscopic residual disease following primary debulking surgery (P &lt; 0.10). Subset analyses of targeted tumor sequencing and IHC data revealed that Cluster 1 tumors showed TP53 mutation and abnormal p53 expression, and Cluster 2 tumors showed aneuploidy and ARID1A/PIK3CA mutation (P &lt; 0.05). Cluster-defining CpGs included 1,388 CpGs residing within 200 bp of the transcription start sites of 977 genes; 38% of these genes (N = 369 genes) were differentially expressed across cluster in transcriptomic subset analysis (P &lt; 10−4). Differentially expressed genes were enriched for six immune-related pathways, including IFNα and IFNγ responses (P &lt; 10−6). Conclusions: DNA methylation clusters in OCCC correlate with disease features and gene expression patterns among immune pathways. Impact: This work serves as a foundation for integrative analyses that better understand the complex biology of OCCC in an effort to improve potential for development of targeted therapeutics.

Abstract Background: Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. Methods: We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values<5x10-8 as genome-wide significant, and p-values<1x10-5 as suggestive. Linkage disequilibrium (LD)-based clumping was performed to identify independent candidate variants.Results: None of the 9.7 million genetic variants tested for interactions with MHT use reached genome-wide significance. Only 213 variants, representing 18 independent loci, had p-values<1x105. The strongest evidence was found for rs4674019 (p-value=2.27x10-7), which showed genome-wide significant interaction (p-value=3.8x10-8) with current MHT use when analysis was restricted to population-based studies only. Limiting the analyses to combined estrogen-progesterone MHT use only or to estrogen receptor (ER) positive cases did not identify any genome-wide significant evidence of interactions. Conclusions: In this large genome-wide SNP-MHT interaction study of breast cancer, we found no strong support for common genetic variants modifying the effect of MHT on breast cancer risk. These results suggest that common genetic variation has limited impact on the observed MHT–breast cancer risk association.