Sherman, Mark E.

Abstract Delayed terminal duct lobular unit (TDLU) involution is associated with elevated mammographic breast density (MD). Both are independent breast cancer risk factors among women with benign breast disease (BBD). Prior digital analyses of normal breast tissues revealed that epithelial nuclear density (END) and TDLU involution are inversely correlated. Accordingly, we examined associations of END, TDLU involution, and MD in BBD clinical biopsies. This study included digitized images of 262 representative image-guided hematoxylin and eosin–stained biopsies from 224 women diagnosed with BBD, enrolled within the cross-sectional BREAST-Stamp project that were visually assessed for TDLU involution (TDLU count/100 mm2, median TDLU span and median acini count per TDLU). A digital algorithm estimated nuclei count per unit epithelial area, or END. Single X-ray absorptiometry of prebiopsy ipsilateral craniocaudal digital mammograms measured global and localized MD surrounding the biopsy region. Adjusted ordinal logistic regression models assessed relationships between tertiles of TDLU and END measures. Analysis of covariance examined mean differences in MD across END tertiles. TDLU measures were positively associated with increasing END tertiles [TDLU count/100 mm2, ORT3vsT1: 3.42, 95% confidence interval (CI), 1.87–6.28; acini count/TDLUT3vsT1, OR: 2.40, 95% CI, 1.39–4.15]. END was significantly associated with localized, but not, global MD. Relationships were most apparent among patients with nonproliferative BBD. These findings suggest that quantitative END reflects different but complementary information to the histologic information captured by visual TDLU and radiologic MD measures and merits continued evaluation in assessing cellularity of breast parenchyma to understand the etiology of BBD.

AbstractSynthetic progestogens (progestins) have been linked to increased breast cancer risk; however, the role of endogenous progesterone in breast physiology and carcinogenesis is less clearly defined. Mechanistic studies using cell culture, tissue culture, and preclinical models implicate progesterone in breast carcinogenesis. In contrast, limited epidemiologic data generally do not show an association of circulating progesterone levels with risk, and it is unclear whether this reflects methodologic limitations or a truly null relationship. Challenges related to defining the role of progesterone in breast physiology and neoplasia include: complex interactions with estrogens and other hormones (eg, androgens, prolactin, etc.), accounting for timing of blood collections for hormone measurements among cycling women, and limitations of assays to measure progesterone metabolites in blood and progesterone receptor isotypes (PRs) in tissues. Separating the individual effects of estrogens and progesterone is further complicated by the partial dependence of PR transcription on estrogen receptor (ER)α-mediated transcriptional events; indeed, interpreting the integrated interaction of the hormones may be more essential than isolating independent effects. Further, many of the actions of both estrogens and progesterone, particularly in “normal” breast tissues, are driven by paracrine mechanisms in which ligand binding to receptor-positive cells evokes secretion of factors that influence cell division of neighboring receptor-negative cells. Accordingly, blood and tissue levels may differ, and the latter are challenging to measure. Given conflicting data related to the potential role of progesterone in breast cancer etiology and interest in blocking progesterone action to prevent or treat breast cancer, we provide a review of the evidence that links progesterone to breast cancer risk and suggest future directions for filling current gaps in our knowledge.

Abstract Black women in the United States are disproportionately affected by early-onset, triple-negative breast cancer. DNA methylation has shown differences by race in healthy and tumor breast tissues. We examined associations between genome-wide DNA methylation levels in breast milk and breast cancer risk factors, including race, to explain how this reproductive stage influences a woman's risk for, and potentially contributes to racial disparities in, breast cancer. Breast milk samples and demographic, behavioral, and reproductive data, were obtained from cancer-free, uniparous, and lactating U.S. black (n = 57) and white (n = 82) women, ages 19–44. Genome-wide DNA methylation analysis was performed on extracted breast milk DNA using the Infinium HumanMethylation450 BeadChip. Statistically significant associations between breast cancer risk factors and DNA methylation beta values, adjusting for potential confounders, were determined using linear regression followed by Bonferroni Correction (P < 1.63 × 10−7). Epigenetic analysis in breast milk revealed statistically significant associations with race and lactation duration. Of the 284 CpG sites associated with race, 242 were hypermethylated in black women. All 227 CpG sites associated with lactation duration were hypomethylated in women who lactated longer. Ingenuity Pathway Analysis of differentially methylated promoter region CpGs by race and lactation duration revealed enrichment for networks implicated in carcinogenesis. Associations between DNA methylation and lactation duration may offer insight on its role in lowering breast cancer risk. Epigenetic associations with race may mediate social, behavioral, or other factors related to breast cancer and may provide insight into potential mechanisms underlying racial disparities in breast cancer incidence.

Abstract Existing risk models underperform among women who have undergone a benign breast disease (BBD) biopsy (> one million performed annually in the US) and with respect to estimating the risk of aggressive BCs. We've shown that molecular pathologic analysis of BBD biopsies can improve individual risk prediction, compared with standard risk models relying on self-reported factors, and provide insights into mechanisms mediating BC risk. BC risk factors such as obesity and ethanol use are proposed to increase production of cytokines and chemokines, resulting in chronic inflammation, and leading to production of DNA damaging free radicals and growth factors (e.g., VEGF, IGFs) that activate pro-carcinogenic pathways (e.g. NF-KB and JAK/STAT). The effects of most BC risk factors on immunity are poorly understood. Further, whereas experimental models implicate immunity throughout carcinogenesis, knowledge of immune markers and mechanisms related to BC development among women is limited. Therefore, we aim to define tissue immune cell content throughout BC development, and particularly at the earliest stages, to improve risk assessment and discover immune-based prevention strategies. Our study combines novel resources and technologies to define the immune landscape in: 1) normal breast tissues in relation to BC risk factors, 2) BBD with respect to BC risk, and 3) invasive BC in relation to neoantigen expression and molecular subtype. We will perform NanoString GeoMxTM Digital Spatial Profiling (DSP) to quantitatively map expression of key immune proteins in healthy breast tissues donated to the Komen Tissue Bank (KTB) in relation to BC risk factors and in BBD biopsies from two cohorts to predict BC risk. We will re-analyze top prognostic markers in BBD biopsies using Vectra multiplex IF staining with machine learning algorithms to refine how immune cell content and organization impacts prognosis, and assess critical immune pathways related to BBD progression with the NanoString PanCancer IO 360 panel, which provides RNA expression of 770 immune genes (13 signatures). Finally, we will evaluate immune responses in BCs categorized for predicted neoantigen load and underlying mutation type with our novel bioinformatics pipeline that enables accurate prediction of MHC class I and class II missense, fusion and frameshift mutation neoantigens generated through faulty DNA repair, aberrant DNA and RNA splicing, insertions, and deletions. Our project demonstrates a novel approach to defining the immune processes in early stages of BC development which may improve BC risk prediction and prevention. We present a plan to comprehensively analyze immunity throughout BC development and define changes that accompany transitions from normal to BBD and BBD to BC. Citation Format: Doug Hinerfeld, Keith Knutson, Derek Radisky, E. Aubrey Thompson, Yan Asmann, Kim McCoy, Amy Degnim, Jodi Carter, Stacey Winham, Michele Cote, Jeroen van der Laak, Mark Sherman. Analysis of the immune microenvironment to advance breast cancer risk prediction and prevention [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 651.

Abstract Background: Mammographic breast density (MBD) is a strong breast cancer (BC) risk factor, but its biologic underpinnings are poorly understood. Use of estrogen plus progestin menopausal hormone therapy is linked to increased MBD and BC risk. Experimental data suggest that ratios of tumor promoting (5α-dihydroprogesterone [5αP]) and anti-tumorigenic (3α-dihydroprogesterone [3αP]) progesterone metabolite levels may be related to BC risk. However, relationships of endogenous progesterone and its metabolites with MBD and BC risk have not been established. Accordingly, we assessed levels of circulating progesterone and its metabolites with MBD. Methods: In this cross-sectional study, serum progesterone and its metabolites were quantified using a novel liquid chromatography-tandem mass spectrometry assay in 103 postmenopausal and 52 premenopausal (luteal menstrual cycle phase) women, ages 40-65, undergoing diagnostic image-guided ipsilateral breast biopsy. MBD was measured as percent fibroglandular volume (MBD-V) on pre-biopsy digital mammograms using single X-ray absorptiometry. Square-root transformed MBD-V was examined across tertile categories of progesterone/progesterone metabolites using age and body mass index (BMI)-adjusted linear regression models. Results: Concentrations of the hormones were as follows among postmenopausal women: progesterone [mean: 12.6 pmol/L (range: 5.2-45.8)], 3αP [5.6 pmol/L (1.4-18.8)], 5αP [100 pmol/L (16.7-388)], and 5αP/3αP ratio [26.1 (2.1-150)]; and among luteal phase premenopausal women: progesterone [2063 pmol/L (13.6-7098), 3αP [12.7 pmol/L (2.4-64.4)], 5αP [243 pmol/L (25.3-774)], 5αP/3αP ratio [25.9 (2.3-73.7)]. Among postmenopausal women, progesterone was positively associated with MBD-V (Tertile 3 vs. 1: β=0.68, p-trend=0.02). A similar borderline positive association was observed among premenopausal women (β=0.74, p-trend=0.10). Additional adjustment for circulating estradiol did not substantively alter observed associations. Levels of 3αP, 5αP and the 5αP/3αP ratio were not associated with MBD-V among pre- or postmenopausal women. Conclusions: Concentrations of progesterone and it metabolites show substantial inter-woman variation. We observed a positive association between endogenous progesterone and MBD-V among both postmenopausal and premenopausal luteal phase women. We did not observe an association with the ratio of 5αP to 3αP levels and MBD-V. These findings suggest the need for additional studies to understand the biological basis of the role of progesterone and its metabolites in MBD and BC risk. Citation Format: Manila Hada, Hannah Oh, Sharon Fan, Roni T. Falk, Berta Geller, Pamela Vacek, Donald Weaver, John Shepherd, Jeff Wang, Bo Fan, Amir P. Mahmoudzadeh, Serghei Malkov, Sally Herschorn, Louise A. Brinton, Xia Xu, Mark E. Sherman, Britton Trabert, Gretchen L. Gierach. Relationship of serum progesterone and progesterone metabolites with mammographic density [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 588.

Abstract Identifying risk factors for women at high risk of symptom-detected breast cancers that were missed by screening would enable targeting of alternative prevention strategies. To identify breast cancer risk factors by mode of detection, we examined these associations in heavily-screened women from the Cancer Prevention Study (CPS)-II Nutrition Cohort. Among 76,406 women followed for a median of 13.8 years, 2,469 screen-detected and 1,189 symptom-detected breast cancer cases were diagnosed. Multivariable-adjusted associations were estimated using joint Cox proportional hazards regression models with person-time calculated contingent on screening. The mean (standard deviation) age at baseline was 62.0 (6.6) years for non-cases, 61.6 (6.1) for screen-detected cases, and 61.5 (6.2) for symptom-detected cases. Women with symptom-detected tumors were diagnosed at a slightly younger age (mean=69.4) and less likely to be diagnosed with a localized tumor (65.3%), than women with a screen-detected tumor (mean age at diagnosis=70.4 and localized tumors=83.3%). Factors associated with higher risks of symptom detected vs. screen detected breast cancer, included: current combined menopausal hormone use (HR=2.04, 95% CI 1.70 - 2.46 vs. HR=1.43, 95% CI 1.25 - 1.63), current estrogen only menopausal hormone use (HR=1.41, 95% CI 1.15 - 1.72 vs. HR=0.94, 95% CI 0.82 - 1.09), and history of benign breast disease (HR=1.89, 95% CI 1.67 - 2.13 vs. HR=1.49, 95% CI 1.36 - 1.62). The opposite pattern of higher risk of screen detected vs. symptom detected breast cancer was observed for greater adult weight gain (HR=2.32, 95% CI 1.91 - 2.82 vs. HR=1.42, 95% CI 1.10 - 1.84) and alcohol intake (HR=1.39, 95% CI 1.24 - 1.64 vs. HR=1.20, 95% CI 0.92 - 1.58). Our results suggest that understanding risk factors for symptom-detected cancers may help identify women who would benefit from more intensive screening to facilitate early detection. Citation Format: Mia M. Gaudet, Emily Deubler, W. Ryan Diver, Samantha Puvanesarajah, Alpa V. Patel, Ted Gansler, Dana Flanders, Mark Sherman, Susan Gapstur. Breast cancer risk factors by mode of detection among screened women in the Cancer Prevention Study-II [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4211.

AbstractBackgroundRacial disparities in breast cancer (BC) outcomes persist where non-Hispanic black (NHB) women are more likely to die from BC than non-Hispanic white (NHW) women, and the extent of this disparity varies geographically. We evaluated tumor, treatment, and patient characteristics that contribute to racial differences in BC mortality in Atlanta, Georgia, where the disparity was previously characterized as especially large.MethodsWe identified 4943 NHW and 3580 NHB women in the Georgia Cancer Registry with stage I–IV BC diagnoses in Atlanta (2010–2014). We used Cox proportional hazard regression to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) comparing NHB vs NHW BC mortality by tumor, treatment, and patient characteristics on the additive and multiplicative scales. We additionally estimated the mediating effects of these characteristics on the association between race and BC mortality.ResultsAt diagnosis, NHB women were younger—with higher stage, node-positive, and triple-negative tumors relative to NHW women. In age-adjusted models, NHB women with luminal A disease had a 2.43 times higher rate of BC mortality compared to their NHW counterparts (95% CI = 1.99 to 2.97). High socioeconomic status (SES) NHB women had more than twice the mortality rates than their white counterparts (HR = 2.67, 95% CI = 1.65 to 4.33). Racial disparities among women without insurance, in the lowest SES index, or diagnosed with triple-negative BC were less pronounced.ConclusionsIn Atlanta, the largest racial disparities are observed in luminal tumors and most pronounced among women of high SES. More research is needed to understand drivers of disparities within these treatable features.

Abstract Purpose: Ovarian cancer is a heterogeneous disease that can be divided into multiple subtypes with variable etiology, pathogenesis, and prognosis. We analyzed DNA methylation profiling data to identify biologic subgroups of ovarian cancer and study their relationship with histologic subtypes, copy number variation, RNA expression data, and outcomes. Experimental Design: A total of 162 paraffin-embedded ovarian epithelial tumor tissues, including the five major epithelial ovarian tumor subtypes (high- and low-grade serous, endometrioid, mucinous, and clear cell) and tumors of low malignant potential were selected from two different sources: The Polish Ovarian Cancer study, and the Surveillance, Epidemiology, and End Results Residual Tissue Repository (SEER RTR). Analyses were restricted to Caucasian women. Methylation profiling was conducted using the Illumina 450K methylation array. For 45 tumors array copy number data were available. NanoString gene expression data for 39 genes were available for 61 high-grade serous carcinomas (HGSC). Results: Consensus nonnegative matrix factorization clustering of the 1,000 most variable CpG sites showed four major clusters among all epithelial ovarian cancers. We observed statistically significant differences in survival (log-rank test, P = 9.1 × 10−7) and genomic instability across these clusters. Within HGSC, clustering showed three subgroups with survival differences (log-rank test, P = 0.002). Comparing models with and without methylation subgroups in addition to previously identified gene expression subtypes suggested that the methylation subgroups added significant survival information (P = 0.007). Conclusions: DNA methylation profiling of ovarian cancer identified novel molecular subgroups that had significant survival difference and provided insights into the molecular underpinnings of ovarian cancer. See related commentary by Ishak et al., p. 5729

Abstract Molecular histology may be conceptualized as the microscopic and molecular characteristics of normal tissues that are required for physiologic function. Over the life course, the molecular histology of the breast changes in response to physiological alterations, imparting spatial and temporal heterogeneity within the breasts of individuals and among women. These transitions contribute to the enormous range and imprecisely defined limits of what pathologists consider normal. Appreciation that molecular histology may reflect the cumulative influence of prior exposures linked to breast cancer risk, and may provide information about risk of developing breast cancer in the future, has stimulated interest in this topic. Unlike the study of breast cancer or its precursors, which represents a focal pathophysiologic deviation from normal, molecular histology, if assessable, would represent the state of the entire at-risk organ, based upon examination of a small tissue sample. The adult breast is characterized by well-developed terminal duct lobular units (TDLUs), which comprise the functional unit of milk production and represent the source of nearly all breast cancer precursors. Physiological changes in human breasts are likely driven by paracrine mechanisms, suggesting that tissue context and cellular topography are critical elements in physiology and pathophysiology. The breast undergoes profound changes with completion of childbearing and aging. Age-related TDLU involution may be conceptualized as a protective mechanism that lowers breast cancer risk following completion of childbearing, and in this context, delayed or incomplete involution is a breast cancer risk factor. With aging, the percent of the breast comprised of fibroglandular tissue declines, which is associated with a reduction in mammographic density, a strong breast cancer risk factor. Mammographic density is also imperfectly correlated with epithelial content in the breast. Women with benign breast disease whose surrounding normal breast tissue does not undergo age-appropriate TDLU involution are at increased risk of developing breast cancer, and both breast density and TDLU involution are independent markers of breast cancer risk. However, an important challenge is to understand the markers and mechanisms that underlie breast involution with aging, including both the epithelial and non-epithelial components, and to learn why both density and TDLU content decline with aging as breast cancer incidence rises. The thesis of this presentation is that understanding the amount of epithelium at-risk, the insults it sustains and the mechanisms that lead to its elimination, persistence or expansion may provide a window into the development of integrative biomarkers of risk that can translate into improved screening and prevention. However, progress towards this goal is quite early. Citation Format: Mark E. Sherman. Life course epidemiology and breast cancer: translating risk into prevention. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr IA11.

Abstract Background: Insulin-like growth factor (IGF)-I and IGF binding protein (IGFBP)-3 play important roles in carcinogenesis, particularly for breast cancer. However, little is known about whether the IGF system influences histologic characteristics of normal glandular tissue and whether relationships vary by race. Lesser degrees of age-related terminal duct lobular unit (TDLU) involution, as reflected by higher numbers of TDLUs and acini per TDLU, have been associated with higher breast cancer risk. We examined the associations of IGF measures with TDLU involution of normal breast using standardized TDLU measures. Methods: Among 715 Caucasian and 283 African American (AA) women with normal breast tissue samples from the Komen Tissue Bank, serum concentrations of IGF-I and IGFBP-3 were quantified using enzyme-linked immunosorbent assay (ELISA). Hematoxilyn and eosin-stained tissue sections were assessed for numbers of TDLUs (“TDLU count”) and acini/TDLU. Zero-inflated Poisson regression models with a robust variance estimator were used to estimate associations of IGF-I, IGFBP-3, and IGF-I:IGFBP-3 molar ratio (tertiles) with TDLU count by race and menopausal status, adjusting for potential confounders. We also tested for interactions by race using likelihood ratio tests. Results: AA (vs. Caucasian) women had higher age-adjusted mean levels of serum IGF-I (137 vs. 131 ng/mL, p=0.07) and lower levels of IGFBP-3 (4165 vs. 4684 ng/mL, p<0.0001); the differences persisted after adjustment for additional covariates including BMI and parity/age at first birth. Postmenopausal IGFBP-3 was inversely associated with TDLU count among both AA (RR T3vs.T1=0.49, 95% CI=0.28-0.84, p-trend=0.04) and Caucasian (RR T3vs.T1=0.63, 95% CI=0.41-0.99, p-trend=0.04) women. In premenopausal women, higher IGF-I:IGFBP-3 ratios were associated with higher TDLU count in Caucasians (OR T3vs.T1=1.33, 95% CI=1.01-1.31, p-trend=0.04) but not in AA (OR T3vs.T1=0.65, 95% CI=0.42-1.00, p-trend=0.05) women. There was no statistically significant interaction by race (p-interaction≥0.10). Conclusions: Our data suggest the potential role of the IGF system, particularly IGFBP-3, in TDLU involution of the normal breast among both Caucasian and AA women. Citation Format: Hannah OH, Ruth M. Pfeiffer, Roni T. Falk, Hisani N. Horne, Jackie Xiang, Michael Pollak, Louise A. Brinton, Anna Maria V. Storniolo, Mark E. Sherman, Gretchen L. Gierach, Jonine D. Figueroa. Serum insulin-like growth factor (IGF)-I and IGF binding protein-3 in relation to terminal duct lobular unit involution in Caucasian and African American women: The Susan G. Komen Tissue Bank [abstract]. In: Proceedings of the Tenth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2017 Sep 25-28; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2018;27(7 Suppl):Abstract nr A36.