Sherman, Mark E.

Abstract Introduction: We used micro-computed tomography (microCT), a high-resolution imaging option, to detect and characterize microcalcifications (MCs) in three dimensions within pathology blocks of benign and malignant breast tissues. Methods: A set of 44 formalin-fixed, paraffin-embedded breast tissue blocks were assessed from n=22 women at two time points: benign breast biopsy and subsequent DCIS or DCIS with invasive disease breast cancer. Blocks were scanned using the Bruker Skyscan 1276 microCT at a resolution of 10 µm. SkyScan analysis CTAn software was utilized to prepare and analyze morphological parameters and multiple MCs contained within each block were averaged. Paired morphological parameters were compared between the benign and subsequent cancer samples within women using Wilcoxon signed-rank tests. Results: Median age of patients was 53 years (range 37-77 years) at initial benign biopsy and developed breast cancer at median of 5.6 years (range: 2.3-12.8 years) later. The initial benign biopsies were for proliferative disease without atypia in the majority (59%), while 23% had non-proliferative lesions and 18% atypical hyperplasia. The average structural model index was consistent with a near rod-like shape (median 2.99, range: 2.71-3.29). Paired comparisons between benign and cancer blocks showed that the average surface area of MCs was significantly higher in the cancer samples (p=0.0467), as was the average volume of MCs (p=0.0298) (Table 1). Conclusions: Preliminarily, we demonstrate that microCT of routinely prepared pathology blocks of breast tissues may be useful in characterizing the 3-D morphometry of MCs with suggestive differences in benign and cancer tissues. Given that MCs are a sentinel radiologic marker of DCIS but are common in benign breast disease, developing improved approaches for classifying MCs may have value in breast cancer screening and management. Table 1. Comparison of MC parameters in biopsy tissues (IQR = Interquartile Range). Benign sample from women who later developed breast cancer Breast cancer after prior benign sample Paired Differences (Cancer - Benign) Wilcoxon signed-rank p value (N=22) (N=22) (N=22) Number of Objects (Median (IQR)) 43.5 (14, 789) 69.5 (33, 289) -6 (-139, 67) 0.6830 Average Surface Area (mm2)(Median (IQR)) 0.0225 (0.0134, 0.0393) 0.0342 (0.0185, 0.0656) 0.0113 (-0.0027, 0.0322) 0.0467 Average Volume (mm3) (Median (IQR)) 0.0003 (0.0001, 0.0007) 0.0007 (0.0003, 0.0022) 0.0003 (0.000002, 0.0020) 0.0298 Average Surface Area/Volume (mm−1)(Median (IQR)) 214.92 (162.25, 328.39) 199.55 (151.89, 230.52) -20.85 (-86.05, 27.04) 0.1433 Average Structural Thickness (mm)(Median (IQR)) 0.0341(0.0196, 0.0446) 0.0395 (0.0336, 0.0505) 0.0074 (-0.0062, 0.0153) 0.1173 Average Structural Model Index (Median (IQR)) 2.9758 (2.8465, 3.1175) 3.0026 (2.9281, 3.0927) 0.0075 (-0.1073, 0.1381) 0.7656 Citation Format: Sarah E. Schrup, Thomas de Bel, Tanya Hoskin, Teresa Allers, Stacey Winham, Derek Radisky, Laura Pacheco-Spann, Lisa Seymour, Amy Degnim, Mark Sherman. High resolution microCT to analyze the 3D morphology of microcalcifications in benign breast disease and breast cancer biopsy tissues. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3587.

Abstract Reproductive events beginning with pregnancy and ending with remodeling of the breast after cessation of breastfeeding alter breast structure and function and produce dramatic changes in systemic biology. In aggregate, these processes lower overall risk for breast, tubo-ovarian and endometrial cancers, albeit differentially by molecular subtypes of these tumors. Herein, we explore opportunities for research on protective mechanisms operative during this period of the life course, with the goal of encouraging studies to advance cancer prevention. See related article by Getz et al., p. 353

Abstract It is estimated that up to 50% to 90% of postmenopausal women may experience genitourinary syndrome of menopause (GSM), which may have a detrimental impact on quality of life. One of the most effective modes of treatment of GSM is low-dose vaginal estrogens. Numerous studies have addressed the safety of these estrogens using endometrial biopsy and/or endometrial thickness on ultrasound. Based on these studies, the consensus is that low-dose vaginal estrogens do not substantially increase the risk of endometrial hyperplasia or cancer; however, the data are severely limited by short duration of follow-up. Although long-term trials are warranted, they are difficult to carry out, costly, and will not yield data for years. More immediate information regarding endometrial safety may be obtained from studies measuring endometrial tissue and serum concentrations of estradiol, estrone, and relevant equine estrogens after administration of different estrogen formulations and doses. This would allow us to understand better the metabolism of estrogens by the vagina and endometrium, and how much estrogen is reaching the endometrium. Here, we discuss metabolism, receptor binding, and signaling of estrogens in vaginal and endometrial tissue, and summarize the existing studies on the endometrial impact of low-dose vaginal estrogen treatment in postmenopausal women.

Abstract Introduction: Benign breast disease (BBD) is an important breast cancer (BC) risk factor, which may be classified as non-proliferative disease (NPD), proliferative disease without atypia (PDWA), or atypical hyperplasia (AH) for risk stratification. Data related to the frequency of specific types of BBD and their relationship to BC risk in the Hispanic American population are limited. To address this knowledge gap, we compared BBD and associated BC risk among Hispanic white (HW) and non-Hispanic white (NHW) in New Mexico (NM). Methodology: A retrospective IRB-approved study was performed of women 19 years or older residing in six counties in NM (Bernalillo, Sandoval, Sante Fe, Socorro, Torrance, Cibola/Valencia) between 1996 and mid-2007 to compare the frequency of BBD subtypes and BC risk among HW and NHW. We excluded women who had a history of BC prior to BBD diagnosis or who were diagnosed with BC within 6 months after BBD biopsy. Race and ethnicity were self-reported by women at the time of biopsy. BBD was categorized as NPD, PDWA, or AH based on medical records. Incident BC (in-situ or invasive) was ascertained via linkage to the NM Surveillance Epidemiology End Results (SEER) Registry and BC risk was assessed using standardized incidence ratios (SIRs), comparing the observed number of BC events to that expected based on the NM SEER six-county race- and ethnicity-specific incidence rates, accounting for age and calendar period. Results: Our analysis included 3,870 HW and 6,996 NHW women with BBD. The HW were younger (47.1 vs. 51 years) compared to NHW. HW women had slightly more NPD (69.4% vs. 66.6%) but less PDWA (26.2% vs. 29.4%) and similar frequency of AH (4.3% vs. 3.9%) as compared to NHW. Over a median post-BBD follow-up period of 13 years (range 6 months-17 years), 644 BCs were observed (4.81% in HW and 6.55% in NHW). The observed BC risk among women with BBD was higher than population-based expected rates (SIR 1.98, 95% CI 1.82-2.13, p<0.001) and showed expected increases in risk with increasing degrees of BBD abnormality: SIR=1.90 for NPD, 2.00 for PDWA, and 3.01 for AH. Comparing BC risk by ethnic subgroups, HW women had an overall risk of BC after BBD that was statistically indistinguishable from NHW women (SIR=2.17, 95% CI 1.86-2.48 in HW women, and SIR=1.91, 95% CI 1.73-2.08 in NHW women). Within the major subgroups of the BBD findings, there were no significant differences in risk of BC after BBD for HW versus NHW women. Conclusions: In this population-based study, benign breast disease subtypes and their associated breast cancer risk were similar among the Hispanic and non-Hispanic white women. Citation Format: Kush Raj Lohani, Andrea M. Nibbe, Robert A. Vierkant, Laura M. Pacheco-Spann, Lisa R. Seymour, Celine M. Vachon, Mark E. Sherman, Amy C. Degnim, Deirdre Hill. Comparison of benign breast disease subtypes and breast cancer risk among Hispanic and non-Hispanic white women in New Mexico. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4213.

Abstract Purpose: Young women’s breast cancers (YBCs), defined herein as breast cancer (BC) diagnosed at age ≤ 40 years, are etiologically and biologically distinct from postmenopausal BCs, demonstrating a higher proportion of estrogen receptor (ER) negative subtypes and a worse prognosis. Studies have not assessed whether risk factors such as recent parity and body mass index (BMI) are linked to protein expression profiles in YBCs. Accordingly, we examined protein expression assessed with GeoMx® Digital Spatial Profiling (DSP) in 640 YBCs prepared as tissue microarrays (TMAs) in the Young Women’s BC Study (YWBCS). Methods: The YWBCS is a multi-institutional cohort of 1,297 women with incident BC diagnosed at age <40 years identified through medical record review, with risk factor data collected via questionnaires. TMAs including 1,505 cores of 640 YBCs that were collected prior to therapy and were suitable for molecular analysis were evaluated for 72 markers with NanoString GeoMx DSP. Associations of log-transformed biomarker expression with BMI and time from last live birth to BC diagnosis were carried out using linear mixed modeling approaches, accounting for multiple tumor tissue cores per individual. Results: Mean age at BC was 35.5 years (range 17-40). Tumor subtypes based on clinical immunostaining were the following: luminal B 46%; luminal A 36%; triple negative 12% and HER2+ 6%. Of 72 biomarkers tested, 53 (74%) were evaluable after QC and normalization. GeoMx ER and PR protein levels were higher in luminal A and luminal B YBCs than in HER2+ and TNBC (p=2x10-94 and 2x10-52, respectively), supporting the accuracy of the GeoMx assay. Compared to nulliparas or those with most recent birth > 3 years before BC, those who gave birth ≤ 3 years prior to BC had tumors with higher expression of PR (8x10-6) and ER (p=0.006), and lower expression of BCL-2 (p=0.006). In contrast, women with last birth ≥ 6 years prior to BC had higher expression of CD8 (p=0.006) and PD-1 (p=0.001) than nulliparas and those with more recent births. Compared to women with BMI between 18.5 and 29.9, those with higher or lower BMIs had higher expression of CD34 (p=0.0003), CD4 (p=0.0009) and CD14 (p=0.001). BCL-2 expression was higher among women with BMI < 18.5 compared to those with higher values (p=0.005). Women with BMI of 30+ had higher β2-microglobulin levels than those with lower BMIs (p=0.003). Inverse dose-response associations (with higher BMI related to lower levels) were observed for expression of ER (p=0.01), pan cytokeratin (p=0.004) and four proteins in the p13K/AKT signaling pathway (p ≤ 0.01 for each). Conclusions: Preliminarily, we identify differences in hormonal and immune markers in YBCs in relation to timing of births and BMI, suggesting that these factors may contribute to etiologic heterogeneity. Multivariate modeling is ongoing to incorporate molecular subtype and other risk factors. Citation Format: Robert A. Vierkant, Laura M. Pacheco-Spann, Stacey J. Winham, Jennifer M. Kachergus, Ji Shi, Craig Snow, Fergus J. Couch, Janet E. Olson, Chen Wang, Derek C. Radisky, Amy C. Degnim, E. Aubrey Thompson, Laura C. Collins, Kathryn J. Ruddy, Ann H. Partridge, Mark E. Sherman. Associations of parity and body mass index with NanoString digital spatial protein profiling in early onset breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1000.

AbstractOur objective was to test whether p53 expression status is associated with survival for women diagnosed with the most common ovarian carcinoma histotypes (high‐grade serous carcinoma [HGSC], endometrioid carcinoma [EC], and clear cell carcinoma [CCC]) using a large multi‐institutional cohort from the Ovarian Tumor Tissue Analysis (OTTA) consortium. p53 expression was assessed on 6,678 cases represented on tissue microarrays from 25 participating OTTA study sites using a previously validated immunohistochemical (IHC) assay as a surrogate for the presence and functional effect of TP53 mutations. Three abnormal expression patterns (overexpression, complete absence, and cytoplasmic) and the normal (wild type) pattern were recorded. Survival analyses were performed by histotype. The frequency of abnormal p53 expression was 93.4% (4,630/4,957) in HGSC compared to 11.9% (116/973) in EC and 11.5% (86/748) in CCC. In HGSC, there were no differences in overall survival across the abnormal p53 expression patterns. However, in EC and CCC, abnormal p53 expression was associated with an increased risk of death for women diagnosed with EC in multivariate analysis compared to normal p53 as the reference (hazard ratio [HR] = 2.18, 95% confidence interval [CI] 1.36–3.47, p = 0.0011) and with CCC (HR = 1.57, 95% CI 1.11–2.22, p = 0.012). Abnormal p53 was also associated with shorter overall survival in The International Federation of Gynecology and Obstetrics stage I/II EC and CCC. Our study provides further evidence that functional groups of TP53 mutations assessed by abnormal surrogate p53 IHC patterns are not associated with survival in HGSC. In contrast, we validate that abnormal p53 IHC is a strong independent prognostic marker for EC and demonstrate for the first time an independent prognostic association of abnormal p53 IHC with overall survival in patients with CCC.

Abstract Background: Better understanding of prognostic factors in tubo-ovarian high-grade serous carcinoma (HGSC) is critical, as diagnosis confers an aggressive disease course. Variation in tumor DNA methylation shows promise predicting outcome, yet prior studies were largely platform-specific and unable to evaluate multiple molecular features. Methods: We analyzed genome-wide DNA methylation in 1,040 frozen HGSC, including 325 previously reported upon, seeking a multi-platform quantitative methylation signature that we evaluated in relation to clinical features, tumor characteristics, time to recurrence/death, extent of CD8+ tumor-infiltrating lymphocytes (TIL), gene expression molecular subtypes, and gene expression of the ATP-binding cassette transporter TAP1. Results: Methylation signature was associated with shorter time to recurrence, independent of clinical factors (N = 715 new set, hazard ratio (HR), 1.65; 95% confidence interval (CI), 1.10–2.46; P = 0.015; N = 325 published set HR, 2.87; 95% CI, 2.17–3.81; P = 2.2 × 10−13) and remained prognostic after adjustment for gene expression molecular subtype and TAP1 expression (N = 599; HR, 2.22; 95% CI, 1.66–2.95; P = 4.1 × 10−8). Methylation signature was inversely related to CD8+ TIL levels (P = 2.4 × 10−7) and TAP1 expression (P = 0.0011) and was associated with gene expression molecular subtype (P = 5.9 × 10−4) in covariate-adjusted analysis. Conclusions: Multi-center analysis identified a novel quantitative tumor methylation signature of HGSC applicable to numerous commercially available platforms indicative of shorter time to recurrence/death, adjusting for other factors. Along with immune cell composition analysis, these results suggest a role for DNA methylation in the immunosuppressive microenvironment. Impact: This work aids in identification of targetable epigenome processes and stratification of patients for whom tailored treatment may be most beneficial.

Abstract The discovery of molecular subtypes has corroborated the heterogeneity of breast cancers. But in clinical routine, treatment selection relies on measuring the aggressiveness of the tumor via histopathology, which is routinely based on grading, a prognostic yet laborious, poorly reproducible, and subjective procedure defined more than 30 years ago, before molecular subtypes existed. In this paper, we present an interpretable deep learning-based computer-aided diagnosis method to automate mitotic count, one of the components of grading; the method complies with current guidelines and automates hot-spot finding on full digital whole-slide images of routinely prepared pathologic slides stained with hematoxylin and eosin. We use the computer model to query the current “one-size-fits-all” mitotic count procedure by investigating subtype-specific prognostic value of mitotic count using an external independent large-scale multicentric dataset of 1,709 breast cancers. We show that for human epidermal growth factor-2 (HER2) positive tumors, mitotic count was not prognostic. In hormone-receptor positive/HER2 negative cancers, an average mitotic count density different from clinically used cut offs predicted worse recurrence free survival in multivariable analysis, adjusted for known clinical prognosticators. We provided some first experimental evidence that the prognostic role of mitotic count should be reviewed.

Abstract Nonsteroidal anti-inflammatory agents (NSAID) are associated with modest inconsistent reductions in breast cancer risk in population-based cohorts, whereas two focused studies of patients with benign breast disease (BBD) have found lower risk with NSAID use. Given that BBD includes fibroinflammatory lesions linked to elevated breast cancer risk, we assessed whether NSAID use was associated with lower breast cancer risk among patients with BBD. Participants were postmenopausal women in the Cancer Prevention Study-II (CPS-II), a prospective study of cancer incidence and mortality, who completed follow-up surveys in 1997 with follow-up through June 30, 2015. History of BBD, NSAID use, and covariate data were updated biennially. This analysis included 23,615 patients with BBD and 36,751 patients with non-BBD, including 3,896 incident breast cancers over an average of 12.72 years of follow-up among participants. NSAID use, overall and by formulation, recency, duration, and pills per month was analyzed versus breast cancer risk overall and by BBD status using multivariable-adjusted Cox models; BBD status and NSAID use were modeled as time-dependent exposures. Patients with BBD who reported using NSAIDs experienced lower breast cancer risk (HR, 0.87; 95% CI, 0.78–0.97), with similar effects for estrogen receptor (ER)-positive breast cancers [HR, 0.85; 95% confidence interval (CI), 0.74–0.97] and ER-negative breast cancers (HR, 0.87; 95% CI, 0.59–1.29); among women without BBD, NSAID use was unrelated to risk (HR, 1.02; 95% CI, 0.92–1.13; Pinteraction = 0.04). Associations stratified by age, obesity, menopausal hormone use, and cardiovascular disease were similar. Among patients with BBD, NSAID use appears linked to lower breast cancer risk. Further studies to assess the value of NSAID use among patients with BBD are warranted. Prevention Relevance: We examined whether NSAID use, a modifiable exposure, is associated with breast cancer risk in postmenopausal women from the Cancer Prevention Study-II with self-reported benign breast disease, an often inflammatory condition associated with higher rates of breast cancer.

Abstract A problematic feature of many human cancers is a lack of understanding of mechanisms controlling organ-specific patterns of metastasis, despite recent progress in identifying many mutations and transcriptional programs shown to confer this potential. To address this gap, we developed a methodology that enables different aspects of the metastatic process to be comprehensively characterized at a clonal resolution. Our approach exploits the application of a computational pipeline to analyze and visualize clonal data obtained from transplant experiments in which a cellular DNA barcoding strategy is used to distinguish the separate clonal contributions of two or more competing cell populations. To illustrate the power of this methodology, we demonstrate its ability to discriminate the metastatic behavior in immunodeficient mice of a well-established human metastatic cancer cell line and its co-transplanted LRRC15 knockdown derivative. We also show how the use of machine learning to quantify clone-initiating cell (CIC) numbers and their subsequent metastatic progeny generated in different sites can reveal previously unknown relationships between different cellular genotypes and their initial sites of implantation with their subsequent respective dissemination patterns. These findings underscore the potential of such combined genomic and computational methodologies to identify new clonally-relevant drivers of site-specific patterns of metastasis.