Digital histologic analysis reveals morphometric patterns of age-related involution in breast epithelium and stroma

Complete age-related regression of mammary epithelium, often termed post-menopausal involution, is associated with decreased breast cancer risk. However, most studies have qualitatively assessed involution. We quantitatively analyzed epithelium, stroma, and adipose tissue from histologically normal breast tissue of 454 patients in the Normal Breast Study (NBS). High-resolution digital images of normal breast Hematoxylin & Eosin stained slides were partitioned into epithelium, adipose tissue, and non-fatty stroma. Percentage area and nuclei per unit area (nuclear density) were calculated for each component. Quantitative data were evaluated in association with age using linear regression and cubic spline models Stromal area decreased (p=0.0002) and adipose tissue area increased (p<0.0001), with an approximate 0.7% change in area for each component, until age 55 when these area measures reached a steady state. While epithelial area did not show linear changes with age, epithelial nuclear density decreased linearly beginning in the third decade of life. No significant age-related trends were observed for stromal or adipose nuclear density. Digital image analysis offers a high-throughput method for quantitatively measuring tissue morphometry and for objectively assessing age-related changes in adipose tissue, stroma, and epithelium. Epithelial nuclear density is a quantitative measure of age-related breast involution that begins to decline in the early premenopausal period

Biology and etiology of young-onset breast cancers among premenopausal African American women: Results from the AMBER Consortium

Background: African American (AA) women have higher incidence of aggressive, young-onset (<40 years) breast cancers. Young- and older-onset disease may have distinct tumor biologies and etiologies; however, studies investigating age differences among AA women have been rare and generally underpowered. Methods: We examined tumor characteristics and breast cancer risk factors associated with premenopausal young (<40) vs. older (40) AA women's breast cancer in the African American Breast Cancer Epidemiology and Risk Consortium (2,008 cases and 5,144 controls). Unconditional logistic regression models assessed heterogeneity of tumor biology and risk factor associations by age, overall, and by estrogen receptor status. Results: Premenopausal AA women <40 years had higher frequency of poorer-prognosis tumor characteristics compared with older women, including negative estrogen and progesterone receptor status, triple-negative subtype, higher grade, higher stage, and larger tumors. Adiposity (i.e., waist-to-hip ratio) and family history of breast cancer were more strongly associated with young-onset disease [case–control OR ¼ 1.46, 95% confidence interval (CI) ¼ 1.04–2.05; OR ¼ 3.10, 95% CI ¼ 2.08–4.63, respectively] compared with older-onset disease (OR ¼ 1.11, 95% CI ¼ 0.91–1.35; OR ¼ 1.57, 95% CI ¼ 1.26–1.94). Breastfeeding showed a slight inverse risk association among young women (OR ¼ 0.70, 95% CI ¼ 0.43–1.16). Oral contraceptive use was associated with increased risk regardless of age. Considering various cutoff points for young age (<40, <45, <50), age-related heterogeneity was greatest when <40 was used. Conclusions: Among premenopausal AA women, diagnosis before age 40 is associated with more aggressive breast tumor biology and some etiologic differences. Impact: Modifiable risk factors including breastfeeding, adiposity, and oral contraceptive use may be important targets for mitigating harms of young-onset breast cancer

Distributed deep learning networks among institutions for medical imaging

Objective Deep learning has become a promising approach for automated support for clinical diagnosis. When medical data samples are limited, collaboration among multiple institutions is necessary to achieve high algorithm performance. However, sharing patient data often has limitations due to technical, legal, or ethical concerns. In this study, we propose methods of distributing deep learning models as an attractive alternative to sharing patient data. Methods We simulate the distribution of deep learning models across 4 institutions using various training heuristics and compare the results with a deep learning model trained on centrally hosted patient data. The training heuristics investigated include ensembling single institution models, single weight transfer, and cyclical weight transfer. We evaluated these approaches for image classification in 3 independent image collections (retinal fundus photos, mammography, and ImageNet). Results We find that cyclical weight transfer resulted in a performance that was comparable to that of centrally hosted patient data. We also found that there is an improvement in the performance of cyclical weight transfer heuristic with a high frequency of weight transfer. Conclusions We show that distributing deep learning models is an effective alternative to sharing patient data. This finding has implications for any collaborative deep learning study

FOXA1 and adaptive response determinants to HER2 targeted therapy in TBCRC 036

Inhibition of the HER2/ERBB2 receptor is a keystone to treating HER2-positive malignancies, particularly breast cancer, but a significant fraction of HER2-positive (HER2+) breast cancers recur or fail to respond. Anti-HER2 monoclonal antibodies, like trastuzumab or pertuzumab, and ATP active site inhibitors like lapatinib, commonly lack durability because of adaptive changes in the tumor leading to resistance. HER2+ cell line responses to inhibition with lapatinib were analyzed by RNAseq and ChIPseq to characterize transcriptional and epigenetic changes. Motif analysis of lapatinib-responsive genomic regions implicated the pioneer transcription factor FOXA1 as a mediator of adaptive responses. Lapatinib in combination with FOXA1 depletion led to dysregulation of enhancers, impaired adaptive upregulation of HER3, and decreased proliferation. HER2-directed therapy using clinically relevant drugs (trastuzumab with or without lapatinib or pertuzumab) in a 7-day clinical trial designed to examine early pharmacodynamic response to antibody-based anti-HER2 therapy showed reduced FOXA1 expression was coincident with decreased HER2 and HER3 levels, decreased proliferation gene signatures, and increased immune gene signatures. This highlights the importance of the immune response to anti-HER2 antibodies and suggests that inhibiting FOXA1-mediated adaptive responses in combination with HER2 targeting is a potential therapeutic strategy

FOXA1 and adaptive response determinants to HER2 targeted therapy in TBCRC 036

Inhibition of the HER2/ERBB2 receptor is a keystone to treating HER2-positive malignancies, particularly breast cancer, but a significant fraction of HER2-positive (HER2+) breast cancers recur or fail to respond. Anti-HER2 monoclonal antibodies, like trastuzumab or pertuzumab, and ATP active site inhibitors like lapatinib, commonly lack durability because of adaptive changes in the tumor leading to resistance. HER2+ cell line responses to inhibition with lapatinib were analyzed by RNAseq and ChIPseq to characterize transcriptional and epigenetic changes. Motif analysis of lapatinib-responsive genomic regions implicated the pioneer transcription factor FOXA1 as a mediator of adaptive responses. Lapatinib in combination with FOXA1 depletion led to dysregulation of enhancers, impaired adaptive upregulation of HER3, and decreased proliferation. HER2-directed therapy using clinically relevant drugs (trastuzumab with or without lapatinib or pertuzumab) in a 7-day clinical trial designed to examine early pharmacodynamic response to antibody-based anti-HER2 therapy showed reduced FOXA1 expression was coincident with decreased HER2 and HER3 levels, decreased proliferation gene signatures, and increased immune gene signatures. This highlights the importance of the immune response to anti-HER2 antibodies and suggests that inhibiting FOXA1-mediated adaptive responses in combination with HER2 targeting is a potential therapeutic strategy

Hyper-palatable foods in elementary school lunches: Availability and contributing factors in a national sample of US public schools.

BackgroundSchool cafeterias are a major point of influence for child nutrition. United States federal legislation requires the presence of important nutrients in school meals. However, legislation overlooks the potential presence of hyper-palatable foods in school lunches, a hypothesized factor that may influence children's eating behavior and obesity risk. The study sought to 1) quantify the prevalence of hyper-palatable foods (HPF) served in US elementary school lunches; and 2) determine whether food hyper-palatability varied based on school geographic region (East/Central/West), urbanicity (urban/micropolitan/rural), or meal item (entrée/side/fruit or vegetable).MethodsLunch menu data (N = 18 menus; N = 1160 total foods) were collected from a sample of six states that represented geographic regions of the United States (Eastern/Central/Western; Northern/Southern) and that had variability in urbanicity (urban, micropolitan, and rural) within each state. A standardized definition from Fazzino et al (2019) was used to identify HPF in lunch menus.ResultsHPF comprised almost half of foods in school lunches (M = 47%; SD = 5%). Compared to fruit/vegetable items, entrées were >23 times more likely to be hyper-palatable and side dishes were >13 times more likely to be hyper-palatable (p values .05). The majority of entrée and side items contained meat/meat alternatives and/or grains and likely aligned with the US federal reimbursable meal components of meat/meat alternatives and/or grains.Conclusions and implicationsHPF comprised almost half of foods offered in elementary school lunches. Entrées and side items were most likely to be hyper-palatable. US school lunches may be a key point of regular exposure to HPF among young children, a risk factor that may elevate child obesity risk. Public policy regulating HPF in school meals may be needed to protect children's health

Interactive multidisciplinary pilot workshop to improve medical student perception of and interest in breast surgical oncology

Background: Exposure to breast surgical oncology (BSO) and the multidisciplinary management of patients with breast cancer is limited in medical school. The purpose of this study was to assess changes in student perceptions of BSO as a career following an interactive multidisciplinary workshop. Methods: Pre-clinical medical students participated in a multidisciplinary, hands-on workshop, composed of breast radiology (BR), breast surgical oncology (BSO) and breast plastic reconstructive surgery (B-PRS). BR presented students screening and diagnostic breast imaging followed by hands-on ultrasound-guided biopsy on phantom simulators. BSO demonstrated lumpectomy, mastectomy, sentinel lymph node biopsy, and axillary lymph node dissections while B-PRS demonstrated oncoplastic techniques and autologous flap reconstruction with cadavers. Pre-and post-workshop surveys assessed student opinions on surgery and BSO. Results were compared using Wilcoxon Signed Rank, Wilcoxon Rank Sum, and Fisher's Exact. Results: The workshop was attended by twenty-four students. There was a statistically significant increase in interest in BSO from 52% to 86% after the workshop (p = 0.003). The event improved understanding of the work and lifestyle in BSO for 79% (19/24). All students (100%) expressed interest to further explore BSO. The most common attractors to a career in BSO were impacts on patients’ lives (N = 23), intellectual stimulation (N = 22), and earnings (N = 20). The most reported deterrents were lack of personal time (N = 18) and stress (N = 15). Conclusion: An interactive, anatomically based exposure to multidisciplinary breast cancer surgery improves medical student perception and interest in BSO. Medical schools should consider incorporating similar events to foster interest in BSO and other surgical subspecialties

Biology and Etiology of Young-Onset Breast Cancers among Premenopausal African American Women: Results from the AMBER Consortium

AbstractBackground: African American (AA) women have higher incidence of aggressive, young-onset (&amp;lt;40 years) breast cancers. Young- and older-onset disease may have distinct tumor biologies and etiologies; however, studies investigating age differences among AA women have been rare and generally underpowered.Methods: We examined tumor characteristics and breast cancer risk factors associated with premenopausal young (&amp;lt;40) vs. older (≥40) AA women's breast cancer in the African American Breast Cancer Epidemiology and Risk Consortium (2,008 cases and 5,144 controls). Unconditional logistic regression models assessed heterogeneity of tumor biology and risk factor associations by age, overall, and by estrogen receptor status.Results: Premenopausal AA women &amp;lt;40 years had higher frequency of poorer-prognosis tumor characteristics compared with older women, including negative estrogen and progesterone receptor status, triple-negative subtype, higher grade, higher stage, and larger tumors. Adiposity (i.e., waist-to-hip ratio) and family history of breast cancer were more strongly associated with young-onset disease [case–control OR = 1.46, 95% confidence interval (CI) = 1.04–2.05; OR = 3.10, 95% CI = 2.08–4.63, respectively] compared with older-onset disease (OR = 1.11, 95% CI = 0.91–1.35; OR = 1.57, 95% CI = 1.26–1.94). Breastfeeding showed a slight inverse risk association among young women (OR = 0.70, 95% CI = 0.43–1.16). Oral contraceptive use was associated with increased risk regardless of age. Considering various cutoff points for young age (&amp;lt;40, &amp;lt;45, &amp;lt;50), age-related heterogeneity was greatest when &amp;lt;40 was used.Conclusions: Among premenopausal AA women, diagnosis before age 40 is associated with more aggressive breast tumor biology and some etiologic differences.Impact: Modifiable risk factors including breastfeeding, adiposity, and oral contraceptive use may be important targets for mitigating harms of young-onset breast cancer. Cancer Epidemiol Biomarkers Prev; 26(12); 1722–9. ©2017 AACR.</jats:p