26 research outputs found

    396 Unraveling the Immunological Basis of Lobular Involution in Breast Cancer Development

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    OBJECTIVES/GOALS: Reveal common immune mechanisms in dysregulated age-related lobular involution (ARLI) and post-partum lobular involution (PPLI) to understand their link to increased breast cancer risk, challenging the traditional view of their distinctiveness. Ultimately, to improve breast cancer risk assessment and personalized prevention METHODS/STUDY POPULATION: The Mayo Clinic Benign Breast Disease (BBD) cohort comprises of ~20,000 women with benign biopsies, including ~1000 women with sequential benign biopsies. Lobular involution (LI) status was assessed by selecting perimenopausal women, ages 45-55, with sequential biopsies, comparing acini number and lobule size between initial and subsequent biopsies. NanoString IO360/ BC360 RNA profiling identified differentially expressed genes associated with dysregulated LI. Using multiplex immunofluorescence (mIF), I'll analyze and spatially map immune biomarkers related to dysregulated ARLI and PPLI in BBD tissue from perimenopausal women who did or did not go on to develop breast cancer, assessing the commonality of ARLI and PPLI markers and exploring their potential as risk biomarkers for breast cancer. RESULTS/ANTICIPATED RESULTS: Preliminary findings link patients who display dysregulated ARLI with an increased breast cancer risk and identify vital PPLI biomarkers in perimenopausal women. I expect the biopsies of women who developed post-menopausal breast cancer (PMBC) and post-partum breast cancer (PPBC) to exhibit elevated levels of dysregulated ARLI immune biomarkers and PPLI biomarkers. Spatially mapping these markers promises to provide a more comprehensive understanding of their interactions, potentially revealing common immunological pathways. These findings could transform our current paradigm of ARLI and PPLI as distinct processes and demonstrate their interconnection in shaping breast cancer risk. DISCUSSION/SIGNIFICANCE: PMBC and PPBC dominate majority of breast cancer cases. Both involve activation of the understudied process of lobular involution, which has been shown to have pro-tumorigenic traits. Elucidating these mechanisms will aid more efficient risk stratification and personalized prevention to reduce incidence and mortality of breast cancer

    Activation of PI3K/Akt/mTOR signaling in the tumor stroma drives endocrine therapy-dependent breast tumor regression

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    Improved efficacy of neoadjuvant endocrine-targeting therapies in luminal breast carcinomas could be achieved with optimal use of pathway targeting agents. In a mouse model of ductal breast carcinoma we identify a tumor regressive stromal reaction that is induced by neoadjuvant endocrine therapy. This reparative reaction is characterized by tumor neovascularization accompanied by infiltration of immune cells and carcinoma-associated fibroblasts that stain for phosphorylated ribosomal protein S6 (pS6), downstream the PI3K/Akt/mTOR pathway. While tumor variants with higher PI3K/Akt/mTOR activity respond well to a combination of endocrine and PI3K/Akt/mTOR inhibitors, tumor variants with lower PI3K/Akt/mTOR activity respond more poorly to the combination therapy than to the endocrine therapy alone, associated with inhibition of stromal pS6 and the reparative reaction. In human breast cancer xenografts we confirm that such differential sensitivity to therapy is primarily determined by the level of PI3K/Akt/mTOR in tumor cells. We further show that the clinical response of breast cancer patients undergoing neoadjuvant endocrine therapy is associated with the reparative stromal reaction. We conclude that tumor level and localization of pS6 are associated with therapeutic response in breast cancer and represent biomarkers to distinguish which tumors will benefit from the incorporation of PI3K/Akt/mTOR inhibitors with neoadjuvant endocrine therapy.Fil: Polo, Maria Laura. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Instituto de BiologĂ­a y Medicina Experimental (i); ArgentinaFil: Riggio, Marina. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Instituto de BiologĂ­a y Medicina Experimental (i); ArgentinaFil: May, Maria. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Instituto de BiologĂ­a y Medicina Experimental (i); ArgentinaFil: Rodriguez, Maria Jimena. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Instituto de BiologĂ­a y Medicina Experimental (i); ArgentinaFil: Perrone, Maria Cecilia. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Instituto de BiologĂ­a y Medicina Experimental (i); ArgentinaFil: Stallings Mann, Melody. Mayo Clinic Comprehensive Cancer Center; Estados UnidosFil: Kaen, Diego. Centro OncolĂłgico Riojano Integral; ArgentinaFil: Frost, Marlene. Mayo Clinic. Department of Medical Oncology; Estados UnidosFil: Goetz, Mattheu. Mayo Clinic. Department of Medical Oncology; Estados UnidosFil: Boughey, Judy. Mayo Clinic. Department of Surgery; Estados UnidosFil: Lanari, Claudia Lee Malvina. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Instituto de BiologĂ­a y Medicina Experimental (i); ArgentinaFil: Radisky, Derek. Mayo Clinic Comprehensive Cancer Center; Estados UnidosFil: Novaro, Virginia. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Instituto de BiologĂ­a y Medicina Experimental (i); Argentin

    Cytotoxic T cell depletion with increasing epithelial abnormality in women with benign breast disease.

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    PURPOSE: We quantified cytotoxic T cells in nonmalignant breast tissues from women with and without subsequent breast cancer to assess evidence of whether immunosurveillance may be suppressed prior to tumor development. METHODS: We used an age-matched set of breast tissues from women with benign breast disease (BBD) who subsequently developed breast cancer (BBD with later BC), women with BBD who remained cancer free (BBD cancer-free), and normal Komen Tissue Bank (KTB) tissue donors (KTB controls). We evaluated terminal duct lobular units (lobules) for degree of epithelial abnormality and density of dual-positive CD8/CD103 T cells, as CD103+ cells are thought to be a subset of CD8+ cytotoxic T cells located primarily in the intraepithelial compartment. RESULTS: In 10 sets of age-matched women, 256 breast lobules were studied: 85 in BBD women with later BC, 85 in BBD cancer-free women, and 86 in KTB donors. The majority of all lobules were histologically normal (N = 143, 56%), with 65 (25%) nonproliferative fibrocystic change, and 48 (19%) proliferative epithelial change (with or without atypia). In BBD women with later BC, median CD8+/CD103+ cell density was 39.6, 31.7, and 10.5 cells/mm CONCLUSION: In women with BBD, breast lobules with increasing epithelial abnormality show significant decreases in cytotoxic T cells as measured by CD8/CD103 staining, suggesting that impaired immunosurveillance may be a component of the earliest stages of breast cancer development

    Automated quantification of levels of breast terminal duct lobular (TDLU) involution using deep learning

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    Convolutional neural networks (CNNs) offer the potential to generate comprehensive quantitative analysis of histologic features. Diagnostic reporting of benign breast disease (BBD) biopsies is usually limited to subjective assessment of the most severe lesion in a sample, while ignoring the vast majority of tissue features, including involution of background terminal duct lobular units (TDLUs), the structures from which breast cancers arise. Studies indicate that increased levels of age-related TDLU involution in BBD biopsies predict lower breast cancer risk, and therefore its assessment may have potential value in risk assessment and management. However, assessment of TDLU involution is time-consuming and difficult to standardize and quantitate. Accordingly, we developed a CNN to enable automated quantitative measurement of TDLU involution and tested its performance in 174 specimens selected from the pathology archives at Mayo Clinic, Rochester, MN. The CNN was trained and tested on a subset of 33 biopsies, delineating important tissue types. Nine quantitative features were extracted from delineated TDLU regions. Our CNN reached an overall dice-score of 0.871 (+/- 0.049) for tissue classes versus reference standard annotation. Consensus of four reviewers scoring 705 images for TDLU involution demonstrated substantial agreement with the CNN method (unweighted kappa = 0.747 +/- 0.01). Quantitative involution measures showed anticipated associations with BBD histology, breast cancer risk, breast density, menopausal status, and breast cancer risk prediction scores (p < 0.05). Our work demonstrates the potential to improve risk prediction for women with BBD biopsies by applying CNN approaches to generate automated quantitative evaluation of TDLU involution
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