Circadian Alterations Increase with Progression in a Patient-Derived Cell Culture Model of Breast Cancer

Circadian rhythm disruption can elicit the development of various diseases, including breast cancer. While studies have used cell lines to study correlations between altered circadian rhythms and cancer, these models have different genetic backgrounds and do not mirror the changes that occur with disease development. Isogenic cell models can recapitulate changes across cancer progression. Hence, in this study, a patient-derived breast cancer model, the 21T series, was used to evaluate changes to circadian oscillations of core clock protein transcription as cells progress from normal to malignant states. Three cell lines were used: H16N2 (normal breast epithelium), 21PT (atypical ductal hyperplasia), and 21MT-1 (invasive metastatic carcinoma). The cancerous cells are both HER2+. We assessed the transcriptional profiles of two core clock proteins, BMAL1 and PER2, which represent a positive and negative component of the molecular oscillator. In the normal H16N2 cells, both genes possessed rhythmic mRNA oscillations with close to standard periods and phases. However, in the cancerous cells, consistent changes were observed: both genes had periods that deviated farther from normal and did not have an anti-phase relationship. In the future, mechanistic studies should be undertaken to determine the oncogenic changes responsible for the circadian alterations found.

Co-expression of transcription factor AP-2beta (TFAP2B) and GATA3 in human mammary epithelial cells with intense, apicobasal immunoreactivity for CK8/18

AP-2β is a new mammary epithelial differentiation marker and its expression is preferentially retained and enhanced in lobular carcinoma in situ and invasive lobular breast cancer. In normal breast epithelium AP-2β is expressed in a scattered subpopulation of luminal cells. So far, these cells have not been further characterized. Co-expression of AP-2β protein and luminal epithelium markers (GATA3, CK8/18), hormone receptors [estrogen receptor (ER), androgen receptor (AR)] and candidate stem cells markers (CK5/14, CD44) were assessed by double-immunofluorescence staining in normal mammary gland epithelium. The subpopulation of AP-2β-positive mammary epithelial cells showed an almost complete, superimposable co-expression with GATA3 and a peculiar intense, ring-like appearing immunoreactivity for CK8/18. Confocal immunofluorescence microscopy revealed an apicobasal staining for CK8/18 in AP-2β-positive cells, which was not seen in in AP-2β-negative cells. Furthermore, AP-2β-positive displayed a partial co-expression with ER and AR, but lacked expression of candidate stem cell markers CK5/14 and CD44. In summary, AP-2β is a new luminal mammary epithelial differentiation marker, which is expressed in the GATA3-positive subpopulation of luminal epithelial cells. These AP-2β-positive/GATA3-positive cells also show a peculiar CK8/18-expression which may indicate a previously unknown functionally specialized mammary epithelial cell population.

Deep Learning Enables Individual Xenograft Cell Classification in Histological Images by Analysis of Contextual Features

Patient-Derived Xenografts (PDXs) are the preclinical models which best recapitulate inter- and intra-patient complexity of human breast malignancies, and are also emerging as useful tools to study the normal breast epithelium. However, data analysis generated with such models is often confounded by the presence of host cells and can give rise to data misinterpretation. For instance, it is important to discriminate between xenografted and host cells in histological sections prior to performing immunostainings. We developed Single Cell Classifier (SCC), a data-driven deep learning-based computational tool that provides an innovative approach for automated cell species discrimination based on a multi-step process entailing nuclei segmentation and single cell classification. We show that human and murine cell contextual features, more than cell-intrinsic ones, can be exploited to discriminate between cell species in both normal and malignant tissues, yielding up to 96% classification accuracy. SCC will facilitate the interpretation of H&E- and DAPI-stained histological sections of xenografted human-in-mouse tissues and it is open to new in-house built models for further applications. SCC is released as an open-source plugin in ImageJ/Fiji available at the following link: https://github.com/Biomedical-Imaging-Group/SingleCellClassifier.

COX-2 Expression in Carcinoma of the Breast and Surrounding Non-neoplastic Breast Tissue

Background: Breast carcinoma is the most common malignant tumor and leading cause of cancer related death in women worldwide. Apart from traditional markers, estrogen receptor, progesterone receptor and Her-2neu, which are important for prognostication and staging purposes, a novel marker cyclooxygenase-2 (COX-2) is being studied extensively. We intend to study the spectrum of COX-2 expression in normal breast tissue, ductal carcinoma in situ (DCIS) adjacent to invasive cancer, and in invasive cancer and compare COX-2 expression with histological prognostic parameters and hormone receptor status.Methods: The present study is a prospective study that was conducted in the department of Pathology, SGT Medical College and Hospital, Gurugram (2019-2020). Fifty patients, aged between 21 and 70, suffering from primary breast cancer constituted the study group. Various histological prognostic parameters were assessed. Immunohistochemical profile of the tumor was assessed. COX-2 score was correlated with various clinicopathologic parameters.Results: Among the total of 50 patients suffering from invasive breast carcinoma, 94 percent (47/50) of cases showed the same COX-2 expression level in normal breast epithelium and corresponding tumor areas and this correlation was statistically significant. The correlation between the level of COX-2 expression in tumor and DCIS was highly significant.Conclusion: Inhibition of COX-2 may represent a potential target for preventing breast cancer oncogenesis and as an adjuvant treatment following surgery to reduce local recurrence.

Circadian Alterations Increase with Progression in a Patient-Derived Cell Culture Model of Breast Cancer

Circadian rhythms are critical regulators of many physiological and behavioral functions; disruption of this time-tracking system can elicit the development of various diseases, including breast cancer. While multiple studies have used cell lines to study the correlation between altered circadian rhythms and cancer, these cells generally have different genetic backgrounds and do not mirror the changes that occur with disease development. Isogenic cell models can represent and recapitulate changes across cancer progression. Hence in the present study, a patient-derived breast cancer model, the 21T series, was used to evaluate changes to circadian oscillations of core clock protein transcription and translation as cells progress from normal to malignant states. Three cell lines from the series were used: H16N2, from normal breast epithelium; 21PT, from Atypical Ductal Hyperplasia; and 21MT, from Invasive Metastatic Carcinoma. Both of the cancerous cell lines are HER2 positive. We assessed the transcriptional profiles of two core circadian clock proteins, BMAL1 and PER2, which represent a positive and negative component of the molecular oscillator. In the normal H16N2 cells, BMAL1 and PER2 both possessed rhythmic mRNA oscillations with close to standard periods and the expected anti-phase relationship. However, in the cancerous cells, consistent changes were observed: both clock genes had periods that deviated farther from normal and did not have an anti-phase relationship. To provide a more complete understanding of circadian alterations in breast cancer, luciferase reporters and real-time luminometry should be used in future studies.

DNA Methylation and Breast Cancer Risk: An Epigenome-Wide Study of Normal Breast Tissue and Blood

Differential DNA methylation is a potential marker of breast cancer risk. Few studies have investigated DNA methylation changes in normal breast tissue and were largely confounded by cancer field effects. To detect methylation changes in normal breast epithelium that are causally associated with breast cancer occurrence, we used a nested case–control study design based on a prospective cohort of patients diagnosed with a primary invasive hormone receptor-positive breast cancer. Twenty patients diagnosed with a contralateral breast cancer (CBC) were matched (1:1) with 20 patients who did not develop a CBC on relevant risk factors. Differentially methylated Cytosine-phosphate-Guanines (CpGs) and regions in normal breast epithelium were identified using an epigenome-wide DNA methylation assay and robust linear regressions. Analyses were replicated in two independent sets of normal breast tissue and blood. We identified 7315 CpGs (FDR < 0.05), 52 passing strict Bonferroni correction (p < 1.22 × 10−7) and 43 mapping to known genes involved in metabolic diseases with significant enrichment (p < 0.01) of pathways involving fatty acids metabolic processes. Four differentially methylated genes were detected in both site-specific and regions analyses (LHX2, TFAP2B, JAKMIP1, SEPT9), and three genes overlapped all three datasets (POM121L2, KCNQ1, CLEC4C). Once validated, the seven differentially methylated genes distinguishing women who developed and who did not develop a sporadic breast cancer could be used to enhance breast cancer risk-stratification, and allow implementation of targeted screening and preventive strategies that would ultimately improve breast cancer prognosis.

90 YEARS OF PROGESTERONE: Progesterone receptor signaling in the normal breast and its implications for cancer

Progesterone is considered as the pregnancy hormone and acts on many different target tissues. Progesterone receptor (PR) signaling is important for normal development and the physiologic function of the breast and impinges on breast carcinogenesis. Both systemically and locally, in the breast epithelium, there are multiple layers of complexity to progesterone action, many of which have been revealed through experiments in mice. The hormone acts via its receptor expressed in a subset of cells, the sensor cells, in the breast epithelium with different signaling outcomes in individual cells eliciting distinct cell-intrinsic and paracrine signaling involving different mediators for different intercellular interactions. PR expression itself is developmentally regulated and the biological outcome of PR signaling depends on the developmental stage of the mammary gland and the endocrine context. During both puberty and adulthood PR activates stem and progenitor cells through Wnt4-driven activation of the myoepithelium with downstream Adamts18-induced changes in extracellualr matrix (ECM) / basal membrane (BM). During estrous cycling and pregnancy, the hormone drives a major cell expansion through Rankl. At all stages, PR signaling is closely tied to estrogen receptor α (ER) signaling. As the PR itself is a target gene of ER, the complex interactions are experimentally difficult to dissect and still poorly understood. Ex vivo models of the human breast and studies on biopsy samples show that major signaling axes are conserved across species. New intraductal xenograft models hold promise to provide a better understanding of PR signaling in the normal breast epithelium and in breast cancer development in the near future.

Synthesis of the first 2-hydroxyanthraquinone substituted cyclotriphosphazenes and their cytotoxic properties

New 2-hydroxyanthraquinone based cyclotriphosphazenes were prepared and their cytotoxic effects were investigated in MCF-7 (breast cancer), MCF-12A (normal breast epithelium), DLD-1 (colon cancer), and CD-18Co (normal colon epithelium) cell lines.