Transforming growth factor-β and breast cancer: Mammary gland development

Transforming growth factor (TGF)-β(1) is a pluripotent cytokine that profoundly inhibits epithelial proliferation, induces apoptosis, and influences morphogenesis by mediating extracellular matrix deposition and remodeling. The physiologic roles of the action of TGF-β in mammary gland, indeed in most tissues, are poorly understood. In order to understand the actions of TGF-β, we need to take into account the complexity of its effects on different cell types and the influence of context on cellular responses. This task is further compounded by multiple mechanisms for regulating TGF-β transcription, translation, and activity. One of the most significant factors that obscures the action of TGF-β is that it is secreted as a stable latent complex, which consists of the 24-kDa cytokine and the 80-kDa dimer of its prepro region, called latency-associated peptide. Latency imposes a critical restraint on TGF-β activity that is often overlooked.The extracellular process known as activation, in which TGF-β is released from the latent complex, is emphasized in the present discussion of the role of TGF-β in mammary gland development. Definition of the spatial and temporal patterns of latent TGF-β activation in situ is essential for understanding the specific roles that TGF-β plays during mammary gland development, proliferation, and morphogenesis

Dual inhibition of TGF-β and PD-L1: a novel approach to cancer treatment

Immune checkpoint inhibitor; Tumor microenvironmentInhibidor del punto de control inmunitario; Microambiente tumoralInhibidor del punt de control immunitari; Microambient tumoralTransforming growth factor-β (TGF-β) and programmed death ligand 1 (PD-L1) initiate signaling pathways with complementary, nonredundant immunosuppressive functions in the tumor microenvironment (TME). In the TME, dysregulated TGF-β signaling suppresses antitumor immunity and promotes cancer fibrosis, epithelial-to-mesenchymal transition, and angiogenesis. Meanwhile, PD-L1 expression inactivates cytotoxic T cells and restricts immunosurveillance in the TME. Anti-PD-L1 therapies have been approved for the treatment of various cancers, but TGF-β signaling in the TME is associated with resistance to these therapies. In this review, we discuss the importance of the TGF-β and PD-L1 pathways in cancer, as well as clinical strategies using combination therapies that block these pathways separately or approaches with dual-targeting agents (bispecific and bifunctional immunotherapies) that may block them simultaneously. Currently, the furthest developed dual-targeting agent is bintrafusp alfa. This drug is a first-in-class bifunctional fusion protein that consists of the extracellular domain of the TGF-βRII receptor (a TGF-β ‘trap’) fused to a human immunoglobulin G1 (IgG1) monoclonal antibody blocking PD-L1. Given the immunosuppressive effects of the TGF-β and PD-L1 pathways within the TME, colocalized and simultaneous inhibition of these pathways may potentially improve clinical activity and reduce toxicity.This manuscript was funded by the healthcare business of Merck KGaA, Darmstadt, Germany (CrossRef Funder ID: 10.13039/100009945), and was previously part of an alliance between the healthcare business of Merck KGaA, Darmstadt, Germany, and GlaxoSmithKline. Medical writing support was provided by Spencer Hughes of ClinicalThinking, Inc., which was also funded by the healthcare business of Merck KGaA, Darmstadt, Germany, and GlaxoSmithKline in accordance with Good Publication Practice guidelines (http://www.ismpp.org/gpp3). This manuscript was funded in part by the Intramural Research Program of the Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA, and by a Cooperative Research and Development Agreement between the National Cancer Institute and EMD Serono, Billerica, MA, USA (CrossRef Funder ID:10.13039/100004755)

Persistent Phenotypic Responses of Human Mammary Epithelial Cells Induced by Ionizing Radiation

Ionizing radiation (IR) is a known human breast carcinogen. Although the mutagenic capacity of IR is widely acknowledged as the basis for its action as a carcinogen, we and others have shown that IR can also induce growth factors and extracellular matrix remodeling. We have shown that irradiating human mammary epithelial cells (HMEC) cultured with that transforming growth factor β1 (TGFβ) can generate a persistent phenotype in daughter cells characterized by spindle cell morphology, increased mesenchymal markers, decreased epithelial markers and increased cellular motility and invasion, which are hallmarks of epithelial to mesenchymal transition (EMT). Neither radiation nor TGFβ alone elicited EMT, although IR increased chronic TGFβ signaling and activity. Gene expression profiling revealed that double-treated cells exhibit a specific 10-gene signature associated with Erk/MAPK signaling. We hypothesized that IR-induced MAPK activation primes nonmalignant HMEC to undergo TGFβ-mediated EMT. Consistent with this, Erk phosphorylation was transiently induced by irradiation and persisted in irradiated cells treated with TGFβ, and inhibition of Erk activation, blocked the EMT phenotype. Preliminary studies suggest that eqi-toxic doses of sparsely and densely ionizing radiation resulted in comparable EMT when cells were cultivated in the presence of TGFβ, Furthermore radiation dose response studies show that this effect has a very low threshold in that a single exposure of 3-200 cGy radiation elicits the ‘same’ phenotypic switch, which is consistent with non-targeted effects. Together, these data show that the interactions between radiation-induced signaling pathways elicit heritable phenotypes that could contribute to radiation carcinogenesis

Multidimensional profiling of cell surface proteins and nuclear markers

Cell membrane proteins play an important role in tissue architecture and cell-cell communication. We hypothesize that segmentation and multidimensional characterization of the distribution of cell membrane proteins, on a cell-by-cell basis, enable improved classification of treatment groups and identify important characteristics that can otherwise be hidden. We have developed a series of computational steps to (i) delineate cell membrane protein signals and associate them with a specific nucleus; (ii) compute a coupled representation of the multiplexed DNA content with membrane proteins; (iii) rank computed features associated with such a multidimensional representation; (iv) visualize selected features for comparative evaluation through heatmaps; and (v) discriminate between treatment groups in an optimal fashion. The novelty of our method is in the segmentation of the membrane signal and the multidimensional representation of phenotypic signature on a cell-by-cell basis. To test the utility of this method, the proposed computational steps were applied to images of cells that have been irradiated with different radiation qualities in the presence and absence of other small molecules. These samples are labeled for their DNA content and E-cadherin membrane proteins. We demonstrate that multidimensional representations of cell-by-cell phenotypes improve predictive and visualization capabilities among different treatment groups, and identify hidden variables

Image-Based Modeling Reveals Dynamic Redistribution of DNA Damage into Nuclear Sub-Domains

Several proteins involved in the response to DNA double strand breaks (DSB) form microscopically visible nuclear domains, or foci, after exposure to ionizing radiation. Radiation-induced foci (RIF) are believed to be located where DNA damage occurs. To test this assumption, we analyzed the spatial distribution of 53BP1, phosphorylated ATM, and γH2AX RIF in cells irradiated with high linear energy transfer (LET) radiation and low LET. Since energy is randomly deposited along high-LET particle paths, RIF along these paths should also be randomly distributed. The probability to induce DSB can be derived from DNA fragment data measured experimentally by pulsed-field gel electrophoresis. We used this probability in Monte Carlo simulations to predict DSB locations in synthetic nuclei geometrically described by a complete set of human chromosomes, taking into account microscope optics from real experiments. As expected, simulations produced DNA-weighted random (Poisson) distributions. In contrast, the distributions of RIF obtained as early as 5 min after exposure to high LET (1 GeV/amu Fe) were non-random. This deviation from the expected DNA-weighted random pattern can be further characterized by “relative DNA image measurements.” This novel imaging approach shows that RIF were located preferentially at the interface between high and low DNA density regions, and were more frequent than predicted in regions with lower DNA density. The same preferential nuclear location was also measured for RIF induced by 1 Gy of low-LET radiation. This deviation from random behavior was evident only 5 min after irradiation for phosphorylated ATM RIF, while γH2AX and 53BP1 RIF showed pronounced deviations up to 30 min after exposure. These data suggest that DNA damage–induced foci are restricted to certain regions of the nucleus of human epithelial cells. It is possible that DNA lesions are collected in these nuclear sub-domains for more efficient repair

New highlights on stroma–epithelial interactions in breast cancer

Although the stroma in which carcinomas arise has been previously regarded as a bystander to the clonal expansion and acquisition of malignant characteristics of tumor cells, it is now generally acknowledged that stromal changes are required for the establishment of cancer. In the present article, we discuss three recent publications that highlight the complex role the stroma has during the development of cancer and the potential for targeting the stroma by therapeutic approaches

Murine Microenvironment Metaprofiles Associate with Human Cancer Etiology and Intrinsic Subtypes

Ionizing radiation is a well established carcinogen in rodent models and a risk factor associated with human cancer. We developed a mouse model that captures radiation effects on host biology by transplanting unirradiated Trp53 null mammary tissue to sham or irradiated hosts. Gene expression profiles of tumors that arose in irradiated mice are distinct from those that arose in naïve hosts. We asked whether expression metaprofiles could discern radiation-preceded human cancer or be informative in sporadic breast cancers

Notch signaling regulates metabolic heterogeneity in glioblastoma stem cells.

Glioblastoma (GBM) stem cells (GSCs) reside in both hypoxic and vascular microenvironments within tumors. The molecular mechanisms that allow GSCs to occupy such contrasting niches are not understood. We used patient-derived GBM cultures to identify GSC subtypes with differential activation of Notch signaling, which co-exist in tumors but occupy distinct niches and match their metabolism accordingly. Multipotent GSCs with Notch pathway activation reside in perivascular niches, and are unable to entrain anaerobic glycolysis during hypoxia. In contrast, most CD133-expressing GSCs do not depend on canonical Notch signaling, populate tumors regardless of local vascularity and selectively utilize anaerobic glycolysis to expand in hypoxia. Ectopic activation of Notch signaling in CD133-expressing GSCs is sufficient to suppress anaerobic glycolysis and resistance to hypoxia. These findings demonstrate a novel role for Notch signaling in regulating GSC metabolism and suggest intratumoral GSC heterogeneity ensures metabolic adaptations to support tumor growth in diverse tumor microenvironments

From mouse to human: cellular morphometric subtype learned from mouse mammary tumors provides prognostic value in human breast cancer

Mouse models of cancer provide a powerful tool for investigating all aspects of cancer biology. In this study, we used our recently developed machine learning approach to identify the cellular morphometric biomarkers (CMB) from digital images of hematoxylin and eosin (H&E) micrographs of orthotopic Trp53-null mammary tumors (n = 154) and to discover the corresponding cellular morphometric subtypes (CMS). Of the two CMS identified, CMS-2 was significantly associated with shorter survival (p = 0.0084). We then evaluated the learned CMB and corresponding CMS model in MMTV-Erbb2 transgenic mouse mammary tumors (n = 53) in which CMS-2 was significantly correlated with the presence of metastasis (p = 0.004). We next evaluated the mouse CMB and CMS model on The Cancer Genome Atlas breast cancer (TCGA-BRCA) cohort (n = 1017). Kaplan–Meier analysis showed significantly shorter overall survival (OS) of CMS-2 patients compared to CMS-1 patients (p = 0.024) and added significant prognostic value in multi-variable analysis of clinical and molecular factors, namely, age, pathological stage, and PAM50 molecular subtype. Thus, application of CMS to digital images of routine workflow H&E preparations can provide unbiased biological stratification to inform patient care.This work was supported by the Department of Defense (DoD)BCRP: BC190820 (J-HM); and the National Cancer Institute (NCI) at the National Institutes of Health (NIH): R01CA184476 (HC). Lawrence Berkeley National Laboratory (LBNL) is a multi-program national laboratory operated by the University of California for the DOE under contract DE AC02-05CH1123