Identification of genetic loci that control mammary tumor susceptibility through the host microenvironment

Systemic inflammation in response to radiation drives the genesis of an immunosuppressed tumor microenvironment

The composition of the tumor immune microenvironment has become a major determinant of response to therapy, particularly immunotherapy. Clinically, a tumor microenvironment lacking lymphocytes, so-called "cold" tumors, are considered poor candidates for immune checkpoint inhibition. In this review, we describe the diversity of the tumor immune microenvironment in breast cancer and how radiation exposure alters carcinogenesis. We review the development and use of a radiation-genetic mammary chimera model to clarify the mechanism by which radiation acts. Using the chimera model, we demonstrate that systemic inflammation elicited by a low dose of radiation is key to the construction of an immunosuppressive tumor microenvironment, resulting in aggressive, rapidly growing tumors lacking lymphocytes. Our experimental studies inform the non-mutagenic mechanisms by which radiation affects cancer and provide insight into the genesis of cold tumors.

The role of lipid metabolism in cancer radioresistance

Radiotherapy is one of the main therapies for cancer. The process leading to radioresistance is still not fully understood. Cancer radiosensitivity is related to the DNA reparation of cancer cells and the tumor microenvironment (TME), which supports cancer cell survival. Factors that affect DNA reparation and the TME can directly or indirectly affect the radiosensitivity of cancer. Recent studies have shown that lipid metabolism in cancer cells, which is involved in the stability of cell membrane structure, energy supply and signal transduction of cancer cells, can also affect the phenotype and function of immune cells and stromal cells in the TME. In this review, we discussed the effects of lipid metabolism on the radiobiological characteristics of cancer cells and the TME. We also summarized recent advances in targeted lipid metabolism as a radiosensitizer and discussed how these scientific findings could be translated into clinical practice to improve the radiosensitivity of cancer.

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.

Adverse outcome pathways for ionizing radiation and breast cancer involve direct and indirect DNA damage, oxidative stress, inflammation, genomic instability, and interaction with hormonal regulation of the breast

Knowledge about established breast carcinogens can support improved and modernized toxicological testing methods by identifying key mechanistic events. Ionizing radiation (IR) increases the risk of breast cancer, especially for women and for exposure at younger ages, and evidence overall supports a linear dose-response relationship. We used the Adverse Outcome Pathway (AOP) framework to outline and evaluate the evidence linking ionizing radiation with breast cancer from molecular initiating events to the adverse outcome through intermediate key events, creating a qualitative AOP. We identified key events based on review articles, searched PubMed for recent literature on key events and IR, and identified additional papers using references. We manually curated publications and evaluated data quality. Ionizing radiation directly and indirectly causes DNA damage and increases production of reactive oxygen and nitrogen species (RONS). RONS lead to DNA damage and epigenetic changes leading to mutations and genomic instability (GI). Proliferation amplifies the effects of DNA damage and mutations leading to the AO of breast cancer. Separately, RONS and DNA damage also increase inflammation. Inflammation contributes to direct and indirect effects (effects in cells not directly reached by IR) via positive feedback to RONS and DNA damage, and separately increases proliferation and breast cancer through pro-carcinogenic effects on cells and tissue. For example, gene expression changes alter inflammatory mediators, resulting in improved survival and growth of cancer cells and a more hospitable tissue environment. All of these events overlap at multiple points with events characteristic of "background" induction of breast carcinogenesis, including hormone-responsive proliferation, oxidative activity, and DNA damage. These overlaps make the breast particularly susceptible to ionizing radiation and reinforce that these biological activities are important characteristics of carcinogens. Agents that increase these biological processes should be considered potential breast carcinogens, and predictive methods are needed to identify chemicals that increase these processes. Techniques are available to measure RONS, DNA damage and mutation, cell proliferation, and some inflammatory proteins or processes. Improved assays are needed to measure GI and chronic inflammation, as well as the interaction with hormonally driven development and proliferation. Several methods measure diverse epigenetic changes, but it is not clear which changes are relevant to breast cancer. In addition, most toxicological assays are not conducted in mammary tissue, and so it is a priority to evaluate if results from other tissues are generalizable to breast, or to conduct assays in breast tissue. Developing and applying these assays to identify exposures of concern will facilitate efforts to reduce subsequent breast cancer risk.

Adverse outcome pathways for ionizing radiation and breast cancer involve direct and indirect DNA damage, oxidative stress, inflammation, genomic instability, and interaction with hormonal regulation of the breast

Knowledge about established breast carcinogens can support improved and modernized toxicological testing methods by identifying key mechanistic events. Ionizing radiation (IR) increases the risk of breast cancer, especially for women and for exposure at younger ages, and evidence overall supports a linear dose-response relationship. We used the Adverse Outcome Pathway (AOP) framework to outline and evaluate the evidence linking ionizing radiation with breast cancer from molecular initiating events to the adverse outcome through intermediate key events, creating a qualitative AOP. We identified key events based on review articles, searched PubMed for recent literature on key events and IR, and identified additional papers using references. We manually curated publications and evaluated data quality. Ionizing radiation directly and indirectly causes DNA damage and increases production of reactive oxygen and nitrogen species (RONS). RONS lead to DNA damage and epigenetic changes leading to mutations and genomic instability (GI). Proliferation amplifies the effects of DNA damage and mutations leading to the AO of breast cancer. Separately, RONS and DNA damage also increase inflammation. Inflammation contributes to direct and indirect effects (effects in cells not directly reached by IR) via positive feedback to RONS and DNA damage, and separately increases proliferation and breast cancer through pro-carcinogenic effects on cells and tissue. For example, gene expression changes alter inflammatory mediators, resulting in improved survival and growth of cancer cells and a more hospitable tissue environment. All of these events overlap at multiple points with events characteristic of "background" induction of breast carcinogenesis, including hormone-responsive proliferation, oxidative activity, and DNA damage. These overlaps make the breast particularly susceptible to ionizing radiation and reinforce that these biological activities are important characteristics of carcinogens. Agents that increase these biological processes should be considered potential breast carcinogens, and predictive methods are needed to identify chemicals that increase these processes. Techniques are available to measure RONS, DNA damage and mutation, cell proliferation, and some inflammatory proteins or processes. Improved assays are needed to measure GI and chronic inflammation, as well as the interaction with hormonally driven development and proliferation. Several methods measure diverse epigenetic changes, but it is not clear which changes are relevant to breast cancer. In addition, most toxicological assays are not conducted in mammary tissue, and so it is a priority to evaluate if results from other tissues are generalizable to breast, or to conduct assays in breast tissue. Developing and applying these assays to identify exposures of concern will facilitate efforts to reduce subsequent breast cancer risk.

Caveolin-1 regulates the ASMase/ceramide-mediated radiation response of endothelial cells in the context of tumor-stroma interactions

The integral membrane protein caveolin-1 (CAV1) plays a central role in radioresistance-mediating tumor–stroma interactions of advanced prostate cancer (PCa). Among the tumor–stroma, endothelial cells (EC) evolved as critical determinants of the radiation response. CAV1 deficiency in angiogenic EC was already shown to account for increased apoptosis rates of irradiated EC. This study explores the potential impact of differential CAV1 levels in EC on the acid sphingomyelinase (ASMase)/ceramide pathway as a key player in the regulation of EC apoptosis upon irradiation and cancer cell radioresistance. Enhanced apoptosis sensitivity of CAV1-deficient EC was associated with increased ASMase activity, ceramide generation, formation of large lipid platforms, and finally an altered p38 mitogen-activated protein kinase (MAPK)/heat-shock protein 27 (HSP27)/AKT (protein kinase B, PKB) signaling. CAV1-deficient EC increased the growth delay of LNCaP and PC3 PCa cells upon radiation treatment in direct 3D spheroid co-cultures. Exogenous C6 and C16 ceramide treatment in parallel increased the growth delay of PCa spheroids and induced PCa cell apoptosis. Analysis of the respective ceramide species in PCa cells with increased CAV1 levels like those typically found in radio-resistant advanced prostate tumors further revealed an upregulation of unsaturated C24:1 ceramide that might scavenge the effects of EC-derived apoptosis-inducing C16 ceramide. Higher ASMase as well as ceramide levels could be confirmed by immunohistochemistry in human advanced prostate cancer specimen bearing characteristic CAV1 tumor–stroma alterations. Conclusively, CAV1 critically regulates the generation of ceramide-dependent (re-)organization of the plasma membrane that in turn affects the radiation response of EC and adjacent PCa cells. Understanding the CAV1-dependent crosstalk between tumor cells and the host-derived tumor microvasculature and its impact on radiosensitivity may allow to define a rational strategy for overcoming tumor radiation resistance improving clinical outcomes by targeting CAV1.

Aggressive Mammary Cancers Lacking Lymphocytic Infiltration Arise in Irradiated Mice and Can Be Prevented by Dietary Intervention

Because the incidence of breast cancer increases decades after ionizing radiation exposure, aging has been implicated in the evolution of the tumor microenvironment and tumor progression. Here, we investigated radiation-induced carcinogenesis using a model in which the mammary glands of 10-month-old BALB/c mice were transplanted with Trp53-null mammary tissue 3 days after exposure to low doses of sparsely ionizing γ-radiation or densely ionizing particle radiation. Mammary transplants in aged, irradiated hosts gave rise to significantly more tumors that grew more rapidly than those in sham-irradiated mice, with the most pronounced effects seen in mice irradiated with densely ionizing particle radiation. Tumor transcriptomes identified a characteristic immune signature of these aggressive cancers. Consistent with this, fast-growing tumors exhibited an immunosuppressive tumor microenvironment with few infiltrating lymphocytes, abundant immunosuppressive myeloid cells, and high COX-2 and TGFβ. Only irradiated hosts gave rise to tumors lacking cytotoxic CD8+ lymphocytes (defined here as immune desert), which also occurred in younger irradiated hosts. These data suggest that host irradiation may promote immunosuppression. To test this, young chimera mice were fed chow containing a honeybee-derived compound with anti-inflammatory and immunomodulatory properties, caffeic acid phenethyl ester (CAPE). CAPE prevented the detrimental effects of host irradiation on tumor growth rate, immune signature, and immunosuppression. These data indicated that low-dose radiation, particularly densely ionizing exposure of aged mice, promoted more aggressive cancers by suppressing antitumor immunity. Dietary intervention with a nontoxic immunomodulatory agent could prevent systemic effects of radiation that fuel carcinogenesis, supporting the potential of this strategy for cancer prevention.

Hyaluronan, Cancer-Associated Fibroblasts and the Tumor Microenvironment in Malignant Progression

This review summarizes the roles of CAFs in forming a “cancerized” fibrotic stroma favorable to tumor initiation and dissemination, in particular highlighting the functions of the extracellular matrix component hyaluronan (HA) in these processes. The structural complexity of the tumor and its host microenvironment is now well appreciated to be an important contributing factor to malignant progression and resistance-to-therapy. There are multiple components of this complexity, which include an extensive remodeling of the extracellular matrix (ECM) and associated biomechanical changes in tumor stroma. Tumor stroma is often fibrotic and rich in fibrillar type I collagen and hyaluronan (HA). Cancer-associated fibroblasts (CAFs) are a major source of this fibrotic ECM. CAFs organize collagen fibrils and these biomechanical alterations provide highways for invading carcinoma cells either under the guidance of CAFs or following their epithelial to mesenchymal transition (EMT). The increased HA metabolism of a tumor microenvironment instructs carcinoma initiation and dissemination by performing multiple functions. The key effects of HA reviewed here are its role in activating CAFs in pre-malignant and malignant stroma, and facilitating invasion by promoting motility of both CAFs and tumor cells, thus facilitating their invasion. Circulating CAFs (cCAFs) also form heterotypic clusters with circulating tumor cells (CTC), which are considered to be pre-cursors of metastatic colonies. cCAFs are likely required for extravasation of tumors cells and to form a metastatic niche suitable for new tumor colony growth. Therapeutic interventions designed to target both HA and CAFs in order to limit tumor spread and increase response to current therapies are discussed.

Unsupervised Transfer Learning via Multi-Scale Convolutional Sparse Coding for Biomedical Applications

The capabilities of (I) learning transferable knowledge across domains; and (II) fine-tuning the pre-learned base knowledge towards tasks with considerably smaller data scale are extremely important. Many of the existing transfer learning techniques are supervised approaches, among which deep learning has the demonstrated power of learning domain transferrable knowledge with large scale network trained on massive amounts of labeled data. However, in many biomedical tasks, both the data and the corresponding label can be very limited, where the unsupervised transfer learning capability is urgently needed. In this paper, we proposed a novel multi-scale convolutional sparse coding (MSCSC) method, that (I) automatically learns filter banks at different scales in a joint fashion with enforced scale-specificity of learned patterns; and (II) provides an unsupervised solution for learning transferable base knowledge and fine-tuning it towards target tasks. Extensive experimental evaluation of MSCSC demonstrates the effectiveness of the proposed MSCSC in both regular and transfer learning tasks in various biomedical domains.

The changing paradigm of tumour response to irradiation

Tumours contain multiple different cell populations, including cells derived from the bone marrow as well as cancer-associated fibroblasts and various stromal populations including the vasculature. The microenvironment of the tumour cells plays a significant role in the response of the tumour to radiation treatment. Low levels of oxygen (hypoxia) caused by the poorly organized vasculature in tumours have long been known to affect radiation response; however, other aspects of the microenvironment may also play important roles. This article reviews some of the old literature concerning tumour response to irradiation and relates this to current concepts about the role of the tumour microenvironment in tumour response to radiation treatment. Included in the discussion are the role of cancer stem cells, radiation damage to the vasculature and the potential for radiation to enhance immune activity against tumour cells. Radiation treatment can cause a significant influx of bone marrow-derived cell populations into both normal tissues and tumours. Potential roles of such cells may include enhancing vascular recovery as well as modulating immune reactivity.

HZE Radiation Non-Targeted Effects on the Microenvironment That Mediate Mammary Carcinogenesis

Clear mechanistic understanding of the biological processes elicited by radiation that increase cancer risk can be used to inform prediction of health consequences of medical uses, such as radiotherapy, or occupational exposures, such as those of astronauts during deep space travel. Here, we review the current concepts of carcinogenesis as a multicellular process during which transformed cells escape normal tissue controls, including the immune system, and establish a tumor microenvironment. We discuss the contribution of two broad classes of radiation effects that may increase cancer: radiation targeted effects that occur as a result of direct energy deposition, e.g., DNA damage, and non-targeted effects (NTE) that result from changes in cell signaling, e.g., genomic instability. It is unknown whether the potentially greater carcinogenic effect of high Z and energy (HZE) particle radiation is a function of the relative contribution or extent of NTE or due to unique NTE. We addressed this problem using a radiation/genetic mammary chimera mouse model of breast cancer. Our experiments suggest that NTE promote more aggressive cancers, as evidenced by increased growth rate, transcriptomic signatures, and metastasis, and that HZE particle NTE are more effective than reference γ-radiation. Emerging evidence suggest that HZE irradiation dampens antitumor immunity. These studies raise concern that HZE radiation exposure not only increases the likelihood of developing cancer but also could promote progression to more aggressive cancer with a greater risk of mortality.

184AA3: a xenograft model of ER+ breast adenocarcinoma

Despite the prevalence and significant morbidity resulting from estrogen receptor positive (ER(+)) breast adenocarcinomas, there are only a few models of this cancer subtype available for drug development and arguably none for studying etiology. Those models that do exist have questionable clinical relevance. Given our goal of developing luminal models, we focused on six cell lines derived by minimal mutagenesis from normal human breast cells, and asked if any could generate clinically relevant xenografts, which we then extensively characterized. Xenografts of one cell line, 184AA3, consistently formed ER(+) adenocarcinomas that had a high proliferative rate and other features consistent with "luminal B" intrinsic subtype. Squamous and spindle cell/mesenchymal differentiation was absent, in stark contrast to other cell lines that we examined or others have reported. We explored intratumoral heterogeneity produced by 184AA3 by immunophenotyping xenograft tumors and cultured cells, and characterized marker expression by immunofluorescence and flow cytometry. A CD44(High) subpopulation was discovered, yet their tumor forming ability was far less than CD44(Low) cells. Single cell cloning revealed the phenotypic plasticity of 184AA3, consistent with the intratumoral heterogeneity observed in xenografts. Characterization of ER expression in cultures revealed ER protein and signaling is intact, yet when estrogen was depleted in culture, and in vivo, it did not impact cell or tumor growth, analogous to therapeutically resistant ER(+) cancers. This model is appropriate for studies of the etiology of ovarian hormone independent adenocarcinomas, for identification of therapeutic targets, predictive testing, and drug development.

The extracellular matrix in breast cancer predicts prognosis through composition, splicing, and crosslinking

The extracellular matrix in the healthy breast has an important tumor suppressive role, whereas the abnormal ECM in tumors can promote aggressiveness, and has been linked to breast cancer relapse, survival and resistance to chemotherapy. This review article gives an overview of the elements of the ECM which have been linked to prognosis of breast cancers, including changes in ECM protein composition, splicing, and microstructure.

Concepts and challenges in cancer risk prediction for the space radiation environment

Cancer is an important long-term risk for astronauts exposed to protons and high-energy charged particles during travel and residence on asteroids, the moon, and other planets. NASA's Biomedical Critical Path Roadmap defines the carcinogenic risks of radiation exposure as one of four type I risks. A type I risk represents a demonstrated, serious problem with no countermeasure concepts, and may be a potential "show-stopper" for long duration spaceflight. Estimating the carcinogenic risks for humans who will be exposed to heavy ions during deep space exploration has very large uncertainties at present. There are no human data that address risk from extended exposure to complex radiation fields. The overarching goal in this area to improve risk modeling is to provide biological insight and mechanistic analysis of radiation quality effects on carcinogenesis. Understanding mechanisms will provide routes to modeling and predicting risk and designing countermeasures. This white paper reviews broad issues related to experimental models and concepts in space radiation carcinogenesis as well as the current state of the field to place into context recent findings and concepts derived from the NASA Space Radiation Program.

Characterizing the DNA Damage Response by Cell Tracking Algorithms and Cell Features Classification Using High-Content Time-Lapse Analysis

Traditionally, the kinetics of DNA repair have been estimated using immunocytochemistry by labeling proteins involved in the DNA damage response (DDR) with fluorescent markers in a fixed cell assay. However, detailed knowledge of DDR dynamics across multiple cell generations cannot be obtained using a limited number of fixed cell time-points. Here we report on the dynamics of 53BP1 radiation induced foci (RIF) across multiple cell generations using live cell imaging of non-malignant human mammary epithelial cells (MCF10A) expressing histone H2B-GFP and the DNA repair protein 53BP1-mCherry. Using automatic extraction of RIF imaging features and linear programming techniques, we were able to characterize detailed RIF kinetics for 24 hours before and 24 hours after exposure to low and high doses of ionizing radiation. High-content-analysis at the single cell level over hundreds of cells allows us to quantify precisely the dose dependence of 53BP1 protein production, RIF nuclear localization and RIF movement after exposure to X-ray. Using elastic registration techniques based on the nuclear pattern of individual cells, we could describe the motion of individual RIF precisely within the nucleus. We show that DNA repair occurs in a limited number of large domains, within which multiple small RIFs form, merge and/or resolve with random motion following normal diffusion law. Large foci formation is shown to be mainly happening through the merging of smaller RIF rather than through growth of an individual focus. We estimate repair domain sizes of 7.5 to 11 µm2 with a maximum number of ~15 domains per MCF10A cell. This work also highlights DDR which are specific to doses larger than 1 Gy such as rapid 53BP1 protein increase in the nucleus and foci diffusion rates that are significantly faster than for spontaneous foci movement. We hypothesize that RIF merging reflects a "stressed" DNA repair process that has been taken outside physiological conditions when too many DSB occur at once. High doses of ionizing radiation lead to RIF merging into repair domains which in turn increases DSB proximity and misrepair. Such finding may therefore be critical to explain the supralinear dose dependence for chromosomal rearrangement and cell death measured after exposure to ionizing radiation.