Quantitative image analysis of laminin immunoreactivity in skin basement membrane irradiated with 1 GeV/nucleon iron particles

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.

Systems biology perspectives on the carcinogenic potential of radiation

This review focuses on recent experimental and modeling studies that attempt to define the physiological context in which high linear energy transfer (LET) radiation increases epithelial cancer risk and the efficiency with which it does so. Radiation carcinogenesis is a two-compartment problem: ionizing radiation can alter genomic sequence as a result of damage due to targeted effects (TE) from the interaction of energy and DNA; it can also alter phenotype and multicellular interactions that contribute to cancer by poorly understood non-targeted effects (NTE). Rather than being secondary to DNA damage and mutations that can initiate cancer, radiation NTE create the critical context in which to promote cancer. Systems biology modeling using comprehensive experimental data that integrates different levels of biological organization and time-scales is a means of identifying the key processes underlying the carcinogenic potential of high-LET radiation. We hypothesize that inflammation is a key process, and thus cancer susceptibility will depend on specific genetic predisposition to the type and duration of this response. Systems genetics using novel mouse models can be used to identify such determinants of susceptibility to cancer in radiation sensitive tissues following high-LET radiation. Improved understanding of radiation carcinogenesis achieved by defining the relative contribution of NTE carcinogenic effects and identifying the genetic determinants of the high-LET cancer susceptibility will help reduce uncertainties in radiation risk assessment.

Rapid and automated multidimensional fluorescence microscopy profiling of 3D human breast cultures

Three-dimensional (3D) tissue culture provides a physiologically relevant microenvironment for distinguishing malignant from non-malignant breast cell phenotypes. 3D culture assays can also be used to test novel cancer therapies and predict a differential response to radiation between normal and malignant cells in vivo. However, biological measurements in such complex models are difficult to quantify and current approaches do not allow for in-depth multifaceted assessment of individual colonies or unique sub-populations within the entire culture. This is in part due to the limitations of imaging at a range of depths in 3D culture resulting from optical aberrations and intensity attenuation. Here, we address these limitations by combining sample smearing techniques with high-throughput 2D imaging algorithms to accurately and rapidly quantify imaging features acquired from 3D cultures. Multiple high resolution imaging features especially designed to characterize 3D cultures show that non-malignant human breast cells surviving large doses of ionizing radiation acquire a "swelled acinar" phenotype with fewer and larger nuclei, loss of cell connectivity and diffused basement membrane. When integrating these imaging features into hierarchical clustering classification, we could also identify subpopulations of phenotypes from individual human tumor colonies treated with ionizing radiation or/and integrin inhibitors. Such tools have therefore the potential to further characterize cell culture populations after cancer treatment and identify novel phenotypes of resistance.

Evidence for formation of DNA repair centers and dose-response nonlinearity in human cells

The concept of DNA "repair centers" and the meaning of radiation-induced foci (RIF) in human cells have remained controversial. RIFs are characterized by the local recruitment of DNA damage sensing proteins such as p53 binding protein (53BP1). Here, we provide strong evidence for the existence of repair centers. We used live imaging and mathematical fitting of RIF kinetics to show that RIF induction rate increases with increasing radiation dose, whereas the rate at which RIFs disappear decreases. We show that multiple DNA double-strand breaks (DSBs) 1 to 2 μm apart can rapidly cluster into repair centers. Correcting mathematically for the dose dependence of induction/resolution rates, we observe an absolute RIF yield that is surprisingly much smaller at higher doses: 15 RIF/Gy after 2 Gy exposure compared to approximately 64 RIF/Gy after 0.1 Gy. Cumulative RIF counts from time lapse of 53BP1-GFP in human breast cells confirmed these results. The standard model currently in use applies a linear scale, extrapolating cancer risk from high doses to low doses of ionizing radiation. However, our discovery of DSB clustering over such large distances casts considerable doubts on the general assumption that risk to ionizing radiation is proportional to dose, and instead provides a mechanism that could more accurately address risk dose dependency of ionizing radiation.

Applications of quantitative digital image analysis to breast cancer research

Our studies of radiogenic carcinogenesis in mouse and human models of breast cancer are based on the view that cell phenotype, microenvironment composition, communication between cells and within the microenvironment are important factors in the development of breast cancer. This is complicated in the mammary gland by its postnatal development, cyclic evolution via pregnancy and involution, and dynamic remodeling of epithelial-stromal interactions, all of which contribute to breast cancer susceptibility. Microscopy is the tool of choice to examine cells in context. Specific features can be defined using probes, antibodies, immunofluorescence, and image analysis to measure protein distribution, cell composition, and genomic instability in human and mouse models of breast cancer. We discuss the integration of image acquisition, analysis, and annotation to efficiently analyze large amounts of image data. In the future, cell and tissue image-based studies will be facilitated by a bioinformatics strategy that generates multidimensional databases of quantitative information derived from molecular, immunological, and morphological probes at multiple resolutions. This approach will facilitate the construction of an in vivo phenotype database necessary for understanding when, where, and how normal cells become cancer.

Total-body irradiation with high-LET particles: acute and chronic effects on the immune system

Although the immune system is highly susceptible to radiation-induced damage, consequences of high linear energy transfer (LET) radiation remain unclear. This study evaluated the effects of 0.1 gray (Gy), 0.5 Gy, and 2.0 Gy iron ion (56Fe(26)) radiation on lymphoid cells and organs of C57BL/6 mice on days 4 and 113 after whole body exposure; a group irradiated with 2.0 Gy silicon ions (28Si) was euthanized on day 113. On day 4 after 56Fe irradiation, dose-dependent decreases were noted in spleen and thymus masses and all major leukocyte populations in blood and spleen. The CD19(+) B lymphocytes were most radiosensitive and NK1.1(+) natural killer (NK) cells were most resistant. CD3(+) T cells were moderately radiosensitive and a greater loss of CD3(+)/CD8(+) T(C) cells than CD3(+)/CD4(+) T(H) cells was noted. Basal DNA synthesis was elevated on day 4, but response to mitogens and secretion of interleukin-2 and tumor necrosis factor-alpha were unaffected. Signs of anemia were noted. By day 113, high B cell numbers and low T(C) cell and monocyte percents were found in the 2.0 Gy 56Fe group; the 2.0 Gy 2)Si mice had low NK cells, decreased basal DNA synthesis, and a somewhat increased response to two mitogens. Collectively, the data show that lymphoid cells and tissues are markedly affected by high linear energy transfer (LET) radiation at relatively low doses, that some aberrations persist long after exposure, and that different consequences may be induced by various densely ionizing particles. Thus simultaneous exposure to multiple radiation sources could lead to a broader spectrum of immune dysfunction than currently anticipated.

Radiation quality and tissue-specific microenvironments following exposure to 1 GeV/amu Fe

This paper summarizes quantitative in vivo laminin immunofluorescence analysis of mammary glands and skin epithelial structures from mice exposed to 1 GeV/amu Fe ions. Digital confocal microscopic images were quantified and linked to the rough "core-penumbra" Fe track physical description. Comparison to gamma-ray sparsely ionizing radiation suggested the core of the Fe track being responsible for a biological response only seen with energetic Fe particles. Conclusions for modeling in vivo responses to radiation were then implied.