Evaluating biomarkers to model cancer risk post cosmic ray exposure.

Robust predictive models are essential to manage the risk of radiation-induced carcinogenesis. Chronic exposure to cosmic rays in the context of the complex deep space environment may place astronauts at high cancer risk. To estimate this risk, it is critical to understand how radiation-induced cellular stress impacts cell fate decisions and how this in turn alters the risk of carcinogenesis. Exposure to the heavy ion component of cosmic rays triggers a multitude of cellular changes, depending on the rate of exposure, the type of damage incurred and individual susceptibility. Heterogeneity in dose, dose rate, radiation quality, energy and particle flux contribute to the complexity of risk assessment. To unravel the impact of each of these factors, it is critical to identify sensitive biomarkers that can serve as inputs for robust modeling of individual risk of cancer or other long-term health consequences of exposure. Limitations in sensitivity of biomarkers to dose and dose rate, and the complexity of longitudinal monitoring, are some of the factors that increase uncertainties in the output from risk prediction models. Here, we critically evaluate candidate early and late biomarkers of radiation exposure and discuss their usefulness in predicting cell fate decisions. Some of the biomarkers we have reviewed include complex clustered DNA damage, persistent DNA repair foci, reactive oxygen species, chromosome aberrations and inflammation. Other biomarkers discussed, often assayed for at longer points post exposure, include mutations, chromosome aberrations, reactive oxygen species and telomere length changes. We discuss the relationship of biomarkers to different potential cell fates, including proliferation, apoptosis, senescence, and loss of stemness, which can propagate genomic instability and alter tissue composition and the underlying mRNA signatures that contribute to cell fate decisions. Our goal is to highlight factors that are important in choosing biomarkers and to evaluate the potential for biomarkers to inform models of post exposure cancer risk. Because cellular stress response pathways to space radiation and environmental carcinogens share common nodes, biomarker-driven risk models may be broadly applicable for estimating risks for other carcinogens.

Generalized time-dependent model of radiation-induced chromosomal aberrations in normal and repair-deficient human cells.

We have developed a model that can simulate the yield of radiation-induced chromosomal aberrations (CAs) and unrejoined chromosome breaks in normal and repair-deficient cells. The model predicts the kinetics of chromosomal aberration formation after exposure in the G0/G1 phase of the cell cycle to either low- or high-LET radiation. A previously formulated model based on a stochastic Monte Carlo approach was updated to consider the time dependence of DNA double-strand break (DSB) repair (proper or improper), and different cell types were assigned different kinetics of DSB repair. The distribution of the DSB free ends was derived from a mechanistic model that takes into account the structure of chromatin and DSB clustering from high-LET radiation. The kinetics of chromosomal aberration formation were derived from experimental data on DSB repair kinetics in normal and repair-deficient cell lines. We assessed different types of chromosomal aberrations with the focus on simple and complex exchanges, and predicted the DSB rejoining kinetics and misrepair probabilities for different cell types. The results identify major cell-dependent factors, such as a greater yield of chromosome misrepair in ataxia telangiectasia (AT) cells and slower rejoining in Nijmegen (NBS) cells relative to the wild-type. The model's predictions suggest that two mechanisms could exist for the inefficiency of DSB repair in AT and NBS cells, one that depends on the overall speed of joining (either proper or improper) of DNA broken ends, and another that depends on geometric factors, such as the Euclidian distance between DNA broken ends, which influences the relative frequency of misrepair.

Calculation of the energy deposition in nanovolumes by protons and HZE particles: geometric patterns of initial distributions of DNA repair foci.

The biological effects of high-linear energy transfer (LET) radiation are different from those caused by low-LET radiation due to the difference in the patterns of energy deposition in cells. In this work, we studied the role of the track structure in the spatial distribution of radiation-induced double-strand breaks (DSBs). In the first part, the irradiation of a cubic volume of 12 µm of side by 300 MeV protons (LET ∼0.3 keV µm(-1)) and by 1 GeV/amu iron ion particles (LET∼150 keV µm(-1)) was simulated with the Monte Carlo code RITRACKS (relativistic ion tracks) and the dose was calculated in voxels of different sizes. In the second part, dose calculations were combined with chromosomes simulated by a random walk (RW) model to assess the formation of DSBs. The number of DSBs was calculated as a function of the dose and particle fluence for 1 GeV protons, 293 MeV/u carbon, and 1 GeV/u iron particles. Finally, the DSB yield was obtained as a function of the LET for protons, helium, and carbon. In general, the number and distribution of calculated DSBs were similar to experimental DNA repair foci data. From this study, we concluded that a stochastic model combining nanoscopic dose calculations and chromosomes simulated by RWs is a useful approach to study radiation-induced DSBs.

Computational model of chromosome aberration yield induced by high- and low-LET radiation exposures.

We present a computational model for calculating the yield of radiation-induced chromosomal aberrations in human cells based on a stochastic Monte Carlo approach and calibrated using the relative frequencies and distributions of chromosomal aberrations reported in the literature. A previously developed DNA-fragmentation model for high- and low-LET radiation called the NASARadiationTrackImage model was enhanced to simulate a stochastic process of the formation of chromosomal aberrations from DNA fragments. The current version of the model gives predictions of the yields and sizes of translocations, dicentrics, rings, and more complex-type aberrations formed in the G(0)/G(1) cell cycle phase during the first cell division after irradiation. As the model can predict smaller-sized deletions and rings (<3 Mbp) that are below the resolution limits of current cytogenetic analysis techniques, we present predictions of hypothesized small deletions that may be produced as a byproduct of properly repaired DNA double-strand breaks (DSB) by nonhomologous end-joining. Additionally, the model was used to scale chromosomal exchanges in two or three chromosomes that were obtained from whole-chromosome FISH painting analysis techniques to whole-genome equivalent values.

Nuclear interactions in heavy ion transport and event-based risk models.

The physical description of the passage of heavy ions in tissue and shielding materials is of interest in radiobiology, cancer therapy and space exploration, including a human mission to Mars. Galactic cosmic rays (GCRs) consist of a large number of ion types and energies. Energy loss processes occur continuously along the path of heavy ions and are well described by the linear energy transfer (LET), straggling and multiple scattering algorithms. Nuclear interactions lead to much larger energy deposition than atomic-molecular collisions and alter the composition of heavy ion beams while producing secondary nuclei often in high multiplicity events. The major nuclear interaction processes of importance for describing heavy ion beams was reviewed, including nuclear fragmentation, elastic scattering and knockout-cascade processes. The quantum multiple scattering fragmentation model is shown to be in excellent agreement with available experimental data for nuclear fragmentation cross sections and is studied for application to thick target experiments. A new computer model, which was developed for the description of biophysical events from heavy ion beams at the NASA Space Radiation Laboratory (NSRL), called the GCR Event Risk-Based Model (GERMcode) is described.

The analysis of the densely populated patterns of radiation-induced foci by a stochastic, Monte Carlo model of DNA double-strand breaks induction by heavy ions.

PURPOSE: To resolve the difficulty in counting merged DNA damage foci in high-LET (linear energy transfer) ion-induced patterns. MATERIALS AND METHODS: The analysis of patterns of RIF (radiation-induced foci) produced by high-LET Fe and Ti ions were conducted by using a Monte Carlo model that combines the heavy ion track structure with characteristics of the human genome on the level of chromosomes. The foci patterns were also simulated in the maximum projection plane for flat nuclei. RESULTS: The model predicts the spatial and genomic distributions of DNA DSB (double-strand breaks) in a cell nucleus for a particular dose of radiation. We used the model to do analyses for three irradiation scenarios: (i) The ions were oriented perpendicular to the flattened nuclei in a cell culture monolayer; (ii) the ions were parallel to that plane; and (iii) round nucleus. In the parallel scenario we found that the foci appeared to be merged due to their high density, while, in the perpendicular scenario, the foci appeared as one bright spot per hit. The statistics and spatial distribution of regions of densely arranged foci, termed DNA foci chains, were predicted numerically using this model. Another analysis was done to evaluate the number of ion hits per nucleus, which were visible from streaks of closely located foci. CONCLUSIONS: We showed that DSB clustering needs to be taken into account to determine the true DNA damage foci yield, which helps to determine the DSB yield. Using the model analysis, a researcher can refine the DSB yield per nucleus per particle. We showed that purely geometric artifacts, present in the experimental images, can be analytically resolved with the model, and that the quantisation of track hits and DSB yields can be provided to the experimentalists who use enumeration of radiation-induced foci in immunofluorescence experiment using proteins that detect DNA damage.

Stochastic properties of radiation-induced DSB: DSB distributions in large scale chromatin loops, the HPRT gene and within the visible volumes of DNA repair foci.

PURPOSE: We computed probabilities to have multiple double-strand breaks (DSB), which are produced in DNA on a regional scale, and not in close vicinity, in volumes matching the size of DNA damage foci, of a large chromatin loop, and in the physical volume of DNA containing the HPRT (human hypoxanthine phosphoribosyltransferase) locus. MATERIALS AND METHODS: The model is based on a Monte Carlo description of DSB formation by heavy ions in the spatial context of the entire human genome contained within the cell nucleus, as well as at the gene sequence level. RESULTS: We showed that a finite physical volume corresponding to a visible DNA repair focus, believed to be associated with one DSB, can contain multiple DSB due to heavy ion track structure and the DNA supercoiled topography. A corrective distribution was introduced, which was a conditional probability to have excess DSB in a focus volume, given that there was already one present. The corrective distribution was calculated for 19.5 MeV/amu N ions, 3.77 MeV/amu alpha-particles, 1000 MeV/amu Fe ions, and X-rays. The corrected initial DSB yield from the experimental data on DNA repair foci was calculated. The DSB yield based on the corrective function converts the focus yield into the DSB yield, which is comparable with the DSB yield based on the earlier PFGE experiments. The distribution of DSB within the physical limits of the HPRT gene was analyzed by a similar method as well. CONCLUSION: This corrective procedure shows the applicability of the model and empowers the researcher with a tool to better analyze focus statistics. The model enables researchers to analyze the DSB yield based on focus statistics in real experimental situations that lack one-to-one focus-to-DSB correspondance.

Subtraction of background damage in PFGE experiments on DNA fragment-size distributions.

The non-random distribution of DNA breakage in pulsed-field gel electrophoresis (PFGE) experiments poses a problem of proper subtraction of the background damage to obtain a fragment-size distribution due to radiation only. As been pointed out by various authors, a naive bin-to-bin subtraction of the background signal will not result in the right DNA mass distribution histogram, and may even result in negative values. Previous more systematic subtraction methods have been based mainly on random breakage, appropriate for low-LET radiation but problematic for high LET. Moreover, an investigation is needed whether the background breakage itself is random or non-random. Previously a new generalized formalism based on stochastic processes for the subtraction of the background damage in PFGE experiments for any LET and any background was proposed, and as now applied it to a set of PFGE data for Fe ions. We developed a Monte Carlo algorithm to compare the naïve subtraction procedure in artificial data sets to the result produced by the new formalism. The simulated data corresponded to various cases, involving non-random (high-LET) or random radiation breakage and random or non-random background breakage. The formalism systematically gives better results than naïve bin-by-bin subtraction in all these artificial data sets.

A robust procedure for removing background damage in assays of radiation-induced DNA fragment distributions.

The non-random distribution of DNA breakage in PFGE (pulsed-field gel electrophoresis) experiments poses a problem of proper subtraction of the background DNA damage to obtain a fragment-size distribution due to radiation only. A naive bin-to-bin subtraction of the background signal will not result in the right DNA mass distribution histogram. This problem could become more pronounced for high-LET (linear energy transfer) radiation, because the fragment-size distribution manifests a higher frequency of smaller fragments. Previous systematic subtraction methods have been based on random breakage, appropriate for low-LET radiation. Moreover, an investigation is needed to determine whether the background breakage is itself random or non-random. We consider two limiting cases: (1) the background damage is present in all cells, and (2) it is present in only a small subset of cells, while other cells are not contributing to the background DNA fragmentation. We give a generalized formalism based on stochastic processes for the subtraction of the background damage in PFGE experiments for any LET and apply it to two sets of PFGE data for iron ions.

Chromatin loops are responsible for higher counts of small DNA fragments induced by high-LET radiation, while chromosomal domains do not affect the fragment sizes.

PURPOSE: To apply a polymer model of DNA damage induced by high-LET (linear energy transfer) radiation and determine the influence of chromosomal domains and loops on fragment length distribution. MATERIALS AND METHODS: The yields of DSB (double-strand breaks) induced by high-LET radiation were calculated using a track structure model along with a polymer model of DNA packed in the cell nucleus. The cell nucleus was constructed to include the chromosomal domains and chromatin loops. The latter were generated by the random walk method. RESULTS AND CONCLUSIONS: We present data for DSB yields per track per cell, DNA fragment sizes, the radial distribution of DSB with respect to the track center, and the distribution of 0, 1, 2, and more DSB from a single particle. Calculations were carried out for a range of particles including He (40 keV/microm), N (225 keV/microm), and Fe ions (150 keV/mum). Situations relevant to PFGE (pulsed-field gel electrophoresis) and microbeam experiments with direct irradiation of the cell nucleus were simulated to demonstrate the applicability of the model. Data show that chromosomal domains do not have a significant influence on fragment-size distribution, while the presence of DNA loops increases the frequencies of smaller fragments by nearly 30% for fragment sizes in the range from 2 kbp (bp = base pair) to 20 kbp.

An adjustable-threshold algorithm for the identification of objects in three-dimensional images.

MOTIVATION: To develop a highly accurate, practical and fast automated segmentation algorithm for three-dimensional images containing biological objects. To test the algorithm on images of the Drosophila brain, and identify, count and determine the locations of neurons in the images. RESULTS: A new adjustable-threshold algorithm was developed to efficiently segment fluorescently labeled objects contained within three-dimensional images obtained from laser scanning confocal microscopy, or two-photon microscopy. The result of the test segmentation with Drosophila brain images showed that the algorithm is extremely accurate and provided detailed information about the locations of neurons in the Drosophila brain. Centroids of each object (nucleus of each neuron) were also recorded into an algebraic matrix that describes the locations of the neurons. AVAILABILITY: Interested parties should send their request for the NeuronMapper(TM) program with the segmentation algorithm to artemp@bcm.tmc.edu.