Track structures and resulting DNA damage in human cells have been simulated for hydrogen, helium, carbon, nitrogen, oxygen and neon ions with 0.25–256 MeV/u energy. The needed ion interaction cross sections have been scaled from those of hydrogen; Barkas scaling formula has been refined, extending its applicability down to about 10 keV/u, and validated against established stopping power data. Linear energy transfer (LET) has been scored from energy deposits in a cell nucleus; for very low-energy ions, it has been defined locally within thin slabs. The simulations show that protons and helium ions induce more DNA damage than heavier ions do at the same LET. With increasing LET, less DNA strand breaks are formed per unit dose, but due to their clustering the yields of double-strand breaks (DSB) increase, up to saturation around 300 keV/μm. Also individual DSB tend to cluster; DSB clusters peak around 500 keV/μm, while DSB multiplicities per cluster steadily increase with LET. Remarkably similar to patterns known from cell survival studies, LET-dependencies with pronounced maxima around 100–200 keV/μm occur on nanometre scale for sites that contain one or more DSB, and on micrometre scale for megabasepair-sized DNA fragments.
Highlights d UBAP2L displays properties of a core component of stress granules d UBAP2L and G3BP1 form stress granule cores that do not always colocalize d UBAP2L forms small RNP granules independent of G3BP1
The understanding of the impact of radiation quality in early and late responses of biological targets to ionizing radiation exposure necessarily grounds on the results of mechanistic studies starting from physical interactions. This is particularly true when, already at the physical stage, the radiation field is mixed, as it is the case for neutron exposure. Neutron Relative Biological Effectiveness (RBE) is energy dependent, maximal for energies ~1 MeV, varying significantly among different experiments. The aim of this work is to shed light on neutron biological effectiveness as a function of field characteristics, with a comprehensive modeling approach: this brings together transport calculations of neutrons through matter (with the code PHITS) and the predictive power of the biophysical track structure code PARTRAC in terms of DNA damage evaluation. Two different energy dependent neutron RBE models are proposed: the first is phenomenological and based only on the characterization of linear energy transfer on a microscopic scale; the second is purely ab-initio and based on the induction of complex DNA damage. Results for the two models are compared and found in good qualitative agreement with current standards for radiation protection factors, which are agreed upon on the basis of RBE data.
BackgroundThe benefit of better ballistic and higher efficiency of carbon ions for cancer treatment (hadron-therapy) is asserted since decades, especially for unresectable or resistant tumors like sarcomas. However, hadron-therapy with carbon ions stays underused and raises some concerns about potential side effects for patients. Chondrosarcoma is a cartilaginous tumor, chemo- and radiation-resistant, that lacks reference models for basic and pre-clinical studies in radiation-biology. Most studies about cellular effects of ionizing radiation, including hadrons, were performed under growth conditions dramatically different from human homeostasis. Tridimensional in vitro models are a fair alternative to animal models to approach tissue and tumors microenvironment.MethodsBy using a collagen matrix, standardized culture conditions, physiological oxygen tension and a well defined chondrosarcoma cell line, we developed a pertinent in vitro 3D model for hadron-biology studies. Low- and high-Linear Energy Transfer (LET) ionizing radiations from GANIL facilities of ~1 keV/μm and 103 ± 4 keV/μm were used respectively, at 2 Gy single dose. The impact of radiation quality on chondrosarcoma cells cultivated in 3D was analyzed on cell death, cell proliferation and DNA repair.ResultsA fair distribution of chondrosarcoma cells was observed in the whole 3D scaffold. Moreover, LET distribution in depth, for ions, was calculated and found acceptable for radiation-biology studies using this kind of scaffold. No difference in cell toxicity was observed between low- and high-LET radiations but a higher rate of proliferation was displayed following high-LET irradiation. Furthermore, 3D models presented a higher and longer induction of H2AX phosphorylation after 2 Gy of high-LET compared to low-LET radiations.ConclusionsThe presented results show the feasibility and usefulness of our 3D chondrosarcoma model in the study of the impact of radiation quality on cell fate. The observed changes in our tissue-like model after ionizing radiation exposure may explain some discrepancies between radiation-biology studies and clinical data.Electronic supplementary materialThe online version of this article (doi:10.1186/s12885-015-1590-5) contains supplementary material, which is available to authorized users.
Our understanding of radiation-induced cellular damage has greatly improved over the past few decades. Despite this progress, there are still many obstacles to fully understand how radiation interacts with biologically relevant cellular components, such as DNA, to cause observable end points such as cell killing. Damage in DNA is identified as a major route of cell killing. One hurdle when modeling biological effects is the difficulty in directly comparing results generated by members of different research groups. Multiple Monte Carlo codes have been developed to simulate damage induction at the DNA scale, while at the same time various groups have developed models that describe DNA repair processes with varying levels of detail. These repair models are intrinsically linked to the damage model employed in their development, making it difficult to disentangle systematic effects in either part of the modeling chain. These modeling chains typically consist of track-structure Monte Carlo simulations of the physical interactions creating direct damages to DNA, followed by simulations of the production and initial reactions of chemical species causing so-called “indirect” damages. After the induction of DNA damage, DNA repair models combine the simulated damage patterns with biological models to determine the biological consequences of the damage. To date, the effect of the environment, such as molecular oxygen (normoxic vs. hypoxic), has been poorly considered. We propose a new standard DNA damage (SDD) data format to unify the interface between the simulation of damage induction in DNA and the biological modeling of DNA repair processes, and introduce the effect of the environment (molecular oxygen or other compounds) as a flexible parameter. Such a standard greatly facilitates inter-model comparisons, providing an ideal environment to tease out model assumptions and identify persistent, underlying mechanisms. Through inter-model comparisons, this unified standard has the potential to greatly advance our under-standing of the underlying mechanisms of radiation-induced DNA damage and the resulting observable biological effects when radiation parameters and/or environmental conditions change.
Purpose There is an increasing interest in calculating linear energy transfer (LET) distributions for proton therapy treatments in order to assess the influence of this quantity in biological terms. Microdosimetric Monte Carlo (MC) simulations are useful tools to calculate dose‐averaged LET, as this has been broadly proposed as the most adequate quantity to characterize these biological effects. However, a straightforward uniform sampling of the scoring site turns out to be computationally unaffordable. In contrast, some issues have been pointed out with the more efficient weighted sampling approach, frequently used in literature. Here, we address the issues associated with the latter method and propose adequate corrections to achieve reliable calculations of dose‐averaged LET values from microdosimetry. Methods and materials Proton track structures have been simulated with Geant4‐DNA considering two different approaches. One version employs a uniform sampling for placing the spherical site and is used as the reference. The other one uses a weighted sampling by considering the spatial distribution of transfer points. Some corrections are proposed for calculating a dose‐averaged LET comparable to the reference case. An additional MC approach is proposed to obtain the weighted mean of the energy imparted per electronic collision of the proton within the site, the δ2 function, related to the straggling distribution, as an intermediate step in the LET calculation. Results Energy imparted per event distributions are different when employing either sampling methods, due to the different geometrical randomness. We have found an agreement below (0.15 ± 0.05) keV/μm in the worst case for uniform and weighted methods in dose‐averaged LET values when the weighted sampling results are corrected according to our proposal. Our analysis is restricted to spherical sites of 1 and 10 μm diameter and monoenergetic beams in the range from 2 to 90 MeV. Conclusions This work shows a reliable and computational‐efficient method to perform calculations of track segment dose‐averaged LET using MC simulations for proton therapy beams, including the necessary considerations for obtaining the straggling distribution characteristics. The validity of this approach remains as long as the stopping power of the proton can be considered as constant along its track within the site.
Colorectal cancer is one of the most frequent type of cancer, with a higher incidence in the developed countries. Colorectal cancer is usually managed with both surgeries, chemotherapy and radiotherapy. Radiotherapy has the well-known advantage of targeting the tumor, minimizing normal tissue exposure. Nevertheless, during radiation treatment, exposure of healthy tissues is of great concern, in particular because of the effects on the intestinal barrier functions and on cells belonging to the immune system. The functional role of intestinal barrier in avoiding paracellular trafficking and controlling bacterial spread from gut it is well known and it is due to the presence of tight junction complexes. However, intestinal barrier is fundamental in participating to the interplay with immune system, especially considering the gut-associated lymphoid tissue. Until few years ago, radiotherapy was considered to bear only a depressive action on the immune system. However, it is now recognized that the release of pro-inflammatory signals and phenotypic changes in tumoral cells due to ionizing radiation could trigger the immune system against the tumor. In this work, we address how intestinal barrier functions are perturbed by X-ray doses in the range 0–10 Gy, focusing on the interplay between tumoral cells and the immune system. To this aim, we adopted a coculture model in which Caco-2 cells can be grown in presence/absence of peripheral blood mononuclear cells (PBMC). We focused our attention on changes in the proliferation, trans-epithelial electrical resistance (TEER), cytokine release, and proteins of the junctional complexes. Our results indicate a high radioresistance of Caco-2 in the investigated dose range, and an increased permeability of the tumoral cell layer due to the presence of PBMC. This is found to be correlated with activation of PBMC, inhibiting the apoptotic pathway, with the enhancement of cytokine release and with variation of tight junction scaffold protein expression levels, assumed to be related to IFN-γ- and TNF-α-mediated signaling.
The consideration of how a given technique affects results of experimental measurements is a must to achieve correct data interpretation. This might be challenging when it comes to measurements on biological systems, where it is unrealistic to have full control (e.g. through a software replica) of all steps in the measurement chain. In this work we address how the effectiveness of different radiation qualities in inducing biological damage can be assessed measuring DNA damage foci yields, only provided that artefacts related to the scoring technique are adequately considered. To this aim, we developed a unified stochastic modelling approach that, starting from radiation tracks, predicts both the induction, spatial distribution and complexity of DNA damage, and the experimental readout of foci when immunocytochemistry coupled to 2D fluorescence microscopy is used. The approach is used to interpret γ-H2AX data for photon and neutron exposures. When foci are reconstructed in the whole cell nucleus, we obtain information on damage characteristics “behind” experimental observations, as the average damage content of a focus. We reproduce how the detection technique affects experimental findings, e.g. contributing to the saturation of foci yields scored at 30 minutes after exposure with increasing dose and to the lack of dose dependence for yields at 24 hours.
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