Modelling radiation-induced bystander effect and cellular communication

Radiation Damage in Biomolecules and Cells 3.0

Ionizing radiation is widely used in medicine, not only as a diagnostic tool but also as a therapeutic agent, since about half of cancer patients are treated with ionizing radiation, while most of them are irradiated with X-rays [...].

A method to predict space radiation biological effectiveness for non-cancer effects following intense Solar Particle Events

In addition to the continuous exposure to cosmic rays, astronauts in space are occasionally exposed to Solar Particle Events (SPE), which involve less energetic particles but can deliver much higher doses. The latter can exceed several Gy in a few hours for the most intense SPEs, for which non-stochastic effects are thus a major concern. To identify adequate shielding conditions that would allow respecting the dose limits established by the various space agencies, the absorbed dose in the considered organ/tissue must be multiplied by the corresponding Relative Biological Effectiveness (RBE), which is a complex quantity depending on several factors including particle type and energy, considered biological effect, level of effect (and thus absorbed dose), etc. While in several studies only the particle-type dependence of RBE is taken into account, in this work we developed and applied a new approach where, thanks to an interface between the FLUKA Monte Carlo transport code and the BIANCA biophysical model, the RBE dependence on particle energy and absorbed dose was also considered. Furthermore, we included in the considered SPE spectra primary particles heavier than protons, which in many studies are neglected. This approach was then applied to the October 2003 SPE (the most intense SPE of solar cycle 23, also known as "Halloween event") and the January 2005 event, which was characterized by a lower fluence but a harder spectrum, i.e., with higher-energy particles. The calculation outcomes were then discussed and compared with the current dose limits established for skin and blood forming organs in case of 30-days missions. This work showed that the BIANCA model, if interfaced to a radiation transport code, can be used to calculate the RBE values associated to Solar Particle Events. More generally, this work emphasizes the importance of taking into account the RBE dependence on particle energy and dose when calculating equivalent doses.

Modeling of ionizing radiation-induced chromosome aberration and tumor prevalence based on two classes of DNA double-strand breaks clustering in chromatin domains

There has been some controversy over the use of radiobiological models when modeling the dose-response curves of ionizing radiation (IR)-induced chromosome aberration and tumor prevalence, as those curves usually show obvious non-targeted effects (NTEs) at low doses of high linear energy transfer (LET) radiation. The lack of understanding the contribution of NTEs to IR-induced carcinogenesis can lead to distinct deviations of relative biological effectiveness (RBE) estimations of carcinogenic potential, which are widely used in radiation risk assessment and radiation protection. In this work, based on the initial pattern of two classes of IR-induced DNA double-strand breaks (DSBs) clustering in chromatin domains and the subsequent incorrect repair processes, we proposed a novel radiobiological model to describe the dose-response curves of two carcinogenic-related endpoints within the same theoretical framework. The representative experimental data was used to verify the consistency and validity of the present model. The fitting results indicated that, compared with targeted effect (TE) and NTE models, the current model has better fitting ability when dealing with the experimental data of chromosome aberration and tumor prevalence induced by multiple types of IR with different LETs. Notably, the present model without introducing an NTE term was adequate to describe the dose-response curves of IR-induced chromosome aberration and tumor prevalence with NTEs in low-dose regions. Based on the fitting parameters, the LET-dependent RBE values were calculated for three given low doses. Our results showed that the RBE values predicted by the current model gradually decrease with the increase of doses for the endpoints of chromosome aberration and tumor prevalence. In addition, the calculated RBE was also compared with those evaluated from other models. These analyses show that the proposed model can be used as an alternative tool to well describe dose-response curves of multiple carcinogenic-related endpoints and effectively estimate RBE in low-dose regions.

Radiation Damage in Biomolecules and Cells 2.0

It is well known that ionizing radiation, when it hits living cells, causes a plethora of different damage types at different levels [...].

Computational Biophysical Modeling of the Radiation Bystander Effect in Irradiated Cells

It is well known that ionizing radiation can cause damages to cells that interact with it directly. However, many studies have shown that damages also occur in cells that have not experienced direct interaction. This is due to the so-called bystander effect, which is observed when the irradiated cell sends signals that can damage neighboring cells. Due to the complexity of this effect, it is not easy to strictly describe it biophysically, and thus it is also difficult to simulate. This article reviews various approaches to modeling and simulating the bystander effect from the point of view of radiation biophysics. In particular, the last model presented within this article is part of a larger project of modeling the response of a group of cells to ionizing radiation using Monte Carlo methods. The new approach presented here is based on the probability tree, the Poisson distribution of signals and the saturated dose-related probability distribution of the bystander effect’s appearance, which makes the model very broad and universal.

REVIEW OF QUANTITATIVE MECHANISTIC MODELS OF RADIATION-INDUCED NON-TARGETED EFFECTS (NTE)

Quantitative mechanistic modeling of the biological effects of ionizing radiation has a long rich history. Initially, it was dominated by target theory, which quantifies damage caused by traversal of cellular targets like DNA by ionizing tracks. The discovery that mutagenesis, death and/or altered behavior sometimes occur in cells that were not themselves traversed by any radiation tracks but merely interacted with traversed cells was initially seen as surprising. As more evidence of such 'non-targeted' or 'bystander' effects accumulated, the importance of their contribution to radiation-induced damage became more recognized. Understanding and modeling these processes is important for quantifying and predicting radiation-induced health risks. Here we review the variety of mechanistic mathematical models of nontargeted effects that emerged over the past 2-3 decades. This review is not intended to be exhaustive, but focuses on the main assumptions and approaches shared or distinct between models, and on identifying areas for future research.

A reaction-diffusion model for radiation-induced bystander effects

We develop and analyze a reaction-diffusion model to investigate the dynamics of the lifespan of a bystander signal emitted when cells are exposed to radiation. Experimental studies by Mothersill and Seymour 1997, using malignant epithelial cell lines, found that an emitted bystander signal can still cause bystander effects in cells even 60 h after its emission. Several other experiments have also shown that the signal can persist for months and even years. Also, bystander effects have been hypothesized as one of the factors responsible for the phenomenon of low-dose hyper-radiosensitivity and increased radioresistance (HRS/IRR). Here, we confirm this hypothesis with a mathematical model, which we fit to Joiner's data on HRS/IRR in a T98G glioma cell line. Furthermore, we use phase plane analysis to understand the full dynamics of the signal's lifespan. We find that both single and multiple radiation exposure can lead to bystander signals that either persist temporarily or permanently. We also found that, in an heterogeneous environment, the size of the domain exposed to radiation and the number of radiation exposures can determine whether a signal will persist temporarily or permanently. Finally, we use sensitivity analysis to identify those cell parameters that affect the signal's lifespan and the signal-induced cell death the most.

Bystander effects and their implications for clinical radiation therapy: Insights from multiscale in silico experiments

Radiotherapy is a commonly used treatment for cancer and is usually given in varying doses. At low radiation doses relatively few cells die as a direct response to radiation but secondary radiation effects, such as DNA mutation or bystander phenomena, may affect many cells. Consequently it is at low radiation levels where an understanding of bystander effects is essential in designing novel therapies with superior clinical outcomes. In this paper, we use a hybrid multiscale mathematical model to study the direct effects of radiation as well as radiation-induced bystander effects on both tumour cells and normal cells. We show that bystander responses play a major role in mediating radiation damage to cells at low-doses of radiotherapy, doing more damage than that due to direct radiation. The survival curves derived from our computational simulations showed an area of hyper-radiosensitivity at low-doses that are not obtained using a traditional radiobiological model.

Cellular automaton-based model for radiation-induced bystander effects

BACKGROUND

The radiation-induced bystander effect is a biological response observed in non-irradiated cells surrounding an irradiated cell. The bystander effect is known to be induced by two intercellular signaling pathways, the medium-mediated pathway (MDP) and the gap junctional pathway (GJP). To investigate the relative contribution of each signaling pathway, we have developed a mathematical model of the cellular response through these two pathways, with a particular focus on cell-cycle modification.

METHODS

The model is based on a cellular automaton and consists of four components: (1) irradiation, (2) generation and diffusion of intercellular signals, (3) induction of DNA double-strand breaks (DSBs), and (4) cell-cycle modification or cell death. The intercellular signals are generated in and released from irradiated cells. The signals through the MDP and the GJP are modeled independently based on diffusion equations. The irradiation and both signals raise the number of DSBs, which determines transitions of cellular states, such as cell-cycle arrest or cell death.

RESULTS

Our model reproduced fairly well previously reported experimental data on the number of DSBs and cell survival curves. We examined how radiation dose and intercellular signaling dynamically affect the cell cycle. The analysis of model dynamics for the bystander cells revealed that the number of arrested cells did not increase linearly with dose. Arrested cells were more efficiently accumulated by the GJP than by the MDP.

CONCLUSIONS

We present here a mathematical model that integrates various bystander responses, such as MDP and GJP signaling, DSB induction, cell-cycle arrest, and cell death. Because it simulates spatial and temporal conditions of irradiation and cellular characteristics, our model will be a powerful tool to predict dynamical radiobiological responses of a cellular population in which irradiated and non-irradiated cells co-exist.

A mathematical model of radiation-induced responses in a cellular population including cell-to-cell communications

Cell-to-cell communication is an important factor for understanding the mechanisms of radiation-induced responses such as bystander effects. In this study, a new mathematical model of intercellular signalling between individual cells in a cellular population is proposed. The authors considered two types of transmission of signals: via culture medium and via gap junction. They focus on the effects that radiation and intercellular signalling have on cell-cycle modification. The cell cycle is represented as a virtual clock that includes several checkpoint pathways within a cyclic process. They also develop a grid model and set up diffusion equations to model the propagation of signals to and from spatially located cells. The authors have also considered the role that DNA damage plays in the cycle of cells which can progress through the cell cycle or stop at the G1, S, G2 or M-phase checkpoints. Results of testing show that the proposed model can simulate intercellular signalling and cell-cycle progression in individual cells during and after irradiation.

Potential implications of the bystander effect on TCP and EUD when considering target volume dose heterogeneity

PURPOSE

In light of in vitro evidence suggesting that radiation-induced bystander effects may enhance non-local cell killing, there is potential for impact on radiotherapy treatment planning paradigms such as the goal of delivering a uniform dose throughout the clinical target volume (CTV). This work applies a bystander effect model to calculate equivalent uniform dose (EUD) and tumor control probability (TCP) for external beam prostate treatment and compares the results with a more common model where local response is dictated exclusively by local absorbed dose. The broad assumptions applied in the bystander effect model are intended to place an upper limit on the extent of the results in a clinical context.

MATERIALS AND METHODS

EUD and TCP of a prostate cancer target volume under conditions of increasing dose heterogeneity were calculated using two models: One incorporating bystander effects derived from previously published in vitro bystander data ( McMahon et al. 2012 , 2013a); and one using a common linear-quadratic (LQ) response that relies exclusively on local absorbed dose. Dose through the CTV was modelled as a normal distribution, where the degree of heterogeneity was then dictated by changing the standard deviation (SD). Also, a representative clinical dose distribution was examined as cold (low dose) sub-volumes were systematically introduced.

RESULTS

The bystander model suggests a moderate degree of dose heterogeneity throughout a target volume will yield as good or better outcome compared to a uniform dose in terms of EUD and TCP. For a typical intermediate risk prostate prescription of 78 Gy over 39 fractions maxima in EUD and TCP as a function of increasing SD occurred at SD ∼ 5 Gy. The plots only dropped below the uniform dose values for SD ∼ 10 Gy, almost 13% of the prescribed dose. Small, but potentially significant differences in the outcome metrics between the models were identified in the clinically-derived dose distribution as cold sub-volumes were introduced.

CONCLUSIONS

In terms of EUD and TCP, the bystander model demonstrates the potential to deviate from the common local LQ model predictions as dose heterogeneity through a prostate CTV varies. The results suggest, at least in a limiting sense, the potential for allowing some degree of dose heterogeneity within a CTV, although further investigation of the assumptions of the bystander model are warranted.

Potential implications on TCP for external beam prostate cancer treatment when considering the bystander effect in partial exposure scenarios

PURPOSE

This work investigated the potential implications on tumour control probability (TCP) for external beam prostate cancer treatment when considering the bystander effect in partial exposure scenarios.

MATERIALS AND METHODS

The biological response of a prostate cancer target volume under conditions where a sub-volume of the target volume was not directly irradiated was modelled in terms of surviving fraction (SF) and Poisson-based TCP. A direct comparison was made between the linear-quadratic (LQ) response model, and a response model that incorporates bystander effects as derived from published in vitro data by McMahon et al. in 2012 and 2013. Scenarios of random and systematic misses were considered.

RESULTS

Our results suggested the potential for the bystander effect to deviate from LQ predictions when even very small (< 1%) sub-volumes of the target volume were directly irradiated. Under conditions of random misses for each fraction, the bystander model predicts a 3% and 1% improvement in tumour control compared to that predicted by an LQ model when only 90% and 95% of the prostate cells randomly receive the intended dose. Under conditions of systematic miss, if even a small portion of the target volume is not directly exposed, the LQ model predicts a TCP approaching zero, whereas the bystander model suggests TCP will improve starting at exposed volumes of around 85%.

CONCLUSIONS

The bystander model, when applied to clinically relevant scenarios, demonstrates the potential to deviate from the TCP predictions of the common local LQ model when sub-volumes of a target volume are randomly or systematically missed over a course of fractionated radiation therapy.

A simulation study of the radiation-induced bystander effect: modeling with stochastically defined signal reemission

The radiation-induced bystander effect (RIBE) has been experimentally observed for different types of radiation, cell types, and cell culture conditions. However, the behavior of signal transmission between unirradiated and irradiated cells is not well known. In this study, we have developed a new model for RIBE based on the diffusion of soluble factors in cell cultures using a Monte Carlo technique. The model involves the signal emission probability from bystander cells following Poisson statistics. Simulations with this model show that the spatial configuration of the bystander cells agrees well with that of corresponding experiments, where the optimal emission probability is estimated through a large number of simulation runs. It was suggested that the most likely probability falls within 0.63–0.92 for mean number of the emission signals ranging from 1.0 to 2.5.

Effect of site-specific bronchial radon progeny deposition on the spatial and temporal distributions of cellular responses

Inhaled short-lived radon progenies may deposit in bronchial airways and interact with the epithelium by the emission of alpha particles. Simulation of the related radiobiological effects requires the knowledge of space and time distributions of alpha particle hits and biological endpoints. Present modelling efforts include simulation of radioaerosol deposition patterns in a central bronchial airway bifurcation, modelling of human bronchial epithelium, generation of alpha particle tracks, and computation of spatio-temporal distributions of cell nucleus hits, cell killing and cell transformation events. Simulation results indicate that the preferential radionuclide deposition at carinal ridges plays an important role in the space and time evolution of the biological events. While multiple hits are generally rare for low cumulative exposures, their probability may be quite high at the carinal ridges of the airway bifurcations. Likewise, cell killing and transformation events also occur with higher probability in this area. In the case of uniform surface activities, successive hits as well as cell killing and transformation events within a restricted area (say 0.5 mm(2)) are well separated in time. However, in the case of realistic inhomogeneous deposition, they occur more frequently within the mean cycle time of cells located at the carinal ridge even at low cumulative doses. The site-specificity of radionuclide deposition impacts not only on direct, but also on non-targeted radiobiological effects due to intercellular communication. Incorporation of present results into mechanistic models of carcinogenesis may provide useful information concerning the dose-effect relationship in the low-dose range.

Radiation-induced perturbation of cell-to-cell signalling and communication

The investigation of the bystander phenomena (i.e. the induction of damage in cells not directly traversed by radiation) is strictly related to the study of the mechanisms of intercellular communication and of the perturbative effects of radiation. A new possible way to try to solve the bystander puzzle is through a 'systems radiation biology' approach with the total integration of experimental and theoretical activities. In particular, this contribution will focus on: (1) 'ad hoc' experiments designed to quantify key parameters involved in intercellular signalling (focusing, as a pilot study, on release, decay and internalization of interleukine-6 molecules, their modulation by radiation, and possible differences between in vivo/in vitro behaviour); (2) the implementation and the development of two different modelling approaches: a stochastic model (based on a Monte Carlo code) that takes account of the local mechanisms of release and internalization of signalling molecules (e.g. cytokines) and an analytical model where signal molecules are treated as a population and their temporal behaviour is described by differential equations. This approach provided instruments to investigate the complex phenomena of signal transmission and the role of cell communication to guarantee (maintain) the robustness of the in vitro experimental systems against the effects of perturbations.

Targeted and non-targeted effects from combinations of low doses of energetic protons and iron ions in human fibroblasts

PURPOSE

In space, astronauts are exposed to mixed radiation fields consisting of energetic protons and high atomic number, high energy (HZE) particles at low dose rates. Therefore, it is critical to understand effects of combinations of low doses of different radiation types at the cellular level.

MATERIALS AND METHODS

AG01522 normal human skin fibroblasts and a transwell insert co-culture system were used. Irradiations used were 1 GeV/amu (gigaelectron volt/atomic mass unit) protons and 1 GeV/amu iron (Fe) ions. DNA damage was measured as micronucleus (MN) formation and p53 binding protein 1 (53BP1) foci induction.

RESULTS

The same magnitude of DNA damage was induced in cells sequentially exposed to 1 cGy protons and 1 cGy Fe ions as in cells irradiated with either protons or Fe ions alone. The same magnitude of DNA damage was also observed in non-irradiated bystander cells sharing medium with cells irradiated with either 1 cGy protons or iron ions or protons plus iron ions. However, when the 'bystander' cells were exposed to 1 cGy protons up to 3 h before co-culture with Fe ion-irradiated cells, no DNA damage in the 'bystander' cells was observed.

CONCLUSIONS

These data provide the first evidence of interactions between targeted and non-targeted DNA damage caused by dual exposure to low doses of energetic protons and iron ions.

A mathematical framework for separating the direct and bystander components of cellular radiation response

A mathematical model for fractional tumor cell survival was developed incorporating components of cell killing due to direct radiation interactions and bystander signals resulting from non-local dose deposition.

MATERIAL AND METHODS

Three possible mechanisms for signal production were tested by fitting predictions to available experimental results for tumor cells (non-small cell lung cancer NCI-H460 and melanoma MM576) exposed to gradient x-ray fields. The parameter fitting allowed estimation of the contribution of bystander signaling to cell death (20-50% for all models). Separation of the two components of cell killing allowed determination of the α and β parameters of the linear-quadratic model both with and without the presence of bystander signaling.

RESULTS AND DISCUSSION

For both cell lines, cell death from bystander signaling and direct radiation interactions were comparable. For NCI-H460 cells, the values for α and β were 0.18 Gy⁻¹ and 0.10 Gy⁻² respectively when direct and bystander effects were combined, and 0.053 Gy⁻¹ and 0.061 Gy⁻² respectively when the signaling component was removed. For MM576, the corresponding respective values were 0.09 Gy⁻¹ and 0.011 Gy⁻² for the combined response, and 0.014 Gy⁻¹ and 0.002 Gy⁻² for the isolated direct radiation response. The bystander component in cell death was found to be significant and should not be ignored. Further experimental evidence is required to determine how these results translate to the in vivo situation where tumor control probability (TCP) models that currently assume cellular independence may need to be revised.

Effects of ionizing radiation on cell-to-cell communication

Cell-to-cell signaling has become a significant issue in radiation biology due to experimental evidence, accumulated primarily since the early 1990s, of radiation-induced bystander effects. Several candidate mediators involved in cell-to-cell communication have been investigated and proposed as being responsible for this phenomenon, but the current investigation techniques (both theoretical and experimental) of the mechanisms involved, due to the particular set-up of each experiment, result in experimental data that often are not directly comparable. In this study, a comprehensive approach was adopted to describe cell-to-cell communication (focusing on cytokine signaling) and its modulation by external agents such as ionizing radiation. The aim was also to provide integrated theoretical instruments and experimental data to help in understanding the peculiarities of in vitro experiments. Theoretical/modeling activities were integrated with experimental measurements by (1) redesigning a cybernetic model (proposed in its original form in the 1950s) to frame cell-to-cell communication processes, (2) implementing and developing a mathematical model, and (3) designing and carrying out experiments to quantify key parameters involved in intercellular signaling (focusing as a pilot study on the release and decay of IL-6 molecules and their modulation by radiation). This formalization provides an interpretative framework for understanding the intercellular signaling and in particular for focusing on the study of cell-to-cell communication in a "step-by-step" approach. Under this model, the complex phenomenon of signal transmission was reduced where possible into independent processes to investigate them separately, providing an evaluation of the role of cell communication to guarantee and maintain the robustness of the in vitro experimental systems against the effects of perturbations.

Nanoparticles can cause DNA damage across a cellular barrier

The increasing use of nanoparticles in medicine has raised concerns over their ability to gain access to privileged sites in the body. Here, we show that cobalt-chromium nanoparticles (29.5 +/- 6.3 nm in diameter) can damage human fibroblast cells across an intact cellular barrier without having to cross the barrier. The damage is mediated by a novel mechanism involving transmission of purine nucleotides (such as ATP) and intercellular signalling within the barrier through connexin gap junctions or hemichannels and pannexin channels. The outcome, which includes DNA damage without significant cell death, is different from that observed in cells subjected to direct exposure to nanoparticles. Our results suggest the importance of indirect effects when evaluating the safety of nanoparticles. The potential damage to tissues located behind cellular barriers needs to be considered when using nanoparticles for targeting diseased states.

Extrapolating radiation-induced cancer risks from low doses to very low doses

There is strong evidence that ionizing radiation increases cancer risks at high doses (e.g., >or=1 Gy), and persuasive, if controversial, epidemiological evidence that cancer risks are increased at low doses ( approximately 10 mGy). Discussed here are the issues related to extrapolating radiation risks from low radiation doses to very low doses (<or=1 mGy) - for which purpose we are forced to rely on radiobiological evidence and biophysical arguments. At high doses, cells are typically hit by many tracks of radiation, while at low doses most cells are typically hit by a single track of radiation; at very low doses proportionately fewer cells are hit, again only by a single track of radiation. Thus, in comparing low doses to very low doses, the damage to hit cells remains essentially the same (a single radiation track passing through a cell), but what changes is the number of cells that are subjected to this same damage, which decreases linearly as the dose decreases. This is the argument for a linear no-threshold (LNT) model. It is important to emphasize that this LNT argument only applies to the extrapolation from low doses to very low doses, not from high to low doses. Of course there are caveats to this argument, such as the potential effects of phenomena such as inter-cellular communication and immunosurveillance, and the possibility of different radiobiological processes at very low doses, compared to low doses. However, there is little conclusive experimental evidence about the significance of these phenomena at very low doses, and comparative mechanistic studies at high doses vs. low doses will not be informative in this context. At present, we do not know whether such radiobiological phenomena would produce small or large perturbations, or even whether they would increase or decrease cancer risks at very low doses, compared with the prediction of a linear extrapolation from low doses.

Experimental and theoretical analysis of cytokine release for the study of radiation-induced bystander effect

PURPOSE

To clarify the experimental conditions that might influence the release of cytokines in the culture medium and give some basic input for building a model for cytokine (e.g., Interleukin-6, IL-6) regulation in the case of 'sham irradiation' and after ionising radiation exposure.

MATERIALS AND METHODS

The influence of cell type, cell density, medium volume, medium storage temperature and other methodological aspects on IL-6 and Interleukin-8 (IL-8) release were investigated. In addition, the effects over the time of different doses of gamma irradiation on the clonogenic survival of bystander cells and on the secretion of these cytokines were studied.

RESULTS

We observed significant decreases of clonogenic survival in AG01522 and T98G cells after the transfer of medium collected 5 and 20 h after low doses of gamma irradiation. Concerning the Interleukins' measurements, our experiments showed that the aggregate removal modalities tested, and up to 10 freeze-thaw cycles, do not have significant influence on the measurements of IL-6 concentration in the medium. We also observed that the IL-6 accumulated in the medium of human fibroblasts is not degraded when maintained at 37 degrees C. Sets of experiments demonstrated that cell density or medium volume do not influence the release of IL-6. On the contrary, our results showed that IL-8 released by glioblastoma cells strongly depends on the amount of medium. Finally, the exposure of fibroblasts to gamma irradiation has influence on the release kinetics of both IL-6 and IL-8 with peculiar features.

CONCLUSIONS

This study solved some of the methodological doubts concerning the study of bystander effects by means of the medium transfer technique; moreover it also highlighted some experimental aspects that need to be considered when approaching this sort of experiments.

Anticancer effect of cation lipofectin-mediated CD/5-FC suicide gene system on liver, biliary duct and pancreas carcinoma cells in vitro

AIM: To investigate the anticancer effect of the CD/5-FC suicide gene system on carcinoma cells of liver (Bel7402), bililary duct (QBC) and pancreas (Bxpc3), and to explore the possible anticancer mechanism.

METHODS: The growth curve and multiplication time of Bel-7402 QBC and Bxpc-3 were monitored by MTT; the transfection efficiency of the three kinds of carcinoma cells were detected by FACS after instant transfection. The anticancer efficiency of cation lipofectin-mediated CD/5-FC suicide gene system were monitored by MTT in vitro. Then, we analyzed the relation among multiplication time, transfection efficiency and anticancer effect; the apoptosis of CD/5-FC on the three cell lines were analyzed by FAM, and the apoptosis cells were stained by Hochest33342.

RESULTS: The multiplication time of Bel-7402, QBC and Bxpc-3 was 34.48, 64.94 and 26.29 h respectively, and difference between QBC and BEL-7402, BXPC-3 was significant (P < 0.05); the transfection efficiency of the three cell line were 26.99%, 2.25% and 30.36%, and the difference between QBC, and BEL-7402 and BXPC-3 was significant (P < 0.05); the anticancer efficiency was 83.24%, 16.97% and 92.32%, respectively. The apoptosis rates of the three kinds of carcinoma cells induced by CD/5-FC suicide gene system were 27.8%, 5.49% and 36.5%, respectively.

CONCLUSION: Carcinoma cells with shorter growth cycle and less multiplication time have higher instant transfection efficiency, and are more responsive to CD/5-FC suicide gene therapy. This suicide gene therapy may be a promising method for later malignant tumor in clinic.