01. SaveChild厨 2012年7月12日 01:00:48
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Francis J. Herodin (FRA), Mark H. Whitnall (USA), and Patricia K. Lillis-Hearne (USA)
Subgroup #3 Co-Chairs
Although the Acute Radiation Syndrome (ARS) has been well documented at the clinical level, and mech-anistic information is accumulating rapidly, successful prophylaxis and treatment for ARS is problematic.
There is a pressing need to develop radiation countermeasures that can be used both in the clinic and outside the clinic in operational and mass-casualty scenarios. Subgroup 3 of NATO HFM-099/RTG-033 was estab-lished to direct research on basic and applied research leading to development of safe and effective radiation countermeasures and to report findings to the RTG.
At the inaugural meeting of the RTG in the US in June 2005, the characteristics of a successful counter-measure were discussed in the context of likely scenarios. Strategies for discovering and developing countermeasures candidates were considered and the compounds under development were listed. High-lighted were findings on 5-androstenediol (5-AED), the tocols, genistein, and cytokines. Keynote talks included "Current Status of Treatment of Radiation Injury in the United States" by COL David G. Jarrett, US, and "Current STANAGS and Concept/Capability Gaps?Prioritized Needs as Identified by the NATO
NBC Medical WG by Wing Commander Victor J. Wallace, UK. It was agreed to form Subgroup 3 to extend these activities, with co-chairs from the US and France.
At the second meeting in Sweden in June 2006, the current status of radiation countermeasure research was updated, with added material on mechanisms of action of the most promising candidates, chelation of internalized radionuclides, and pegylated cytokines. The two keynote presentations directly relevant to Sub-group 3‘s aims were "Medical emergency preparedness for activities connected to remediation of Adreeva Bay?Norwegian and Russian Federation regulatory cooperation between authorities and experts," by Dr. Alicja Jaworska, Norway, and "Mitigating the clinical effects of ionising radiation: An update on perceived capability and research gaps from the NATO NBC Medical Working Group," by Dr. David C. Bates, UK.
The third meeting in the Czech Republic in June 2007 presented advances in studies on the candidates discussed at previous meetings, and also included a presentation on cell and gene therapy.
The fourth and final meeting was held in France in June 2008. Two keynote lectures related to the subgroup‘s goals: "Medical management of irradiated victims in nuclear/biological accidents or mass-casualty acts of
terrorism," by Dr. T. De Revel, and "State of art of the medical management of radiological burns," by Dr. Herve Lebever, both of France. In addition to updates on countermeasures in development, there was an added
emphasis on responses to radiation dispersal devices, with a talk by Dr. Daniela Stricklin on that subject.
It is clear from the research and development efforts discussed in Subgroup 3 that promising countermeasure candidates exist at the preclinical stage. Development programs are moving into trials in large animal models as
well as clinical safety trials, with the appropriate interactions with regulatory agencies taking place to facilitate eventual approval of these countermeasures as human pretreatments and therapies. No countermeasures for
ARS have been approved for human use in a radiation disaster scenario. The most progress has been made in terms of mitigating the consequences of radiation doses corresponding to the ―hematopoietic syndrome,?
although it is recognized that interactions between multiple organ systems are involved. Efforts are underway to develop countermeasures appropriate for higher radiation doses causing the ―gastrointestinal syndrome.?
1.4 RTG 033 Subgroup 4: Combined Injuries and Treatment: Summary of Activities
Terry C. Pellmar (USA), Daniela L. Stricklin (SWE), and David C.B. Holt (GBR) Subgroup #4 Co-Chairs
Combined injuries of radiation plus trauma or other exposures are likely to be more deadly than any injury or exposure alone. Clinical, animal, and cellular studies suggest synergistic effects. To be fully prepared for a nuclear or radiological event, it will be important to understand the potential interactions, medical con-sequences, and treatment options when combined effects are encountered. In its inaugural meeting, NATO
HFM-099/RTG-033 established a subgroup to address the problem of combined injury. At the first meeting, delegates from the US, UK, SW agreed to co-chair a group to consider the state of the research, status of casualty prediction models as they relate to consideration of combined injuries, and areas of potential labor-atory collaboration.
At the first meeting (June 2005; agenda), the US presented an overview of the effects of radiation in combination with trauma, infectious disease, or chemical exposures. Another presentation addressed the issues associated with antimicrobials in the management of post-irradiation infection. Approaches to dealing with wounds from depleted uranium fragments were discussed in two talks, one providing a synopsis of the status of health concerns about military use of depleted uranium and surrogate metals in munitions, and the other on the development of a colorimetric test for uranium. At this meeting the task group outlined its goals for the three years and began the process of defining the critical aspects of this research effort.
Discussions at the second meeting (June 2006; agenda) centered on biomarkers for combined injuries. The delegates from Sweden discussed concepts regarding the relevance of biomarkers of chemical-induced injury. The delegates from France spoke on their studies of responses to combined injuries in nonhuman primates and relevant neuro-immune biomarkers of prognosis. Discussions at this meeting raised concerns regarding exposures to chemicals in the environment following a radiological or nuclear event. As a result, the focus expanded from only co-exposures of radiation and battlefield trauma or WMD to likely exposures to endemic toxicants, pathogens, and industrial chemicals.
Presentations at the third meeting (June 2007; agenda) addressed the status of ountermeasures for combined injury in radiation threat environment and mathematical modeling of radiation health effects, current state and future plans. These resentations clearly revealed some of the gaps in the field. Few radiation counter-measures had been tested with combined injuries and some of those that were produced nexpected results.
The modeling of combined injury was still in its early stages. It was clear from iscussions that additional experiments were needed to feed into the models and that the models could provide some interesting predictions that should be tested in the laboratory.
At the fourth and final meeting (June 2008; agenda) the presentations focused on modeling efforts. One talk provided an update on mathematical modeling of radiation health effects. Another presentation reviewed the
models of human response to nuclear effects as a function of systems, signs, and symptoms that would be used for operational purposes.
Discussions over the lifetime of this panel have raised awareness of the concerns about combined injuries and stimulated new interactions and collaborative efforts among the NATO members. Countries have sought to contribute by building on their own strengths. Animal research, where it is possible, has contributed to understanding combined injuries in relationship to systemic effects. Cellular research has pointed out new areas of concern. Incorporation of the data into models have benefited from stimulating intellectual discussions among all participating colleagues regarding anticipated scenarios and their consequences. From the interactions of the task group, the efforts on combined injury have evolved into a richer and more mature area of investigation.
Subgroup 4 of NATO HFM-099/RTG-033 has written a final report that summarizes its discussions and interactions. The final report describes 1) the likelihood of combined injuries; 2) the complexities of interactions of radiation with trauma, infectious agents, and chemical agents; 3) the capability of biomarkers of individual susceptibility to provide new diagnostic tools; and 4) models of the human response to combined injury that can guide future studies to define mechanisms, assess outcomes and develop countermeasures. RTG 033 Subgroup 1: Radiobiology Mechanisms and Late Effects
Chapter 2
Development of Models to Study Radiation-Induced Late Effects
Alexandra C. Miller
Armed Forces Radiobiology Research Institute Uniformed Services University
8901 Wisconsin Avenue, Building 42 Bethesda, MD 20889-5603 USA ABSTRACT Military and NATO personnel can potentially be exposed to external and internal radiation during military operations. Radiation exposure can cause late effects like cancer, leukemia, genetic effects, and possible effects to offspring. A multi-parametric in vitro and in vivo approach has shown effectiveness in providing information regarding radiation induced carcinogenicity, promising radiation countermeasures, and trans-generational radiation effects. These in vitro and in vivo models can be used evaluate the specific radiation exposure scenarios experienced by military and NATO personnel.
1.0 INTRODUCTION
Military and NATO personnel can potentially be exposed to external and internal radiation during military operations. The external radiation can occur via a nuclear weapons explosion; another scenario is the use of a “dirty bomb” by terrorists. Nuclear weapons exposure is a significant health hazard; while the damage due to radiation from a dirty bomb could be significantly lower, there is still a threat of some type of radiation injury. In terms of internal radiation exposure to military personnel, the radioactive heavy metal depleted uranium (DU) is the most possible type of exposure. DU is used in military munitions and personnel can be wounded by DU shrapnel. A soldier wounded by internalized DU is considered to be carrying an internal emitter. While radioactive material that is inhaled or swallowed would be excreted from the system, embedded DU via a wound would not be rapidly excreted and presents a long-term hazard. These types of “battlefield” radiation exposures are unique to military personnel and are different than the high-dose fractionated therapeutic exposures that the average civilian might be exposed to during their lifetime.
High-dose radiation exposure can cause significant acute health effects including radiation syndrome and potentially death. Late health effects caused by radiation are also a significant health hazard. These late effects include cancer, leukemia, cytogenetic effects, and transgenerational effects to offspring. It is well known that radiation exposure can lead to cancer development and in particular to development of leukemia [1?4]. While there is significant human and animal data regarding the induction of high-dose radiation-induced cancers, less attention has been paid to whether the unique military radiation exposures like internalized DU or low-dose radiation potentially from dirty bombs can cause late health effects like cancer and genetic effects. To better study the radiation late effects induced by the unique military radiation exposures a multi-parametric approach has been used in our laboratory at AFRRI. Implementation of cell- and animal-based multi-parametric assays can provide predictive information and be a guide as to whether human studies should be ursued. This strategic research approach involving the progression from cellular studies to animal model has been applied to radiation and heavy-metal studies in our laboratory (Figure 1).
Carcinogenic Hazard Evaluation
Transformation + Mutagenicity + Cytogenicity
Animal Carcinogenesis Model
Human Epidemiology
Figure 1: Short-term tests for carcinogenicity 2.0 LONG-TERM GOALS
The long-term research goals and benefits using the multi-parametirc approach are three-fold. First, the evaluation of potential carcinogenic exposures from radiation and/or DU in exposed individuals can be evaluated. Secondly, the development of nontoxic countermeasures to radiation-induced cancers can be undertaken. Thirdly, the potential discovery of biomarkers of exposure and disease development should be conducted simultaneously to the in vitro and in vivo cancer studies. The technical objectives of this approach include: 1) development of in vitro models to study radiation-induced late effects and radiobiology mech-anisms, and 2) development of in vivo models to study radiation-induced late effects and evaluate efficacy of pharmacological countermeasures. 3. 0 MULTI-PARAMETRIC RESEARCH APPROACH
The in vitro models that we have developed in our laboratory can be applied to everal research questions related to radiation late effects. These include: 1) neoplastic transformation models using human cells have been used to assess transformation; 2) the same transformation models have been used for rapid screening of pharmacological countermeasures; 3) a mutagenesis assay, the HPRT mutation assay (hypoxanthine guanine phosphoribosyl transferase), to measure mutagenesis has been established; 4) chromosomal aberration assays to measure chromosomal damage and genomic instability (potentially involved in carcinogenesis) have been
developed; and 5) clonal cell assays to measure radiobiology mechanisms, i.e., uranium “bystander” effects have been established.
Several of these assays can be used in combination to address the question as to whether a particular type of exposure is potentially carcinogenic. For example, our laboratory at AFRRI has used these in vitro assays to evaluate whether DU is carcinogenic. As shown in Figure 2, neoplastic transformation, mutagenicity, genotoxicity, and genomic instability were used to assay potential DU carcinogenicity. This slide contains data from our DU studies using human osteoblast cells (HOS) as our model system. Four endpoints were examined. These include mutagenicity, genotoxicity, neoplastic transformation, and genomic instability. A comparison was made to nickel and to external alpha particles. The DU exposure resulted in 17% of the cell nuclei being traversed by an alpha particle as measured by microdosimetry. In this multi-parametric in vitro approach, human cells are exposed to the test exposure/material and then plated for colony formation. An evaluation of colony morphology was used to define the state of transformation of the exposed cells. Further studies on the genotoxicity (measured as a sister chromatid exchange) and mutagenicity (measured as a mutation in the HPRT gene) were used in this multi-parameter approach.
Figure 2: In vitro assays to assess carcinogenic potential
These studies were the first to show that DU could transform human cells into the malignant phenotype and thus demonstrate the carcinogenic potential of DU. The additional assays including mutagenicity, geno-toxicity, and genomic instability, performed with this uranium compound further supported the finding the DU had carcinogenic potential even before animal or human studies were conducted. These in vitro models are an effective means to evaluate the carcinogenic potential of a particular type of exposure because they will enable the investigation to study a range of carcinogenic endpoints and provide rapid results.
This use of this multi-parametric approach is also effective for evaluating potential countermeasures to the late effects of radiation or internal emitters like DU. In particular the neoplastic transformation endpoint has been used to study potential radiation countermeasures. For example, as shown in Figure 3, our laboratory was able to preliminarily assess the efficacy of several pharmacological agents. In this assay we assessed the ability of these candidate drugs to inhibit malignant transformation in vitro. Data (transformation frequency) are shown in this figure for radiation (60Cobalt γ-rays) followed by a 15 day incubation with the candidate
agents. In this case we tested phenylactetate (PA), androstendiol (AED), and epigallocatechin gallate (EGCG), which were selected based on mechanistic considerations and low toxicity in vitro. Suppression of radiation-induced transformation was observed in cells treated with PA, AED, and EGCG under certain drug treatment conditions (drug exposure for 15 continuous days post-radiation).
Figure 3: Application of neoplastic transformation assay to screen potential chemoprevention agents
These data confirm that the in vitro transformation model can be used to screen for efficacy of potential radiation-chemopreventive agents and specifically indicate which of these agents should be next tested in the more laborious and expensive in vivo assays.
To evaluate potential late effects of radiation exposures to military personnel, in vivo models are also used. A multiparametric approach, similar to the in vitro approach, has been developed using several different animal models to study radiation carcinogenic effects. In contrast to in vitro models these in vivo models do not just focus on the development of late effects in the exposed cells or animals but are extended to an evaluation of how radiation exposure to one individual can affect another unexposed individual. Furthermore, these in vivo models enable a study of the most promising pharmacological countermeasures that were identified using the
in vitro methods. This multi-parametric in vivo approach involves the use of a leukemia model, a rapid trans-planted tumor model, and a transgenerational animal model to investigate offspring effects (Figure 4).
Development and application of in vivo models
1. Radiation- or depleted uranium-induced leukemia model in mice to study carcinogenesis and test late-effects countermeasures.
2. “Big blue” transgenic mouse model to study transgenerational radiation or DU effects on unexposed offspring.
3. Transplanted S-180 mouse tumor to rapidly screen pharmacological countermeasures rapidly (within 45 days).
Figure 4: Development and application of in vivo models First, a leukemia model is used to determine whether the type of exposure in questions can induce leukemia.
This model involves the injection of immature hematopoietic cells into irradiated or DU-exposed mice (Figure 5).
Figure 5: Radiation-induced leukemia DBA mice + (FDCPI cells) 60Cobalt gamma
The leukemia takes about 90?120 days to develop in irradiated animals. Control animals (un-irradiated) develop age-related leukemia only after approximately 300 days. This model is appropriate to evaluate radiation quality, radiation dose-rate, and radiation route-of-exposure effects, i.e., DU. For example our laboratory has used the model to examine and compare the effects of 60Cobalt γ-rays induced leukemia versus DU-induced leukemia (Figure 6) [5]. This leukemia model can also be further studied to evaluate the potential mechanisms involved in the leukemogenic process including epigenetic effects and the role of genomic instability. This model also has the potential to be used to assess the efficacy of late effects counter-measures since a comparison of the candidate drug to a vehicle can be conducted using this model.
Figure 6: DU carcinogenicity in vivo
An in vivo model to rapidly assess late effects radiation countermeasures is the transplanted tumor model. In this mode a lymphoma cell line is transplanted into the shoulder of a mouse and allowed to grow into a solid tumor. Within 21 days the tumor is palpable and can easily be measured. To test potential pharmacological countermeasures, the tumor is implanted, allowed to grow, and then the candidate drug (s) is administered. The effect on the size of the tumor is measured as a means to assess the efficacy of the drug. Results with PA and EGCG, previously identified as promising candidates with in vitro techniques, are shown in Figure 7. Thus a combination of the in vitro and in vivo methods has enabled us to identify the most promising coun-termeasures which can be further studied in more elaborate animal models.
Figure 7: Effect of EGCG and PA on tumor volumes of S-180 tumor-bearing mice
The third type of in vivo model used to assess radiation late effects involves a mouse model that enables us to determine whether radiation exposure to the parent can affect an unexposed offspring. It is well known that radiation exposure to a pregnant female can cause deleterious offspring effects during gestation [6]. Studies have demonstrated however, that parental preconceptional exposure (PPE) to certain qualities of radiation or heavy metal can induce cancer in unexposed offspring [7?9]. A transgenic mouse model is available that allows an investigation of whether parentral exposure causes offspring effects. This model, known as the
“Big Blue” is particularly effective in assessing whether a father’s exposure can affect unexposed offspring. It employs a transgenic mouse which has been engineered to carry the lacI regulatory gene in all tissues. Therefore, if a transgenic male is mated to a non-transgenic female mouse, approximately 50% of the offspring will carry the transgene, which they can only inherit from their transgenic father. The “Big Blue”
mutation model is appropriate to evaluate offspring responses in fathers exposed to the radiation or type of exposure of interest. Specifically, this model uses a mutation system [8] employing a λ shuttle vector carried by cells of a transgenic mouse (Stratagene Big Blue) that carries the target lacI gene. Big Blue male mice can be exposed to the exposure of interest (i.e., radiation, DU), mated with unexposed non-transgenic females and then the DNA can be recovered from the fathers and the tissues of the F1 offspring (Figure 8).
The recovered DNA is packaged and then assayed in vitro for mutations and detected in viral plaques by the blue color resulting from cellular metabolism. This model has been used in our laboratory to determine whether paternal exposure to DU can transmit genetic damage to the offspring. Bone marrow DNA from offspring identified as lacI carriers in treated and control groups was screened for mutations in the lacI transgene. Table 1 summarizes the bone marrow mutation frequencies found in the hemizygous F1 offspring of male parents exposed to DU, Ta, Ni, or 60Co radiation from the three experiments conducted. “Big Blue” Mutation and Offspring Assessment Assay
Figure 8: Model to assess transgenerational effects of radiation or heavy metals
Theses indicated that mutation frequencies from F1 offspring of DU-implanted fathers demonstrated a dose-dependent increase in comparison to control F1 offspring. Using this transgenic mouse model our laboratory was able to show that internalized DU exposure can cause adverse effects in unexposed offspring. This type of model is applicable to questions of parental exposure and potential deleterious offspring health effects. Table 1: Genotyping of offspring for transmission of the lacI gene Treatment
1
Based on expected 50% transmittal rate, the observed rates do not differ significantly (p > 0.05).
SUMMARY AND CONCLUSIONS
To better study the radiation late effects induced by the unique military radiation exposures, this multi-parametric approach has been used in our laboratory at AFRRI. Implementation of cell- and animal-based multi-parametric assays can provide predictive information and be a guide as to whether human studies should be pursued. This strategic research approach involving the progression from cellular studies to animal model has been applied to radiation and heavy metal studies in our laboratory and has provided a rapid and effective research approach to evaluating radiation risks for NATO and military personnel.
REFERENCES
1. Seed, T.M. Radiation Protectants: Current status and future prospects. Health Physics, 89(5):531?545, (2005).
2. Seed, T,M., Kumar, S., Whitnall, M., Venkataraman, S., Singh, V., Elliott, T., Landauer, M., Miller, A., Chang, C.-M., Inal, C., Deen, J., Genlhaus, M., Jackson III, W., Hilyard, E., Pendergrass, J., Toles, R.,
Villa, V., Miner, V., Stewart, M., Benjack, J., Danilenko, D., and Farrell, C., New strategies for the prevention of radiation Injury. J. Radiat. Res., 43: Suppl.:S239?S244, (2002).
3. Grdina, D.J., Murley, J.S., and Kataoka, Y. Radioprotectants: Current status and new directions. Oncology, 63 Suppl 2:2?10, (2002).
4. Dorr, R.T. Radioprotectants: pharmacology and clinical applications of amifostine. Semin. Radiat. Oncol., 8 (4 Suppl 1):10?13, (1998).
5. Miller, A.C. Leukemic transformation of hematopoietic cells in mice internally exposed to depleted uranium. Molecular Cellular Biochemistry 279(1-2):97?104, (2005).
6. Rugh R. The impact of radiation on the embryo and fetus. AJR, 89:181?190, 1963.
7. Gardner, M.J., Sneed, M.P., Hall, A.J., Powell, C.A., Downes, S., and Terrell, J.D. Results of case-control study of leukemia and lymphoma among young people near Sellafield nuclear plant in West
Cumbria. British Medical Journal. 300(6722):423?9, (1990).
8. Luke, G.A., Riches, A.C., Bryant, P.E., Genomic instability in hematopoietic cells of F1 generation mice of irradiated male parents. Mutagenesis 12(3):147?52, (1997).
9. Lord, B.I., Transgenerational susceptibility to leukemia induction resulting from preconception, paternal irradiation. Int. J. Radiat. Biol. 75(7):801?10, (1999).
10. Miller, A.C. Transgenerational Effects of Depleted Uranium, Health Physics, in press.
HFM Panel-099 RTG-033 Activity: Radiation Bioeffects and Countermeasures RTG 033 Subgroup 1: Radiation Mechanisms and Late Effects
Chapter 3
Stimulation of the natural anti-tumour cells by single or fractionated irradiations of mice with X-rays
M.K. Janiak, E.M. Nowosielska, A. Cheda, J. Wrembel-Wargocka Military Institute of Hygiene & Epidemiology
4 Kozielska Str., Warsaw, Mazovia 01-163 Poland
1.0 INTRODUCTION
In the present day military scenarios involving radiation exposure the majority of the personnel is likely to absorb low to intermediate doses1 of predominantly low-LET2
ionising radiation [2]. Indeed, such doses will be incurred in areas of the enhanced radiation level due to the elevated natural background, contamination after explosions in nuclear installations or dispersal of radioactive material in the environment by other
means (radiation dispersal devices) and even after detonations of tactical nuclear bombs. Absorption of such doses will not evoke any of the acute post-irradiation effects but can potentially be associated with a long-term risk of subsequent cancers. Interestingly, however, accumulating evidence from the recent years indicates that absorption of doses of X- and γ-rays below 0.25 Gy may inhibit rather than exacerbate the development of various neoplasms [3?16].
One of the possible mechanisms of this effect is stimulation of anti-tumour immunity. Natural killer (NK) lymphocytes and activated cytotoxic macrophages are first-line effectors of the anti-neoplastic surveillance system. These cells non-specifically suppress the growth of tumour targets through secretion of a number of cytokines, such as perforins, granzymes, IL-2, IFN-γ, TNF-α, glutathione (NK lymphocytes) or IL-1, IL-12, TNF-α, GM-CSF, nitric oxide, and superoxide anions (activated macrophages). All these factors either directly induce apoptotic death of tumour cells or stimulate other cytolytic effector lymphocytes.
In view of the above, the aim of our study was to assess the effects of single and multiple low- and inter-mediate-level exposures to X-rays on the kinetics and mechanisms of non-specific cytotoxic reactions medi-ated by NK cells and/or macrophages and to correlate these effects with the anti-tumour activity of the irradiations.
We used male BALB/c mice aged 6?8 weeks. Peritoneal macrophages (Mφ) and NK cell-enriched spleeno-cytes (NK cells) obtained form the mice were irradiated in vitro with 0.1, 0.2, or 1.0 Gy X-rays or collected from the animals exposed to: a) single irradiation with 0.1, 0.2 or 1.0 Gy per mouse, or b) fractionated (5 days/week for 2 weeks) irradiation to obtain the absorbed doses of 0.01, 0.02 or 0.1 Gy per mouse per
1
According to the UNSCEAR 1986 Report [1], acute doses above 2 Gy, between 2 and 0.2 Gy, and below 0.2 Gy are regarded as high, intermediate, and low, respectively.
2
LET (Linear Energy Transfer) is a measure of the energy transferred to material as an ionizing particle travels through it. Typically this measure is used to quantify the effects of ionizing radiation on biological specimens.
fraction, so that total absorbed doses per mouse equalled to 0.1, 0.2 or 1.0 Gy, respectively. After the irradi-ations some mice were intravenously injected with syngeneic L1 sarcoma cells, sacrificed fourteen days later and tumour colonies were counted on the surface of the removed lungs. In the separated cell populations the following assays were carried out: a) cytotoxic activity and its suppression by specific inhibitors; b) blockade of the selected mechanisms of cytotoxicity; d) secretion of cytotoxic factors such as nitric oxide (NO), IL-1β, IL-2, IL-12, IFN-γ or TNF-α; e) apoptotic death.
2.0 RESULTS
2.1 Anti-tumour effects of low doses of X rays
The four separate experiments indicated that single whole body irradiation (WBI) of mice with 0.1 or 0.2 Gy led to the significant inhibition of the development of the pulmonary tumour colonies (expressed as percent of the control values measured in the sham-exposed animals). In contrast, no statistically significant reduction in the number of pulmonary tumour nodules could be detected when mice were pre-exposed to 1.0 Gy X-rays (Fig. 1A). The two consecutive experiments indicated that the fractionated WBI of mice with both 0.1 and 0.2 Gy X-rays resulted in the insignificant retardation of the development of pulmonary tumour colonies, whereas irradiation of mice with 1.0 Gy led to the slight increase in the number of the colonies (Fig. 1B).
Figure 1: Relative numbers (percentages of the control values indicated as solid line at 100%) of pulmonary L1 sarcoma cell colonies in mice exposed to single (A) or fractionated (B) 0.1, 0.2 or 1.0 Gy X-rays and two hours later i.v. injected with L1 sarcoma cells. Data are mean values ± SD. Results of four (A) or two (B) independent experiments are shown: each experimental group consisted of 12 mice. *?indicates statistically significant (p < 0.05) difference from the control (100%) value. Injection of the blockers of NK cells (anti-asialo GM1 antibody, anti-GM1 Ab) or macrophages (carrageenan,
CGN) almost totally eliminated the differences in the numbers of tumour colonies between the irradiated and control groups (Fig. 2). This effect was markedly more pronounced in the CGN- than in the anti-GM1 Ab-treated mice.
Figure 2: Relative numbers of pulmonary colonies after single WBI of mice and i.p. injection of anti-GM1Ab or CGN. C?sham-exposed, control mice; 0.1 Gy?mice exposed to a single WBI with 0.1 Gy X-rays; 0.2 Gy ? mice exposed to a single WBI with 0.2 Gy X-rays; 1.0 Gy?mice exposed to a single WBI with 1.0 Gy X-rays; PBS?mice i.p. injected with phosphate buffered saline; Ab?mice i.p. injected with anti-asialo GM1 antibody; CGN?mice i.p. injected with CGN. Presented are means ± SD from three independent experiments; each experimental group consisted of at least 12 mice. *?indicates statistically significant (p < 0.05) difference from the control/PBS (100%) value.
2.2 Mechanisms of the anti-neoplastic activity of NK lymphocytes
A single whole-body exposure of mice to any of the three doses of X-rays significantly stimulated the cytotoxic activity of NK cells, the effect being most pronounced on the second day after the irradiation.
Interestingly, the WBI of mice with 1.0 Gy (the dose that did not lead to inhibition of the growth of the pulmonary tumour nodules) appeared to be a more potent stimulator of the NK cell-mediated cytotoxicity than exposures to either 0.1 or 0.2 Gy X-rays (Fig. 3A). However, stimulatory effect of 1.0 Gy X-rays on the activity of NK cells could be partially explained by the possible elimination of radio-sensitive T and B cells
from the spleen leading to the relative increase in the percentage of the NK effectors in the cytotoxic assay (data not shown). In fact, as indicated by Lin et al. [17] and Harrington et al. [18] NK cells appear to exhibit the greatest radioresistance among the splenic lymphoid cells. Fractionated WBI of mice with either of the three applied doses of X-rays led to the significant enhancement of the cytotoxic function of NK cells to the comparable level in all the three groups (Fig. 3B).
Figure 3: Cytotoxic activity of NK cells tested on various days after the single (A) and fractionated (B) WBI of mice. C?sham-exposed, control mice; 0.1 Gy?mice exposed to WBI with 0.1 Gy X-rays;
0.2 Gy?mice exposed to WBI with 0.2 Gy X-rays; 1.0 Gy?mice exposed to WBI with 1.0 Gy X-rays. Mean values ± SD obtained from three independent experiments are presented; each experimental group consisted of five mice. When mice were injected with the anti-GM1 Ab, the activity of these cells, as tested 2 days later, was totally abrogated. This inhibition could not be reversed by WBI with 0.1 or 0.2 Gy X rays (Fig. 4).
Figure 4: Cytotoxic activity of splenic NK cells (at 100:1 E:T ratio) on the second day after irradiation of mice with 0.1, 0.2 or 1.0 Gy X-rays. C?sham-exposed, control mice; 0.1 Gy?mice exposed to a single WBI with 0.1 Gy X-rays; 0.2 Gy?mice exposed to a single WBI with 0.2 Gy X-rays; 1.0 Gy? mice exposed to a single WBI with 1.0 Gy X-rays; NK?mice i.p. injected with PBS;
NK+Ab?mice injected with anti-asialo GM1 Ab. Presented are means ± SD from three independent experiments; each experimental group consisted of at least three mice. ^?indicates statistically
significant (p<0.05) difference from the control value; *?indicates statistically significant (p<0.05) difference within sham-irradiated and irradiated groups between mice injected with PBS and mice
injected with anti-asialo GM1 Ab.
The elevated cytolytic activity of NK lymphocytes after irradiation of mice with all the three doses of single or fractionated X-rays was, for the most part, mediated by the perforin and the Fas receptor ligand (FasL) pathways (Fig. 5). This was corroborated by the finding that NK cells obtained from mice 2 days after the
single WBI with 0.1 and 0.2 Gy X-rays (i.e. at the time when the cytotoxic function of these cells was maximally stimulated) demonstrated the significantly increased surface expression of FasL as compared to
the cells collected form the sham-exposed animals. No such effect was detected after the irradiation of mice with 1.0 Gy X-rays (Fig. 6).
Figure 5: Inhibition of the NK-type cytotoxic activity of splenocytes by CMA and the anti-FasL Ab on the 2nd day after the single (A) and on the 3rd day after the fractionated (B) WBI of mice. C?sham-exposed, control mice; 0.1 Gy?mice exposed to WBI with 0.1 Gy X-rays; 0.2 Gy?mice exposed to WBI with 0.2 Gy X-rays; 1.0 Gy?mice exposed to WBI with 1.0 Gy X-rays; NK?NK cells incubated without blockers; NK+CMA?NK cells incubated with CMA; NK+ anti-FasL?NK cells incubated with anti-FasL antibody; NK+CMA+anti-FasL? NK cells incubated with CMA and anti-FasL antibody. Mean values ± SD obtained from three independent experiments are presented; each experimental group consisted of five mice. ^?indicates statistically significant (p<0.05) difference between NK cells collected from irradiated mice and the respective NK cells obtained from non-irradiated mice. *?indicates statistically significant (p<0.05) difference within sham-
irradiated or irradiated groups between NK cells incubated with CMA and/or anti-FasL antibody and NK cells incubated without blockers.
Figure 6: Relative (percentage of the control value indicated as solid line at 100%) surface expression of FasL on NK cells two days after a single WBI of mice with 0.1, 0.2 or 1.0 Gy X-rays.
C?sham-exposed, control mice; 0.1 Gy?mice exposed to a single WBI with 0.1 Gy X-rays; 0.2 Gy?
mice exposed to a single WBI with 0.2 Gy X-rays; 1.0 Gy ?mice exposed to a single WBI with 1.0 Gy X-rays. Mean values ± SD obtained from three independent experiments are presented; each experimental group consisted of three mice. *?indicates statistically significant (p<0.05) difference from the control (100%) value.
However, both concanamicin A (CMA), a blocker of perforin, as well as the anti-FasL antibody were unable to totally suppress the cytolytic function the NK cells. These results suggested that the residual cytotoxic activity of the effector cell populations might be due to synthesis and/or secretion of additional cytotoxic and/or cytostatic factors likely to be involved in elimination of neoplastic cells. Indeed, we demonstrated that both single and fractionated WBI of mice with all the three doses of X-rays significantly stimulated synthesis of IL-2 and IFN-γ in the splenocytes and the NK cells, respectively (Figs. 7 and 8). IL-2 is a prominent activator of cytotoxic T and NK lymphocytes [19,20] whereas IFN-γ, although usually not directly cytocidal for tumour cells, stimulates cytolytic functions of macrophages and, together with the macrophage-derived TNF-α and IL-1β, can exert a strong anti-neoplastic effect [21,22].
Figure 7: Production of IL-2 by splenocytes after single (A) or fractionated (B) WBI of mice and incubation with PHA. C?sham-exposed, control mice; 0.1 Gy?mice xposed to WBI with 0.1 Gy X-rays; 0.2 Gy?mice exposed to WBI with 0.2 Gy X-rays; 1.0 Gy?mice exposed to WBI with 1.0 Gy X-rays. Mean values ± SD obtained from three independent experiments are presented; each experimental group consisted of three mice.
Figure 8: Production of IFN-γ by NK cells after single (A) or fractionated (B) WBI of mice and incubation with YAC-1 cells. C?sham-exposed, control mice; 0.1 Gy?mice exposed to WBI with 0.1 Gy X-rays; 0.2 Gy?mice exposed to WBI with 0.2 Gy X-rays;1.0 Gy?mice exposed to WBI with 1.0 Gy X-rays. Mean values ± SD obtained from three independent experiments are presented; each experimental group consisted of three mice. Irradiation of mice with 0.1 or 0.2 Gy of X-rays did not affect the rate of apoptosis in the examined NK cell-suspensions, whereas similar irradiations with 1.0 Gy enhanced the number of apoptotic NK lymphocytes (Fig. 9).
Figure 9: Apoptosis of NK cells after WBI of mice. C?sham-exposed, control mice; 0.1 Gy?mice exposed to WBI with 0.1 Gy X-rays; 0.2 Gy?mice exposed to WBI with 0.2 Gy X-rays ;1.0 Gy?mice exposed to WBI with 1.0 Gy X-rays. Mean values ± SD obtained from three independent experiments are presented; each experimental group consisted of three mice.
2.3 Mechanisms of the anti-neoplastic activity of peritoneal macrophages The three separate experiments indicated that a single WBI of mice with either 0.1 or 0.2 Gy X-rays led to the significant elevation of the cytotoxic activity of the IFN-γ- and LPS-boosted Mφ against the L1 tumour cells, the effect being most pronounced between the third and fifth days post-exposure to X-rays. In contrast,
a single WBI of mice with 1.0 Gy did not affect the cytotoxic function of Mφ (Fig. 10A).
Fractionated WBI of mice with either of the three applied doses of X-rays resulted in the significant enhance-ment of the cytotoxic activity of Mφ to the same level in all the three groups, the effect being most pro-nounced between the second and fifth days post-irradiation and then declined (Fig. 10B).
Figure 10: Cytotoxic activity of the IFN-γ- and LPS-treated Mφ after single (A) or fractionated (B) WBI of mice and incubation with L1 cells. C?sham-exposed, control mice; 0.1 Gy?mice exposed to WBI with 0.1 Gy X-rays; 0.2 Gy?mice exposed to WBI with 0.2 Gy X-rays; 1.0 Gy?mice exposed to WBI with 1.0 Gy X-rays. Mean values ± SD obtained from three independent experiments are presented; each experimental group consisted of five mice.
The stimulated Mφ-mediated cytolysis of susceptible tumour targets was for the most part associated with the elevated production of nitric oxide (NO) that expressed similar kinetics as the cytotoxic activity of these cells (Fig. 11).
Figure 11: Production of NO by the IFN-γ- and LPS-treated Mφ after single (A) or fractionated (B) WBI of mice. C?sham-exposed, control mice; 0.1 Gy?mice exposed to WBI with 0.1 Gy X-rays; 0.2 Gy?mice exposed to WBI with 0.2 Gy X-rays; 1.0 Gy?mice exposed to WBI with 1.0 Gy X-rays. Mean values ± SD obtained from three independent experiments are presented; each experimental group consisted of five mice.
Mφ collected from mice pre-injected with CGN were significantly less cytotoxic against the L1 cells than macrophages obtained from the CGN-untreated animals. Even more pronounced reduction of the cytotoxic
function of Mφ was detected in the cells obtained from the CGN-untreated mice and incubated in vitro in the presence of aminoguanidine (AG) (Fig. 12A). Also, production of NO by Mφ obtained from both the sham-
and X-ray-exposed mice pre-treated with CGN was almost totally suppressed in all the groups. As expected, addition of AG to the incubation medium of the collected Mφ led to the significant inhibition of the production of NO whose level was even lower than in cells collected from the CGN-treated mice (Fig. 12B).
Figure 12: CGN- and AG-induced suppression of cytotoxic activity (A) and production of NO (B) by the IFN-γ- and LPS-treated (S) Mφ on the third day after single WBI of mice. C?sham-exposed, control mice; 0.1 Gy?mice exposed to WBI with 0.1 Gy X-rays; 0.2 Gy?mice exposed to WBI with 0.2 Gy X-rays ;1.0 Gy?mice exposed to WBI with 1.0 Gy X-rays. M + S?Mφ obtained from the CGN-untreated mice; M + S + CGN?Mφ obtained from mice pretreated with CGN; M + S + AG?Mφ obtained from the CGN-untreated mice and incubated in vitro in the presence of AG. M + S + CGN + AG?Mφ obtained from mice pretreated with CGN and incubated in vitro in the presence of AG.
Mean values ± SD obtained from two independent experiments are presented; each experimental group consisted of five mice ^?indicates statistically significant (p<0.05) difference between Mφ collected from irradiated mice and the respective Mφ obtained from non-irradiated mice. *?indicates statistically significant (p<0.05) difference from the results obtained in group M + S.
However, neither i.p. injection of mice with CGN, a lysosome-disrupting and phagocyte-damaging com-pound, nor addition to the culture medium of AG, a classical inhibitor of the inducible NO synthase, totally abrogated the cytotoxic activity of Mφ even when both blockers were used concurrently. These results sug-gested that the residual cytotoxic activity of the effector cell populations might be due to synthesis and/or secretion of additional cytotoxic and/or cytostatic factors that are likely to be involved in elimination of neoplastic cells. Indeed, our investigations demonstrated that both single and fractionated irradiations of mice with all the three applied doses of X-rays significantly stimulated Mφ to produce a number of cytokines with potential anti-neoplastic properties. These include IL-1β, IL-12, TNF-α (Figs. 13?15).
Figure 13: Production of IL-1β by the IFN-γ- and LPS-treated Mφ after single (A) or fractionated (B)
WBI of mice and incubation with L1 cells. C?sham-exposed, control mice; 0.1 Gy?mice exposed to WBI with 0.1 Gy X-rays; 0.2 Gy?mice exposed to WBI with 0.2 Gy X-rays; 1.0 Gy?mice exposed
to WBI with 1.0 Gy X-rays. Mean values ± SD obtained from three independent experiments are presented; each experimental group consisted of five mice.
Figure 14: Production of IL-12 by the IFN-γ- and LPS-treated Mφ after single (A) or fractionated (B)
WBI of mice and incubation with L1 cells. C?sham-exposed, control mice; 0.1 Gy?mice exposed to WBI with 0.1 Gy X-rays; 0.2 Gy?mice exposed to WBI with 0.2 Gy X-rays; 1.0 Gy?mice exposed
to WBI with 1.0 Gy X-rays. Mean values ± SD obtained from three independent experiments are presented; each experimental group consisted of five mice.
Figure 15: Production of TNF-α by the IFN-γ- and LPS-treated Mφ after single (A) or fractionated (B)
WBI of mice and incubation with L1 cells. C?sham-exposed, control mice; 0.1 Gy?mice exposed to WBI with 0.1 Gy X-rays; 0.2 Gy?mice exposed to WBI with 0.2 Gy X-rays; 1.0 Gy?mice exposed
to WBI with 1.0 Gy X-rays. Mean values ± SD obtained from three independent experiments are presented; each experimental group consisted of five mice.
2.4 NK cell- and macrophage-mediated activity after single in vitro irradiations Unlike the low-level irradiations of mice, single exposures of the isolated NK cells and Mφ to either of the
applied single doses of X-rays did not boost the cytotoxic activities of these cells (Table 1).
Table 1: Activity of NK cells and IFN-γ- and LPS-treated Mφ after in vitro irradiation. C?sham-exposed, control cells; 0.1 Gy?cells exposed to 0.1 Gy X-rays; 0.2 Gy?cells exposed to 0.2 Gy X-
rays; 1.0 Gy? cells exposed to 1.0 Gy X-rays. Mean values ± SD obtained from two independent experiments are presented; each experimental group consisted of five mice.
Irradiation of the isolated NK cells with 0.1 or 0.2 Gy X-rays did not affect the rate of apoptosis in the examined cell suspensions, whereas irradiation with 1.0 Gy enhanced the number of apoptotic NK cells (Fig. 16).
Figure 16: Apoptosis of NK cells after in vitro irradiation. C?sham-exposed, control cells; 0.1 Gy? cells exposed to 0.1 Gy X-rays; 0.2 Gy?cells exposed to 0.2 Gy X-rays; 1.0 Gy?cells exposed to
1.0 Gy X-rays. Mean values ± SD obtained from two independent experiments are presented; each experimental group consisted of five mice.
The in vitro irradiations of Mφ with 0.1, 0.2, or 1.0 Gy X-rays did not affect the rate of apoptosis (Fig. 17).
Figure 17: Apoptosis of IFN-γ- and LPS-treated Mφ after in vitro irradiation C?sham-exposed, control cells; 0.1 Gy? cells exposed to 0.1 Gy X-rays; 0.2 Gy?cells exposed to 0.2 Gy X-rays; 1.0
Gy?cells exposed to 1.0 Gy X-rays. Mean values ± SD obtained from two independent experiments are presented; each experimental group consisted of five mice. 3. 0 CONCLUSIONS
The obtained data indicate that:
1. Both single and fractionated whole-body exposures of mice to low (0.1 and 0.2 Gy) but not intermediate (1.0 Gy) doses of X-rays inhibit (single irradiation) or tend to inhibit (fractionated irradiation) the
development of the induced pulmonary tumour colonies;
2. The suppression may result from stimulation of the natural defence reactions mediated by NK lymphocytes and/or cytotoxic macrophages;
3. Boosting of the cytolytic functions of the above anti-neoplastic effectors by low-level exposures to X-rays requires the presence of other cells and/or environmental factors available in the in vivo but not the
in vitro conditions.
4.0 REFERENCES
[1] UNSCEAR (1986) United Nations scientific committee on the effects of atomic radiation, 1986 Report to the general assembly, with annexes. Genetic and somatic effects of ionizing radiation United
Nations Publ. E.86.IX, UN, New York, p 170.
[2] Potential radiation exposure in military operations. Protecting the soldier before, during and after (1999), Thaul S, O’Maonaigh H (Eds) Institute of Medicine, National Academy Press Washington D.C.
[3] Hashimoto S, Shirato H, Hosokawa M, Nishioka T, Kuramitsu Y, Matushita K, Kobayashi M, Miyasaka K (1999) The suppression of metastases and the change in host immune response after low-
dose total-body irradiation in tumor-bearing rats. Radiat Res 151:717?724.
[4] Ju GZ, Liu SZ, Li XY, Liu WH, Fu HQ (1995) Effect of high versus low dose radiation on the immune system. In: Hagen U, Harder D, Jung H, Streffer C (eds) Radiation research 1895?1995. Proceedings
on tenth international congress of radiation research, Wurzburg, Germany, 27 August September 1995. IARR, Wurzburg, pp 709 714.
[5] Kojima S, Ishida H, Takahashi M, Yamaoka K (2002) Elevation of glutathione induced by low-dose gamma rays and its involvement in increased natural killer activity. Radiat Res 157:275?280.
[6] Liu SZ, Xiao PX, Ma SY, Xu GZ, Tian CH, Yu HY, Zhang LM (1982) A study of the immune status of inhabitants in an area of high natural radioactivity in Guangdong. Chin J Radiol Med Prot 2:64?68.
[7] Liu SZ, Xu GZ, Li XY, Xia FQ, Yu HY, Qi J, Wang FL, Wang SK (1985) A restudy of immune functions of the inhabitants in a high natural radioactivity area in Guangdong. Chin J Radiol Med Prot 5:124?127.
[8] Liu SZ (1989) Radiation hormesis. A new concept in radiological science. Chin Med J 102:750?755.
[9] Liu SZ, Su X, Zhang YC, Zhao Y (1994) Signal transduction in lymphocytes after low dose radiation. Chin Med J 107:431?436.
[10] Liu SZ, Zhang YC, Mu Y, Su X, Liu JX (1996) Thymocyte apoptosis in response to low-dose irradiation. Mutat Res 358:185?191.
[11] Liu SZ (2004) Cancer control related to stimulation of immunity by low dose radiation. In: Proceedings of 14th pacific basin nuclear conference, Honolulu, HI, 21?25 March 2004. American
Nuclear Society, La Grange Park, pp 368?372.
[12] Luckey TD (1999) Nurture with ionising radiation: a provocative hypothesis. Nutr Cancer 34:1?11
[13] Pandey R, Shankar BS, Sharma D, Sainis KB (2005) Low dose radiation induced immunomodulation: effect on macrophages and CD8+ T cells. Int J Radiat Biol 81:801?812.
[14] Safwat A (2000) The immunology of low-dose total-body irradiation: more questions than answers. Radiat Res 153:599?604.
[15] Safwat A (2000) The role of low-dose total body irradiation in treatment of non-Hodgkin’s lymphoma: a new look at an old method. Radiother Oncol 56:1?6.
[16] Safwat A, Bayoumy Y, El-Sharkawy N, Shaaban K, Mansour O, Kamel A (2003) The potential palliative role and possible immune modulatory effects of low-dose total body irradiation in relapsed or chemo-resistant non-Hodgkin’s lymphoma. Radiother Oncol 69:33?36.
[17] Lin IH, Hau DM, Chen WC, Chen KT (1996) Effects of low dose gamma-ray irradiation on peripheral leukocyte counts and spleen of mice. Chin Med J 109:210?214.
[18] Harrington NP, Chambers KA, Ross WM, Filion LG (1997) Radiation damage and immune suppression in splenic mononuclear cell populations. Clin Exp Immunol 107:417?424.
[19] DeBlaker-Hohe DF, Yamauchi A, Yu CR, Horvath-Arcidiacono JA, Bloom ET (1995) IL-12 synergises with IL-2 to induce lymphokine-activated cytotoxicity and perforin and granzyme gene expression in fresh human NK cells. Cell Immunol 165:33?43.
[20] Miller GM, Kim DW, Andres ML, Green LM, Gridley DS (2003) Changes in the activation and reconstitution of lymphocytes resulting from total-body irradiation correlate with slowed tumor
growth. Oncology 65:229?241.
[21] Al-Sarireh B, Eremin O (2000) Tumour-associated macrophages (TAMS): disordered function, immune suppression and progressive tumour growth. J R Coll Surg Edinb 45:1?16.
[22] Belardelli F, Ferrantini M (2002) Cytokines as a link between innate and adaptive antitumour immunity. Trends Immunol 23:201?208. |
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02. 2012年7月17日 01:35:58
: pi0fYycp4s
Chapter 4
German Contributions Using Gene Expression Studies to Detect Radiation Targets and to Discriminate Radiation Associated Tumors from Other Ethiologies
Matthias Port
1
, Christian G. Ruf
2
, Armin Riecke
2
and Michael Abend2
1
Department of Hematology, Hemostaseology, Oncology and Stem Cell Transplantation, Hannover Medical School, Hannover, Germany
2
Bundeswehr Institute of Radiobiology, German Armed Forces, Munich, Germany
ABSTRACT
Within this chapter we describe nowadays used modern approaches for detection of radiation induced gene targets employing whole genome microarrays for screening purposes of candidate genes and their quanti-
tative analysis using RTQ-PCR (two stage study design). Besides this methodological focus (also including results on normalization procedures) we describe gene expression examinations which allow to discriminate
radiation associated thyroid cancer tumors from those developed due to other etiologies which might be of importance in the context of compensation requests occurring after e.g. accidental or occupational radiation
exposures.
1.0 APPROACHES FOR DETECTION OF RADIATION INDUCED GENE TARGETS
1.1 Combining whole genome microarray with RTQ-PCR Recently Cam and coworker hybridized one cDNA probe on three different microarray platforms in order to
compare the overall agreement among these platforms. A total of 4 from 185 genes tested were similarly detected with all three microarrays [Tan et al. 2003]. This was another experiment raising doubts about gene
expression analysis using microarrays and about the reproducibility of this method. In 2005 the so called “MicroArray Quality Control” (MAQC) project was initiated by the U.S. Food and Drug Admininistration
[Casciano and Woodcock 2006]. A consortium of 137 researchers from 51 different organizations examined reproducibility across laboratories by putting 20 microarray products and three alternative technologies
through more than 1,300 tests [Couzin 2006].
It is widely accepted using real-time quantitative PCR (RTQ-PCR) as a reference method for quantification of RNA-copy numbers [Canales et al. 2006, Mackay et al. 2002, Wang et al. 2006]. That holds true
especially due to its advantages in detection sensitivity, sequence specificity, large dynamic range as well as its high precision and reproducible quantitation compared to other techniques [Wong and Medrano 2005, Wilhelm and Pingoud 2003].
In general small amounts of RNA are amplified before doing the hybridization on the microarray. In previous experiments we showed a high variability inherent to this step. As an alternative we pooled RNA
from several experiments. This allowed reducing the RNA needed for a complete gene expression experi-ment including RTQ-PCR validation down to less than 5 μg per individual. Furthermore we demonstrate that
when methods are well established in a laboratory one array and RTQ-PCR measurements performed only in duplicates reaching effectiveness and reliability comparable to the results of the MAQC consortium (sub-
mitted for publication).
1.2 Normalization of gene expression using RTQ-PCR
A large number of housekeeping genes for normalization purposes of gene expression data exist. Companies even offer platforms (96-well format) in order to find out about the appropriate gene or combination of genes.
Figure 1: Comparison of absolute gene expression of 3 house-keeping genes in 3 tissue types of 9 human individuals. Bars represent the mean calculated from 3 individuals. Error bars show the
SEM, n=3 (modified graph published by Port et al. 2007a).
Depending on the experimental design (kind and intensity of exposure, endpoint, biological sample and time) the desired gene might differ. Among many other genes 18S ribosomal RNA (18S rRNA) is widely used for
normalization purposes.
We in particular examined the usefulness of known housekeeping genes (Figure 1) for normalization purposes after ionising radiation in different models and points in time after radiation (Figure 2).
In summary, 18S rRNA proved its superiority over other widely used genes for normalization purposes after radiation exposure in a large variety of biological models [Port et al. 2007a].
1.3 CLARCC array, a quantitative gene expression platform for known radiation induced signal transduction pathways Recently the dependency in the mode of cell death on three parameters has been demonstrated. These
parameters include the kind and intensity of the stressor as well as the irradiated model [Abend et al. 1995, 1996, 2000]. Depending on these parameters a shift in the mode of cell death happens [Abend 2003].
Not only apoptosis, but also certain kind of necrosis and even the process of micronucleation or mitotic catastrophe seem to be regulated by the cell on the gene expression level (Stassen et al. 2003, Seidl et al. 2007).
Figure 2: Comparing differential gene expression (relative to control) in two irradiated in vitro cell lines up to 48 h after radiation exposure and in normal tissues of 3 tissue types of 9 human individuals,
human testis tumors and different dog tissues [modified graphs published by Port et al. 2007a].
A RTQ-PCR based low density array was designed (CLARCC array, acronym for cell cycle, lipid metabolism, apoptosis, repair and cytokinesis & chromosome segregation, Figure 3). With altogether 380
genes measured simultaneously it covers the nowadays most important known genes coding for the bio-logical processes including different modes of cell death (lipid metabolism, apoptosis and cytokinesis &
chromosome segregation), proliferation and repair (e.g. dsb). Moreover, since the platform chosen is a RTQ-PCR technique it represents the gold standard for gene expression measurements leading to quantitative and
not only semiquantitative results of several hundred genes at the same time.
Recently, the CLARCC array was used to examine a gene expression “fingerprint” on a human gastric tumor cell line (HSC) exposed to an alpha-emitting radionuclide (Seidl et al. 2007). Actually it is used on HL-60
cells (model for apoptosis) after gamma ray exposure. Figure 3: Description of gene categories associated to biological processes covering cell cycle, lipid metabolism, apoptosis, repair and cytokinesis & chromosome segregation (CLARCC array).
2.0 DISCRIMINATING RADIATION ASSOCIATED TUMOURS FROM OTHER
ETIOLOGIES
In general, the cause of a developing tumor and in particular the causal link to ionizing radiation cannot be made. However, due to possible compensation requests of exposed individuals it is desirable to be able to do that.
For this reason, pooled RNA from 10 tumour tissues (papillary thyroid cancer, PTC) of Belarusian patients (total number of patients was 11) subjected to radiation after the Chernobyl nuclear accident and pooled
RNA from 10 individuals of a control group consisting of 41 Caucasian patients originating from south-eastern Germany and suffering from thyroidal carcinoma of similar histology but lacking a radiation
exposure history were hybridised on a whole genome microarray for screening of potentially upregulated or downregulated genes. Results of microarrays are semiquantitative and must be validated with another
method, preferably quantitative real time polymerase chain reaction (RTQ-PCR), the well accepted, convenient and economical method to confirm array data for gene expression measurements. Nearly 100 of
the most promising genes screened with the microarray were examined quantitatively on each of the biopsies with a recently developed RTQ-PCR-based technology called low-density array (LDA) in order to identify
the most promising genes for distinguishing between sporadic and radiation-induced PTC.
Table 1: Characterization of the seven most promising gene targets for distinguishing between post-Chernobyl PTC and a control group lacking an additional radiation exposure history.
Information were taken from NCBI Entrez Gene database (updated Mar 2006). Only literature associating the genes with tumour development was cited. The abbreviation “n.e.” means “no
entry” in the database. Data were taken from published work [Port et al. 2007b].
In summary, our microarray data on post-Chernobyl PTC reflect a positive stimulus for tumor growth (overrepresentation of upregulated genes coding for G-proteins and growth factor) and increased
aggressiveness caused by overexpressed oxidoreductases, while the immune defense (overrepresentation of downregulated genes coding for immunglobulin) appeared weakened. For the first time, a complete
differentiation of post-Chernobyl PTC from controls either characterized by comparable aggressiveness (PTC of older patients, median age: 60 years) or comparable age (n =4) was accomplished by a selection of
seven gene targets (Table 1). Further examinations on larger groups are needed in order to determine whether these findings are applicable as a diagnostic tool for identifying radiation-induced PTC.
3. REFERENCES
[1] Abend, M., Rhein, A., Gilbertz, K.P., Blakely, W.F., van Beuningen, D. Correlation of micronucleus and apoptosis assays with reproductive cell death. Int. J. Radiat. Biol. 67(3):315?26, (1995).
[2] Abend, M., Rhein, A., Gilbertz, K.P., van Beuningen, D. Evaluation of a modified micronucleus assay.
Int. J. Radiat. Biol. 69(6):717?27, (1996).
[3] Abend, M., Kehe, K., Kehe, K., Riedel, M., van Beuningen, D. Correlation of micronucleus and apop-tosis assays with reproductive cell death can be improved by considering other modes of death. Int. J.
Radiat. Biol. 76(2):249?59, (2000).
[4] Abend, M. Reasons to reconsider the significance of apoptosis for cancer therapy. Int. J. Radiat. Biol. 79:927?941,(2003).
[5] Casciano, D.A., Woodcock, J. Empowering microarrays in the regulatory setting. Nat. Biotechnol. 24(9):1103, (2006).
[6] Couzin, J. Genomics. Microarray data reproduced, but some concerns remain. Science. 313(5793):1559, (2006).
[7] Canales, R.D., Luo, Y., Willey, J.C., Austermiller, B., Barbacioru, C.C., Boysen, C., Hunkapiller, K., Jensen, R.V., Knight, C.R., Lee, K.Y. et al.: Evaluation of DNA microarray results with quantitative
gene expression platforms. Nat. Biotechnol. 24:1115?1122, (2006).
[8] Mackay, I.M., Arden, K.E., Nitsche, A. Real-time PCR in virology. Nucleic Acids Res. 30:1292?1305, (2002).
[9] Port, M., Schmelz, H.U., Stassen, T., Mueller, K., Stockinger, M., Obermair, R., Abend, M.. Correcting false gene expression measurements from degraded RNA using RTQ-PCR. Diagn. Mol.
Pathol. 16(1):38?49, (2007a).
[10] Port, M., Boltze, C., Wang, Y., Roper, B., Meineke, V., Abend, M. A radiation-induced gene signature distinguishes post-Chernobyl from sporadic papillary thyroid cancers. Radiat Res. 168(6): 639?49,
(2007b).
[11] Seidl, C., Port, M., Gilbertz, K.P., Morgenstern, A., Bruchertseifer, F., Schwaiger, M., Roper, B., Senekowitsch-Schmidtke, R., Abend, M. 213Bi-induced death of HSC45-M2 gastric cancer cells is
characterized by G2 arrest and up-regulation of genes known to prevent apoptosis but induce necrosis and mitotic catastrophe. Mol. Cancer. Ther. 6(8):2346?59, (2007).
[12] Stassen, T., Port, M., Nuyken, I., Abend, M. Radiation-induced gene expression in MCF-7 cells. Int. J. Radiat. Biol. 79(5):319?31, (2003).
[13] Tan, P.K., Downey, T.J., Spitznagel, E.L. Jr, Xu, P., Fu, D., Dimitrov, D.S., Lempicki, R.A., Raaka, B.M., Cam, M.C. Evaluation of gene expression measurements from commercial microarray
platforms. Nucleic Acids Res. 31(19):5676?84, (2003).
[14] Wang, Y., Barbacioru, C., Hyland, F., Xiao, W., Hunkapiller, K.L., Blake, J., Chan, F., Gonzalez, C., Zhang, L., Samaha, R.R. Large scale real-time PCR validation on gene expression measurements from
two commercial long-oligonucleotide microarrays. BMC Genomics 7:59, (2006).
[15] Wong, M.L., Medrano, J.F. Real-time PCR for mRNA quantitation. Biotechniques. 39(1):75?85, (2005).
[16] Wilhelm, J., Pingoud, A. Real-time polymerase chain reaction. Chembiochem. 4(11):1120?8, (2003). Chapter 5
Molecular Biomarkers of Acute Radiation Syndrome and Radiation Injury William F. Blakely,Gregory L. King,Matthias Port, and Natalia I. Ossetrova1
Armed Forces Radiobiology Research Institute Uniformed Services University
8901 Wisconsin Avenue Bethesda, MD 20889-5603 USA
and Department of Hematology, Hemostaseology, Oncology and Stem Cell Transplantation Hannover Medical School Hannover, Germany
ABSTRACT
The acute radiation syndrome or sickness (ARS) represents signs and symptoms associated with various organ and tissues systems response after exposure to radiation. Here we review the current status of
knowledge on the use of molecular and other metabolic biomarkers, based on specific organs and tissue systems, as candidate bioindicators for radiation injury severity. An assessment of the confounders and
research gaps for diagnostic use of molecular biomarkers, in complementation with conventional diagnostic methodologies, in the development of medical treatment decisions is discussed.
1.0 INTRODUCTION
Acute radiation syndrome or sickness (ARS) constitutes a constellation of signs and symptoms from several organ subsystems (i.e., cerebrovascular, hematopoietic system, gastrointestinal or GI, cutaneous, respiratory,
etc.), each exhibiting distinct time- and dose-dependent responses from the radiation injury [Waselenko et al. 2004; Gorin et al. 2006]. Effective medical management of a suspected radiation-overexposure patient
necessitates recording dynamic medical clinical data, measuring appropriate radiation bioassays, and estimating dose from dosimeters and radioactivity assessments in order to provide diagnostic information to
the treating physician and dose assessment for personnel radiation-protection records. The accepted generic multiparameter approach includes measuring radioactivity and monitoring the exposed individual; observing
and recording prodromal signs/symptoms including erythema; obtaining complete blood counts (CBC) with white blood cell differential; sampling blood for the chromosome-aberration cytogenetic bioassay using the
―gold standard? dicentric assay for dose assessment and dose in-homogeneity (whole- vs. partial-body exposure); bioassay sampling, if appropriate, to determine radioactivity contamination; and using other
available dosimetry [Blakely et al. 2005] and clinical approaches. Professor Fliedner and colleagues (University of Ulm, Germany) have developed an ARS severity scoring system based on clinical signs and
symptoms for the major subsyndromes (i.e., neurovascular, gastrointestinal, hemopoietic, cutaneous, etc.).
Called ― Medical Treatment Protocols (METREPOL) it presents a grading score to quantify the severity level for the various subsyndromes of ARS (Fliedner et al. 2001) and forms the basis of a medical treatment
decision guidance. AFRRI recently updated it Biological Dosimetry worksheet, available on AFRRI’s website (www.afrri.usuhs.mil), to include a modified version of METREPOL.
Biochemical or molecular biomarkers represent an additional complementary diagnostic approach that has the potential to provide information on radiation injury and hence formulate medical treatment decisions. For
example, blood plasma or serum biochemical markers of radiation exposure have been advocated for use in early triage and injury assessment of radiation casualties [Bertho et al. 2001; Blakely et al. 2003a, 2003b;
Roy et al. 2005; Marchetti et al. 2006; Ossetrova et al. 2007, 2009, 2010; Blakely et al. 2007, 2010; Okunieff et al. 2008; Guipaud and Bendritter et al. 2009; Ossetrova and Blakely 2010] (Table 1). Biomarkers can fall
into two classes, early expressed biomarkers of radiation injury as well as organ-specific injury biomarkers that are exhibited at various times after radiation exposure in a time- (Figure 1) and dose-dependent (Figure
2) fashion based on organ- and tissue-specific cell-renewal transit times [Hall and Giaccia, 2006], which have been validated in several radiation models, see Table 2.
The blood plasma or serum biomarker approach has several advantages. Early biomarkers may contribute along with other biodosimetric indices, clinical signs and symptoms, and evidence of physical dose to initiate use of
non-toxic medical countermeasures that demonstrate greater efficacy when started 24 h after radiation exposure [MacVittie et al. 2005]. Organs and tissues leak tissue and organ specific bio-indicators into blood when
responding to radiation damage, so their measurements in blood can provide useful diagnostic information about the severity of specific organ and tissue system to radiation injury. In this report, we review the current
status of use of molecular and other biomarkers of tissues and organs systems associated with ARS and radiation injury. We also identify some potential major confounding variables and research gaps with this
approach and provide a medical perspective on the use of biomarkers along with currently conventional diagnostic approach for formulating medical treatment decisions.
2.0 ORGAN AND TISSUE SYSTEMS
2.1 Salivary Glands
The major salivary glands are the parotid, submandibular, submaxillary, and sublingual glands. Besides these glands, there are many tiny glands called minor salivary glands located in the lips, inner cheek area (buccal
mucosa), and extensively in other linings of the mouth and throat. The epithelial cells of the salivary gland divide only rarely, hence this tissue would be expected to be relatively radiation resistant. In man, however,
the salivary gland shows a high sensitivity to ionizing radiation. The parotid gland seems to be more sensitive to irradiation than the submandibular gland [Henriksson et al. 1994], although the molecular
mechanism is not known. The post-irradiation induced proliferative activity was greater in the intercalated duct compartment of the parotid gland than that of the submandibular gland, which may be related to the
increased radiosensitivity [Peter et al. 1994]. Nagler suggested that the causes for the specific parotid radiosensitivity are transition, highly redox-active metal ions, such as Fe and Cu, associated with secretion
granules [Nagler et al. 1997].
A few hours after irradiation injury, cells in the salivary gland show acute inflammation and degenerative changes resulting in increases in plasma or serum amylase activity. An increase in serum amylase activity
(hyperamylasemia) from the irradiation of salivary tissue has been proposed as a biochemical measure of early radiation effect in a normal tissue [Becciolini et al. 1984; Leslie and Dische, 1992]. These concepts are based
on studies involving radio-iodine therapy [Maier and Bihl, 1987; Becciolini et al. 1994a, 1994b], radiation therapy [Chen et al. 1973; Dubray et al. 1992; Leslie and Dische, 1992; Becciolini et al. 2001], and recently a
radiation accident [Akashi et al. 2001]. Histochemical, isozyme analysis, and partial-body exposure studies confirm that the increase in serum amylase activity originates from the parotid glands.
Table 1: Candidate radiation biomarkers and functional tests from various tissue system or organs
Tissue system or organ Candidate radiation biomarker Candidate radiation bioindicator or functional test Radiation pathology Reference Gastrointestinal (GI) or Digestive System
Parotid salivary gland Amylase activity ↑ Serum or urinary amylase activity Mucositis Chen et al. 1973; Hofmann et al. 1990;
Dubray et al. 1992; Becciolini et al.
2001; Blakely et al. 2007; Blakely et al.
2010
Small
intestine
Citrulline, neurotensin and
gastrin hormones
↓ Serum or plasma citrulline,
neurotensin or gastrin;
↑ sugar concentration ratios using
dual-sugar permeability test
measured in serum
GI ARS
subsyndrome
Lutgens et al. 2003, 2004; Vigneulle et
al. 2002; Dublineau et al. 2004;
Bertho et al. 2008
Liver
C-reactive protein (CRP);
Serum amyloid A (SAA)
Oxysterol 7a-
hydroxycholesterol
↑ Serum or plasma CRP or SAA;
↑ Plasma oxysterol 7a-
hydroxycholesterol
ARS subsyndrome;
Hepatic tissue
radiation injury
Mal’tsev et al. 1978, 2006; Goltry et al.
1998; Koc et al. 2003; Roy et al. 2005;
Ossetrova et al. 2007; 2010;
Ossetrova and Blakely 2009; Blakely
et al. 2010;
Hemopoietic System
Bone
marrow
Flt-3 ligand (Ftl-3), IL-6, G-CSF ↑ Serum or plasma Flt-3
Bone marrow ARS
subsyndrome
Bertho et al. 2001, 2008
Cutaneous System
Cytokines (IL-1, IL-6, tumor
necrosis factor, GM-CSF,
TGF-β, intracellular adhesion
molecule, MMP
↑ IL-1, IL-6, GM-CSF, TGF- β,
intracellular adhesion molecule, and
MMP measured from skin tissues
Cutaneous ARS
subsyndrome
Martin et al. 1997; Ulrich et al. 2003;
Liu et al. 2006; Muller and Meineke
2007; Guipard et al. 2007
Respiratory System
Lung Oxysterol 27-hydrocholesterol
↑ plasma oxysterol 27-
hydrocholesterol
Respiratory ARS
subsyndrome
Roy et al. 2005
Cerebrovascular/Central Nervous System
Oxysteril 24S-
hydroxycholesterol
↑ plasma oxysteril 24S-
hydroxycholesterol
Cerebrovascular
ARS subyndrome
Roy et al. 2005
Figure 1: Radiation Biomarker Concept?Time Course. Schematic illustrating the time dependency of tissue- or organ-specific radiation biomarkers’ radioresponse. Representative data for parotid glands
[Chen et al., 1973], liver [Mal’tsev et al. 1978], GI [Lutgens et al. 2003], bone marrow [Bertho et al. 2001], and skin [Guipaud et al. 2007] are shown. See text for additional details.
Figure 2: Radiation Protein Biomarker Concept?Dose Response. Schematic illustrating the dose dependence of tissue- or organ-specific candidate radiation biomarkers’ radioresponse. Representative
data for parotid glands [Dubray et al., 1992], liver [Mal’tsev et al. 1978], GI [Lutgens et al. 2003], bone marrow [Bertho et al. 2001], and skin [Guipaud et al. 2007] are shown. See text for additional details.
Table 2: Select list of radiation-responsive blood based proteomic, metabolomic, and hematology biomarkers showing their dose range
(for various models) and time-window for meaningful diagnosis of radiation injury and dose*
Proposed blood or
serum biomarker
Pathways
Dose range (Gy) Time
window for
meaningful
diagnostics
References
Rodent
studies
NHP
studies
Human
radiation
therapy
Human
radiation
accidents
Salivary α-amylase
activity
Parotid gland
tissue injury
NA 0?8.5 Gy 0.5?10 Gy
3.5, 8, and
18 Gy
(Tokai-
mura)
12?36 h;
peaks at 24 h
Hofmann et al. 1990; Dubray
et al. 1992; Becciolini et al.
2001; Blakely et al. 2007;
Blakely et al. 2010
IL-6, G-CSF
Immunostimulatory
effects on bone
marrow cells
1?7 Gy 6.5 Gy NA 1?10 Gy
4?48 h;
3?8 d
Beetz et al. 1997; Gartel et al.
2002; Bellido et al. 1998;
Ossetrova et al. 2007, 2009
Flt-3 ligand
Bone marrow
aplasia
1?7 Gy 1?14 Gy NA
0.25 to 4.5
Gy
24 h?10 d
Bertho et al. 2001; Bertho et
al. 2008
CRP, SAA
Acute-phase
reaction
1?7 Gy
(SAA)
1?14 Gy
(CRP)
1?20 Gy
(CRP)
1?10 Gy
(CRP)
6 h?4 d;
5?14 d
Mal’tsev et al. 1978, 2006;
Koc et al. 2003; Goltry et al.
1998; Ossetrova et al. 2007,
2010; Ossetrova and Blakely,
2009; Blakely et al. 2010
Citrulline
Small bowel
epithelial injury
1?14 Gy Not done
1?20 Gy
(2-Gy daily
fractions)
~4.5 Gy >24 h
Lutgens et al. 2003, 2004;
Bertho et al. 2008
Lymphocytes,
neutrophils, and ratio
of neutrophils to
lymphoyctes
Hematopoietic
tissue injury
1?7 Gy 1?8.5 Gy 1?20 Gy 0?30 Gy 2 h?8 d
Goans et al. 1997; Guskova
et al. 1997; Blakely et al.
2005, 2007; Ossetrova et al.
2010
*Concept to use of multiple biomarkers for radiation injury and dose assessment (Blakely, Ossetrova et al., U.S. Patent Application No. 60/812,596.)
Serum amylase activity increases occur early after head and neck irradiation of humans [Kashima et al., 1965] and generally show peak values between 18?30 h after exposure, returning to normal levels within a
few days [Chen et al. 1973] (Figure 1). Radiation dose-dependent increases in the early (1 day) hyper-amylasemia are supported by radio-iodine therapy [Becciolini et al. 1994a, 1994b], radiotherapy [Hennequin
et al. 1989; Hofmann et al. 1990; Dubray et al. 1992; Becciolini et al. 2001], and limited data from three individuals exposed in a criticality accident [Akashi et al. 2001]. Significant inter-individual variations are
reported in these radiation studies [Chen et al. 1973; Dubray et al. 1992; Leslie and Dische, 1992] (Figure 2).
This inter-individual variation in biochemical response is not unexpected, since it is well known that the radiation level causing irreversible failure of the hematopoietic system varies among individuals and may
reflect genetic and physiological differences and relative differences in the radiosensitivity of hematopoietic stem/progenitor cells [Dainiak, 2002] as well as radiation exposure parameters (i.e., partial-body exposures,
shielding, dose-rate, etc.) [Koenig et al. 2005].
Limited studies have previously evaluated serum amylase activity radioresponse using rhesus-monkey radiation models. Dubray and colleagues cite an unpublished observation by L.C. Stephens demonstrating
radiation-induced increases in serum amylase activity using a rhesus monkey radiation model but note ―tremendous individual variation and no dose response relationship? apparent [Dubray et al. 1992]. Blakely
and colleagues [Blakely et al. 2007] using a rhesus monkey model system also reported significant inter-individual variation (3.4?to 30.5-fold at 1 day after irradiation) following exposure to whole-body acute
radiation exposure (6.5-Gy
60
Co- rays). Similar but less pronounced inter-individual variations (1.8?5.6 fold) were seen in the plasma amylase protein levels [Ossetrova et al. 2007].
2.2 Gastrointestinal system
There have been no survivors of those victims known to have been exposed to ionizing radiation doses of sufficient strength to cause injury to the gastrointestinal (GI) system [Monti et al. 2005; Genyao and
Changlin, 2005]. Although one approach of medicinal science has been to develop and evaluate treatments for this injury, another has been an attempt to identify a biomarker for this injury. Finding such a biomarker,
especially if it is expressed before GI injury is clinically evident, could assist medical personnel in triage of patients.
As reviewed by Lutgens and Lambin [Lutgens and Lambin, 2007], the current and most promising candidate biomarker for GI injury is the amino acid citrulline. Lutgens and colleagues showed that in mice following
total-body-irradiation (TBI) there was a radiation time- (Figure 1) and dose- (Figure 2) dependent decrease in plasma citrulline levels with a statistically significant radiation-dose citrulline-response relationship occur-
ring at 84-h post-irradiation [Lutgens et al. 2003]. At this time interval post-irradiation, the citrullinemia significantly correlated with both jejunal crypt regeneration and the measured circumference of the epithelial
surface lining. They also measured citrulline in patients undergoing abdominal fractionated radiotherapy and found significant decreases as a function of total radiation dose, the volume of bowel treated, and the clinical
toxicity grading [Lutgens et al. 2004].
The notion of citrulline as a GI marker for the status of intestinal enterocyte mass is based on several physiological principles. First, circulating citrulline is almost completely produced in the enterocytes of the
small intestine. Second, citrulline passes from the intestine via the portal hepatic vein to the liver. However, it is not metabolized in the liver, but from there passes into the general circulation to reach the kidney, where
it is metabolized to arginine in the proximal renal tubules (Figure 3).
Figure 3: Serum citrulline as a potential surrogate marker for radiation-induced intestinal damage. Schematic illustrates the mechanisms for radiation induced decreases in plasma citrulline, derived
from the intestinal-hepato-renal axis. See manuscript text for additional details.
These principles were first taken advantage of by Crenn and colleagues, who showed a significant decrease in plasma levels of citrulline associated with the level of bowel failure in 57 patients, who had undergone
bowel resection (e.g., short bowel syndrome) at least two years earlier [Crenn et al. 2000]. In that study, citrulline concentration was measured along with parenteral nutrition dependence to define permanent and
transient intestinal failure. Citrulline levels were significantly lower in the patients than in the control population, and the citrullinemia was significantly correlated with bowel length. Citrulline has also been
shown to be reduced in patients, who had undergone small-intestinal transplantation and in which graft had begun to show signs of rejection [David et al. 2006, 2007].
There are three other promising biomarkers for radiation-induced GI damage. The first is a clinical dual sugar permeability test. This test has been used successfully in patients with several GI disorders, for example, celiac
disease [Cox et al. 1999]. In this test, a solution of two inert and non-absorbable sugars of unequal diameters and in equal concentrations was taken orally. Lactulose and rhamnose were two such examples, the former
being a disaccharide, the latter, a monosaccharide (although other inert agents can be used). Two were used because they both were affected in the same manner by GI transit, gastric emptying, etc.
The sugars passively cross the GI mucosa, the larger one by the paracellular pathway (e.g., tight junctions), and the smaller one by the transcellular pathway?or through the cell membrane?although there are several other
hypotheses as to how this transport occurs under normal conditions. Transport of the smaller sugar prevails and the ratio of the two recovered concentrations, for example lactulose/rhamnose (L/R), under normal conditions,
favors the smaller sugar and the value is small. Under pathological conditions, the reverse occurs and passage of the larger molecule dominates the transport processes, increasing the value of the L/R ratio.
Historically, the ratio of these two sugars was measured from urine, 5?6 h after ingestion. Recently however, it has been shown that the ratio can be recovered from the serum within 1?2 hours after ingestion of the
sugars [Cox et al. 1999]. The serum values within that short time frame are very similar to the values recovered in urine after 6 h. This time savings would greatly facilitate any medical management for someone
who might have a GI radiation injury. A new, dried blood spot (DBS) technology has been applied to this sugar permeability testing, which requires only a pin-prick on the finger to retrieve enough blood (~ 25 μl)
for analysis [Katouzian et al. 2005]. In addition, the DBS methodology has been used for monitoring serum citrulline values and there is a strong linear correlation between DBS-reported citrulline concentrations and
those from HPLC [Yu et al. 2005].
While there have been some clinical evaluations of intestinal permeability following irradiation, these evaluations have been performed and associated with patients undergoing fractionated radiotherapy [Pia de
la Maza et al. 2001]. In addition, there has been one instance in which the sugar permeability test has been used experimentally in the nonhuman primate [Vigneulle et al. 2002]. In this study, the ratios of serum levels
of lactulose vs. 3-O-methylglucose (3-OM) and lactulose vs. mannitol were respectively measured to eval-uate the respective transcellular and paracellular permeabilities before and at several time intervals after 9.5-
Gy total abdominal irradiation (TAI) in the nonhuman primates. They found a statistically significant changes (i.e., increase in permeabilities for both sugars) at 7-days post-irradiation, although there were non-
significant increases on d 5 and days beyond 7 d. Further studies are needed in this area to make this approach useful for diagnostic applications.
The other two potential markers are the GI hormones gastrin and neurotensin (NT). Dublineau and colleagues investigated a panel of 7 hormones following 16-Gy TBI in pigs [Dublineau et al. 2004]. Of these
GI hormones, only gastrin and NT dramatically changed within 24-h post-irradiation, both falling. The former hormonal change was thought to reflect stomach damage; the latter, small intestine. Although the NT
data from this study are more compelling, the small sample size (n = 3) of the study strongly suggest further verification of these observations.
2.3 Hematopoietic (bone marrow) system
Bertho and colleagues proposed using animal irradiation models that plasma flt-3 ligand is a potential new bioindicator for radiation-induced aplasia (Figures 1 and 2) [Bertho et al. 2001]. Plasma flt-3 ligand concen-
tration also was correlated with radiation-induced bone marrow damage using local fractionated radiotherapy study [Hutchet et al. 2003]. The number of circulating white blood cells and platelets inversely correlated with plasma flt-3 ligand levels. In a recent radiation accident the measured flt-3 ligand levels were indicative
of the severity of bone marrow aplasia [Bertho et al. 2008; Bertho and Roy, 2009].
2.4 Hepatic (liver) system
C-reactive protein (CRP) is primarily formed in the liver and an acknowledged non-specific biomarker for various stresses. Plasma CRP increases is an exquisitely sensitive systemic marker of inflammation and
tissue damage and also has been shown to play an essential role in radiation injury [Tukachinski and Moiseeva, 1961; Mal’tsev et al. 1978, 2006; Ossetrov et al. 2007; Blakely et al. 2010]. Time- (Figure 1) and
dose-response (Figure 2) calibration curves for CRP expression measured in blood of 70 nonhuman primates -irradiated to a broad dose range up to 12 Gy and time-points from 2 h to 30 d revealed significantly
increased plasma CRP levels observed at 8?72 h post irradiation with a threshold about 0.5 Gy [Mal’tsev et al. 1978]. CRP levels were determined using a method of capillary precipitation of specific C-reactive
antiserum (the most sensitive existing method at that time). The time-interval for the second phase of appearance of CRP in the blood of irradiated animals correlate with the time interval for the expressed development of the cytolytic and destructive processes induced by irradiation [Mal’tsev et al. 1978].
Numerous studies show that dynamics and content of CRP exactly reflect the course and severity of the radiation sickness and may play a role as a factor in the prognosis [Petrov, 1962; Tukachinski and Moiseeva,
1961]. Mal’tsev and colleagues reported that indexes of CRP content in a peripheral blood of 147 patients damaged at the Chernobyl accident have been found to provide information for the prognosis of the probable
level of acute radiation sickness [Mal’tsev et al. 2006].
Roy and colleagues have proposed that the plasma concentration of the oxysterol 7α-hydroxycholesterol reflects hepatic damage following irradiation [Roy et al. 2005]. This oxysterol results from liver tissue
specific enzymatic degradation (via cytochrome P450) of cholesterol (CYP7A1). In this report, after a 10-Gy TBI to rats, there was a five-fold and statistically significant decrease in this specific sterol on the third day
post-irradiation when compared with controls. Roy and co-workers suggest that its diminished levels are part of multi-organ radiation damage.
2.5 Respiratory system
While increases in plasma levels of the oxysterol 27-hydroxycholesterol are reported to reflect pulmonary damage, Roy and colleagues have found that the plasma concentration of the 2,7-hydroxycholesterol is
unchanged following irradiation [Roy et al. 2005]. This oxysterol results from lung tissue specific enzymatic degradation (via cytochrome P450) of cholesterol (CYP27A1). These authors suggest that these levels
remained within control values because other undamaged tissues also produce and release it into the circulation.
2.6 Cerebrovascular/central nervous system
Roy and colleagues have proposed that increases in the plasma concentration of the oxysterol 2,4 S-hydroxycholesterol reflects brain damage following irradiation [Roy et al. 2005]. The oxysterol results from
brain tissue specific enzymatic degradation (via cytochrome P450) of cholesterol (CYP46A1). In this report, after a 10-Gy TBI to rats there was a statistically significant increase in this specific sterol on the third day
post-irradiation. As discussed above, Roy and co-workers suggest that these elevated levels of oxysterols are indicative of multi-organ radiation damage.
2.7 Cutaneous system
The symptoms of the cutaneous radiation syndrome (CRS) are based on a combination of inflammatory processes and altered cellular proliferation, all of which result from a specific pattern of transcription-activated
pro-inflammatory cytokines and growth factors. In the simplest terms, the phases can be distinguished as the prodromal stage, the manifest illness stage, and the chronic stage [Meineke, 2005], although [Peter et al. 2001]
have further subdivided and defined them by their latency and persistence. In this latter scheme, the latency of the prodromal stage is within minutes to hours, and can persist from 0.5 to 36 hours. The manifestation stage
has a latency of 3 weeks, and can last for 1?2 weeks. The former stage is manifest by erythema and pruritis; the latter, by these symptoms as well as bullae and ulcers. The prodromal stage typically occurs after 2-Gy
irradiation, while the other stages occur after radiation doses greater than 3 Gy.
1
Muller and Meineke [Muller and Meineke, 2007] reported that cutaneous tissue’s radioresponse involves the major cytokines including changes in interleukin-1 (IL-1) in both forms (IL-1α and IL-1β), IL-6, tumor
necrosis factor-α (TNF-α), transforming growth factor-β (TGF-β), as well as granulocyte-macrophage colony-stimulating factor (GM-CSF), and such chemotactic cytokines, as IL-8 and eotaxin. This is a
1
Personal communication with Dr. Viktor Meineke, Bundeswehr Institute of Radiobiology, Munich, Germany. burgeoning new area of work and much of the data are from in vitro research. From those data taken from
skin or skin biopsies, the following items are noteworthy for this report. In skin taken from mice, Liu and colleagues have shown increased expression of IL-1β and matrix metalloproteases (MMPs) at 19 d after 30-
Gy irradiation [Liu et al. 2006]. This was the time when early dermatitis appeared. In skin taken from pig 6-h after a 16-Gy irradiation, Martin showed significantly elevated TGF-1β gene expression although this was
transient, returning to control values at 24 h [Martin et al. 1997]. Whether and how this is related to the involvement of TGF-1β with late development of radiation-induced skin lesions is unknown. In a study of
skin biopsies from patients presenting with basal cell carcinoma, Muller and colleagues found elevated levels of intercellular adhesion molecule-1 (ICAM-1) after a 15-Gy cumulative radiotherapy treatment [Muller et
al. 2006]. These results were compared with biopsy material taken before irradiation. Since the tissue was taken from the tumor site, these results may not reflect normal tissue. Lastly, and related to the elevated
MMP levels, Ulrich and colleagues have demonstrated that serum levels of MMP-2 and MMP-9 are signify-cantly elevated between 3 and 14 d in patients with burns, who underwent skin excision and autografting
[Ulrich et al. 2003]. These patients’ cases were compared with a control group undergoing elective plastic surgery. MMPs are zinc-dependent endopeptidases in general and MMP-2 and MMP-9 are implicated in
tissue maintenance/repair and are elevated after thermal injury.
Using a novel approach to irradiate only the skin in a murine model, Guipaud and colleagues recently evaluated 64 serum proteins following varied radiation doses (Figures 1 and 2). The analysis was done on
days 1, 5, 14, 21, and 33 post-irradiation [Guipaud et al. 2007]. While the greatest level of expression (whether up or down) was seen on day 14, there were a number of proteins significantly different from
control in days 1 and 5. Many of these were acute-phase proteins, associated with injury of any sort, while some are involved in coagulation.
In summary, while there are numerous clinical indices and novel medical devices used to score the CRS [Peter et al. 2001], the notion of biomarkers for such an injury and the research in this area are in its infancy.
3. CONFOUNDING VARIABLES, GAPS, AND LIMITATIONS
Severe inflammation of the salivary glands, pancreas, and gastrointestinal tissues can cause increases in serum alpha-amylase activity. For example, 10-fold or greater elevations can be indicative of pancreatitis, cancer of
the pancreas, gall-bladder disease, and mumps. Five- to ten-fold increases may indicate renal failure and disease of gastrointestinal tissue as well as salivary gland trauma. The time course for the radioresponse
elevations of serum alpha-amylase is from 18 to 36 h after irradiation, with a peak value at 24 h and returning to near control levels by 48 h (Figure 1). The transitory elevation in serum alpha-amylase activity, while
limiting the diagnostic utility of this radiation biomarker for practical applications, can be useful to rule out non-radiation pathologies.
Hematopoietic cytokines are involved in the proliferation and differentiation of various blood cell progenitor cell populations. Flt-3 ligand stimulates various blood cell populations, including neutrophils. Disorders that
result in the induction of proliferation of hematopoietic progenitor cell populations would be expected to cause elevations in plasma hematopoietic cytokines. In addition, hematopoietic cytokines are elevated during
the initial acute-phase of inflammation, particularly as a result of bacterial infection and some cancers.
However, normal peripheral blood neutrophil counts, along with an expected corresponding lower baseline serum Flt-3 levels, are seen in certain populations (i.e., people of African and Middle Eastern descent)
[Bertho et al. 2008; Bertho and Roy, 2009]. Diagnostic use of serum hematopoietic cytokines for radiation exposure assessment will require comparison of results with baseline levels appropriate controls.
CRP is one member of the acute-phase reactants and increases dramatically (>100-fold) during the inflame-mation process and is believed to play a role in innate immunity, as an early defense against infections.
Moderate increases in CRP are associated with increased risk of diabetes, hypertension, and cardiovascular disease. Normal concentration in healthy human serum is usually lower than 10 mg/L, slightly increasing with
ageing. Higher levels are found in late pregnant women, mild inflammation and viral infections (10?40 mg/L), active inflammation, bacterial infection (40?200 mg/L), severe bacterial infections and burns (>200 mg/L)
[Clyne and Olshaker 1999]. It might be elevated with complications or treatment failures in patients with pneumonia, pancreatitis, pelvic inflammatory disease (PID), and urinary tract infections. In patients with
meningitis, neonatal sepsis, and occult bacteremia, CRP is also usually elevated. As a generally acknowledged non-specific biomarker for a variety of disorders, elevated CRP levels cannot be used alone for a definitive
specific diagnosis. AFRRI scientists have recently advocated using elevated CRP levels as an early-phase triage tool to identify individuals suspected of severe life-threatening radiation exposure [Ossetrova et al. 2007;
Blakely et al. 2010]. This concept is based on Mal’tsev and colleagues’ results [Mal’tsev et al. 1978], which show that CRP levels increase after radiation exposure based on dose- and time-radioresponse studies using a
nonhuman primate model, and results from analysis of samples from Chernobyl victims (Figures 1 and 2) [Mal’tsev et al. 2006]. Plasma CRP levels at 1 to 3 d after radiation doses greater than 1 Gy, based on the
nonhuman primate radiation model of Mal’tsev, are significantly higher from baseline level.
With regard to GI markers for radiation damage, there are numerous gaps in the knowledge and under-standing of the potential markers discussed. First and foremost, each of these markers must be repeatedly
tested and validated in other animal models. Citrulline, for example, should be evaluated in an animal model that would allow for serial sampling, like what was done with the dual-sugar permeability test and the panel
of gut hormones (e.g., gastrin and NT).
In addition, there should be investigations of the dose-response characteristics of each potential biomarker. This was best done for citrulline, but the other markers were evaluated only after a single isolated dose of
ionizing radiation. It will be important to know how the other markers compare with regard to their dose-responsiveness to lower doses of irradiation. This may be especially true for gastrin and NT, since the pig is
not a well-characterized animal model for studying the GI syndrome. The benchmark for the GI syndrome has always been the radiation dose corresponding to the LD50/6 or LD50/7, a value that is more readily
attainable in rodents.
A third limitation of these biomarkers is with regard to the timing of its appearance. Lutgens and colleagues reported in mice after single dose TBI a significant dose-response relationship for radiation vs. citrulline only
84-h post-irradiation [Lutgens et al. 2003]. If this time interval were identical in humans, they might already be showing signs and symptoms (i.e., diarrhea, etc.) of the GI radiation syndrome. Evaluation of such signs
and symptoms in rodents is not easy to accomplish. In addition, post-irradiation diarrhea in the rodent can be very transient. With regard to the intestinal permeability testing, it is not known whether such a clinical test
could predict the onset of diarrhea, for example, or intestinal damage. Vigneulle and colleagues reported the onset of diarrhea five d following 9.5-Gy TAI [Vigneulle et al. 2002]. While the L/3-OM ratio was elevated
on this day, both this ratio and the L/M ratio were not significantly elevated until seven days post-irradiation, after the onset of diarrhea. Other than prior to irradiation to determine the control values, the testing was not
done before day 5 post-irradiation. The authors also report that the diarrhea continued through 14 d post-irradiation but the L/3-OM ratio did not return to normal until 27 d post-irradiation and the L/M ratio did not
return to normal until 35 d post-irradiation. The falls in gastrin and NT reported by Dublineau and colleagues were 24 h post-irradiation [Dublineau et al. 2004]. It may be that the rate of change in one of these markers
at early time intervals post-irradiation can be used for predicting that organ damage, rather than the precise value. The data from mice on citrulline clearly show that different rates of fall over the first several days post-irradiation are radiation dose-dependent.
For the individual specific biomarkers described (e.g., citrulline, gastrin, and NT), there may be potentially confounding variables that need to be evaluated in order to discriminate GI organ damage or pathology from
an insult other than irradiation. For example, it has been shown in the nonhuman primate that prolonged fasting can lower serum citrulline concentrations [Cameron et al. 1985]. The clinical literature has not been
so precise. In one study, Beaumier and colleagues showed that serum citrulline values in humans were significantly greater after a meal but these differences disappeared if the meal was supplemented with L-
arginine [Beaumier et al. 1995]. Conversely, this same group showed no difference in serum citrulline values between the fed and fasted states under similar conditions [Castillo et al. 1995]. There has been one clinical
report that intestinal permeability is increased during malnutrition but this is somewhat controversial [Ferraris and Carey, 2000] and the data are limited. George and colleagues showed that fasting and a
circadian pattern of food intake can influence circulating levels of NT [George et al. 1987]. Levels of gastrin also fall during starvation [Lichtenberger et al. 1976; Goodlad et al. 1983]. Because it is well documented
that food and water intake are reduced following ionizing radiation, and in a radiation-dose-dependent manner, it may be important to understand how this alone contributes to the reduced citrulline, gastrin or NT
observed following radiation.
4. MEDICAL PERSPECTIVE ON USE OF BIOMARKERS ALONG WITH CURRENT RECOMMENDED METREPOL ARS SEVERITY SCORE
INDICATORS
Medical treatment decisions of radiation victims were traditionally based on assessment and reconstruction of the radiation dose applied to the individual. Physical parameter-based classification systems have some
major drawbacks for clinicians treating radiation victims. The main interest of clinicians is applying medical care to improve patients’ outcome. Therefore, a severely score based on a classification system and/or bio-
markers levels should ideally predict the outcome of a patient, taking into account the kind of radiation including radiation quality, the heterogeneity and the individual radiation sensitivity. Furthermore, con-
comitant injuries or disorders have a major impact on the clinical course of the irradiated person. The ideal classification marker should integrate all this topics and the application of the marker should be easy, fast
and worldwide accessible. To date only CRP levels have been evaluated as a biomarker or classification system to predict the outcome of irradiated persons (Mal’tsev et al. 2006).
In medical settings, a lot of data can be gained easily by the physicians and their routine applications. For instance, medical history-taking, medical examination, and basic laboratory testing are accessible at any site
where radiation victims can be treated. Fliedner and co-workers spent enormous efforts in creating a database called SEARCH (System for Evaluation and Archiving of Radiation accidents based on Case Histories). Based
on the database, which contains radiation accidents and medical recordings over the last 50 years, an evidence-based clinical classification system was developed [Fliedner et al. 2001]. The concept of the ―response
categories? (RC) focuses not on the etiology of the radiation syndrome (physical dose, biological dose) but on the changes in the health status of the individual. Using easy-to-acquire clinical signs and focusing on the
organ-specific changes, the most important organ-system alterations were used for grading to create an overall classifier called response category. The organ systems used are neurovascular, hematopoietic, cutaneous and
gastrointestinal. Every organ system is graded from 1 to 4 and the integration is the RC.
As an example, the hematopoietic system is described briefly. Impairment of hematopoiesis by whole-body irradiation leads to clinical symptoms like susceptibility to infections, bleeding disorders or wound healing
disorders, which are summarized under the term hematopoietic syndrome (HS) of the acute radiation syn-drome. The radiosensitivity of hematopoietic stem cells and their damage in the bone marrow is the patho-
physiologic background of the hematopoietic syndrome. The change of lymphocyte, granulocyte and platelet counts over time can be used for a clinical-based classification system. The repeated measurement of single
parameters is essential for the grading of the hematopoietic syndrome. Irradiation leads to hypoplasia or aplasia of the bone marrow, resulting in pancytopenia. Although the probability of the HS increases with
physical dose applied, there is no save threshold. Usually the HS occurs at total-body doses from 1 to 1.5 Gy, but the dose-effect concept is of little importance for the clinical grading of individuals [Fliedner et al. 2001;
Friesecke et al. 2000]. A H4 (hematopoietic syndrome grade 4) damage shows a rapid decline for lympho-cytes within 24 h below 0.25 × 109/L, an initial granulocytosis up to 48 hours followed by a rapid decline
below 0.5 × 109/L. The nadir reached for lymphocytes, granulocytes and thrombocytes will last for at least several weeks. Patients graded as H3 show a decline in lymphocytes within the first 48 h down to 0.25 ×
109/L and 1.0 × 109/L. There is also an initial granulocytosis followed by a subsequent decrease until day 5.
A very important finding is an abortive rise starting at around day 5, increasing granulocyte counts again for about 5?8 days and followed by a second decline down to 0.5 × 109
/L. The nadir of the platelets will be reached with counts from 0?50 × 109/L around day 16?18. Autologous recovery will start around day 30?40. In H2 patients lymphocytes usually stay between 0.5 × 109
/L and 1.5 × 109L, granulocytes drop below 1.0 × 109/L around day 20 and thrombocytes show a nadir of around 50 × 109/L cells.
This description of the HS grading is a vast simplification of the grading process. The curve of the cell changes, including abortive rise, are the basis for the grading and their interpretation needs expert
knowledge. Patients with RC1 need little support to cope with the radiation damage. In RC2 patients, autologous recovery is certain and medical treatments are needed to bridge transient damage. RC3 patients
need maximum medical effort to be rescued including, for instance, differential antimicrobial therapy, cytokines or reverse isolation. When the radiation damage is graded as RC4, irreversible organ damage will
occur thus leading to multiple organ failure. There is a small therapeutic window for patients with a grade-4 hematopoietic syndrome (H4) to be rescued by stem-cell transplantation. The detailed grading system was
published in 2001 [Fliedner et al. 2001] and adoptions from scientific societies and groups were widespread widely spread [Dainiak et al. 2003; Waselenko et al. 2004; Gorin et al. 2006; Ganser 2007]. The RC concept
allows predicting the clinical course of the HS and the probability of autochtone regeneration [Fliedner et al. 2007]. Interpretation difficulties may arise in combined injuries accompanying diseases, such as in patients
with low exposition of the ARS severity level or in early diagnostic situations. Only patients with a very high probability to develop multiple organ failure due to very high radiation express clinical signs and symptoms
to permit clinical classification systems to predict the clinical course in the first hours. Granulocyte and lymphocyte kinetics or their ratio might offer the potential for early diagnosis but evaluation in radiation
accidents is still a matter of research.
Biomarkers offer a great opportunity to solve many remaining problems. For example, Mal’tsev and colleagues show that early-phase (1?2 and 3?9 d) CRP levels measured in Chernobyl victims was correlated
with the ARS sub-syndrome severity levels (Mal’tsev et al. 2006). Similar studies need to be performed for additional candidate organ-specific biomarkers. The development and evaluation of biomarkers uses cell
culture experiments, animal models or medical treatment procedures like radiation therapy or nuclear medicine applications. The advantage of these models is the simple determination or measurement of applied
physical dose, which then can be used easily to build dose effect curves. The ―gold standard? biomarker is the lymphocyte dicentric bioassay introduced in 1962 [Bender and Gooch, 1962]. Although robust and
widely used, its application is time consuming and laborious. Evaluation of measurements in radiation accidents and correlation to the response categories of patients show a concordance of about 70?80% of
measurements, depending on the cut off for RC4 patients, although distinguishing between RC2 and RC3 patients was not possible in the cohort examined.
2
An ideal radiation injury biomarker would include fast and reliable measurements, the potential for automation of the measurements, small and easy to obtain sample specimens, and the use of standard
detection technology, obviating the need for special training. Also, the biomarker should be correlated both to physical dose as well as ARS severity score levels, similar to that done by Mal’tsev and colleagues
[Mal’tsev et al. 2006], which would permit prediction of clinical outcome of future radiation scenarios such as radiation accidents. Medical applications like radiation therapy might help to test the markers in humans.
Today, many different biological, chemical and even physical effects are used to develop biological markers.
Our research focuses in changes of gene expression or protein measurements. Ongoing research demonstrates that mRNA changes in three genes, namely GADD45α, CDKN1 and ATF3, at 8, 24 and 48 h
post irradiation correlate with radiation dose from 0 to 2 Gy (data not shown). Similar findings were previously demonstrated by Amundson, Blakely, and Grace [Amundson et al. 2000; Blakely et al. 2003;
Grace et al. 2002; Amundson et al. 2004; Grace and Blakely 2007]. Use of multiple biomarkers today offer the opportunity to verify that irradiation has happened and to predict the outcome of a group of irradiated
patients with a distinct probability, which might help to plan and effectively use the available resources in a mass-casualty situation.
There is a clear need to develop and prospectively test biomarkers for radiation casualties. This is important not only for prediction of clinical outcome and assistance in clinical decision-making, but also for under-
standing acute radiation syndrome and developing new medical-care strategies. The authors strongly believe that only a combined approach with a set of distinct genes, proteins or other biomarkers in combination with
clinical classification systems might improve the rapid and correct classification of radiation victims.
5. ACKNOWLEDGMENTS
The views expressed here are those of the authors; no endorsement by the U.S. Department of Defense has been given or inferred. AFRRI supported this research under work units RAB4AL, RAB4AM, and
RBB4AR. The authors wish to thank David J. Sandgren for his assistance and AFRRI’s editorial staff for their expert editorial contributions. and AFRRI’s editorial staff for their expert editorial contribution.
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08. SaveChild厨 2012年10月03日 01:31:06
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Chapter 6
Biodosimetry and Biomarkers for Radiological Emergency Response
D. Wilkinson (CAN), D.C.B. Holt (GBR), K. Rothkamm (GBR), A. Jaworska (NOR), W.F. Blakely (USA), D.L. Stricklin (SWE)
Subsection 2 Contribution Authors
E. Waller (CAN), K. Millage (USA), W.F. Blakely (USA), J.B. Nemhauser (USA), Carl A. Curling (USA), Deena S. Disraelly (USA), Ira H. Levine (USA), David J. Sandgren (USA), James A. Ross (USA), J.S. Nasstrum (USA), G. Sugiyama (USA), S. Homann (USA), B.R. Buddemeier (USA)
Subsection 4 Contributing Authors
ABSTRACT
In 2006 NATO Research Task Group HFM-099/RTG-033 addressed the development of new and improved methods to counter the effects of increased risk scenarios such as nuclear/radiological threats. The group’s objective was to develop the scientific basis for the improved methods to prevent, assess, treat, and manage casualties and long-term health effects associated with ionizing radiation exposure. Radiation Injury Assessment and Biodosimetry Subgroup #2 identified a Program of Work outlining specific tasks recognized by all member states as essential areas of interest. These tasks are to: (a) develop an evaluation tool that will guide the selection, advancement, implementation and validation of complementing biodosimetry assays [CAN, GBR, SWE, USA]; (b) develop and validate lead candidate multi-parameter biodosimetry tools [CAN, CZE, DEU, FRA, GBR, NOR, POL, SWE, USA]; (c) evaluate software applications designed to provide radiation injury assessment, biological dosimetry information and guidance to the first-responder and first- receiver communities [CAN, CZE, DEU, FRA, GBR, SWE, USA]; (d) develop injury assessment and biological dosimetry guides and documents [GBR, USA]; and (e) develop a proposal for Advanced Demonstration Technology by the final RTG-099 meeting [CAN, CZE, DEU, FRA, GBR, NOR, POL, SWE, USA]. 1.0 INTRODUCTION
NATO recognizes that current physical and biomedical scientific support is not sufficient to provide the necessary advice for consequence management and medical countermeasures in scenarios involving radio- logical exposures. Research Task Group HFM-099/RTG-033 undertook the development of new and im-proved methods/tools to assist the medical community in responding to radiological/nuclear events involving casualties. The group‘s objective was to develop the scientific basis for new and improved methods to prevent, assess, treat, and manage casualties and long-term health effects associated with ionizing radiation exposure. Five specific tasks were identified by the group as targets for advanced research. Efforts undertaken within each of these tasks are described in this summary document.
2.0 DEVELOP AN EVALUATION TOOL THAT WILL GUIDE THE SELECTION, ADVANCEMENT, IMPLEMENTATION AND VALIDATION OF COMPLEMENTING BIODOSIMETRY ASSAYS [CAN, GBR, SWE, USA, FIN, NOR]
2.1 Biodosimetry Assay Evaluation Tool Medical and scientific communities are well aware of the challenges to be encountered in management of Radiological/Nuclear mass casualty disasters. Available medical resources will need to be stringently controlled and directed towards optimal outcomes. Identification of casualties needing medical intervention would be the primary challenge for the medical community. At the present time, there is no biodosimetry assay that is suitable for all scenarios. The selection of the most appropriate assay or assays will depend on the scenario circum-stances, the number of casualties that need to be assessed, and the available resources. An ideal dosimeter, or more likely a combination of the most suitable dosimeters, may need to be identified for each scenario. The task of this working group is to provide cumulative information on different assays available and rate each one according to the NATO Technology Readiness Level (TRL) Assessment guide.
It is hoped that the outcome of is process will result in a tool that will assist casualty management controllers in their selection of the most appropriate and relevant biodosimetry tools for the particular scenario and will guide the international research programs for improved methods based on the TRL evaluation process.
The initial approach to facilitating this tool development was to first identify all possible assays and then categorize them according to their function properties. The next step was to rate each assay according to the NATO‘s TRL guide (Table 1). The first step, identification of all possible assays, was relatively easy because the Working Group participants had a broad understanding of existing and surfacing technologies. The list of potential assays was all- encompassing and became too large for a single table format. It was agreed that the assays needed to be sorted according to their functional properties. Four separate functional property groupings were established: 1) prodromata; 2) haematological/biochemical; 3) cytogenetic; and 4) physical. Within each functional area, technologies/assays were characterized by a number of Rating Criteria; these were the same in all functional groups for all technologies (Specificity, Sensitivity, Low Background, Low Donor Variability, Doubling Dose, Dose Response Calibration, Persistent Effect, Ease of Sampling, Early Sampling, Ease of Analysis, Rapid Analysis, Simplicity of Analysis, Low Inter-observer Error Probability, Low Intra-observer Error Probability, Cost, Risk Meter, Relative Biological Effect (RBE), Partial Body Exposure, Automation, and Deployable). Once the criteria were established, the Working Group members evaluated each Rating Criteria using the TRL guide. The average TRL was determined by averaging the TRL scores for all Rating Criteria in a given technology. The confidence of each assay was determined by tabulating the total number of Rating Criteria against the accompanying average TRL. This cumulative evaluation of the available technologies is presented in Figures 1 through 4.
Table 1:
Technology Readiness Level (TRL) Assessment guide 0
Basic Research with Future Military Capability in Mind
1
Basic Principles Observed and Reported in Context of a Military Capability Shortfall
2
Technology Concept and / or Application Formulated
3
Analytical and Experimental Critical Function and / or Characteristic Proof of Concept
4
Component and / or “Breadboard” Validation in a Laboratory / Field (e.g., ocean) Environment
5
Component and / or “Breadboard” Validation in a Relevant (operating) Environment
6
System / Subsystem Model or Prototype Demonstration in a Realistic (operating) Environment or Context
7
System Prototype Demonstration in an Operational Environment or Context (e.g. exercise)
8
Actual System Completed and Qualified through Test and Demonstration
9
Actual System Operationally Proven through Successful Mission Operations The first step, identification of all possible assays, was relatively easy because the Working Group participants had a broad understanding of existing and surfacing technologies. The list of potential assays was all- encompassing and became too large for a single table format. It was agreed that the assays needed to be sorted according to their functional properties. Four separate functional property groupings were established: 1) prodromata; 2) haematological/biochemical; 3) cytogenetic; and 4) physical. Within each functional area, technologies/assays were characterized by a number of Rating Criteria; these were the same in all functional groups for all technologies (Specificity, Sensitivity, Low Background, Low Donor Variability, Doubling Dose, Dose Response Calibration, Persistent Effect, Ease of Sampling, Early Sampling, Ease of Analysis, Rapid Analysis, Simplicity of Analysis, Low Inter-observer Error Probability, Low Inta-observer Error Probability, Cost, Risk Meter, Relative Biological Effect (RBE), Partial Body Exposure, Automation, and Deployable). Once the criteria were established, the Working Group members evaluated each Rating Criteria using the TRL guide. The average TRL was determined by averaging the TRL scores for all Rating Criteria in a given technology. The confidence of each assay was determined by tabulating the total number of Rating Criteria against the accompanying average TRL. This cumulative evaluation of the available technologies is presented in Figures 1 to 4.
Figure 1: Prodromata Functional Area. Each point represents different Technology/Assay listed in the table legend and plotted against the Total Number of Criteria Scored. Rating Criteria evaluations for Prodromata Functional Area included: Specificity, Sensitivity, Low Background, Low Donor Variability, Doubling Dose, Dose Response Calibration, Persistent Effect, Ease of Sampling, Early Sampling, Ease of Analysis, Rapid Analysis, Simplicity of Analysis, Low Inter-observer Error Probability, Low Intra-observer Error Probability, Cost, Risk Meter, Relative Biological Effect (RBE), Partial Body Exposure, Automation, and Deployable. Note.
FRAT: First-responders Radiological Assessment Triage.
Figure 2: Haematological/Biochemical Functional Area. Each point represents different Technology/ Assay listed in the table legend and plotted against the Total Number of Criteria Scored. Rating Criteria evaluations for Haematological / Biochemical Functional Area included: Specificity, Sensitivity, Low Back- ground, Low Donor Variability, Doubling Dose, Dose Response Calibration, Persistent Effect, Ease of Sampling, Early Sampling, Ease of Analysis, Rapid Analysis, Simplicity of Analysis, Low Inter-observer Error Probability, Low Intra-observer Error Probability, Cost, Risk Meter, Relative Biological Effect (RBE), Partial Body Exposure, Automation, and Deployable. Note.
BAT (LDK): Biodosimetry Assessment Tool ? lymphocyte depletion kinetics algorithm. Figure 3: Cytogenetic Dosimetry Functional Area. Each point represents different Technology/Assay listed in the table legend and plotted against the Total Number of Criteria Scored. Rating Criteria evaluations for Cytogenetic Dosimetry Functional Area included: Specificity, Sensitivity, Low Background, Low Donor Variability, Doubling Dose, Dose Response Calibration, Persistent Effect, Ease of Sampling, Early Sampling, Ease of Analysis, Rapid Analysis, Simplicity of Analysis, Low Inter-observer Error Probability, Low Intra-observer Error Probability, Cost, Risk Meter, Relative Biological Effect (RBE), Partial Body Exposure, Automation, and Deployable. Note. PCC: premature chromosome condensation; RICA: rapid interphase chromosome aberration assay.
Figure 4: Physical Dosimetry Functional Area. Each point represents different Technology/Assay listed in the table legend and plotted against the Total Number of Criteria Scored. Rating Criteria evaluations for Physical Dosimetry Functional Area included: Specificity, Sensitivity, Low Background, Low Donor Variability, Doubling Dose, Dose Response Calibration, Persistent Effect, Ease of Sampling, Early Sampling, Ease of Analysis, Rapid Analysis, Simplicity of Analysis, Low Inter-observer Error Probability, Low Intra-observer Error Probability, Cost, Risk Meter, Relative Biological Effect (RBE), Partial Body Exposure, Automation, and Deployable. Note. TLD: Themoluminescence dosimetry: OSL: optically stimulated luminescence.
2.2 Interpretation of the Results
Each Functional Area (Figures 1 to 4) presented a distribution of TRLs for the different technologies/assays evaluated. For Prodromata (Figure 1), the top scoring assays were: 1) Time of, or to, Vomiting; and 2) Time of, or to, Nausea. Time of, or to, Vomiting had the highest average TRL score (7.7), while Time of, or to, Nausea scored second highest with an average TRL of 6.2. The total criteria evaluated for both of these technol- ogies/assays were the greatest of all Prodromata, indicating the highest evaluator confidence. Most of the other technologies/assays evaluated had a much lower value for total number of criteria scored suggesting a lower confidence in these assays. Therefore, these other assays had an overall lower score even though they may have been scored high on the TRL scale. For Haematological/Biochemical technologies/assays (Figure 2), the top scoring assay was the Lymphocyte Depletion Kinetics with an average TRL score of 7.1 and the highest evaluator confidence.
Other assays may havred slightly higher on the TRL scale but fewer criteria were able to be evaluated indicating lower evaluator confidence. The Dicentric Assay scored the highest with an average TRL of 6.6 in the Cytogenetic Functional Area (Figure 3). The total number of criteria scored for all Cytogenetic Functional Area assays was very similar, and indicated a very high evaluator confidence level for all evaluated technologies/assays.
Figure 4 represented evaluation data for Physical Functional Area. Of all the technologies listed (Film badge, thermoluminescence dosimeter (TLD), optically stimulated luminescence (OSL), Neutron (Track H-polyallyldiglycol carbonate (PADC)), Neutron (Bubble), Neutron (Albedo effect single or multiple element), only three were evaluated. Although the confidence of the evaluations was low, the average TRL for all three physical technologies was very high (between 7.5 and 7.7). Based on the data analysis using the limited evaluator information, it can be concluded that the highest average TRLs were achieved with Physical Dosimetry, followed by Prodromata, Cytogenetic and then Heamatological/Biochemical technologies/assays. However, the highest evaluator confidence was observed in the Cytogenetic Functional Area followed by Haematological/Biochemical, Prodromata and then Physical. It is important to note that the Working Group participants contributing to the evaluation of this tool had an expertise bias in the biological Functional Areas. However, it is also important to note that medical professionals do not treat a dose but rather the symptoms of a dose exposure, and as such physical dosimeters alone should not dictate specific medical treatment decisions.
2.3 Critical Evaluation of the Tool
The developed Tool presented in Figures 1 to 4 and discussed in Section 2.2 is intended for guiding the selection, advancement, implementation and validation of complementary biodosimetry assays. Although this evaluation of cumulative data as a tool has merit and could lead to useful information, significant challenges
need to be overcome before this methodology would become fully useful. Some of these challenges include: 1. Differing Requirements by End-users: Early in the evaluation process, the question arose as to who would be using this information and how to provide this information in the most useful template. Initially it was
thought that this information would be used by the Military Planners and Medical First Responders for the purpose of planning and responding to Radiological/Nuclear emergency events. As a tool targeted to the medical community and planners, it had to be user friendly without a specific requirement for scientific details.
In addition to using this tool during emergency response scenarios and for planning, the question was also posed whether the provided information may be useful in the long-term medical management of irradiated casualties. Early and ongoing guidance on appropriate selection of assay methodologies may be required in a mass casualty disaster. This requirement may vary depending on the number of casualties, the type of injuries and the available resources. Again, in this case there would be no need for detailed scientific information.
The final application for this tool was to develop a TRL-based survey of presently available and upcoming technologies that would guide the directed funding and future research of the scientific community. For this requirement, a more detailed scientific overview was required 2. Coverage of Functional Areas: All presently available or upcoming technologies/assays were grouped according to four Functional Areas: 1) Prodromata; 2) Haematological/Biochemical; 3) Cytogenetic; and 4) Physical. The question was raised as to the completeness in coverage by these four functional areas and if there is a need for adding the Biophysical Functional Area (i.e. Radiobioassays). Biophysical Functional Area would deal with body fluid samples such as urinary, faecal, nose swabs and blows, and wound swabs. Due to the complexity of analysis, high dependence on the physico-chemical properties of the contaminating radionuclides, and the route of entry, this additional information could be meaning-less without expert interpretation. Even though it was decided to abstain from including this massive, unmanageable information, it was deemed an important Functional Area that needed to be recognised.
3. Assignment of TRL values: As the process evolved, it became very evident that it was difficult to assign a TRL value to a number of Rating Criteria characterizing each technology/assay. The TRL was calcu-lated by determining the average TRL across all criteria rated. Some responders felt that it was too dif-ficult to assign a TRL-based value to many of the Rating Criteria. Others suggested that the challenge
of assigning the most appropriate TRL to each criterion would require significant analysis by an extensive team of experts, and as a consequence they chose to abstain from the evaluation process.
Additionally, a question was posed: Does each of the evaluated Rating Criteria have equal weight or are some criteria more important than others? This biased weighting would result in different TRL values than those presented in Figures 1 to 4 and discussed in Section 2.2. The assignment of appropriate weight-ing factors to each of the Rating Criteria is foreseen as a daunting task with a potential for significant debates.
4. Selection of Rating Criteria: Aside from assigning the TRL value to each criterion, there was also some concern with the selected Rating Criteria. The Rating Criteria for each technology/assay in each Functional Area are the same. They are: Specificity, Sensitivity, Low Background, Low Donor Variability, Doubling Dose, Dose Response Calibration, Persistent Effect, Ease of Sampling, Early
Sampling, Ease of Analysis, Rapid Analysis, Simplicity of Analysis, Low Inter-observer Error Probability, Low Intra-observer Error Probability, Cost, Risk Meter, Relative Biological Effect (RBE),
Partial Body Exposure, Automation, and Deployable. Some of the reviewers questioned the appropriate-ness of applying the same Rating Criteria against some technologies/assays. In some cases not all Rating
Criteria were given a TRL. For this reason the total number of criteria rated by all evaluators was different for different technologies/assays.
5. Lack of Evaluator Response: Early in the process it became evident that despite the diligent efforts of the participants, there was a strong hesitation to complete the evaluation process. The lack of sufficient
responses indicated that the resulting evaluation process may be biased and in line with opinions of very few responders; in all cases only 3 or fewer data sets contributed to the evaluation of average
TRLs. This would suggest that the presented TRLs in Figures 1 to 4 may not be representative of a broader scientific community.
6. Bias in Expertise: There was a strong bias in evaluating the rating criteria for the biological techno- logies/assays (Figures 1 to 3), as discussed in Section 2.2. Comparatively, expertise in evaluating the Physical Functional Area technologies was lacking.
TRL Variation: Finally, even with a small number of respondents, it was evident that the experts contributing to the evaluation process had different opinions on the appropriate TRL for many of the Rating Criteria. In
some cases there was a great variance in the criteria scored and the allocated TRLs.
Proposed Solutions/Recommendations
1. The proposed tool has a strong potential for providing ―finger tip? information to medical profession- als, emergency planners and the supporting scientific community. For maximum impact, the tool
would need to be expanded to provide more detailed information for the scientific community and the funding agencies, and then compressed for rapid and easy access by the medical professionals and
emergency planners. In both circumstances, for the tool to be of value, it would have to be kept as current as possible with the latest scientific developments.
2. It is recognized that the tool is lacking the Biophysical Functional Area. The information gained through Biophysical technologies/assays is of significant importance and needs to be acknowledged.
Useful integration of this information can only be achieved through the use of computer automation.
3. The process of developing this tool was based on evaluating the same Rating Criteria across different Functional Areas. One recommendation may be to introduce unique and most appropriate Rating Criteria
for each Functional Area. Moreover, even though it may be justifiable to introduce calculated weighting factors for different Rating Criteria, it is very clear that such activity would be subject to broad debate
and scrutiny and therefore not feasible.
4. Finally, for this assay to be most useful, the data input would need to come from a much broader group of experts, including experts in physical and biophysical dosimetry. By expanding the number of
evaluators who bring different expertise it is likely that the calculation of average TRL values would be more representative of the broader scientific community. Increasing the number of evaluators
may result in a more realistic and non-biased calculations of TRLs and also provide some prediction of opinion-deviances.
2.4 Summary
The proposed tool intended to guide the selection, advancement, implementation and validation of complementing biodosimetry assays is most likely to be of greatest benefit to the community of biodosimetry
experts who may in turn support and advise medical and emergency response professionals. The information gathered through contributions from an extensive group of experts could lead to a very useful tool that would
need to be continually updated and maintained to provide the best information. Finally, it is important to remember that the final selection of appropriate technologies/assays will depend on
the unique scenario, the available resources and expertise, and on the interactive communications among many disciplines.
3.0 DEVELOP AND VALIDATE LEAD CANDIDATE MULTI-PARAMETER BIODOSIMETRY TOOLS [CAN, CZE, DEU, FRA, GBR, NOR, POL, SWE, USA] Medical management of radiation casualties necessitates the use of multiple parameter biological dosimetry
assessment. Even more desirable (and more difficult to accomplish) is the identification of parameters (biomarkers) predicting the extent of radiation induced cell damage, the biological response to it and finally
the prognosis.
Figure 5: Summary on RTG033 efforts for elucidating gene expression significance for biodosimetry. In vitro models either comprise irradiated peripheral mononucleated cells (PMNC) or peripheral blood lymphocytes (PBL). No single parameter is sufficient to cover the large variety of possible scenarios (from dirty bomb to nuclear
weapon) and specific requirements on the measurements. For acute radiation effects, results within the first 4 days after exposure are required. In case of late effects, measurements performed years after exposure should
provide some clues to the potential exposure. The dicentric chromosomal aberration assay (DCA assay) represents the most established assay for dose estimates. As an effort of RTG033 this kind of analysis was combined with known dose dependency of acute
clinical signs/symptoms occurring after radiation exposure together with physical dosimetric measurements and other parameter to a software called BAT (Biodosimetry Assessment Tool). Still, this approach
necessitates inputs from further areas in order to combine the strength of different assays and to compensate for their limitations.
Nowadays, there is overall agreement on the potential of radiation associated gene expression changes for biodosimetry (Amundson 2000, 2001, Blakely 2003, Grace 2002). Less is known on the prediction of
radiation induced cell damage by radiation associated gene expression changes. Candidates like GADD45A, CDKN1A (p21) or Bax showed a dose-response relationship in a large variety of different in vitro and in vivo
models. Besides these promising findings a systematic approach is needed for contributing to the task described above. This includes a meaningful combination of in vitro and in vivo models together with a corresponding sequence of different gene expression methods and platforms (Figure 5).
Different nations (FRA, GER, USA) exchanged results on gene expression within the framework of RTG033 and plan to continue working together on future joint projects. As a result of these efforts a variety of in vitro
and in vivo models using different exposures and platforms for gene expression analysis evolved (Figure 6). The concept, interplay and results (summarized) of these efforts are shown below.
Figure 6: Fold-changes in radiation associated GADD45A gene expression relative to control utilizing different in vitro models and time points up to 48 h after irradiation. PMNCs were incubated
at different conditions (room temperature, left graph or at 37°C remainder two graphs) and GADD45A gene expression was measured either on PMNCs or at CD4+ lymphocytes only, as indicated in the
graphs. Data in the left and right graphs represent unpublished data (GER). Fold-changes of PMNC incubated at 37°C (graph in the middle) are mean values examined in three individuals and are drawn
from RTG033 2005 report (Grace et al.). Symbols represent mean values and error bars are SEM (n=30 for PMNC at room temperature and n=6 for CD4+ lymphocytes incubated a 37°C).
3.1 Exposures
Exposures using different quality of radiation, doses and desirably different dose rates are needed in order to cover a large variety of possible exposure scenarios. AFRRI provided and will continue to provide the
professional support (physical dosimetry department) requirements. A USA study on primates irradiated with sub-lethal and supra-lethal doses was completed in 2009 with samples archived for GER to perform a 2-stage
study design. First, a whole genome screening utilizing a microarray will be done to search for radiation associated up- and down- regulated genes. Second, the ―h ot candidate genes? resulting from the microarray
screening will be examined quantitatively using a certain high throughput quantitative real-time PCR platform (TaqArray or low Density Array, LDA).
3.2 In Vitro/In Vivo Models
Three in vitro models were established (Figure 5). These models probably depict different aspects of in vivo models; however these in vitro models need to be validated against in vivo models. In this context the
following features must be considered. Radiosensitivity of blood subpopulations differs according to the following sequence (from highest to lowest sensitivity): B-lymphocytes > CD4+
lymphocytes > CD8+ lymphocytes > NK cells (Louagie et al. 1999).
The number within each blood subpopulation differs among individuals.
The blood in the human body is circulating. This facilitates an interaction with other body parts to occur.
The peripheral blood represents only one compartment of the hematopoietic system. Examinations focusing on peripheral blood do not cover other compartments such as the bone marrow or lymphatic
system. About 1% of all lymphocytes are circulating in the periphery and about 50% are located in the gastrointestinal tract. Radiosensitivity of the hematopoetic system is higher than for most other organ systems.
In other words, the significance of examinations of whole blood in vitro models is limited. Only by compari-son with results from in vivo models can their impact for biodosimetry be judged.
In a first attempt, all contributing nations examined whether a dose response relationship of already assumed/known radiation-induced genes using semiquantitive microarrays (Amundson et al. 2000) can be
demonstrated/shown in their in vitro models, by utilizing more quantitative methods (RTQ-PCR). In particular GADD45A (and others) proved to be of significance (Figure 6 and Grace et al. RTG033 2005 report).
Nevertheless, the pros/cons of the in vitro models (Table 2) necessitate in vivo examinations using in vivo models. Provided the agreement between the models is satisfying, further examinations (e.g. changes in dose
rate) could continue to be performed in in vitro models. This strategy amplifies the task of RTG033 by significantly reducing the number of animal experiments as much as possible. Hence, cooperation between partners combining their expertise will enable joint experiments, as outlined above, in the forthcoming USA primate study. An ongoing French-German cooperation examines gene expression changes on irradiated swine epidermis.
Table 2: Characteristics (pros/cons) of different in vitro models using peripheral mononucleated cells (PMNC) or isolated peripheral blood lymphocytes (PBL with CD4+/CD8+).
3.3 Platforms/Chemistries
A large variety of commercially available chemistries and platforms can be utilized for gene expression-based biodosimetry. The endpoint for these models is gene expression changes measured in peripheral blood after radiation exposure. RNA is a sensitive molecule and can degrade easily because of ubiquitously existing RNases (e.g., contamination from hands).
PAXGene refers to a system which lyses the peripheral blood after venipuncture using Bectin Dickerson‘s Vacutainer R technology (Bectin Dickerson, Franklin Lakes, NJ, USA).
Using this technology platsform RNases become inhibited thus stabilizing the RNA and gene expression changes induced in vivo become ― frozen?. However, cell subpopulations ( e.g., lymphocytes) can not be selected with this method. This method provides an overall picture for gene expression changes occurring within the whole peripheral blood. For selection of cell subpopulations CPT-tubes could be utilized. After venipuncture using a CPT Vacutainer
R system these tubes are centrifuged leading to a physical separation of serum and PMNC from erythrocytes.
This system is stable for 2 days at room temperature. Since it is not required to open the tubes for this procedure the samples remain sterile. Interestingly, cells remaining in these tubes provide an opportunity for examining them under almost normal conditions, such as human serum, without adding artificial substitutes.
Artificial substitutes (e.g. fetal calf serum, RPMI 1640 medium, antibiotics) are added into plastic dishes for in vitro culturing when collecting peripheral blood in EDTA tubes. Although this approach sounds very
artificial it represents the most common procedure, presumably due to decades of experience with this system for the purpose of examining another endpoint (i.e. the dicentric chromosomal aberrations). This approach
was slightly changed in a model established by the German contributor by adding 10% of human serum to the cell culture.
For quantification of gene expression changes occurring in already known radiation induced genes, a single or a multiplex quantitative RT-PCR is utilized (USA, GER). The latter would be preferable, because of
lower costs and probably higher precision (Grace et al, 2003), but additional experiments for establishing a quadruplex RTQ-PCR (USA), for example, are required.
For quantification of gene expression changes occurring in unknown radiation induced genes, a two-stage study design was developed (USA, GER). A genome wide screening with microarrays allows for detection of
potential candidate genes. In the second stage, the gene expression of these genes becomes quantified using a high-throughput RTQ-PCR platform called TaqArray. This platform allows quantifying gene expression of
384 genes at the same time. Details are described in the final report SG1.
This two stage study was utilized in one in vitro model (GER) and is planned to be expanded into the forthcoming primate model. Data are currently under examination. Interesting, about 50% of the candidate
genes selected reveal no changes in gene expression levels.
3.4 Summary
In summary, the significance of already established in vitro models has to be validated by complementary in vivo experiments in near future. This next step will allow us to go back to the validated in vitro models in order to
continue more detailed examinations on the dose response relationships, but avoiding further animal models.
4.0 EVALUATE SOFTWARE APPLICATIONS DESIGNED TO PROVIDE RADIATION INJURY ASSESSMENT, BIOLOGICAL DOSIMETRY INFORMATION AND GUIDANCE TO THE FIRST-RESPONDER AND FIRST-
RECEIVER COMMUNITIES [CAN, CZE, DEU, FRA, GBR, SWE, USA]
There are numerous software tools available for field deployment, reach-back, training and planning use in the event of a radiological or nuclear (RN) terrorist event. Specialized software tools used by CBRNe responders can increase information available and the speed and accuracy of the response, thereby ensuring that radiation
doses to responders, receivers, and the general public are kept as low as reasonably achievable. Software designed to provide health care providers with assistance in selecting appropriate countermeasures or
therapeutic interventions in a timely fashion can improve the potential for positive patient outcome. Several software packages are described in this section and by Waller et al., 2009; although the list of software
presented here is not exhaustive, it does provide a reasonable overview of the types of materials available to the NATO community.
Software tools can be categorized in different manners. One method is to categorize by end user such as: first- on-scene, CBRNe responder, incident commander, health physics reach-back, hospital emergency services,
biodosimetrist, or forensics criminal investigator. A second method is by application use such as: hazard prediction, human effects estimation, and medical triage, dosimetry and treatment. Regardless of the
categorization method used, some of the software tools will fit into multiple categories. It should be noted that since these software tools are, in general, developed for a particular target user, it is very important that they
be used within their intended scope and that users be appropriately trained.
4.1 Hazard Prediction Models
The first group of software tools described in this section are fundamentally hazard prediction models. The codes will allow the user to define an incident or source term and using various transport and dispersion
models, will predict the resultant plume or hazard area. The models estimate the resultant dose or dose rates that might be expected as a result of the dispersed material and some of the models will also
estimate the human response to the dose. Many of these models will perform similar calculations for chemical and biological hazards.
4.1.1 Hazard Prediction and Assessment Capability (HPAC)
The Hazard Prediction and Assessment Capability (HPAC) is a software application that models the transport and dispersion of chemical, biological, radiological and nuclear (CBRN) releases into the atmosphere and
predicts the effects of those hazards on civilian and military populations. HPAC was first released in 1992 and continues to be improved through development funding by the Defense Threat Reduction Agency (DTRA).
HPAC includes several integrated source terms for chemical and biological hazards, as well as for radiological dispersal devices (RDDs), nuclear facility accidents, and nuclear weapon detonations. The transport engine for
the HPAC software, a second-order closure, integrated puff (SCIPUFF) model, is based on a 3-dimensional puff methodology. The transport and dispersion calculation utilizes local terrain effects, including urban
terrain, and can utilize real-time weather input. The airborne concentration and downwind deposition of the hazard plumes are calculated and the results can be used to predict human effects. As a result, the model can
plot not only airborne and deposited activity concentrations, but also internal and external dose estimates. In addition, casualty predictions are estimated based on both prompt nuclear weapon effects and protracted
radiation exposure.
HPAC is used by both military and civilian users for planning, training and exercises, as well as for real-time assessments of on-going incidents. Requests for HPAC software can be made at the following website:
https://acecenter.cnttr.dtra.mil/registration/mainpage.cfm.
4.1.2 HotSpot |
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