42 resultados para Radiation dose reduction
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The prognosis for lung cancer patients remains poor. Five year survival rates have been reported to be 15%. Studies have shown that dose escalation to the tumor can lead to better local control and subsequently better overall survival. However, dose to lung tumor is limited by normal tissue toxicity. The most prevalent thoracic toxicity is radiation pneumonitis. In order to determine a safe dose that can be delivered to the healthy lung, researchers have turned to mathematical models predicting the rate of radiation pneumonitis. However, these models rely on simple metrics based on the dose-volume histogram and are not yet accurate enough to be used for dose escalation trials. The purpose of this work was to improve the fit of predictive risk models for radiation pneumonitis and to show the dosimetric benefit of using the models to guide patient treatment planning. The study was divided into 3 specific aims. The first two specifics aims were focused on improving the fit of the predictive model. In Specific Aim 1 we incorporated information about the spatial location of the lung dose distribution into a predictive model. In Specific Aim 2 we incorporated ventilation-based functional information into a predictive pneumonitis model. In the third specific aim a proof of principle virtual simulation was performed where a model-determined limit was used to scale the prescription dose. The data showed that for our patient cohort, the fit of the model to the data was not improved by incorporating spatial information. Although we were not able to achieve a significant improvement in model fit using pre-treatment ventilation, we show some promising results indicating that ventilation imaging can provide useful information about lung function in lung cancer patients. The virtual simulation trial demonstrated that using a personalized lung dose limit derived from a predictive model will result in a different prescription than what was achieved with the clinically used plan; thus demonstrating the utility of a normal tissue toxicity model in personalizing the prescription dose.
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The object of this work was to study the possibility that microtubule assembly might be involved in radiation sensitivity effect. The proliferating hair follicle was used to study the effects of cooling c-AMP, colcemid, and vincristine on the survival of the hair after irradiation. It was found that after 2 hours of cooling at the rewarming stage of the hair follicles, the sensitivity to irradiation increased and colcemid reversed this effect. c-AMP decreased radiosensitivity and together with colcemid, sensitivity decreased considerably. It is proposed that the assembly of microtubules is sensitive to irradiation.^ Total tubulin in L-P59 tumor measured immediately after irradiation was found to decrease in a dose specific manner after single doses ranging from 500 to 2000 rad. It is proposed that the change in Ca('2+) concentration after irradiation might cause this effect. Irradiation inhibited the increase in specific viscosity of 3x and 1x tubulin irradiated at the time of assembly. A small reduction in specific viscosity was found when polymerized microtubules were irradiated.^ From these experiments it is proposed that the assembly of microtubules is affected by irradiation. It may be the result of an increase in CA('2+) concentration in the tissue after irradiation or an inactivation of the initiation centers. The effects of irradiation on unassembled tubulin or assembled microtubules is negligible. ^
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The considerable search for synergistic agents in cancer research is motivated by the therapeutic benefits achieved by combining anti-cancer agents. Synergistic agents make it possible to reduce dosage while maintaining or enhancing a desired effect. Other favorable outcomes of synergistic agents include reduction in toxicity and minimizing or delaying drug resistance. Dose-response assessment and drug-drug interaction analysis play an important part in the drug discovery process, however analysis are often poorly done. This dissertation is an effort to notably improve dose-response assessment and drug-drug interaction analysis. The most commonly used method in published analysis is the Median-Effect Principle/Combination Index method (Chou and Talalay, 1984). The Median-Effect Principle/Combination Index method leads to inefficiency by ignoring important sources of variation inherent in dose-response data and discarding data points that do not fit the Median-Effect Principle. Previous work has shown that the conventional method yields a high rate of false positives (Boik, Boik, Newman, 2008; Hennessey, Rosner, Bast, Chen, 2010) and, in some cases, low power to detect synergy. There is a great need for improving the current methodology. We developed a Bayesian framework for dose-response modeling and drug-drug interaction analysis. First, we developed a hierarchical meta-regression dose-response model that accounts for various sources of variation and uncertainty and allows one to incorporate knowledge from prior studies into the current analysis, thus offering a more efficient and reliable inference. Second, in the case that parametric dose-response models do not fit the data, we developed a practical and flexible nonparametric regression method for meta-analysis of independently repeated dose-response experiments. Third, and lastly, we developed a method, based on Loewe additivity that allows one to quantitatively assess interaction between two agents combined at a fixed dose ratio. The proposed method makes a comprehensive and honest account of uncertainty within drug interaction assessment. Extensive simulation studies show that the novel methodology improves the screening process of effective/synergistic agents and reduces the incidence of type I error. We consider an ovarian cancer cell line study that investigates the combined effect of DNA methylation inhibitors and histone deacetylation inhibitors in human ovarian cancer cell lines. The hypothesis is that the combination of DNA methylation inhibitors and histone deacetylation inhibitors will enhance antiproliferative activity in human ovarian cancer cell lines compared to treatment with each inhibitor alone. By applying the proposed Bayesian methodology, in vitro synergy was declared for DNA methylation inhibitor, 5-AZA-2'-deoxycytidine combined with one histone deacetylation inhibitor, suberoylanilide hydroxamic acid or trichostatin A in the cell lines HEY and SKOV3. This suggests potential new epigenetic therapies in cell growth inhibition of ovarian cancer cells.
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The RPC developed a new phantom to ensure comparable and consistent radiation administration in spinal radiosurgery clinical trials. This study assessed the phantom’s dosimetric and anatomic utility. The ‘spine phantom’ is a water filled thorax with anatomy encountered in spinal radiosurgery: target volume, vertebral column, spinal canal, esophagus, heart, and lungs. The dose to the target volume was measured with axial and sagittal planes of radiochromic film and thermoluminescent dosimeters (TLD). The dose distributions were measured with the radiochromic film calibrated to the absolute dose measured by the TLD. Four irradiations were administered: a four angle box plan, a seven angle conformal plan, a seven angle IMRT plan, and a nine angle IMRT plan (denoted as IMRT plan #1 and plan #2, respectively). In each plan, at least 95% of the defined tumor volume received 8 Gy. For each irradiation the planned and administered dose distributions were registered via pinpricks, and compared using point dose measurements, dose profiles, isodose distributions, and gamma analyses. Based on previous experience at the RPC, a gamma analysis was considering passing if greater than 95% of pixels passed the criteria of 5% dose difference and 3 mm distance-to-agreement. Each irradiation showed acceptable agreement in the qualitative assessments and exceeded the 95% passing rate at the 5% / 3 mm criteria, except IMRT plan #1, which was determined to have been poorly localized during treatment administration. The measured and planned dose distributions demonstrated acceptable agreement at the 5% / 3 mm criteria, and the spine phantom was determined to be a useful tool for the remote assessment of an institution’s treatment planning and dose delivery regimen.
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The motion of lung tumors during respiration makes the accurate delivery of radiation therapy to the thorax difficult because it increases the uncertainty of target position. The adoption of four-dimensional computed tomography (4D-CT) has allowed us to determine how a tumor moves with respiration for each individual patient. Using information acquired during a 4D-CT scan, we can define the target, visualize motion, and calculate dose during the planning phase of the radiotherapy process. One image data set that can be created from the 4D-CT acquisition is the maximum-intensity projection (MIP). The MIP can be used as a starting point to define the volume that encompasses the motion envelope of the moving gross target volume (GTV). Because of the close relationship that exists between the MIP and the final target volume, we investigated four MIP data sets created with different methodologies (3 using various 4D-CT sorting implementations, and one using all available cine CT images) to compare target delineation. It has been observed that changing the 4D-CT sorting method will lead to the selection of a different collection of images; however, the clinical implications of changing the constituent images on the resultant MIP data set are not clear. There has not been a comprehensive study that compares target delineation based on different 4D-CT sorting methodologies in a patient population. We selected a collection of patients who had previously undergone thoracic 4D-CT scans at our institution, and who had lung tumors that moved at least 1 cm. We then generated the four MIP data sets and automatically contoured the target volumes. In doing so, we identified cases in which the MIP generated from a 4D-CT sorting process under-represented the motion envelope of the target volume by more than 10% than when measured on the MIP generated from all of the cine CT images. The 4D-CT methods suffered from duplicate image selection and might not choose maximum extent images. Based on our results, we suggest utilization of a MIP generated from the full cine CT data set to ensure a representative inclusive tumor extent, and to avoid geometric miss.
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Introduction Commercial treatment planning systems employ a variety of dose calculation algorithms to plan and predict the dose distributions a patient receives during external beam radiation therapy. Traditionally, the Radiological Physics Center has relied on measurements to assure that institutions participating in the National Cancer Institute sponsored clinical trials administer radiation in doses that are clinically comparable to those of other participating institutions. To complement the effort of the RPC, an independent dose calculation tool needs to be developed that will enable a generic method to determine patient dose distributions in three dimensions and to perform retrospective analysis of radiation delivered to patients who enrolled in past clinical trials. Methods A multi-source model representing output for Varian 6 MV and 10 MV photon beams was developed and evaluated. The Monte Carlo algorithm, know as the Dose Planning Method (DPM), was used to perform the dose calculations. The dose calculations were compared to measurements made in a water phantom and in anthropomorphic phantoms. Intensity modulated radiation therapy and stereotactic body radiation therapy techniques were used with the anthropomorphic phantoms. Finally, past patient treatment plans were selected and recalculated using DPM and contrasted against a commercial dose calculation algorithm. Results The multi-source model was validated for the Varian 6 MV and 10 MV photon beams. The benchmark evaluations demonstrated the ability of the model to accurately calculate dose for the Varian 6 MV and the Varian 10 MV source models. The patient calculations proved that the model was reproducible in determining dose under similar conditions described by the benchmark tests. Conclusions The dose calculation tool that relied on a multi-source model approach and used the DPM code to calculate dose was developed, validated, and benchmarked for the Varian 6 MV and 10 MV photon beams. Several patient dose distributions were contrasted against a commercial algorithm to provide a proof of principal to use as an application in monitoring clinical trial activity.
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Dominant-negative mutations in the homopentameric extracellular matrix glycoprotein cartilage oligomeric matrix protein (COMP) result in inappropriate intracellular retention of misfolded COMP in the rough endoplasmic reticulum of chondrocytes, causing chondrocyte cell death, which leads to two skeletal dysplasias: pseudoachondroplasia (PSACH) and multiple epiphyseal dysplasia (EDM1). COMP null mice show no adverse effects on normal bone development and growth, suggesting a possible therapy involving removal of COMP mRNA. The goal of this study was to assess the ability of a hammerhead ribozyme (Ribo56, designed against the D469del mutation) to reduce COMP mRNA expression. In COS7 cells transfected with plasmids that overexpress wild-type or mutant COMP mRNA and Ribo56, the ribozyme reduced overexpressed normal COMP mRNA by 46% and mutant COMP mRNA by 56% in a dose-dependent manner. Surprisingly, the use of recombinant adenoviruses to deliver wild-type or mutant COMP mRNA and Ribo56 simultaneously into COS7 cells proved problematic for the activity of the ribozyme to reduce COMP expression. However, in normal human costochondral cells (hCCCs) infected only with adenoviruses expressing Ribo56, expression of endogenous wild-type COMP mRNA was reduced in a dose-dependent manner by 50%. In chondrocytes that contain heterozygous COMP mutations (D469del, G427E and D511Y) that cause PSACH, Ribo56 was more effective at reducing COMP mRNA (up to 70%). These results indicate that Ribo56 is effective at reducing mutant and wild-type COMP levels in cells and suggests a possible mode of therapy to reduce the mutant protein load.
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Proton radiation therapy is gaining popularity because of the unique characteristics of its dose distribution, e.g., high dose-gradient at the distal end of the percentage-depth-dose curve (known as the Bragg peak). The high dose-gradient offers the possibility of delivering high dose to the target while still sparing critical organs distal to the target. However, the high dose-gradient is a double-edged sword: a small shift of the highly conformal high-dose area can cause the target to be substantially under-dosed or the critical organs to be substantially over-dosed. Because of that, large margins are required in treatment planning to ensure adequate dose coverage of the target, which prevents us from realizing the full potential of proton beams. Therefore, it is critical to reduce uncertainties in the proton radiation therapy. One major uncertainty in a proton treatment is the range uncertainty related to the estimation of proton stopping power ratio (SPR) distribution inside a patient. The SPR distribution inside a patient is required to account for tissue heterogeneities when calculating dose distribution inside the patient. In current clinical practice, the SPR distribution inside a patient is estimated from the patient’s treatment planning computed tomography (CT) images based on the CT number-to-SPR calibration curve. The SPR derived from a single CT number carries large uncertainties in the presence of human tissue composition variations, which is the major drawback of the current SPR estimation method. We propose to solve this problem by using dual energy CT (DECT) and hypothesize that the range uncertainty can be reduced by a factor of two from currently used value of 3.5%. A MATLAB program was developed to calculate the electron density ratio (EDR) and effective atomic number (EAN) from two CT measurements of the same object. An empirical relationship was discovered between mean excitation energies and EANs existing in human body tissues. With the MATLAB program and the empirical relationship, a DECT-based method was successfully developed to derive SPRs for human body tissues (the DECT method). The DECT method is more robust against the uncertainties in human tissues compositions than the current single-CT-based method, because the DECT method incorporated both density and elemental composition information in the SPR estimation. Furthermore, we studied practical limitations of the DECT method. We found that the accuracy of the DECT method using conventional kV-kV x-ray pair is susceptible to CT number variations, which compromises the theoretical advantage of the DECT method. Our solution to this problem is to use a different x-ray pair for the DECT. The accuracy of the DECT method using different combinations of x-ray energies, i.e., the kV-kV, kV-MV and MV-MV pair, was compared using the measured imaging uncertainties for each case. The kV-MV DECT was found to be the most robust against CT number variations. In addition, we studied how uncertainties propagate through the DECT calculation, and found general principles of selecting x-ray pairs for the DECT method to minimize its sensitivity to CT number variations. The uncertainties in SPRs estimated using the kV-MV DECT were analyzed further and compared to those using the stoichiometric method. The uncertainties in SPR estimation can be divided into five categories according to their origins: the inherent uncertainty, the DECT modeling uncertainty, the CT imaging uncertainty, the uncertainty in the mean excitation energy, and SPR variation with proton energy. Additionally, human body tissues were divided into three tissue groups – low density (lung) tissues, soft tissues and bone tissues. The uncertainties were estimated separately because their uncertainties were different under each condition. An estimate of the composite range uncertainty (2s) was determined for three tumor sites – prostate, lung, and head-and-neck, by combining the uncertainty estimates of all three tissue groups, weighted by their proportions along typical beam path for each treatment site. In conclusion, the DECT method holds theoretical advantages in estimating SPRs for human tissues over the current single-CT-based method. Using existing imaging techniques, the kV-MV DECT approach was capable of reducing the range uncertainty from the currently used value of 3.5% to 1.9%-2.3%, but it is short to reach our original goal of reducing the range uncertainty by a factor of two. The dominant source of uncertainties in the kV-MV DECT was the uncertainties in CT imaging, especially in MV CT imaging. Further reduction in beam hardening effect, the impact of scatter, out-of-field object etc. would reduce the Hounsfeld Unit variations in CT imaging. The kV-MV DECT still has the potential to reduce the range uncertainty further.
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Intensity modulated radiation therapy (IMRT) is a technique that delivers a highly conformal dose distribution to a target volume while attempting to maximally spare the surrounding normal tissues. IMRT is a common treatment modality used for treating head and neck (H&N) cancers, and the presence of many critical structures in this region requires accurate treatment delivery. The Radiological Physics Center (RPC) acts as both a remote and on-site quality assurance agency that credentials institutions participating in clinical trials. To date, about 30% of all IMRT participants have failed the RPC’s remote audit using the IMRT H&N phantom. The purpose of this project is to evaluate possible causes of H&N IMRT delivery errors observed by the RPC, specifically IMRT treatment plan complexity and the use of improper dosimetry data from machines that were thought to be matched but in reality were not. Eight H&N IMRT plans with a range of complexity defined by total MU (1460-3466), number of segments (54-225), and modulation complexity scores (MCS) (0.181-0.609) were created in Pinnacle v.8m. These plans were delivered to the RPC’s H&N phantom on a single Varian Clinac. One of the IMRT plans (1851 MU, 88 segments, and MCS=0.469) was equivalent to the median H&N plan from 130 previous RPC H&N phantom irradiations. This average IMRT plan was also delivered on four matched Varian Clinac machines and the dose distribution calculated using a different 6MV beam model. Radiochromic film and TLD within the phantom were used to analyze the dose profiles and absolute doses, respectively. The measured and calculated were compared to evaluate the dosimetric accuracy. All deliveries met the RPC acceptance criteria of ±7% absolute dose difference and 4 mm distance-to-agreement (DTA). Additionally, gamma index analysis was performed for all deliveries using a ±7%/4mm and ±5%/3mm criteria. Increasing the treatment plan complexity by varying the MU, number of segments, or varying the MCS resulted in no clear trend toward an increase in dosimetric error determined by the absolute dose difference, DTA, or gamma index. Varying the delivery machines as well as the beam model (use of a Clinac 6EX 6MV beam model vs. Clinac 21EX 6MV model), also did not show any clear trend towards an increased dosimetric error using the same criteria indicated above.
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Advances in radiotherapy have generated increased interest in comparative studies of treatment techniques and their effectiveness. In this respect, pediatric patients are of specific interest because of their sensitivity to radiation induced second cancers. However, due to the rarity of childhood cancers and the long latency of second cancers, large sample sizes are unavailable for the epidemiological study of contemporary radiotherapy treatments. Additionally, when specific treatments are considered, such as proton therapy, sample sizes are further reduced due to the rareness of such treatments. We propose a method to improve statistical power in micro clinical trials. Specifically, we use a more biologically relevant quantity, cancer equivalent dose (DCE), to estimate risk instead of mean absorbed dose (DMA). Our objective was to demonstrate that when DCE is used fewer subjects are needed for clinical trials. Thus, we compared the impact of DCE vs. DMA on sample size in a virtual clinical trial that estimated risk for second cancer (SC) in the thyroid following craniospinal irradiation (CSI) of pediatric patients using protons vs. photons. Dose reconstruction, risk models, and statistical analysis were used to evaluate SC risk from therapeutic and stray radiation from CSI for 18 patients. Absorbed dose was calculated in two ways: with (1) traditional DMA and (2) with DCE. DCE and DMA values were used to estimate relative risk of SC incidence (RRCE and RRMA, respectively) after proton vs. photon CSI. Ratios of RR for proton vs. photon CSI (RRRCE and RRRMA) were then used in comparative estimations of sample size to determine the minimal number of patients needed to maintain 80% statistical power when using DCE vs. DMA. For all patients, we found that protons substantially reduced the risk of developing a second thyroid cancer when compared to photon therapy. Mean RRR values were 0.052±0.014 and 0.087±0.021 for RRRMA and RRRCE, respectively. However, we did not find that use of DCE reduced the number of patents needed for acceptable statistical power (i.e, 80%). In fact, when considerations were made for RRR values that met equipoise requirements and the need for descriptive statistics, the minimum number of patients needed for a micro-clinical trial increased from 17 using DMA to 37 using DCE. Subsequent analyses revealed that for our sample, the most influential factor in determining variations in sample size was the experimental standard deviation of estimates for RRR across the patient sample. Additionally, because the relative uncertainty in dose from proton CSI was so much larger (on the order of 2000 times larger) than the other uncertainty terms, it dominated the uncertainty in RRR. Thus, we found that use of corrections for cell sterilization, in the form of DCE, may be an important and underappreciated consideration in the design of clinical trials and radio-epidemiological studies. In addition, the accurate application of cell sterilization to thyroid dose was sensitive to variations in absorbed dose, especially for proton CSI, which may stem from errors in patient positioning, range calculation, and other aspects of treatment planning and delivery.
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The MDAH pencil-beam algorithm developed by Hogstrom et al (1981) has been widely used in clinics for electron beam dose calculations for radiotherapy treatment planning. The primary objective of this research was to address several deficiencies of that algorithm and to develop an enhanced version. Two enhancements have been incorporated into the pencil-beam algorithm; one models fluence rather than planar fluence, and the other models the bremsstrahlung dose using measured beam data. Comparisons of the resulting calculated dose distributions with measured dose distributions for several test phantoms have been made. From these results it is concluded (1) that the fluence-based algorithm is more accurate to use for the dose calculation in an inhomogeneous slab phantom, and (2) the fluence-based calculation provides only a limited improvement to the accuracy the calculated dose in the region just downstream of the lateral edge of an inhomogeneity. The source of the latter inaccuracy is believed primarily due to assumptions made in the pencil beam's modeling of the complex phantom or patient geometry.^ A pencil-beam redefinition model was developed for the calculation of electron beam dose distributions in three dimensions. The primary aim of this redefinition model was to solve the dosimetry problem presented by deep inhomogeneities, which was the major deficiency of the enhanced version of the MDAH pencil-beam algorithm. The pencil-beam redefinition model is based on the theory of electron transport by redefining the pencil beams at each layer of the medium. The unique approach of this model is that all the physical parameters of a given pencil beam are characterized for multiple energy bins. Comparisons of the calculated dose distributions with measured dose distributions for a homogeneous water phantom and for phantoms with deep inhomogeneities have been made. From these results it is concluded that the redefinition algorithm is superior to the conventional, fluence-based, pencil-beam algorithm, especially in predicting the dose distribution downstream of a local inhomogeneity. The accuracy of this algorithm appears sufficient for clinical use, and the algorithm is structured for future expansion of the physical model if required for site specific treatment planning problems. ^
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Ultraviolet (UV) radiation produces immunological alterations in both humans and animals that include a decrease in the delayed type hypersensitivity (DTH) response to complex antigens, and to the induction of the suppressor T cell pathway. Cell-mediated immunity of the type that is altered by UV radiation has been shown to be important in host resistance against microorganisms. My dissertation addresses questions concerning the effects of UV radiation on the pathogenesis of opportunistic fungal pathogens such as Candida albicans.^ The (DTH) response of C3H mice exposed to ultraviolet (UV) radiation before (afferent arm of DTH) or after (efferent arm of DTH) infection with Candida albicans was markedly and systemically suppressed. Although suppression of both the afferent and efferent phases of DTH were caused by similar wavebands within the ultraviolet region, the dose of UV radiation that suppressed the efferent arm of DTH was 10-fold higher than the dose that suppressed the afferent arm of the DTH reaction.^ The DTH response of C57BL/6 mice was also suppressed by UV radiation; however the suppression was accomplished by exposure to significantly lower doses UV radiation compared to C3H mice. In C57BL/6 mice, the dose of UV radiation that suppressed the afferent phase of DTH was 5-fold higher than the dose that suppressed the efferent phase.^ Exposure of C3H mice to UV radiation before sensitization induced splenic suppressor T cells that upon transfer to normal recipients, impaired the induction of DTH to Candida. In contrast, the suppression caused by UV irradiation of mice after sensitization was not transferable. Spleen cells from sensitized mice exhibited altered homing patterns in animals that were exposed to UV radiation shortly before receiving cells, suggesting that UV-induced suppression of the efferent arm of DTH could result from an alteration in the distribution of effector cells.^ UV radiation decreased the survival of Candida-infected mice; however, no correlation was found between suppression of the DTH response and the course of lethal infection. This suggested that DTH was not protective against lethal disease with this organism. UV radiation also changed the persistence of the organism in the internal organs. UV-irradiated, infected animals had increased numbers of Candida in their kidneys compared to non-irradiated mice. Sensitization prior to UV irradiation aided clearance of the organism from the kidneys of UV-irradiated mice.^ These data show that UV radiation suppresses cell-mediated immunity to Candida albicans in mice and increases mortality of Candida-infected mice. Moreover, the data suggest that an increase in environmental UV radiation could increase the severity of pathogenic infections. ^
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Ultraviolet B (UVB) radiation, in addition to being carcinogenic, is also immunosuppressive. Immunologically, UVB induces suppression locally, at the site of irradiation, or systemically, by inducing the production of a variety of immunosuppressive cytokines. Systemic effects include suppression of delayed-type hypersensitivity (DTH) responses to a variety of antigens (e.g. haptens, proteins, bacterial antigens, or alloantigens). One of the principal mediators of UV-induced immune suppression is the T helper-2 (Th2) cytokine interleukin-10 (IL-10); this suggests that UV irradiation induces suppression by shifting the immune response from a Th1 (cellular) to a Th2 (humoral) response. These "opposing" T helper responses are usually mutually exclusive, and polarized Th1 or Th2 responses may lead to either protection from infection or increased susceptibility to disease, depending on the infectious agent and the route of infection.^ This study examines the effects of UVB irradiation on cellular and humoral responses to Borrelia burgdorferi (Bb), the causative agent of Lyme disease (LD) in both immunization and infectious disease models; in addition, it examines the role of T cells in protection from and pathology of Bb infection. Particular emphasis is placed on the Bb-specific antibody responses following irradiation since UVB effects on humoral immunity are not fully understood. Mice were irradiated with a single dose of UV and then immunized (in complete Freund's adjuvant) or infected with Bb (intradermally at the base of the tail) in order to examine both DTH and antibody responses in both systems. UVB suppressed the Th1-associated antibodies IgG2a and IgG2b in both systems, as well as the DTH response to Bb in a dose dependent manner. Injection of anti-IL-10 antibody into UV-irradiated mice within 24 h after UV exposure restored the DTH response, as well as the Th1 antibody (IgG2a and IgG2b) response. In addition, injecting recombinant IL-10 mimicked some of the effects of UV radiation.^ Bb-specific Th1 T cell lines (BAT2.1-2.3) were generated to examine the role of T cells in Lyme borreliosis. All lines were CD4$\sp+,$ $\alpha\beta\sp+$ and proliferated specifically in response to Bb. The BAT2 cell lines not only conferred a DTH response to naive C3H recipients, but reduced the number of organisms recovered from the blood and tissues of mice infected with Bb. Furthermore, BAT2 cell lines protected mice from Bb-induced periarthritis. ^
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Radiotherapy involving the thoracic cavity and chemotherapy with the drug bleomycin are both dose limited by the development of pulmonary fibrosis. From evidence that there is variation in the population in susceptibility to pulmonary fibrosis, and animal data, it was hypothesized that individual variation in susceptibility to bleomycin-induced, or radiation-induced, pulmonary fibrosis is, in part, genetically controlled. In this thesis a three generation mouse genetic model of C57BL/6J (fibrosis prone) and C3Hf/Kam (fibrosis resistant) mouse strains and F1 and F2 (F1 intercross) progeny derived from the parental strains was developed to investigate the genetic basis of susceptibility to fibrosis. In the bleomycin studies the mice received 100 mg/kg (125 for females) of bleomycin, via mini osmotic pump. The animals were sacrificed at eight weeks following treatment or when their breathing rate indicated respiratory distress. In the radiation studies the mice were given a single dose of 14 or 16 Gy (Co$\sp{60})$ to the whole thorax and were sacrificed when moribund. The phenotype was defined as the percent of fibrosis area in the left lung as quantified with image analysis of histological sections. Quantitative trait loci (QTL) mapping was used to identify the chromosomal location of genes which contribute to susceptibility to bleomycin-induced pulmonary fibrosis in C57BL/6J mice compared to C3Hf/Kam mice and to determine if the QTL's which influence susceptibility to bleomycin-induced lung fibrosis in these progenitor strains could be implicated in susceptibility to radiation-induced lung fibrosis. For bleomycin, a genome wide scan revealed QTL's on chromosome 17, at the MHC, (LOD = 11.7 for males and 7.2 for females) accounting for approximately 21% of the phenotypic variance, and on chromosome 11 (LOD = 4.9), in male mice only, adding 8% of phenotypic variance. The bleomycin QTL on chromosome 17 was also implicated for susceptibility to radiation-induced fibrosis (LOD = 5.0) and contributes 7% of the phenotypic variance in the radiation study. In conclusion, susceptibility to both bleomycin-induced and radiation-induced pulmonary fibrosis are heritable traits, and are influenced by a genetic factor which maps to a genomic region containing the MHC. ^
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Lung cancer is the leading cause of cancer death. However, poor survival using conventional therapies fuel the search for more rational interventions. The objective of this study was to design and implement a 4HPR-radiation interaction model in NSCLC, employing a traditional clinical modality (radiation), a relatively new, therapeutically unexplored agent (4HPR) and rationally combining them based on molecular mechanistic findings pertaining to their interactions. To test the hypothesis that 4HPR sensitizes cells to radiation-induced cell death via G2+M accumulation, we designed a working model consisting of H522 adenocarcinoma cells (p53, K-ras mutated) derived from an NSCLC patient; 4HPR at concentrations up to 10 μM; and X radiation up to 6 Gy generated by a patient-dedicated Phillips RT-250 X ray unit at 250 KV, 15 mA, 1.85 Gy/min. We found that 4HPR produced time- and dose-dependent morphological changes, growth inhibition, and DNA damage-inducing enhancement of reactive oxygen species. A transient G2+M accumulation of cells maximal at 24 h of continuous 4HPR exposure was used for irradiation time scheduling. Our data demonstrated enhanced cell death (both apoptotic and necrotic) in irradiated cells pre-treated with 4HPR versus those with either stressor alone. 4HPR's effect of increased NSCLC cells' radioresponse was confirmed by clonogenic assay. To explore these practical findings from a molecular mechanistic perspective, we further investigated and showed that levels of cyclin B1 and p34cdc2 kinase—both components of the mitosis promoting factor (MPF) regulating the G2/M transition—did not change following 4HPR treatment. Likewise, cdc25C phosphatase was not altered. However, enhanced p34cdc2 phosphorylation on its Thr14Tyr15 residues—indicative of its inactivation and increased expression of MPF negative regulators chk1 and wee1 kinases—were supportive of explaining 4HPR-treated cells' accumulation. Hence, p34cdc2 phosphorylation, chk1, and wee1 warrant further evaluation as potential molecular targets for 4HPR-X radiation combination. In summary, we (1) demonstrated that 4HPR not only induces cell death by itself, but also increases NSCLC cells' subsequent radioresponse, indicative of potential clinical applicability, and (2) for the first time, shed light on deciphering 4HPR-X radiation molecular mechanisms of interaction, including the finding of 4HPR's role as a p34cdc2 inactivator via Thr14Tyr15 phosphorylation. ^