Reduction of setup uncertainties and tumor motion in the radiation therapy of lung tumors

Because the goal of radiation therapy is to deliver a lethal dose to the tumor, accurate information on the location of the tumor needs to be known. Margins are placed around the tumor to account for variations in the daily position of the tumor. If tumor motion and patient setup uncertainties can be reduced, margins that account for such uncertainties in tumor location in can be reduced allowing dose escalation, which in turn could potentially improve survival rates. ^ In the first part of this study, we monitor the location of fiducials implanted in the periphery of lung tumors to determine the extent of non-gated and gated fiducial motion, and to quantify patient setup uncertainties. In the second part we determine where the tumor is when different methods of image-guided patient setup and respiratory gating are employed. In the final part we develop, validate, and implement a technique in which patient setup uncertainties are reduced by aligning patients based upon fiducial locations in projection images. ^ Results from the first part indicate that respiratory gating reduces fiducial motion relative to motion during normal respiration and setup uncertainties when the patients were aligned each day using externally placed skin marks are large. The results from the second part indicate that current margins that account for setup uncertainty and tumor motion result in less than 2% of the tumor outside of the planning target volume (PTV) when the patient is aligned using skin marks. In addition, we found that if respiratory gating is going to be used, it is most effective if used in conjunction with image-guided patient setup. From the third part, we successfully developed, validated, and implemented on a patient a technique for aligning a moving target prior to treatment to reduce the uncertainties in tumor location. ^ In conclusion, setup uncertainties and tumor motion are a significant problem when treating tumors located within the thoracic region. Image-guided patient setup in conjunction with treatment delivery using respiratory gating reduces these uncertainties in tumor locations. In doing so, margins around the tumor used to generate the PTV can be reduced, which may allow for dose escalation to the tumor. ^

Mechanisms of adenovirus 5 E1A -mediated tumor suppression and E1A-mediated apoptosis

The adenovirus type 5 E1A gene products have numerous functions in cells, which serve as useful tools in studying the mechanisms of either oncogenesis or tumor suppression. To understand the mechanisms of E1A-mediated tumor suppression, we introduced an Ad5 E1A gene into murine melanoma cells, and characterized E1A-mediated biological functions both in vitro and in vivo. The results of the study indicated that: (i) Ad5 E1A mediated tumor suppression in rodent tumor cells; (ii) E1A-mediated tumor suppression is associated with E1A-mediated apoptosis in vivo.^ To determine which functional region(s) of E1A is(are) required for E1A-mediated apoptosis and whether E1A-mediated apoptosis is required for E1A-mediated tumor suppression, we established stable transfectants of E1A mutants, which have deletion mutation at either the N-terminal (p300-binding) or the CR2 (pRb-binding) domain or both, and then characterized biological functions both in vitro and in vivo. The results of the study indicate that the CR2 domain of E1A is required for E1A-mediated apoptosis, while the N-terminal domain of E1A is dispensable. Interestingly, either of the two domains is able to mediate tumor suppression, since mutant E1A with a single deletion at either domain still suppressed tumor growth. Importantly, deletion mutations at both the N-terminal and the CR2 domains of E1A abrogated E1A-mediated tumor suppression, suggesting both regions are required for E1A-mediated tumor suppression. The results demonstrate that E1A-mediated apoptosis is not the only mechanism for E1A-mediated tumor suppression. Thus, the N-terminal and CR2 domains of E1A mediated two independent mechanisms of tumor suppression.^ To understand the mechanism of E1A-mediated apoptosis, we examined the temporal relationship of molecular events during the apoptotic cascades after UV radiation and serum depletion in both the E1A-expressing cells and parental cells. Kinetic analysis of JNK activity indicates that the JNK pathway is greatly increased in response to UV light in E1A transfectants, suggesting that extracellular stress stimuli have been converted into intracellular stress signals with greater magnitude in E1A transfectants than those in parental cells. Thus, E1A-mediated sensitization precedes these events. As ceramide has been proposed as second messenger and upstream activator of JNK pathway for stress-induced apoptosis, we also examined the roles of ceramide in apoptosis and the relationship with JNK pathway. The results indicate that E1A transfectants do not have increased sensitivity to ceramide. Therefore, E1A-mediated sensitization to UV radiation cannot be attributed to an increased sensitivity to ceramide. Furthermore, UV-induced JNK activation correlates with UV-induced apoptosis, while lethal dose of ceramide does not activate JNK. Thus, activation of JNK pathway is independent of the ceramide pathway. In addition, E1A transfectants also have increased activation of NF-kB in response to UV. These results suggest that E1A-mediated sensitization is an early event which associates with conversion of extracellular stress stimuli into amplified intracellular signals. The mechanism of E1A-mediated sensitization and its relationship with other pathways are discussed. ^

A BAYESIAN APPROACH TO DOSE-RESPONSE ASSESSMENT AND DRUG-DRUG INTERACTION ANALYSIS: APPLICATION TO IN VITRO STUDIES

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.