Project 1. Sustained, high rates of production of nitric oxide (NO) by cells of the immune system, as occurs during chronic inflammation, has been strongly implicated in the development of various forms of cancer. Quantifying pathophysiological levels of NO is crucial for understanding the relationship between endogenous NO synthesis and carcinogenesis. Equally important is knowing the concentrations of reactive intermediates derived from NO, such as nitrogen dioxide (NO2), nitrous anhydride (N2O3), and peroxynitrite (ONOO-), because these species are likely mediators of damage to cells arising from NO. It is not feasible to directly measure the concentrations of any of these compounds under most conditions of interest, yet such information is needed to correlate levels of toxicity and rates of mutation in cell cultures with actual levels of exposure, and to extrapolate those findings to situations in the body. There is a need also for """"""""delivery systems"""""""" to control the exposure of cells or biological solutions to specific reactive nitrogen compounds, so that mechanistic hypotheses can be tested in vitro. It is proposed to address these needs using a combination of delivery system development, tissue modeling, and kinetic analysis. Reactors employing gas- permeable tubing will be used to provide a new method for NO2 delivery at physiological levels and to improve methods for controlled exposure to N2O3. Microfluidics technology will be exploited to develop a novel approach for delivery of ONOO-. Computational models will be developed to predict NO concentrations in specific tissues, including inflamed colon and melanoma. Rates of NO synthesis, NO consumption, and O2 consumption will be measured in cell lines that are representative of these tissues, providing key inputs for the models. A kinetic analysis of NO oxidation pathways and of reactions involving antioxidants and cellular lipids will be used to predict concentrations of NO2, N2O3, and related radicals in defined solutions and in cells. These predictions will be tested by measuring rates of production of selected biomarkers in vitro.
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