DOI

10.17077/etd.oh1kpg43

Document Type

Dissertation

Date of Degree

Spring 2016

Degree Name

PhD (Doctor of Philosophy)

Degree In

Human Toxicology

First Advisor

Buettner, Garry R.

First Committee Member

Cullen, Joseph J.

Second Committee Member

Doorn, Jonathan A.

Third Committee Member

Goswami, Prabhat C.

Fourth Committee Member

Ludewig, Gabriele

Abstract

Basic health science research, which includes cell culture, typically underpins clinical and toxicological research. The results are used to predict biological effects of xenobiotics, e.g. environmental toxins and drugs, in humans. A goal of this research program was to apply aspects of quantitative redox biology to three separate, but interrelated projects that address improvements that can be made to evidence-based biological and toxicological research. This includes using absolute quantitation: to improve the specification of dose of xenobiotics added to cell culture systems; to determine absolute differences between the antioxidant capacity of tumor and normal cells; and to predict the implications of this new knowledge on the use of pharmacological ascorbate as an adjuvant in cancer therapy.

Dose is a central parameter in determining the biological consequences of a xenobiotic; however, the dose of a xenobiotic at which these consequences are observed is dependent not only on biological variables, but also the physical aspects of cell culture experiments (i.e. cell number, medium volume). This is often overlooked due to the unrecognized ambiguity in the dominant metric used to express dose, i.e. initial concentration of xenobiotic. We hypothesized that specifying the dose of xenobiotics absolutely (as moles of xenobiotic per cell; mol cell-1) will reduce this ambiguity and provide additional information that is difficult to discern when traditional dosing metrics (initial concentration) are used. We investigated the use of mol cell-1 as an informative dosing metric using two model compounds: 1,4-benzoquinone and oligomycin A. When the dose of these two compounds was specified as mole cell-1, the toxicity observed was independent of the physical conditions used (i.e. number of cells, volume of medium). This makes it a scalable dosing metric that reduces ambiguity between experiments having different physical conditions; allows direct comparison between different cell types; addresses the important issue of repeatability of experimental results, and could increase the translatability of information gained from in vitro experiments.

We utilized quantitative methods to explore the absolute differences in the ability of tumor vs. normal cells to remove H2O2 and how this impacts the use of pharmacological ascorbate as an adjuvant in cancer therapy. Ascorbate (AscH-, vitamin C) functions as a versatile reducing agent. At pharmacological doses (P-AscH-, plasma levels ≥ 20 mM), achievable through IV delivery, the oxidation of ascorbate can produce a high flux of H2O2 in tumors. We hypothesized that the increased sensitivity of tumor cells to P-AscH- compared to normal cells (i.e. non-transformed) is due to their lower capacity to remove H2O2. The rate constants (kcell) for removal of H2O2 revealed a differential in the capacity of cells to remove H2O2, with the average kcell for normal cells (N = 10) being twice that of tumor cells (N = 15). The ED50 of P-AscH- correlated directly with the capacity of cells to remove H2O2. Quantitation made it possible to make comparisons across very different cell lines on an absolute basis. These results indicate that the capacity of cells to remove H2O2 varies widely and in vivo measurement of this may predict which tumors may respond best to P-AscH- therapy.

By designing experiments that begin with a quantitative dosing metric and utilize quantitation to produce absolute information from the results of experiments, we can better leverage data. We propose that this will lead to better predictions from such experiments. These enhancements to in vitro cell culture studies will increase the success in translation of data from in vitro experiments to in vivo animal studies and ultimately impact the success of extrapolation of basic science research to human clinical studies.

Public Abstract

Many years of basic health science research are typically needed before data can be extrapolated to humans, be it testing for the potential toxicity of environmental pollutants or the development of new drugs. Unfortunately, there have been a large number of failures in long-term studies, with the pre-clinical/basic science data not reflecting the biological consequences in humans. In vitro cell culture studies are major contributors to these preliminary studies. Much of the data derived from these experiments consists of relative comparisons across different treatment groups. We hypothesized that using absolute quantitation could improve the repeatability of experimental results, allow direct comparisons between different cell types, and increase the translatability of information gained from in vitro experiments. Here, we use absolute quantitation to: improve the specification of dose in cell culture model systems; determine absolute differences between the antioxidant capacity of tumor and normal cells; and explore what implications this has for the use of pharmacological ascorbate (high-dose vitamin C) as an adjuvant in cancer therapy. By designing experiments that begin with a quantitative metric for the dose of a xenobiotic (i.e. toxicant, pharmaceutical agent, biochemical tool) and utilizing approaches that yield absolute quantitative data from experiments, we can better leverage data to improve human health. We propose that these quantitative data will lead to better predictions, increasing the success in translation of data derived from in vitro experiments to in vivo animal studies and ultimately impact the success of extrapolation of basic science research to improve human health.

Pages

xv, 147 pages

Bibliography

Includes bibliographical references (pages 135-147).

Copyright

Copyright © 2016 Claire Marie Doskey

Included in

Toxicology Commons

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