Two University of Arizona SBRP investigators, Clark Lantz and Jeff Burgess, were recently awarded an EPA Science to Achieve Results (STAR) grant to conduct research on the application of biomarkers to environmental health and risk assessment. The title of their grant is, "Pulmonary Biomarkers Based on Alterations in Protein Expression Following Exposure to Arsenic." This project is an extension of research supported by the SBRP and has been funded from January 8, 2005 - January 7, 2008. This grant is one of the three submissions funded out of fifty-nine applications.
Exposure to arsenic (As) has been linked to lung cancer. Environmental exposure to these metals will result in multiple adverse effects, which can be characterized through evaluation of alterations in protein expression. We will evaluate such alterations as biomarkers of exposure and effect prior to the development of cancer. This study will use the technology of proteomics to evaluate and identify biomarkers of chronic environmental exposure to As by evaluating large numbers of proteins simultaneously. We will compare alterations in protein expression in exposed human populations in Arizona, human cell lines, and in vivo rodent studies. Patterns of alterations in protein expression, both common and unique to these different cell types, will be identified. These will be correlated with alterations in DNA oxidation in induced sputum from the lung.
This study examines exposure indicators through cell lines, in vivo models and through epidemiological assessment of humans and human tissue for intermediate biological endpoints associated with cancer risk. Overall patterns of alterations in protein expression may vary among in-vitro, in vivo, and human studies. However, suites of proteins in specific pathways (e.g. apoptosis, cell-cycle control, etc.) may demonstrate similar patterns, thus providing us not only with biomarkers, but also with indicators as to the mechanism(s) of action of arsenic. These similarities and differences will help inform risk assessment by suggesting which mechanisms and biological endpoints in humans can be reasonably modeled using non-human studies.