This is an Oregon State University press release from 5-8-15 that shares about the collaborative research project of Project 1 and Core C – Biostatistics and Modeling.

– By Gail Wells, 541-737-1386, gail.wells@oregonstate.edu, on Twitter @OregonStateExt
Source: Susan Tilton, 541-737-1740, susan.tilton@oregonstate.edu
http://bit.ly/OSU_AgNews1542

CORVALLIS, Ore. – Scientists at Oregon State University have developed a faster, more accurate method to assess cancer risk from certain common environmental pollutants.

Researchers found that they could analyze the immediate genetic responses of the skin cells of exposed mice and apply statistical approaches to determine whether or not those cells would eventually become cancerous.

The study focused on an important class of pollutants known as polycyclic aromatic hydrocarbons, or PAHs, that commonly occur in the environment as mixtures such as diesel exhaust and cigarette smoke.

Dr. Susan Tilton
Dr. Susan Tilton

“After only 12 hours, we could predict the ability of certain PAH mixtures to cause cancer, rather than waiting 25 weeks for tumors to develop,” said Susan Tilton, an environmental toxicologist with OSU’s College of Agricultural Sciences.

For at least some PAH mixtures, the new method is not only quicker but produces more accurate cancer-risk assessments than are currently possible, she said.

“Our work was intended as a proof of concept,” said Tilton, who is also affiliated with the OSU’s multidisciplinary Superfund Research Program, a center funded by the National Institute of Environmental Health Sciences (NIEHS).

“The method needs to be tested with a larger group of chemicals and mixtures. But we now have a model that we can use to develop larger-scale screening tests with human cells in a laboratory dish.”

Such a method will be particularly useful for screening PAHs, a large class of pollutants that result from combustion of organic matter and fossil fuels. PAHs are widespread contaminants of air, water and soil. There are hundreds of different kinds, and some are known carcinogens, but many have not been tested.

Humans are primarily exposed to PAHs in the environment as mixtures, which makes it harder to assess their cancer risk. The standard calculation, Tilton said, is to identify the risk of each element in the mix – if it’s known – and add them together.

But this method doesn’t work with most PAH mixes. It assumes the risk for each component is known, as well as which components are in a given mix. Often that information is not available.

This study examined three PAH mixtures that are common in the environment – coal tar, diesel exhaust and cigarette smoke – and various mixtures of them.

They found that each substance touched off a rapid and distinctive cascade of biological and metabolic changes in the skin cells of a mouse. The response amounted to a unique “fingerprint” of the genetic changes that occur as cells reacted to exposure to each chemical.

By matching patterns of genetic changes known to occur as cells become cancerous, they found that some of the cellular responses were early indicators of developing cancers. They also found that the standard method to calculate carcinogenic material underestimated the cancer risk of some mixtures and overestimated the combined risk of others.

“Our study is a first step in moving away from risk assessments based on individual components of these PAH mixtures and developing more accurate methods that look at the mixture as a whole,” Tilton said. “We’re hoping to bring the methodology to the point where we no longer need to use tumors as our endpoint.”

Tilton collaborated on the research with Katrina Waters of the Pacific Northwest National Laboratory, and others. Their findings appeared in a recent edition of Toxicological Sciences.

The study was funded by NIEHS, which supports the Superfund Research Program, a multi-partner collaboration that includes OSU and PNNL.

Chemistry graduate student Ivan Titaley has been immersed in polycyclic aromatic hydrocarbon (PAH) research within SRP Project 5 – Formation of Hazardous PAH Breakdown Products in Complex Environmental Mixtures at Superfund Sites under Dr. Staci Simonich.

Ivan Titaley
Ivan Titaley

Recently, Ivan was selected by Dr. Dayle Smith as a sponsored fellow at the Pacific Northwest National Laboratory (PNNL) to get hands-on training in modeling of polycyclic aromatic hydrocarbons. This program is through the Office of Science and Engineering Education (SEE) at PNNL. The selection is commendable, and will allow Ivan to apply new modeling techniquesl in his own research on OPAHs and OHPAHs transformation processes.

To financially support Ivan on this unique training opportunity, he has been awarded an SRP Trainee Externship Award through the SRP Training Core. This activity provides important synergy between Project 5 and Core C – Biostatistics and Modeling.

Dr. Smith will provide mentoring for Ivan to perform computational chemistry work to predict the formation of oxygenated-PAHs (OPAHs) and hydroxy-PAHs (OHPAHs) from higher molecular weight parent PAHs. More specifically, Ivan will be working using the NWChem 6.5 computational chemistry software. Using thermodynamic data on potential OH-PAH-adduct, he will be able to show which compounds will form based on thermodynamic stability.

Congratulations, Ivan!

 

Our Center is multi-investigator, multi-disciplinary and multi-institutional. In partnership with Pacific Northwest National Laboratories (PNNL), and other stakeholders and collaborators, we are developing new technologies to identify and quantitate known and novel polycyclic aromatic hydrocarbons (PAHs) found at many of the nation’s Superfund sites and assess the risk they pose for human health.

Women@Energy: Dr. Katrina Waters  Photo credit: energy.gov
Women@Energy: Dr. Katrina Waters
Photo credit: energy.gov

The research projects in our Center collect large amounts of molecular and chemical data. This data includes measuring PAH mixtures in environmental samples, determining toxicity of PAH mixtures, and the mechanism(s) of action for these toxic endpoints.

Our Biostatistics and Modeling Core, lead by Dr. Katrina Waters, greatly enhances our Center by providing expert statistical and bioinformatics data analysis support and software solutions for data management and interpretation.

Katrina Waters recently became the Deputy Director for the Biological Sciences Division at the Pacific Northwest National Lab (PNNL). Her expertise is in computational biology, and she works collaboratively with all of the research projects and co-authors with them.

This multidisciplinary training of toxicology students and fellows at OSU and PNNL is a unique strength of our program. Our SRP Trainees have benefited greatly from the PNNL partnership.  Students have gone to the lab in Richland, WA to be trained in Bioinformatics, Statistics and Study Design. More training workshops are being scheduled for this summer and fall.

Waters presented at SOT’s FutureTox II: In Vitro Data and In Silico Models for Predictive Toxicology on January 16, 2014. Her talk was entitled Computational Tools for Integration of High Throughout Screening (HTS) Data. She utilized examples from the collaboration with Robert Tanguay and his zebrafish assay for toxicity testing (Project 3).

Susan Tilton
Susan Tilton works with Dr. Katrina Waters and the OSU SRP Biostatistics and Modeling Core Group

 

Dr. Susan Tilton, also from PNNL,  presented at FutureTox as well. The title of her presentation was ‘Pathway-based prediction of tumor outcome for environmental PAH mixtures’.  In this study, they developed a mechanism-based approach for prediction of tumor outcome after dermal exposure to PAHs and environmental PAH mixtures.  Their model was successfully utilized to distinguish early regulatory events during initiation linked to tumor outcome and shows the utility of short-term initiation studies in predicting the carcinogenic potential of PAHs and PAH mixtures.

“Dr. Waters and her group have proven to be of great value in not just the interpretation of extremely large and complicated data sets, but also in the “front-end” study design, which results in enrichment of the subsequent data obtained.”
Dr. David Williams, OSU SRP Center Director