Utilizing his background in biostatistics, postdoctoral research fellow at the Geisel School of Medicine Devin Koestler is investigating the use of white blood cell variation to develop a method of diagnosing non-blood cancers using blood samples. Though not yet ready for clinical use, the research lays the groundwork for a new form of noninvasive diagnostics, acccording to Koestler.
Koestler's primary focus is on the development of computational and statistical tools for investigating the process of DNA methylation, a process in which a molecule known as a methyl group attaches itself to DNA and has the potential to alter DNA function dramatically. In past studies, researchers found strikingly different methylation patterns in cancer and cancer-free patients, which led them to investigate methylation patterns in blood, according to Koestler.
Koestler hypothesized that analyzing blood using DNA methylation can be used to determine whether a cell is cancerous or non-cancerous. Therefore, by simply drawing a person's blood, a doctor could identify the person's probability of cancer and save patients from invasive diagnostic procedures, according to Koestler.
"The most exciting part of this for me is the prospect that what we are using to diagnose cancer is non-invasive," Koestler said. "The hope is that someday, you will be able to walk into the doctor's office, get a finger prick, and tell you if you're at risk for certain diseases."
Geisel School professor Brock Christensen said that the application of Koestler's research on methylation has implications outside the realm of cancer diagnosis.
"This is the tip of the iceberg in terms of understanding what is really going on," Koestler said. "This is really just the beginning. The book does not stop here. We are always trying to make sense of the complexities of DNA methylation."
DNA methylation in blood may be used to study the patterns of DNA in pregnant women exposed to arsenic and how this exposure affects children later in life, according to Koestler.
Despite his recent work, Koestler did not initially pursue a career in cancer research.
"I started out as an engineering major, but halfway thorough my first undergraduate year, I found I enjoyed my math classes the most, so I decided to study applied mathematics," Koestler said.
With a love of mathematics, Koestler pursued a graduate degree in biostatistics from the Rochester Institute of Technology School of Mathematical Sciences and a PhD at Brown University. While at Brown, Koestler began work with a group that sparked his interest in non-genetic research.
"I have not taken a biology class since high school, but I like the application of theoretical math concepts to something that is very real," Koestler said.
Christensen reiterated the significance of Koestler's contribution to the lab.
"We are very luck to have [Koestler] here at Dartmouth," Christensen said. "As a bona fide biostatistician, he has a truly critical skill set that allows us to use very large data sets and analyze the epigenetic data found in blood samples."
