UNT statistician develops risk prediction model for childhood cancer survivors to avoid anthracycline-related cardiomyopathy

Friday, May 31, 2019 - 08:45

University of North Texas associate professor Xuexia “Helen” Wang first noticed a correlation between anthracycline, a class of chemotherapy drugs used to treat cancer patients, and cardiomyopathy, a type of heart disease, in childhood cancer survivors when she worked as a researcher for City of Hope in 2010. 

Since then, she has dedicated her career to better understanding cancer, cancer-treatments and the side effects.

“Childhood cancer survivors are at a five- to 15-fold increased risk of anthracycline-related cardiomyopathy, also known as ARC, when compared with the general population. The anthracycline class of drugs is the most popular treatment currently in use, but it comes with a risk for some patients,” said Wang, a statistics faculty member in UNT’s College of Science. “What really drew my attention, however, was the inter-patient variability in risk. This suggested that it wasn’t only the drugs involved with ARC, but something about the patients themselves.”

Wang believed that there could be a genetic susceptibility among some patients who developed ARC. Working with other researchers, physicians and geneticists, she set out to look for genes and gene variants that could provide pathways for the disease.

“In 2016, we published a paper describing a genome-wide association study that involved childhood cancer survivors with and without ARC. We found that the patients with ARC shared a mutated gene that significantly increased the risk of developing ARC. In fact, there were two genetic variants of two genes identified by me and my collaborators that both increased risk at different percentages,” Wang said. “Discovering those gene variants now allows us to assign a risk to a specific patient based on their genes as well as other factors.”

Wang will be presenting a risk prediction model for ARC at the 2019 American Society of Clinical Oncology meeting in Chicago May 31 – June 4, 2019. The model will utilize the latest genetic findings along with patient treatment history and health information to give a specific risk level for a specific patient.

“Now, patients and doctors will be better informed and able to make a better decision on the type of treatment to utilize,” Wang said. “And, I hope that the discovery of the genetic aspect of ARC will lead to new medicines that can eliminate the risk of ARC all together.”


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