To treat esophageal cancer, professor turns to mathematical models
A mathematician at The University of Texas at Arlington is developing a data-driven mathematical framework to analyze the progression of esophageal cancer.
Individuals with esophageal cancer often receive a late diagnosis because the disease presents no early symptoms. With a low survival rate, esophageal cancer is one of the leading causes of cancer mortality in the United States.
To seek solutions, the National Science Foundation’s (NSF) Launching Early-Career Academic Pathways in the Mathematical and Physical Sciences (LEAPS-MPS) program awarded Souvik Roy, assistant professor of mathematics, a two-year, $215,000 grant to mathematically model the dynamic behaviors of biomarkers that present altered genetic expressions during esophageal cancer.
Roy’s goal is to develop stochastic computational frameworks that can accurately represent the random behavior of signaling pathways (a series of chemical reactions in which a group of cell molecules work together to control cell function). These frameworks will then be used to provide a rapid, cost-effective recommendation of cancer therapies to treat the disease.
“Imagine a software application where you could input esophageal cancer patient data along with available drug information, and then receive a recommended optimal course of treatments,” Roy said. “It would make the clinician’s job easier and improve survival rates.”
Mathematics advances cancer research by using methods that are impractical or impossible for traditional experimentation to execute, Roy said. Without mathematical models, experiments to understand the mechanics of cancer would be tedious, expensive and time consuming. Once models have been developed, mathematicians can use them to study and predict the disease’s long-term behavior, thereby facilitating rapid and accurate treatment recommendations.
Besides supporting Roy’s research, the LEAPS-MPS funding will provide training and research opportunities for both undergraduate and graduate students, primarily from underrepresented groups, with an aim of establishing a long-term collaboration among mathematics, biology and nursing students on UTA’s campus. With collaborator Zui Pan, professor of nursing, biology, bioengineering and kinesiology, Roy plans to develop a UTA center where students can learn in an integrative mathematical biology experimental research environment.
“Interdisciplinary research is key to tackling urgent problems of disease prevention and treatment,” Roy said. “Through this project, faculty and students from mathematics, biology and nursing can come together to solve problems that are at the forefront of our day-to-day lives.”