Dr. Wen-Yee Lee in her science lab. Story on Detecting Kidney & Prostate Cancer with Urine Samples, Tuesday, July 16, 2019, in El Paso, Texas. Photo by Ivan Pierre Aguirre/UTEP Communications
Research being conducted at The University of Texas at El Paso by Wen-Yee Lee, Ph.D., is helping pave the way for advances in early detection methods for prostate cancer, one of the leading causes of cancer death among men, according to the American Cancer Society.
The associate professor of chemistry and biochemistry at UTEP was invited to join a team of researchers from the Massachusetts Institute of Technology (MIT) and other institutions to develop a miniaturized detector that can mimic a canine nose and brain, with 200 times greater sensitivity to detect chemical and microbial content of an air sample to help detect prostate cancer.
The overall goal is to make the device accessible through cellphones in the future.
Lee lent her expertise in the area of chemical analysis of urine to advance the study to meet the need for alternative detection methods.
The keen sense of smell of trained medical dogs is often used to help detect several diseases and illnesses, but due to issues of training, access and availability, an alternative reliable method for detection is key.
“Advancing personalized medicine through inexpensive and accurate point-of-care technologies represents an exciting frontier in patient care,” said Robert Kirken, Ph.D., dean of UTEP’s College of Science.
“Dr. Wen-Yee Lee and colleagues’ recent work is very exciting because it validates that it is possible to use such an approach, even for highly complex diseases like prostate cancer that have few reliable disease markers. The development of such technologies, coupled with artificial intelligence for analysis, should lead to early and better cancer diagnosis, treatment monitoring and ultimately patient outcomes.”
The findings of the multi-institutional team were published in the journal PLOS ONE. The study involved the use of professionally trained dogs and the miniaturized detection tool to look for specific biomarkers in 50 urine samples that included both prostate cancer positive specimens and a control group.
Using artificial intelligence, the researchers compared patterns of the two groups of samples that could help the artificial sensors detect the disease.
They found that the detection system was highly comparable to the rate of detection by the canines, with both scoring a rate of accuracy of 70% or greater.
“With this study we have a very good start, and we will continuously try to get more samples to validate the results,” Lee said. “I hope in the future we are able to validate this study and get more data to prove that we are capable of using a handheld sensor to detect cancer. It can be moved to a point-of-care and we can reach out to the community and people who have a hard time accessing cancer testing.”