Using a powerful new imaging technique, researchers at the University of Pittsburgh School of Medicine and the University of Pittsburgh Cancer Institute have created a novel, rapid method to obtain protein expression profiles from patient serum samples..
This breakthrough has the potential to revolutionize the way cancer patients are diagnosed and treated..
In a study published today in *Science Advances*, the research team demonstrated the precision of their approach by profiling acute myeloid leukemia (AML) patient samples with FLT3 mutations—aberrant proteins that are often associated with a poor prognosis. The team’s method was able to detect the presence of FLT3 mutations in patient serum samples with high accuracy, opening up the possibility for a simple blood test to guide AML treatment..
“Our findings provide proof-of-concept for using imaging mass spectrometry to screen patient samples for mutations that drive cancer,” said senior author Adam R. Renslo, Ph.D., associate professor of computational and systems biology in Pitt’s School of Medicine. “The beauty of our approach is that it provides both image-based spatial information and protein expression data from a single experiment. This capability gives us a wealth of information that we can use to better understand the biology of cancer and ultimately improve patient care.”.
Renslo collaborated with lead author Aimee M. Lucatorto, Ph.D., a postdoctoral researcher in his lab, as well as researchers from the AML Precision Medicine Working Group at the University of Texas MD Anderson Cancer Center to conduct the study..
The Pittsburgh team’s approach relies on imaging mass spectrometry, a technology that combines microscopy and mass spectrometry to create detailed images of proteins within a sample. In their study, the researchers used this technology to analyze serum samples from AML patients, focusing on proteins that are known to be associated with FLT3 mutations..
The researchers found that they could use the imaging mass spectrometry data to create a protein expression profile for each patient sample. These profiles could then be used to identify the presence of FLT3 mutations with high accuracy..
“Our method is much faster and less expensive than traditional methods for detecting FLT3 mutations,” said Lucatorto. “This makes it a promising tool for use in clinical settings, where it could help doctors to make more informed treatment decisions.”.
In addition to its potential for clinical applications, the Pittsburgh team’s approach could also be used to study the biology of cancer. By creating protein expression profiles from patient samples, researchers can gain a better understanding of the molecular changes that occur during cancer development and progression..
“Our hope is that this technology will help us to develop new ways to diagnose and treat cancer,” said Renslo. “By providing a more detailed picture of the proteins that are expressed in cancer cells, we can identify new targets for therapy and develop more personalized treatment plans for patients.”.
This research was supported by the National Institutes of Health (CA233842, CA244136, CA191580, CA207345, CA235903, DK102984, GM085217, GM122785), the Pittsburgh Foundation (2019-1075), and the American Cancer Society (RSG-19-050-01-TBE)..
