Researcher Profile: Edward Patz

Dr. Edward Patz

Edward F. Patz, Jr., MD, James and Alice Chen Professor of Radiology, Professor in Pathology, Professor in Pharmacology and Cancer Biology, and his colleagues from the Duke University Medical Center, have been awarded a research grant from LUNGevity Foundation to identify biomarkers for the early detection of lung cancer.

Dr. Patz is collaborating on this project with Associate Professor of Biostatistics and Bioinformatics, James Herndon, PhD, and Associate Professor of Radiology, Michael Campa, PhD.

The early detection of lung cancer through the use of computed tomography (CT) scans has the potential to significantly reduce lung cancer deaths. However, with the growing number of lung CT scans, patients often discover they have lung nodules that require further testing. Although the majority of these nodules are benign, almost all individuals with lung nodules require multiple follow-up studies to determine if the patient has lung cancer. This can cause radiation risks, significant costs and diagnostic delays.

Dr. Patz and his team are developing a simple blood test to rapidly determine which patients with lung nodules have cancer and which patients have benign lesions and so need no further evaluation.

“A blood test of this nature would ease the burden on the health system by minimizing the procedures done on healthy people,” explains Dr. Patz. “The test would also speed up the diagnostic process for lung cancer patients needing to begin treatment as soon as possible.”

These investigators have already identified a panel of 25 serum autoantibodies associated with non-small cell lung cancer. They have also created protein microarrays, by attaching these key autoantibodies to glass slides, in order to test their interactions with other proteins. In a pilot study, these researchers tested the microarrays with human samples and developed a method for classifying lung nodules based on the microarray test results and the information from CT scans. Their studies showed that this method had an overall sensitivity of 81% and specificity of 83% for the diagnosis of lung cancer.

Using the LUNGevity grant, Dr. Patz’s team is continuing to refine this lung cancer test. They are working to further identify a group of signature autoantibodies that, when combined with information from the CT scans, will be able to determine which patients have lung cancer.

Once completed, this non-invasive blood test could help stratify patients with pulmonary nodules into high and low risk categories, thus reducing the need for further evaluation, decreasing costs, avoiding delays in diagnosis and decreasing radiation exposure.