Tracking Tumor Progression with a Drop of Blood or Small Tissue Sample

Researchers at Stanford University School of Medicine have developed a technique to identify cancer-associated proteins that may one day lead to the use of a drop of blood or a small tissue sample to track tumor progression and to see if proteins were modified in response to treatment.

Alice Fan, MD, clinical instructor, division of oncology, and lead author of the study, separated cancer-associated proteins in a tube in accordance with their charge, which changes based on whether they had been phosphorylated on the surface. Antibodies were then used to see “the relative amounts and positions of the various proteins.”

In cultured tumor cells, the technique was able to pinpoint oncogene activation, and was also effective in “small lymphoma samples taken from laboratory mice with small, hollow needles,” according to the researchers. They could see varying levels of expression for two common oncogenes in 44 of the 49 lymphoma samples when compared to controls, and they were able to distinguish some lymphoma types from others.

Additionally, the researchers were able to detect small differences in the phosphorylation in several other cancer-associated proteins.

“Some of these proteins can exist as five or six phosphorylated variants,” said senior author Dean Felsher, MD, PhD, associate professor of medicine and of pathology, and leader, Stanford Molecular Therapeutics Program. “With this technology, we can see changes that occur in as little as 10 percent of the total protein pool. Now we have a tool that will really help us look at what’s happening in cells over time.”

This study focused on blood cancers, but Fan is expanding the research to include head and neck cancers. Both she and Felsher added that more studies must be done before this technique can be widely used in clinical settings.

“This is really a complement to existing diagnostic and therapeutic methods,” Fan said.

In a related story, also from Stanford University, a new imaging technology may allow scientists to measure up to 100 or more distinct features on a single cell. To read more, click here.