Phosphoproteins Identified as Biomarkers for Cancer

The team devised a strategy to isolate and identify phosphoproteins in extracellular vesicles (EVs) from human plasma as potential markers to differentiate disease from healthy states.

The investigator used centrifuges to separate plasma from red blood cells, and high-speed and ultra-high-speed centrifuges to further separate microvesicles and exosomes. Those particles, which are released from cells and enter the bloodstream, may play a role in intercellular communication and are thought to be involved in metastasis, spreading cancer from one place to another in the body. They also encapsulate phosphoproteins, which they identified using mass spectrometry. The Easy-nLC 1000 Liquid Chromatography system was coupled online with a hybrid high-resolution LTQ-Orbitrap Velos Pro mass spectrometer.

The scientists identified close to 10,000 unique phosphopeptides in EVs isolated from small volumes of plasma samples. Using label-free quantitative phosphoproteomics, they identified 144 phosphoproteins in plasma EVs that are significantly higher in patients diagnosed with breast cancer as compared to healthy controls. Several novel biomarkers were validated in individual patients using Paralleled Reaction Monitoring for targeted quantitation. This study demonstrates that the development of phosphoproteins in plasma EV as disease biomarkers is highly feasible and may transform cancer screening and monitoring.

W. Andy Tao, PhD, a professor of biochemistry and senior author of the study said, “There are so many types of cancer, even multiple forms for different types of cancer, that finding biomarkers has been discouraging. This is definitely a breakthrough, showing the feasibility of using phosphoproteins in blood for detecting and monitoring diseases. Extracellular vesicles, which include exosomes and microvesicles, are membrane-encapsulated. They are stable, which is important. The samples we used were five years old, and we were still able to identify phosphoproteins, suggesting this is a viable method for identifying disease biomarkers.” The study was published on March 21, 2017, in the journal Proceedings of the National Academy of Science USA.