The first year of the two-year award will be devoted to developing and refining the technology needed to compare approaches for discovering new biomarkers and making sure they are reliable and accurate signposts of disease. The second year will focus on testing the technology's ability to detect diagnostic protein biomarkers that are associated with several different mouse models of human cancer, including those of the breast, prostate, ovary, pancreas, skin and lung.
The researchers have their work cut out for them. Although the entire human genome contains only about 30,000 genes, the number of predicted protein forms approaches 1 million. So far, less than 1 percent of the proteins have been detected in serum.
The quest to identify and analyze protein patterns in the blood the focus of a relatively new field called proteomics involves extracting proteins from blood, urine or other tissue. The proteins are then analyzed with a technique called mass spectrometry, which creates patterns of protein fragments. These unique protein signatures are then sorted with an artificial-intelligence computer program that identifies the discrepancies in protein patterns between people with and without cancer. Proteins linked to cancer may then serve as biomarkers to detect early disease and predict responsiveness to therapy or the likelihood of recurrence. Such biomarkers also could be used to classify the genetic subtype of the cancer so that treatment could be better tailored to the individual.
Geneticist and clinical oncologist Amanda Paulovich, M.D., Ph.D., of Fred Hutchinson's Clinical Research Division, is co-principal investigator of the award. Her work focuses on developing blood-
Contact: Kristen Woodward
Fred Hutchinson Cancer Research Center