UPPSALA, Sweden—Improvement in proteomic technologies have resulted in increased interest in the identification of disease-related biomarkers and particularly in those that offer prognostic and diagnostic value. The Human Protein Atlas (HPA) was one attempt to identify tissue-specific protein expression patterns that relied on screening of healthy and diseased tissue microarrays (TMAs) with an extensive panel of human protein-specific antibodies. In its present form, however, the atlas can only be searched in a gene/protein-specific manner.
Researchers at Uppsala University and Stockholm's Royal Institute of Technology recently addressed this limitation with a novel search algorithm.
As they described in Molecular and Cellular Proteomics, the researchers scanned stained TMA sections digitally and separated the data into individual spots that were then evaluated and annotated by pathologists for a variety of immunohistochemical parameters. The researchers stored the information regarding tissues, annotation, and the images themselves in a MySQL database.
They then generated new search functions that would allow users to query the database with more complex questions than whether a certain protein was expressed. For example, users could query the database for all proteins that were expressed in certain tissue types but NOT others, providing clues to potential biomarkers or even drug target candidates for specific conditions. In proof-of-concept queries, they were able to not only identify previously unknown proteins associated with given tissues or disease states, but also patterns of differential expression that could be linked back to the relative risk of disease progression.
