The use of in vitro cell culture model systems has revealed many potential mediators and candidate biomarkers of various disease phenotypes. To be of clinical utility, the expression of these candidates must be assessed in patient samples such as tissue, urine or blood. However, typical "omic" experiments may produce candidates in such large numbers that it is usually impossible to test all of these in clinical samples. Here, we present a proteomic approach to discover and prioritize candidate biomarkers that are more likely to be found in serum. Using a combination of experimental and in silico approaches, we have demonstrated this approach using an isogenic cell culture model of breast cancer invasion. Differential proteomics (2D-DIGE) was used to discover a number of candidate biomarkers and a subset of these were identified as "extracellular". We tested the validity of this approach by screening serum from breast cancer patients for these candidates and then verified the presence of several of these "extracellular" proteins. This approach provides a pragmatic approach to prioritizing candidates that may be most suitable for downstream assays such as multiple reaction monitoring.
University College Dublin ->