Real-world Application of Skyline in the Development of a Clinically Actionable Protein Measurement

Targeted quantification in a high throughput clinical setting (>100 samples/hour) requires consideration of all facets of LC-SRM measurement workflow to elucidate the one (or two) signature peptide(s) that will enable robust (CV < 15%), accurate (error < 15%), and sensitive (200 amole on column) measurement. To that end, this presentation will focus on how Skyline was used to streamline the development work-flow of a single cancer biomarker, thyroglobulin, from in-silico selection of putative signature peptides, to optimization of peptide enrichment parameters. Using Skyline, 26 potential signature peptides were identified in-silico based on their proteotypic characteristics. Crude, synthetic peptides were subsequently used to coarsely identify the top 8 SRM transitions for each peptide, which were further optimized empirically using the tuning/optimization feature of Skyline. A series of 96 solvent chemistries, 21 reversed phase column chemistries, and optimal combinations therein were tested to identify a ubiquitous, optimal LC-SRM platform that was used to identify 8 of the 26 peptides as candidate signature peptides based on their absolute signal response following tryptic digestion of neat thyroglobulin. Stable isotope-labeled peptides were then used to evaluate and elucidate digestion conditions (chaotrope, trypsin type, etc) that would facilitate rapid and efficient recovery of the candidate peptides from thyroglobulin in serum. Finally, using all optimized parameters, absolute sensitivity of each signature peptide was compared to identify the single peptide with the greatest analytical sensitivity incorporating proteolytic efficiency.