Evaluation of Serum\nProteome Sample Preparation Methods\nto Support Clinical Proteomics Applications

Serum contains several proteins that are associated with\ndisease-related\nprocesses. Mass spectrometry (MS)-based proteomics approaches greatly\nfacilitate serum protein biomarker development. However, the serum\nproteome complexity presents a technical challenge for the accurate,\nsensitive, and reproducible quantification of proteins by MS. Thus,\nefficient sample preparation methods are of critical importance for\nserum proteome analyses. In this study, we evaluated the technical\nperformance of two serum proteome sample preparation methods using\nsera from patients with high-grade serous ovarian cancer and patients\nwith benign nongynecological conditions with a goal of providing insight\ninto their compatibility with clinical proteomics workflows. One method\nentailed the use of immobilized trypsin (SMART Digest Trypsin) with\nRapiGest SF, an acid-labile surfactant designed to enhance the in-solution\nenzymatic digestion of proteins. The other method incorporated a commercially\navailable sample preparation kit, iST-BCT, which contains standardized\nreagents. Significantly higher protein sequence coverage, albeit with\nlower digestion efficiency, was obtained with the immobilized trypsin\n+ RapiGest SF workflow, whereas the iST-BCT workflow was quicker and\nhad marginally better reproducibility. Protein relative abundance\nanalysis revealed that the serum proteomes clustered primarily by\nthe sample processing workflow and secondarily by disease state. We\nconducted a time course study to determine whether differences in\nthe relative abundance of diagnostic high-grade serous ovarian cancer\nserum protein biomarker candidates were biased according to the duration\nof enzymatic digestion. Our results highlight the importance of optimizing\nenzymatic digestion kinetics according to the peptide targets of interest\nwhile considering the sensitivity of the downstream analytical method\nutilized in clinical proteomics workflows designed to measure biomarkers.