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Serum contains several proteins that are associated with disease-related processes. Mass spectrometry (MS)-based proteomics approaches greatly facilitate serum protein biomarker development. However, the serum proteome complexity presents a technical challenge for the accurate, sensitive, and reproducible quantification of proteins by MS. Thus, efficient sample preparation methods are of critical importance for serum proteome analyses. In this study, we evaluated the technical performance of two serum proteome sample preparation methods using sera from patients with high-grade serous ovarian cancer and patients with benign nongynecological conditions with a goal of providing insight into their compatibility with clinical proteomics workflows. One method entailed the use of immobilized trypsin (SMART Digest Trypsin) with RapiGest SF, an acid-labile surfactant designed to enhance the in-solution enzymatic digestion of proteins. The other method incorporated a commercially available sample preparation kit, iST-BCT, which contains standardized reagents. Significantly higher protein sequence coverage, albeit with lower digestion efficiency, was obtained with the immobilized trypsin + RapiGest SF workflow, whereas the iST-BCT workflow was quicker and had marginally better reproducibility. Protein relative abundance analysis revealed that the serum proteomes clustered primarily by the sample processing workflow and secondarily by disease state. We conducted a time course study to determine whether differences in the relative abundance of diagnostic high-grade serous ovarian cancer serum protein biomarker candidates were biased according to the duration of enzymatic digestion. Our results highlight the importance of optimizing enzymatic digestion kinetics according to the peptide targets of interest while considering the sensitivity of the downstream analytical method utilized in clinical proteomics workflows designed to measure biomarkers.

Ovarian carcinoma is usually diagnosed at an advanced stage with peritoneal dissemination and/or lymph node metastasis, and the prognosis for such advanced carcinoma is very poor. Therefore, new biomarkers to predict patient prognosis are needed. Miyamoto et al. previously showed that keratan sulfate (KS) detected by the 5D4 monoclonal antibody was expressed in ovarian carcinoma. However, the detailed structure of such KS was not determined, and the biological significance of this finding remained to be clarified. We previously generated the 297-11A monoclonal antibody, which recognizes galactose (Gal)-6-O-sulfated N-acetyllactosamine (LacNAc) located at the nonreducing terminus. Because the 297-11A epitope overlaps with that of 5D4, here we chose to use the 297-11A antibody as a tool to analyze KS and related structures. We conducted immunohistochemical analysis of 98 ovarian carcinoma cases with 297-11A antibody combined with a series of glycosidases and performed mass spectrometry analysis of the human serous ovarian carcinoma cell line OVCAR-3 to deduce the glycan structure of 297-11A-sulfated glycans. We also performed western blot analysis to assess a potential association of 297-11A-sulfated glycans with the mucin core protein mucin 16 (MUC16; also known as cancer antigen 125 (CA125)). Finally, we examined the relationship between 297-11A expression and patient prognosis. Consequently, 297-11A-sulfated glycans were primarily expressed in serous and endometrioid carcinomas and poorly expressed in mucinous and clear cell carcinomas. We reveal that structurally, 297-11A-sulfated glycans expressed in ovarian carcinoma are O-glycans carrying partially sialylated, Gal-6-O-sulfated LacNAc and that these glycans are likely displayed on MUC16 mucin core proteins. Of clinical importance is that expression of 297-11A-sulfated glycans correlated with shorter progression-free survival in patients. Thus, 297-11A-sulfated glycans may serve as a predictor of ovarian carcinoma recurrence., (Copyright © 2024 United States & Canadian Academy of Pathology. Published by Elsevier Inc. All rights reserved.)