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A Paramagnetic Microbead-Based Biofluid Enrichment Method Enables Proteomic Ovarian Cancer Biomarker Development Using Ascites Fluid.

Unknown authors
Sep 2026 · Proteomics · pp. e70185 · 0 citations
Medicine

Abstract

Ascites, the pathological accumulation of fluid in the peritoneal cavity, is common at diagnosis and with recurrence in high-grade serous ovarian carcinoma (HGSOC). Higher volumes of ascites fluid are associated with greater likelihood of recurrent disease and poor prognosis. Due to its availability-volume and frequency-and its reflection of tumors and their microenvironments, ascites is a valuable resource for proteomic biomarker discovery. However, ascites has not been widely studied. Similar to plasma, relatively few proteins comprise the majority of the broad dynamic range of protein mass in ascites fluid, necessitating an enrichment or depletion strategy for proteomic sample preparation. ENRICH-iST and ENRICHplus kits enrich low-abundance proteins using paramagnetic beads. These enrichment strategies have not previously been validated for use with ascites fluid. Our goal was to evaluate the ENRICH-iST and ENRICHplus kits using ascites fluid from HGSOC patients with differing extents of tumor resection during debulking surgery. This Dataset Brief describes the technical performance of these enrichment strategies based on DIA-MS proteome depth, reproducibility of identified proteins, Gene Ontology (GO) term enrichment (Biological Processes, Molecular Functions, and Cellular Components), and Human Protein Atlas-based protein abundance ranking. ENRICHplus outperformed ENRICH-iST by 1.4-fold based on depth of proteome coverage. Relative to the total proteome coverage, ENRICH-iST reduced the proportional contribution of the top 12 high-abundance proteins more effectively than ENRICHplus, thereby increasing the representation of lower-abundance proteins despite identifying fewer overall proteins. Analysis of the differential abundance of the proteins enriched from ascites fluid using these enrichment strategies could greatly facilitate HGSOC biomarker development.

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