Advancing Plasma Proteomics for the Discovery of Ovarian Cancer Biomarkers

The development of ultrasensitive proteomic methods for detecting potential protein tumor biomarkers remains a key challenge in modern biomedicine. We integrated data from classical reference proteomic methodsboth panoramic (DDA-Shotgun LC-MS/MS) and targeted (MRM)with a novel AFM-based enrichment approach coupled to mass spectrometry (AFM-MS), providing lower detection limits. This integrated strategy enabled the compilation of an expanded list of proteins associated with ovarian cancer progression. We identified a panel of previously unreported, ovarian cancer–specific candidate markers. A total of 371 proteins were found to be potentially involved in the pathological process, with 33% detected exclusively by the ultrasensitive AFM-MS method and 26% discovered through metabolomic associations. Notably, 6% of the identified proteins correspond to previously recognized ovarian cancer–specific markers, validating our multiplatform approach. Nine potential biomarkers are proposed for the first time, including ATRN, CPN1, APOF, TGM3, and CRNN. Immunoglobulin variable region peptides were reclassified as low-specificity background signals due to their high abundance and inflammation dependence. The identified biomarkers are present in blood at concentrations ranging from 10–12 to 10–6 mol/L. The proposed approach overcomes the sensitivity limitations of conventional proteomic methods and may be adapted for the discovery of candidate markers in other multifactorial diseases.