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.