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.