Tumor-proximal deep serum analysis to identify protein biomarkers associated with ovarian cancer

Ovarian cancer diagnosis is often delayed due to poorly defined clinical symptoms, underscoring the need for novel biomarkers than enable earlier detection. Protein biomarker discovery in blood samples using mass spectrometry is challenging as high-abundance proteins can obscure dectection of low-abundance biomarkers. Researchers at Adelaide University (Australia) collected ovarian vein (‘ovarian’) and median cubital vein (‘peripheral’) serum from healthy women and patients with benign or malignant (majority stage I) serous ovarian tumors. Proteograph XT assay was employed as protein enrichment methodology prior to LC-MS/MS analyses to obtain deeper proteome coverage in these samples. From an initial cohort of 53 samples, the reseachers identified 6603 proteins across all samples, including 3467 proteins uniquely identified in ovarian serum. Following exclusion of red blood cell-contaminated samples, differential abundance analysis identified 86 and 101 malignancy-associated protein candicates in ovarian and peripheral samples, respectively. Notably, ANK1, CAND1, and GMPR2 were differentially abundant across both sample types. Using logistic regression with repeated cross-validation and permutation testing, ANK1 demonstrated strong discriminatory performance (AUC 0.97) when combined with CA125 measurements. The authors conclude that these findings highlight the importance of ovarian vein sampling for enhanced access to tumor-associated proteins for early ovarian cancer detection.