Abstract
Initial identification of biomarkers predicting the exact prognosis of high-grade serous ovarian carcinoma (HGSOC) is important in precision cancer medicine. This study aimed to investigate prognostic biomarkers of HGSOC through proteomic analysis. We conducted label-free liquid chromatography-mass spectrometry using chemotherapy-naïve, fresh-frozen primary HGSOC specimens, and compared the results between a favorable prognosis group (progression-free survival (PFS) ≥ 18 months, n = 6) and a poor prognosis group (PFS < 18 months, n = 6). Among 658 differentially expressed proteins, 288 proteins were upregulated in the favorable prognosis group and 370 proteins were upregulated in the poor prognosis group. Using hierarchical clustering, we selected α1-antitrypsin (AAT), nuclear factor-κB (NFKB), phosphomevalonate kinase (PMVK), vascular adhesion protein 1 (VAP1), fatty acid-binding protein 4 (FABP4), platelet factor 4 (PF4), apolipoprotein A1 (APOA1), and α1-acid glycoprotein (AGP) for further validation via immunohistochemical (IHC) staining in an independent set of chemotherapy-naïve primary HGSOC samples (n = 107). Survival analyses revealed that high expression of AAT, NFKB, and PMVK were independent biomarkers for favorable PFS. Conversely, high expression of VAP1, FABP4, and PF4 were identified as independent biomarkers for poor PFS. Furthermore, we constructed models predicting the 18-month PFS by combining clinical variables and IHC results. Through leave-one-out cross-validation, the optimal model was based on initial serum CA-125, germline BRCA1/2 mutations, residual tumors after surgery, International Federation of Gynecology and Obstetrics (FIGO) stage, and expression levels of the six proteins. The present results elucidate the proteomic landscape of HGSOC and six protein biomarkers to predict the prognosis of HGSOC.