Novel Diagnostic Biomarkers for High-Grade Serous Ovarian Cancer Uncovered by Data-Independent Acquisition Mass Spectrometry

ABSTRACT: High-grade serous ovarian cancer (HGSOC) represents the major histological type of ovarian cancer (OC), and lack of effective screening tools and early detection methods significantly contributes to the poor prognosis of HGSOC. Currently, there is no reliable diagnostic biomarkers for HGSOC. In this study, we performed liquid chromatography data-independent acquisition tandem-mass spectrometry on depleted serum samples from 26 HGSOC cases and 24 healthy controls (HCs) to discover potential HGSOC diagnostic biomarkers. A total of 1,847 proteins were identified across all samples, among which 116 proteins showed differential expressions between HGSOC patients and HCs. Network modeling showed activations of coagulation and complement cascades, platelet activation and aggregation, NET formation, TLR4, IGF, and TGF-β signaling, and suppression of lipoprotein assembly and FcγR activation in HGSOC. Based on the network model, we prioritized 28 biomarker candidates, and validated 18 of them using targeted MS assays in an independent cohort. Predictive modeling showed a sensitivity of 1 and specificity of 0.91 in the validation cohort. Finally, in vitro functional assays on four potential biomarkers (FGA, VWF, ARHGDIB, and SERPINF2) suggested that they may play an important role in cancer cell proliferation and migration in HGSOC.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Serum

DISEASE(S): Malignant Neoplasm Of Ovary

SUBMITTER: Sunghyun Huh  

LAB HEAD: Un-Beom Kang

PROVIDER: PXD033169 | Pride | 2022-08-11

REPOSITORIES: Pride