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

Authors
Huh, SunghyunKang, ChaewonPark, Ji EunNam, DowoonKim, Se IkSeol, AeranChoi, KyerimHwang, DaeheeYu, Myeong-HeeChung, Hyun HoonLee, Sang-WonKang, Un-Beom
Issue Date
9월-2022
Publisher
AMER CHEMICAL SOC
Keywords
serum biomarker; high-grade serous ovarian cancer; proteomics; mass spectrometry; data-independent acquisition
Citation
JOURNAL OF PROTEOME RESEARCH, v.21, no.9, pp.2146 - 2159
Indexed
SCIE
SCOPUS
Journal Title
JOURNAL OF PROTEOME RESEARCH
Volume
21
Number
9
Start Page
2146
End Page
2159
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/146088
DOI
10.1021/acs.jproteome.2c00218
ISSN
1535-3893
Abstract
High-grade serous ovarian cancer (HGSOC) represents the major histological type of ovarian cancer, and the lack of effective screening tools and early detection methods significantly contributes to the poor prognosis of HGSOC. Currently, there are no reliable diagnostic biomarkers for HGSOC. In this study, we performed liquid chromatography data-independent acquisition tandem mass spectrometry (MS) 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, neutrophil extracellular trap formation, toll-like receptor 4, insulin-like growth factor, and transforming growth factor beta signaling, as well as suppression of lipoprotein assembly and Fc gamma receptor 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 a 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. All raw data were deposited in PRIDE (PXD033169).
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