Abstract

e17564 Background: Ovarian cancer (OC) is one of the most common causes of cancer-related death among women worldwide. High-grade serous ovarian cancer (HGSOC) represents the major OC histological type, and challenges associated with its early detection and prediction of clinical outcomes significantly contribute to the high prevalence and poor prognosis of OC. Lack of reliable biomarkers further exacerbates the low survival rate of patients with HGSOC. Methods: In this study, we performed liquid chromatography data independent acquisition tandem-mass spectrometry (LC-DIA-MS/MS) experiments on depleted serum samples [26 HGSOC cases, 24 healthy controls (HCs)] to identify potential diagnostic and prognostic biomarkers for HGSOC. Results: A total of 1,148 proteins were identified in all samples combined, representing one of the largest quantifications in the serum proteome of OC to date. Among them, 122 proteins showed differential expressions between the serum proteome of HGSOC patients and HCs, including 109 up- and 14 down-regulated proteins in HGSOC. These potential diagnostic biomarkers were involved in the pathways related to immune response, TGF- β and IGF signaling, and lipid metabolism. Moreover, we performed Kaplan-Meier survival analysis on the HGSOC patients with and without recurrence, and identified several potential prognostic biomarkers highly associated with progression free survival (PFS). Using independent cohort samples, we validated the expression levels of HGSOC serum biomarker candidates using targeted proteomics approaches (MRM and PRM). In vitro functional assays revealed that some of these biomarkers may play an essential role in cancer cell migration and proliferation in HGSOC. Conclusions: In summary, our LC-DIA-MS/MS analysis of the HGSOC serum proteome successfully identified novel diagnostic and prognostic biomarkers for HGSOC, some of which were experimentally shown to have functional relevance to the pathophysiology of OC.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call