Screening by Q Exactive liquid chromatography/tandem mass spectrometry identified Choline, 25-hydroxyvitamin D2, and SM(d18:0/16:1(9Z) (OH)) as biomarkers for high-grade serous ovarian cancer

Abstract

High-grade serous ovarian cancer (HGSOC) has a high death rate and poor prognosis. The main causes of poor prognosis are asymptomatic early disease, no effective screening method at present, and advanced disease. Changes in cellular metabolism are characteristic of cancer, and plasma metabolome analysis can be used to identify biomarkers. In this study, we used Q Exactive liquid chromatography tandem mass spectrometry (LC–MS/MS, QE) to compare the differentiation between plasma samples (22 HGSOC samples and 22 normal samples). In total, we detected 124 metabolites, and an orthogonal partial least-squares-discriminant analysis (OPLS-DA) model was useful to distinguish HGSOC patients from healthy controls. Choline, 25-hydroxyvitamin D2, and sphingomyelin (d18:0/16:1(9Z) (OH))/SM(d18:0/16:1(9Z) (OH)) showed significantly differential plasma levels in HGSOC patients under the conditions of variable importance in projection (VIP) > 1, p < 0.05 using Student's t-test, and fold change (FC)  ≥ 1.5 or ≤ 0.667. Metabolic pathway analysis can provide valuable information to enhance the understanding of the underlying pathophysiology of HGSOC. In conclusion, the Q Exactive LC/MS/MS method validation-based plasma metabolomics approach may have potential as a convenient screening method for HGSOC and may be a method to monitor tumor recurrence in patients with HGSOC after surgery

Significance

High-grade serous ovarian cancer (HGSOC) has a high death rate and poor prognosis. The main causes of poor prognosis are asymptomatic early disease, no effective screening method at present, and advanced disease. Changes in cellular metabolism are characteristic of cancer, and plasma metabolome analysis can be used to identify biomarkers. In this study, we used Q Exactive liquid chromatography tandem mass spectrometry (LC–MS/MS, QE) to compare the differentiation between plasma samples (20 HGSOC samples and 20 normal samples). In total, we detected 124 metabolites, and an orthogonal partial least-squares-discriminant analysis (OPLS-DA) model was useful to distinguish HGSOC patients from healthy controls. Choline, 25-hydroxyvitamin D2, and sphingomyelin (d18:0/16:1(9Z) (OH))/SM(d18:0/16:1(9Z) (OH)) showed significantly differential plasma levels in HGSOC patients under the conditions of variable importance in projection (VIP) > 1, p < 0.05 using Student's t-test, and fold change (FC) ≥ 1.5 or ≤ 0.667. Metabolic pathway analysis can provide valuable information to enhance the understanding of the underlying pathophysiology of HGSOC. In conclusion, the Q Exactive LC/MS/MS method validation-based plasma metabolomics approach may have potential as a convenient screening method for HGSOC and may be a method to monitor tumor recurrence in patients with HGSOC after surgery.