Metabolomic Analysis of Amino Acid and Organic Acid Profiles in Tissue From Ovarian Cancer Patients Using High-Performance Liquid Chromatography-Tandem Mass Spectrometry (HPLC-MS/MS) and Gas Chromatography-Tandem Mass Spectrometry (GC-MS/MS)

Abstract

Targeted metabolomics studies on organic acids (OAs) and amino acids (AAs) were performed to search for biomarkers for ovarian cancer progression. Simultaneous AA profiling analysis method was developed through LC-MS/MS. Under optimal conditions, method showed good linearity (r ≥ 0.998) with limits of detection (LOD) ≤ 0.22 ng/mL and limits of quantification (LOQ) of ≤0.72 ng/mL. Repeatability varied from 1.4 to 17.3 relative standard deviation (%RSD) and accuracy varied from −20.6% to 12.1% relative error (% RE). Twenty-six AAs and 13 OAs were detected in the analyses of ovarian tissue from patients with benign ovarian tumors (BOT), borderline tumors (BT), and ovarian serous carcinoma (OSC). Star pattern recognition analysis was performed by normalizing each group to the BOT group. The star symbol plots in the BT and OSC groups were distinct and easily distinguished from those in the BOT group. The BT and the OSC groups exhibited higher 3-hydroxybutyric acid and lactic acid levels, lower pyruvic acid and OA levels in the TCA cycle, and alterations in AA metabolic patterns in comparison to the BOT group. Especially, citrulline and leucine were significantly reduced, while fumaric acid and malic acid significantly increased in the OSC group compared to the BT group. The BT and the OSC groups were completely separated in orthogonal partial least squares-discriminant analysis (OPLS-DA) and heatmap analysis. These findings, elevated ketone body levels, increased anaerobic glycolysis, reduced energy production related to mitochondrial dysfunction in the TCA cycle, and AA metabolic patterns associated with the impaired antioxidant system, may explain the characteristic metabolic reprogramming and Warburg effect related to the progression of the OSC into malignancy.

Keywords:

• Amino acids
• gas chromatography–tandem mass spectrometry (GC-MS/MS)
• high-performance liquid chromatography–tandem mass spectrometry (HPLC-MS/MS)
• metabolomics
• organic acids
• ovarian cancer
• orthogonal partial least squares-discriminant analysis (OPLS-DA)

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This paper was supported by Sunchon National University Research Fund (Grant number: 2023-0291) in 2023.