Development of New Liquid Chromatography-Tandem Mass Spectrometry Methods for the Quantification of Seven Metabolites in Three Related Breast Cancer Cell Lines

Metabolites of the tricarboxylic acid (TCA) cycle play crucial roles in cancer biology, and their accurate quantification is essential for understanding energy metabolism, signaling dynamics, and identifying metabolic vulnerabilities in cancer cells. However, traditional liquid chromatograph-tandem mass spectrometry (LC-MS/MS) methods for these polar metabolites often encounter challenges, such as limited retention on reversed-phase columns and ion suppression. This study developed and validated two LC-MS/MS methods for the accurate quantification of seven key TCA cycle metabolites in MDA-MB-231, M67-2 (MEMO1 knockdown), and M67-9 (MEMO1 knockout) breast cancer cell lines. For five metabolites, namely citrate (CA), L-malate (MA), fumarate (FA), α-ketoglutarate (AKG), and glutamate (GA), an isotope-coded derivatization approach utilizing 12 C/ 13 C-labeled dimethylaminophenacyl (DmPA) bromide was employed. Inefficient DmPA derivatization in aqueous matrices was addressed by optimizing sample preparation in non-aqueous conditions, and the presence of multiple peaks of AKG was resolved by selecting triethanolamine (TEOA) as the reaction base to improve specificity. Conversely, due to persistent interferences with DmPA derivatization, pyruvic acid (PA) and succinic acid (SA) were quantified using another novel hydrophilic interaction liquid chromatography (HILIC)-MS/MS method in their native underivatized forms. Both methods were validated according to regulatory bodies, ensuring linearity, accuracy, precision, selectivity, and stability. The methods ensured the utilization of two multiple reaction monitoring (MRM) transitions to enhance specificity. The validation approach was adjusted to fit tissue culture studies. The validated methods were successfully used to measure the TCA metabolites in tested cell lines, providing valuable tools for investigating metabolic dynamics in cancer research.