Mass spectrometry-based analytical platforms in the analysis of lipidome alterations in cancer

Abstract

The introduction of high-throughput and robust methods for lipid quantitation in biological samples is one of the main directions for developing current lipidomics. Lipids are key signaling and regulatory molecules, basic building blocks of plasma membranes, and constitute the only effective chemical form for energy storage. Considering the biological roles of lipids, alterations in lipidome are one of the hallmarks of cancer. Thus, quantitative analysis of lipids can potentially deliver new therapeutic targets and, as a complete set of alterations in lipid profiles, biomarkers differentiating cancer patients from healthy individuals. Here, developing a direct infusion mass spectrometry platform is presented. The loop injection (flow injection analysis, FIA) was utilized for sample introduction, and the bottom-up strategy was selected for detecting lipids based on class-specific precursor ion scans and neutral loss scans (MS/MS) on the QTRAP mass spectrometer. The method was carefully optimized to achieve high sample throughput and sensitivity, with an emphasis on eliminating undesirable lipid accumulation and contaminants in the system. The method was validated, thoroughly tested, and, within one day, transferred to the clinical laboratory at General University Hospital in Prague to measure a cohort of 205 serum samples taken from patients with pancreatic cancer and healthy controls. The final method throughput in the clinical laboratory reached 257 samples/day. Strong resemblances were observed between results obtained using the FIA-MS/MS platform in Prague and Pardubice and a standard method for lipid quantitation utilized in our lab ? supercritical fluid chromatography (SFC) coupled with a QTOF mass spectrometer (SFC-MS). The samples were measured again after three months, and the results showed a high consistency with the earlier findings. This provides evidence that the developed FIA-MS/MS constitutes a robust platform for the quantitative analysis of lipids in oncolipidomics, with potential for future clinical applications. Additionally, the observed alterations in the lipidome of patients with kidney, pancreatic, prostate, and breast cancers were briefly summarized across multiple lipidomics platforms used in our laboratory and discussed here. In the final project, a comprehensive tutorial, including an article and a complementary GitBook with R and Python scripts, was prepared for novices, supporting the first steps in R and Python for statistical analysis of lipidomics and metabolomics data. Taken together, the PhD thesis shows the development of the robust direct infusion mass spectrometry-based platform for lipid quantitation ? from optimizing sample introduction method and mass spectrometer parameters through applications in oncolipidomics to statistical analysis of lipidomics data.