Discovery lipidomics study for colorectal cancer using a Xevo™ MRT Mass Spectrometer and Lipostar data processing workflow

Importance of the Topic

Colorectal cancer remains a leading cause of morbidity and mortality worldwide and is closely linked to alterations in lipid metabolism. High-throughput lipid profiling can reveal biomarkers for early detection, prognosis and mechanistic insights into disease progression, enhancing both research and clinical workflows.

Study Objectives and Overview

This study presents a discovery lipidomics workflow integrating a Xevo MRT mass spectrometer operated in data independent acquisition mode with Lipostar2 software for comprehensive analysis of plasma samples from colorectal cancer patients and healthy controls. The aim is to streamline data acquisition, processing and identification to detect dysregulated lipid pathways associated with cancer types.

Methodology and Instrumentation

The workflow employs reversed phase ultraperformance liquid chromatography on an ACQUITY Premier system using a CSH C18 column (2.1×100 mm) with a 12-minute gradient from 50 to 99 percent organic phase (ammonium formate in acetonitrile:water to isopropanol:acetonitrile). The Xevo MRT mass spectrometer acquires high-resolution DIA data. Raw files are transferred from waters_connect to Lipostar2 via the UNIFI API or converted to mzML. Lipid features are processed through peak picking, alignment, statistical analysis, identification via rule-based fragmentation matching and pathway mapping within Lipostar2.

Main Results and Discussion

Supervised PLS-DA models demonstrate tight clustering of quality control samples and clear separation of control versus colorectal cancer cohorts, with additional stratification of colon and rectum cancer groups. Loading plots, S-Plots and VIP scoring identified key lipid variables, including ceramide and lysophosphatidylcholine species, driving group separation. Ceramide species showed increased abundance in cancer samples, while LPC classes were generally downregulated. Identification confidence was supported by low mass errors, fragment scores and retention time clustering. Quantitative calibration curves spanning five orders of magnitude enable concentration reporting of lipid analytes.

Benefits and Practical Applications

• Rapid, robust and reproducible lipidomic analysis across large sample sets
• Integrated acquisition and data processing accelerates biomarker discovery
• Flexible data export to third-party platforms supports diverse informatics pipelines
• Quantitative output improves comparability across laboratories and geographies

Future Trends and Potential Applications

Future developments may include targeted lipidomics for validation of candidate biomarkers, integration with other omics platforms and expansion to additional disease states. Advances in software automation, database curation and artificial intelligence–driven interpretation will further enhance lipidomics throughput and depth.

Conclusion

The combined use of reversed-phase UPLC, the Xevo MRT mass spectrometer and Lipostar2 software provides a streamlined, high-performance workflow for discovery lipidomics in colorectal cancer research, enabling robust identification, quantification and biological interpretation of lipid dysregulation.

Used Instrumentation

• Xevo MRT mass spectrometer
• ACQUITY Premier UPLC with CSH C18 column
• waters_connect platform and UNIFI API
• Lipostar2 software