Metabolite profiling applied to biomarker discovery in pancreatic cancer using high resolution LC-MS/MS

Importance of the Topic

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with early metastatic spread and poor prognosis. Reliable biomarkers for early detection remain scarce. Metabolite profiling by high resolution liquid chromatography–tandem mass spectrometry (LC-MS/MS) offers a powerful approach to uncover biochemical changes in patient serum, supporting earlier diagnosis and better clinical outcomes.

Objectives and Overview

This study aimed to apply an untargeted high resolution QTOF LC-MS/MS method to serum samples from PDAC patients and healthy controls to identify candidate metabolic biomarkers. A direct probe ionisation mass spectrometry (DPiMS) approach was run in parallel to validate findings and assess the complementarity of these two acquisition techniques.

Methodology and Instrumentation

Sample Cohort

• 30 PDAC patient sera and 30 healthy control sera approved by the PCRFTB.

LC-MS/MS Profiling

• LC: reverse-phase C18 column, 35 min binary gradient (0.1 % formic acid in water/acetonitrile), flow 0.4 mL/min.
• MS: Shimadzu LCMS-9030 QTOF, ESI positive and negative modes; full scan m/z 60–1000 followed by data-independent DIA-MS/MS (35 Da windows, CE spread 5–55 V).

DPiMS Direct Analysis

• Shimadzu DPiMS QTOF; direct probe, no LC separation; TOF MS m/z 100–1500; DIA-MS/MS (1 Da window, CE spread 5–55 V).

Data Processing

• MS-DIAL for feature detection, alignment and filtering (feature present in >50 % QCs, RSD <20 %).
• MetaboAnalyst 5.0 for univariate statistics and volcano plots (fold change >1.5, p<0.1).
• LabSolutions Insight and MS-DIAL MSP for metabolite identification to MSI level 1 or 2.

Main Results and Discussion

Key metabolic alterations in PDAC serum included elevated levels of bile acids, carnitines, free fatty acids, lysophospholipids and phospholipids, alongside reduced lysophosphatidylethanolamines (LPEs), lysophosphatidylcholines (LPCs) and phosphatidylcholines (PCs). Volcano plot analysis highlighted multiple lipid species with significant fold changes. DPiMS results aligned in directionality with LC-MS/MS for major lipid candidates such as LPE 18:2 and LPC 18:2, though DPiMS could not resolve sn-1/sn-2 isomers. The combination of LC separation and MS/MS fragmentation improved structural confidence and isomer discrimination.

Benefits and Practical Applications

• High resolution LC-MS/MS provides broad metabolome coverage and robust identification at MSI level 1–2.
• Complementary DPiMS analysis offers rapid screening with minimal sample prep.
• Validated biomarker panels could inform early PDAC screening and prognosis in clinical research.

Future Trends and Applications

Integration of advanced chromatography with ion mobility and trapped ion methods may further enhance structural resolution. Machine learning models trained on high-dimensional metabolomics data can refine biomarker panels and predictive accuracy. High-throughput platforms combining LC-MS/MS and direct analysis will support large-scale clinical screening and multi-omics studies.

Conclusion

This work demonstrates that high resolution LC-MS/MS metabolite profiling, supported by direct probe ionisation MS, can identify and validate a set of lipid and polar metabolite biomarkers distinguishing PDAC patients from healthy controls. The dual-approach enhances confidence in biomarker discovery and sets the stage for future diagnostic assay development.

References

1. Mandel A et al Application of Probe Electrospray Ionization Mass Spectrometry (PESI-MS) to Clinical Diagnosis Solvent Effect on Lipid Analysis J Am Soc Mass Spectrom 2012 23(11) 2043–2047
2. Chung W et al Using probe electrospray ionization mass spectrometry and machine learning for detecting pancreatic cancer with high performance Am J Transl Res 2020 12(1) 171–179